SOCIO-ECONOMIC STATUS AND THE UTILISATION OF PHYSICIANS' SERVICES:

RESULTS FROM THE NATIONAL POPULATION HEALTH SURVEY

SHERYL DUNLOP

A thesis in conformity with the requirements for the Degree of Master of Science

Graduate Department of Community Health University of Toronto

@Copyright by Sheryl Lynn Dunlop, 1998

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ABSTRACT

Socio-economic Status and the Utilisation of Physician Services: Results From the National Population Hedth Survey.

Sheryl Dunlop, B.A., 1998 Department of Community Health, University of Toronto

Objectives: To assess the extent to which Canada's universal health care system

eliminates socio-economic barriers in the use of physician services. This is done by

examuiing the role of socio-economic status in the differential use of publicly-insured,

primary and s pecialist healt h care services.

Maho&: Data corn the 1994 National Population Health Survey, a nationally

representative survey, was analysed using multiple logistic regression. In order to control

for correlation between GP utilisation and specialist utilisation, a two-staged les t squares

method was used for models explainhg specialist utilisation.

R e s r t k The factors found to be most consistentiy associated with increased physician

utilisation, for both primary and specialist care, were the indicators of health need.

Whereas the likelihood of an individual making at least one visit to a primary care

physician was found to be independent of incorne, those with lower incomes were more

kely to become frequent users of prirnary care, that is, make at les t six visits to a

primary care physician. M e r adjusting for the greater utilisation of primary care services

by those in lower socio-economic groups, the utilisation of specialist services was greater

among those in higher socio-economic groups. Canadians lacking a regular medical

doctor were less likely to receive primary and specialist care, even after adjustments for

socio-economic variables such as income and education.

Conclusions: Although financial barriers may not directly impede access to heaith care

seMces in Canada, difrentids in the use of physician seMces with respect to socio-

econornic status persist. Despite universal health care, after adjusting for differences in

health need, Canadians with lower incomes and fewer years of schooling visit specialists at

a lower rate than those with moderate or high incomes and higher levels of education

att ained.

ACKNOWLEDGEMENTS

1 gratefully acknowledge with thanks the help of my supe~sor, Dr. Peter Coyte

for his t h e and expertise. 1 appreciate the helpfil cornrnents received from Dr. Warren

McIsaac, Dr. Rhonda Cockerill and Dr. David Woodhouse and the valuable statistical

assistance nom Ruth Croxford. I am grateful for my parents and brother, Ricky, for their

unconditional support. Finally, thanks to Derek, Kim, f i s , Liz, Nicole, Shannon, and

Tara for ensuring my year was not aii work.

TABLE OF CONTENTS

1 LNTRODUCTION ................................................................................................ 1

....................................................................... II LITERATURE REVIEW *.m*.0..e*e...5

................. ....... 1 . 0 Role of Socio-econornic status in the use of health care senrices ...... 6

......... 2.0 Impact of having a regular medical doctor on the use of heaith care services - 1 1

.................. 3 . 0 The use of a two-staged mode1 in the analysis of health care utilisation 14

................................. ........... 4.0 Behavioural Mode1 of Health Service Utilisation ... 17

............................................................................................. 4.1 Measuring Need 17

4.2 Measuring Socio-Economic Status .................................................... .. ........ 19

....... 5 . 0 Data and statistical techniques to expldpredict utilisation of health services -22

................................................................................... 5.1 Discriminant Analysis 26

................................................................... 5.2 Analysis of Variance (ANOVA) -26

.......................................................................... 5.3 Multiple Linear Regression -26

. . ......................................................................... 5.4 Multiple Logistic Regression 27

.................................................................................. 6.0 Summary of the Literature -231

IIlt METEODS ................................................................... ...*..*0*****m...*..*.m.....*****.**...33

............................................................................................... 1 -1 Sample Design 3 4

........................................ 1.2 Questionnaire Design and Data Collection Method -36

.................................................................................... 1.3 Weighting Procedures 38

2.0 DEPENDENT VARIABLES ................................................................................ 39

.......................................................................... 3 .O INDEPENDENT VARIABLES -41

TABLE OF CONTENTS cont . .................................................. ............................... 3.1 Predisposing factors .. -42

3.2 Enabhg factors ............................................. .. .......................................... 44

.......................................................................... 3 -3 Variables representing need -47

........................................................................................... 3 . 4 Health Be haviour 47

...................................................... 3.5. GP Utilisation as an independent variable 48

.......................................................................................................... 4 .O ANALYSIS 49

.................................................................................................... 4.1 Goodness-of-fit 52

IV RESULTS ............e.~~.~.m~..~~~~~.~.~........................................e... 54

........................................................ 1 . 0 Descriptive Statistics for Physician Utilisation 54

..................................................................... 2.0 UTILISATION OF GP SERWCES 5 6

................................................ 2.1 At Least One Visit to a GP (Non-use Versus Use) 56

.................................. ........................... 2.1 1 Variables representing need ...... 5 6

................................................................................... 2.12 Predisposing variables 57

....................................................................................... 2.1 3 Enabling variables .. 58

..................................................................... ........... 2.14 Health Behaviour ... 58

2.2 At Least Six Visits to a GP (Non-frequent Use Versus Frequent Use) .................. 59

............................................................................. 2.2 1 Variables Indicating Need 59

.................................................................................. 2.22 Predisposing Variables 60

........................................................................................ 2.23 Enabling Variables 60

.......................................................................................... 2.24 Health B ehaviour 61

............................................ 3 . 0 UTILISATION OF SPECIALIST SERVICES 61

TABLE OF CONTENTS cont . .................................................................................................. VI REFERENCES 8 9

VtU TABLES. FIGURES ......................................................................................... 97

APPENDICES .......................................................................................................... 126

LIST OF TABLES, FIGURES AMI APPENDICES

Figure 1 ................................... Distribution of reported contacts with GPs among males and females 97

Figure 2 ............. ......,.....*............... Percentage of Males and Females with at Least 1 GP Visit .... 98

Figure 3 .......................................... Percentage of Males and Females with at Least 1 Specialist Visit 99

Table 1 .................................. A brief summary of major research in the area of Physician Utilisation 100

Table 2 ....................... Visits to Canadian Physicians in a 12 month period by Males and Females ..... 102

Table 3 Goodness of Fit Measures .................................................................................................. 1 03

Table 4 Factors related to one or more visits to a GP for females ................................................... 104

Table 5 Factors related to one or more visits to a GP for males ................................................... 105

Table 6 Factors related to one or more visits to a GP for females and males combined .................... 106

Table 7 Factors related to six or more visits to a GP for fernales ...................................................... 107

Table 8 ......................................................... Factors related to six or more visits to a GP for males IO8

Table 9 Factors related to six or more visits to a GP for fernales and males combined ...................... 1 10

Table 10 ........................................... Factors related to one or more visits to a specialist for females 112

Table 1 1 .............................................. Factors related to one or more visits to a specialist for males 113

Table 12 Factors related to one or more visits to a specialist for females and males combined.. .......... - 1 14

Table 13 ......................................... Factors related to six or more visits to a specialist for fernales.. 1 1 5

Table 14 ................................................. Factors related to six or more visits to a specialist for males 1 16

Table 15 Factors related to six or more visits to a speciaiist for femaies and males combined .............. 1 17

Table 16 ............................................................... Factors related to having a regular medical doctor 1 18

Table 17 Summary of the effect of education and income on visits to a GP and Specialist ................... 1 19

Table 18a ..................................................................... Summary of the bivariate anaiysis for females -120

Table 18b ......................................................................... Sumrnary of the bivariate andysis for males 12 1

Table 18c Summary of the bivariate anaiysis for fexnaies and males ................................................... 1 2 2

Table 19a ................................................................ Summary of the multivariate analysis for fernales .123

Table 19b ................................................................... Summary of the rnultivariate analysis for males .124

Table 19c Siimmary of the multivariate andysis for females and males ............................................. 125

Appendix 1 . . .................................................................................... Description of dependent variables.. 126

Appendix 2 ........................................................................................ Variables with missing responses 127

Appendix 3 .................................................................. The derivation of the incorne adequacy variable 128

Appendix 4 ................................ The derivation of the variable representing number of health problems 128

Appendix 5 The probability of making 5,6,7 visits to a GP for females ................................................... 129

Appendix 6 The probability of making 5,6,7 visits to a GP for females.. ................................................ 130

Appendix 7 The probability of making 5,6,7 visits to a GP for fernales. .................................................. 1 3 1

Appendix 8 The probability of making 5,6,7 visits to a GP for females ................... ... .......................... 132

Appendix 9 The probability of making 5,6.7 visits to a GP for fernales. ................................................ 133

Chapter 1: CNTRODUCTION

The implementation of a universai, publicly-funded medical i m a n c e program in

Canada was justified on the grounds that all citizens should have access to health-care

seMces on the basis of need rather than ability to pay.Iy One of its primary purposes is

to provide al1 Canadian residents with necessary medical care on a prepaid basis, thereby

reducing health inequalities and financial uncertainty." An important characteristic related

to inequaiities in the health of Canadians and their need for health care is socio-economic

status. The link between socio-economic status and health status has long been

recognised, with lower income associated with poorer heaith tat tus."^ Not only is this

relationship positive, it aiso has no threshold; the differentials do not merely affect the

poor in relation to the wealthy but extend throughout al1 social classes.10

Since the implementation of hospitai insurance in 1958 and medical insurance in

1968, Canada's national health insurance system has done much to overcome financial

barriers to health care services." One major study found that the Mplementation of

universal health care has resulted in a shift in the use of physician services fkom persons in

higher income groups to persons in lower income groups.2 Despite this shift in utilisation,

barriers to the use of health care by the poor persist. 4,5,12,13 In theory, universal heaith care

coverage should result in "reasonable access" to health care services, that is, health care

utilisation being unrelated to socio-economic status and determined instead by health need.

However, though financial constraints may not impede equal access to primaty health care

in Canada when universal health insurance prevails, social-class differentials in both health

and heaith services utilisation continue to exist. 5,1213

While ùisured residents may self-refer for primary care services, speciality and non-

p r imq medical health services usudy require referral fiom a general practitioner.'4*15

Many of these services, including surgeons, allergists, rheumatologists, gynaecologists and

psychiatrists, may be necessary to restore function or to enhance health status. Utilisation

of referred seMces is cornprised of two components. First, self-referral to a primary care

provider is initiated by the patient, and second, referral to subsequent speciality care often

depends on a Msit to a primary care practitioner. By separating health care utilisation into

actions initiated by the patient and actions that require a referd fiom a generai

practitioner, greater understanding of the role of socio-econornic status on health care

utilisation may be gained. According to a study based on the Ontario Health Survey, low

income groups were more likely to make use of primary health care (general practitioners)

and less iikely to make use of secondaq health care (specialists) than were high income

grouPd That is, when specific speciaiity services are considered, varying discrepancies in

the utilisation and the conditional probability of referrai for specific specialist services d e r

primary care utilisation were both demonstrated to depend, in part, on socio-economic

satus.

The majority of research on the utilisation patterns of heaith care seMces by

Canadians has been iimited to the residents of a given community or province and has

been limited in the range of variables u ~ e d . ~ * ' " ' ~ The Canadian studies that did consider a

broad range of socio-demographic, economic and need characteristics, when examioing

the use of physician services, ernployed data fiom the 1979 Canadian H d t h Survey

(CHS) but did aot distinguish prirnary care utilisation from the utilisation of ~~eci&sts.~'

McIsaac et al. examined the utilisation of primary and speciality seMces separately using

the Ontario Health Survey (OHS) but there has been no nationdy-representative study

conducted assessing these patterns for the 1990's. In addition, this analysis contributes to

the research on the utilisation of physician seMces and access by incorporating a two-

staged least squares method to explain specialist utilisation and by using an improved set

of explanatory variables, narnely, the inclusion of a variable indicatuig the extent to which

one identifies with a regular medical doctor and the predicted probability of persons

making six or more visits to a general practitioner.

This thesis uses data fiorn the 1994 National Population Health Survey to examine

the role of various factors in the utilisation of physician services. The primary objective of

this thesis is to explain, in a nationally representative sample, the role of socio-economic

status in the Werential use of publicly-insured, primaty and speciality seMces in order to

assess the extent to which socio-economic barriers in the use of physician seMces exist in

Canada's universal heaith care system. A two-staged mode1 will be used to examine the

determhants of two dimensions of prirnary care and speciality use. The first stage will

assess access to physician services, that is, the characteristics of those individuals who saw

a physician in a one year period compared to those who did not. The second stage will

examine the Uinuence of the same characteristics on the fiequency or volume of physician

visits by respondents who experienced at least one physician visit.Ig In addition, the

models examining specialist care utilisation will also control for primary care utilisation.

The study wiii also assess the impact of having a reguiar general practitioner on the use of

physician s e ~ c e s for persons in varying socio-econornic groups.

Chapter II: LITERATURE REVIIEW

Literature identified through electronic literature searches and bibliographies of

relevant articles were reviewed. A MEDLIME search strategy from 1976 to Decernber

1997 was used with the following keywords used singularly and in combination: hedth

care utilisation, health care use, access, socio-econornic status, primary health care,

specialist, referrais, and regular physicim, resulting in approxknately 300 references. The

abstracts of these articles were examined and those studies addressing patterns of health

service use by socio-economic status, as well as other factors sigdicantly influencing

health s e ~ c e utilisation, under publicly-fùnded health insurance were selected. Particular

attention was paid to Canadian studies of access to health care s e ~ c e s . Three areas of

interest were examined: 1) the relationship between socio-economic status and heaith; 2)

the role of socio-economic status in the utilisation of different types of health sewices; and

3) the impact of having a regular general practitioner on the use of health care services.

In order to provide a basis for selecting variables for modeiling heaith care utilisation by

groups with different income and education levels a behavioural model of health services

utilisation will be used. Therefore, a section of this review wiU be dedicated to the

background and framework of this model.

Assessing health care utilisation is one approach to understanding the fbnctioning

of the health seMces system. The objective of most health care utilisation studies is to

explain the use of health care seMces (most commonly expressed as the number of

physician contacts or visits) in relation to a number of socio-economic, socio-demographic

and other characteristics. A major type of utilisation shidy is one that assesses the success

of the universal health insurance system in achieving equitable access to health seMces

regardless of socio-econornic Currently, this type of study is done by assessing

the extent to which the use of health care seMces is determined by medical need rather

than by non-medical factors such as income and education.

1.0 Role of socio-economic status in the utilisation of health services

Much of the early Canadian research comparing data before and after the

introduction of a universal health care insurance system conclude that its implementation

led to an increase in relative accessibility to physicians for the low-income classe^.^^*'"'^

However, these studies were limited by assessing accessibility to physician services

primarily in terms of income class, failing to control for the health care needs of the

population.' Due to the positive relationship between health status and income" it is

important to examine access to health care in relation to the health need of the population.

Studies examinhg access to health care should address whether or not utilisation

Merentials are in proportion to health need by answering the question; "Given the same

needs, do individuals of varying socio-economic status receive equal amounts of health

care?" E there is a negative correlation between the need for heaith care and socio-

economic status, as suggested by the positive relationship between health status and socio-

economic status, then it is feasible that a situation in which there is no statistical Werence

in the utilisation of health care by socio-economic status may stil i be inequitable. Table 1

provides a summary of Canadian studies of physician utilisation including the data used,

whether or not health need was controlied for and the results.

The 1979 Canada Health Survey provided information on heaith stahis, which

dowed investigators to control for the health needs of the population. The results of this

s w e y iadicated that peopIe of lower income groups and with lower levels of education do

not enjoy the same level of health as those Canadians with higher socio-economic status.'l

The findings of the more recent literature, using data fiom suweys such as the CHS to

control for the heaith needs of the population, are mainly consistent with those reported in

most of the earlier Canadian studies that did not control for need. More specifically the

results agreed that "need is the most important determinant of primary heaith care

utilisation and that the measure of an individual's ability to pay did not contribute to the

discrimination of users from non-users. 3-5-1 1-12 Further, these studies also suggest that it is

those of lower socio-economic status who generally have poorer heaith and in tum, use a

higher proponion of health care services. wu3

At first glance, these results would seem to support the contention that universal

coverage in Canada has resulted in a more equitable distribution of health seMces arnong

different social groups; that is, health status is the most important determinant of physician

utilisation and that those groups with poorer heaith status and greatei health needs make

more use of the health care system. However, one important issue surroundhg these

resdts is whether the poor are acquuing a dflerent mix of heaith care services fi-om the

more suent. For instance, it has been demonstrated that those of lower income groups

tend to use specialist and preventive care Iess frequently and emergency care more

fiequently than their high income c~unterpar ts .~~~ ' When interpreting results of utilisation

studies, it is important to take a closer look at how the data was measured. Unfortunately,

most of the literahire assessing the utilisation of health care s e ~ c e s use a broadly-defined

independent variable which makes no distinction between preventive, curative or

emergency service.

According to Aday and Andersen the utilisation of health services may be

characterised in tems of its type, site and purpose. lg Type of health care refers to the kind

of senrice received and whether it is provided by a general practitioner, dentist or

speciaiist. Site of service refers to the place where the care was received; for example, a

physician's office, emergency room or walk-in clinic. The purpose of the s e ~ c e could

refer to preventive, iliness-related, or custodiaf care.

Most of the studies whose results conclude that universal heaith care coverage has

the effect of equalising the use of health-care seMces were conducted without

dflerentiating between type, site or purpose of health service utilisation. For instance, the

majority of utilisation studies do not separate the use of general practitioners fiom the use

of specialia physicians, yet one would expea the model explaining GP visits to be

different nom the model explaining specialist use.' Once this distinction between type of

service is made, it is possible that the health statu of the individual is no longer the sole

factor determinhg utilisation of aii types of semice and that the distribution of health

seMces may not appear to be so equitable. Nevertheless, even if the distribution of

physician services does not ciiffer once different characteristics of visits are included in the

equation of utilisation, one will have a greater understanding of the use of seMces by

groups of varying socio-economic status and need.

Recent research that has made the distinction between type of service, mainly in

the U.K. and Canada, indicates that health inequalities and differential use of certain types

of physician services by socio-economic status persist within universal health care

systerns. 5*1337193U3 or instance, patterns of health care utilisation for these dEereat

types of services suggest that after controlling for age and socio-dernographic variables,

those of higher socio-economic status experience more specialist encounters than those of

lower socio-economic status. 5.13.32 These findings suggest that the use of specialist

services displays the exact opposite tendency of the use of general practice.

The study of Mcisaac et al.' examined patterns of the utilisation of general

pradtioner and specialist seMces by adults in Ontario in 1990. Results showed that need

for medical care was the best predictor of both GP and specialist physician visits. Socio-

economic status was not related to utilisation when physician utilisation was defined as "at

least one visit to a GP." Therefore, to the extent that measures of utilisation reflect access

to tare,* this finding supports the contention that Canada's heaith care system has resulted

in more equitable access to health care services.

It was also found in the same study, that those in the lower income groups were

more Wrely to make six or more GP visits in one year. This pattern contrasted with that of

specialist visits: after cont rohg for GP visits and health status, those in higher income

groups were more likely to make at least one specialist visit compared to those in lower

income groups. Few studies, when examinhg the dserential use of publicly-insured

physician services, separate GPs and specialists hto two different types of utilisation, and

no nationaily representative study has been done dealing with this issue.

Both physiciaas and patients work together in determinhg levels of health care

utilisati~n.'~*'~ Patients usualiy make the initiai contact with a primary care physician and

it is then, for the most part, the physician, through referral, who influences the subsequent

utilisation of other publicly-financed health care services provided by speciali~ts.'"'~ For

this reasoq a distinction should be made between the concepts of patient-initiated demand

and the probability of subsequent referral to secondary medical care. In order to assess

whether Canada's health care system has been successful in achieving an equitable

distribution of health services arnong different socio-economic groups, the "ideai" care

system should reveal that health status measures are the main determinants of visiting a

speciaiist. Studies have shown, however, that patient preference plays an important role in

accounting for the difrentid use of specialist services between those of high and low

socio-economic status. For instance, one studyfound that "patients wishes" was the most

important factor influencing decisions by GPs to refer for consultation with a specialist. 34

Due to the probability that the Less educated or poor may be less able to express their need

for care, they may be less Wrely than the more educated and rniddle income groups to gain

entry to specialist ser~ices.~ Furthemore, those of higher socio-econornic status rnay have

different attitudes about the benefits that can be realised by accessing speciaiist care and

may in tum be more motivated to seek opportunities by requesting specific kinds of

physician visits.

It has been shown that even under a system of universal coverage, class

inequalities in the utilisation of specialist services e~ist.~'' A study exploring determinants

of referrds to specialists found that there was a higher rate of referrals of patients with

higher education attainment, indicating a bias towards higher social status groups-3s

McIsaac et d. dso found that individuals of higher socio-econornic status had better

access to specialised health care services, with respect to aeed, than those fiom lower

socio«onomic status groups. If these specialised seMces are essentiai to maintainhg

and enhancing the stock of health capitai, then it follows that social advantage enables an

increased capacity to produce and sustain positive hedth and thereby enhance well-being.

Access to health seMces continues to be a major policy goal based on the

assumption that improved access to health care will lead to greater equity in heaith

s t a t ~ s . ~ ~ Removal of hancial barriers to care was an important goal of nationalised health

care. However, the literanire shows that it is not sufficient to raise use by those in lower

income groups to optimal levels, because disparities by class in the amount and different

types of health care received may still e~ist.~''~

2.0 Impact on persons of having a reguiar medical doctor

The major component of health care in Canada is primary medical care. Most

primary care is provided in the community through general practitioners in private

practicu. Having a regular general practitioner has been found to be an important

correlate of utili~ation.'~' Therefore, it is not surprising that access to health seMces is

comrnoniy measured andlor determined by whether or not one has a regular physician. 42-44

The few studies that have actuaily examined the impact of persons having a regular

physician and whether or not it promotes better quality of care or enhances utilisation,

have found it to be a significant variable. In particular, those with a regular physician

receive sigruticantly greater medical care than those with~ut.~~"'

ui the fiterature, information on whether or not one has a regular medicai doaor is

usudy obtained through interviews with questions sunilar to ''1s there one person or place

in particular you usuafly go to when you are sick or want advice about your health?"'

Nthough a very high proportion of individuals report having a regular physician, smailer

proportions of individuais f?om certain population groups report hating a regular

physician. Lacking a regular medical doctor has been associated with such population

chmeristics as being a member of racial or ethnic mhority and being econornically

disadvantaged . 24.28.51.45 Another factor that has been shown to be very strongly associated

with having a regular physician is the prevalence of chronic disease or poor health status in

general.28*41 In turn, it has been çuggeaed that the relationship between havhg a regular

physician and high health care utilisation is most probably one of cause and effect. That is,

the sick will normaiiy find a regular physician and those with a regular physician will

norrnally receive more tare."

In recent years there has been an increased emphasis on disease prevention and

hedth promotion. Recornmendations to physicians regarding primary and secondary

preventive meanires were made by the Canadian Task Force in 1979 and are continually

being updated as new information becomes available." It is recomrnended that physicians

focus their attention on disease prevention and health promotioa through activities such as

blood pressure checks, breast examinations, mammographies and cervical smears.

Whether or not having a regular general practitioner improves efficiency, with regard to

containhg costs or promoting better quality of care has not been a widely researched

issue. However, it is hypothesised that the degree to which persons are considered to

have a regular fimily physician affects such outcornes as receipt of recommended

preventive s e ~ c e s . * It therefore folfows, as the literature suggests, that havhg a regdar

general practitioner is positively and significantly related to the receipt of recommended

preventive ser~ices.~-'"'*"~' Similarly, lacking a regular physician may be a risk factor

for not receiving recommended preventive medical are.'^^^ For example, those who did

not have a regular physician were less likely to receive breast and cervical cancer screening

and less likely to have seen a physician when they had a serious medical symptom. 41.42

High income groups were more likely to have had their blood pressure checked than low-

income groups and those with higher incomes were less likely to have higher blood

pressure than those with low inc~mes.'~

Although the majority of primary medicai care is received through pnvate practices

by general practitioners, a small part of the population seeks their pnmary medical care

through a wak-in clinic or a hospital emergency department." Having a regular physician

has been shown to have a arong negative relationship with the use of the emergency

department. 17,18.28,33,4 I.49.50 Individuals regdarly seeking care at physicians' offices are

more likely to have a regular physician while those who regularly seek care at the

emergency department or walk-in chic are more iikely to lack a regular physician.

The literature suggests individuals identifjmg with a regular rnedical doctor have

better access to both primary and preventive care than those not identifjing with a regular

physician. Although it has been found that many of the individuais lacking a regular

source of care do not feel it necessary, these individuds may be at greater ri& for not

receiving the care they need. Therefore, it has been suggested that heaith care reform

advocating a system linking individuals to a reguiar source of care will be effective in

promothg access to appropriate care and recomrnended health care s e ~ c e s . ~ '

The literature does not contribute a great deal to the understanding of the impact

of having a source of continuous care on outcornes defined as receipt of primary and

specialist care. It has been indicated that the lack of research on this topic lies in the

difEculty of separating the specific effect of having a regular source of care from other

enabling factors such as those contributing to socio-economic s t a t d In this study, the

eEect of having a regular medicai physician on the use of both primary and specialist

services, after controlling for socio-economic, socio-demograp hic and need factors, wili be

assessed.

3.0 The Use of a Two-Staged Mode1 in the Analysis of Health Care Utilisation

Many previous studies of health care utiiisation have used a two-staged mode1 to

assess factors associated with the use or non-use of physician services as well as the

factors associated with the volume of physician senrices consumed by those who have

made at least one contact with the health care system. 5.8,9,50-53 The first stage examines the

infiuence of independent variables on the variation between different groups in the

probability of making at least one contact d u ~ g a specified period. Those who have

made at least one contact to a health care practitioner have made access to the health care

system. Therefore, the measure of accessibility applied here is the proportion of

individuals in a given group who have made use of the heaith care system in a specifk

period of This is a reasonable measure of accessibility as utilisation was analysed

separately for type of s e ~ c e (specialist or GP) and assessed the extent to which need

variables could explain variations in the incidence and quantity of use controlling for

socio-economic statu. The second stage examines how the same set of independent

variables explains the volume of use or fiequency of use among those who have made at

least one contact. In other words, the first stage of the model is a measure of the

propensity to make use of health care services, the second stage of the model is a measure

of the intensity of use. In turn, utilisation of health care seMces is equal to the propensity

multiplied by the intensity of use.

It is important to analyse separately the volume of use consumed by those who

have had at least one contact as it cannot be assumed that the effect of any independent

variable d be the same on the probability of use and the volume of use. Results from

research considering usefnon-use separately corn the volume of use usually show that the

influence of socio-economic status on uselnon-use and the volume of use is

heter~~eneous.'.~*~ More specifically, it is found that the usehon-use of medical services

is rnainly determineci by medical need, suggesting that the likelihood of those experiencing

an episode of care is independent of socio-economic aatus. However, examinations of the

volume of use usually £ind that those of lower socio-econornic status use significantly

more physician services than those of higher socio-economic status. For instance, Broyles

et al. found that incorne did not contribute to the discrimination of users fiom non-users of

health care services; however, incorne was ùiversely related to the volume of their usea8

Another important reason for dividing utilisation into usdnon-use and volume of

seMces consumed is the skewed distribution of physician visits. Andersen et al. found

using the, US.-based, National Health Interview Survey (NHIS), about 75% of the

population bad seen a physician within the pst year and that this proportion varied little

by The authon ais0 found the mean number of physician visits per person per

year to be somewhat higher for the low-income group than for middle and high income

groups. However, Andersen et al.'s use of the mean number of visits as a measure of

physician utilisation is not appropriate due to the skewed distribution of physician visits.

There is a large proportion of individuais with zero visits during the study period, thereby

imposing a distribution of physician use with a heavy weighting at zero? Therefore, using

the mean number of visits as a measure would overernphasise the contribution of

individu& who are high users of primary care. It is due to this skewed distribution of

physician visits that other researchers have disthguished usehon-use and have further

dichotomised those who have made at least one visit into fiequent-use and non-fiequent

use; for example, 6 or more visits as opposed to 1-5 vi~its.'*'~ These two groups of

"'usen" are then examined by socio-economic level. The results from the study of

McIsaac et al. showed that socio-econornic aatus was not associated with making at least

one visit to a general practitioner but those of lower socio-economic status were more

likely to make six or more visits to a generai practitioner.5

Due to the skewed distribution of physician visits and the belief that factors

associated with the use or non-use of physician services may be dEerent f?om the factors

associated with the volume of use, physician visits wiff be assessed in two stages in this

study. To be consistent, as wefi as allowing for cornparison with previous research, the

decision was made to divide each mode1 into those who made 1-5 visits and those who

made 6 or more visits.

4.0 Behavioural Mode1 of Health Semce Utilisation

The behavioural model of health seMces utilisation is an atternpt to provide a basis

for selecting variables for modelling hedth care utilisation by groups with dserent income

and education levels. Since its development by Andersen and Newman in the late 1960s.

the mode1 has been used by many investigators to explain or predict the use of health care

services. The model suggests that the use of health care is a function of need (perceived

and evaluated iiiness-related factors), enabling factors (famiy and community resources)

and predisposing factors (demographic characteristics, social stmcture, beliefs). These

factors help to determine the health care people receive and should serve as a guide in the

selection of significant variables to include in a model attempting to predict or explain

hedth care utilisation.

4.1 Measurinn Need.

Andersen and Newman suggest that "need" includes subjective and objective

determinants. Ig Objective or evaluated determinants of need represent professionai

judgement about people's health aatus and their need for medical attention. Subjective

determinants of need are basicdy a social phenornenon largely explained by social

structure and health beiiefs. Because patients' perceptions and physicians' evaluatioas of

need may Mer, boot of these aspects should be considered when selecting a measurement

of need.

Health status is a multi-dimensional variable. There is Iittie consensus on which

measures of need are most andyticaiiy appropriate. Holding health status constant in an

analysis of physician utilisation is difncult not only because data are iimited but because

the range and intensity of these conditions differ considerably. Many different measures of

need have been used by past investigators, based on diagnosis, symptoms and an

individual's own perception of her or his health." Measures of health status have included

number of accidents, use of prescribed rne~tications,~~~*~~ number of disability days or days

of limited activity, 8*56 number of health pro blems or medical ~ o n d i t i o n s . ~ ~ ~ * ' ~ * ~ ~ previous

i l lne~ses,"~~~ hospital admission^,^ and chronic conditions. '* Yet a person's ill health is not

only detemiined by physical characteristics, but may also be determined by pyscho-social

characteristics or perceptions of change in usual functioning and feeling." That is, an

indwidual may Feel unwell without having a diagnosable illness. Hence most recent studies

that attempt to measure health status involve no direct assessrnent, based on diagnosis,

tiom a physician. Instead, these studies use self-assessed health status such as asking if

the respondent feels she or he is in excellent, very good, good, fair or pour health6 Such

a measure has been shown to be a very good predictor of physician use, morbidity and

mortality, or perceived health relative to other persons of comparable age. 5.58.59 Not only

is self-rated health associated with physical health status but it is aiso associated with

social well-being, which may be an important predictor of the use of health care s e ~ c e s . ' ~

Nevertheless self-reports of health status obtained in interviews have obvious

limitations. Individuais dEer in knowledge of their own health, their readiness to report

iiiness, and their interpretation of questions. Furthermore, reported health problems may

not have been confirrned by a health professional. Still, there are two very important

advantages of using information obtained by survey methods to control for heaith status.

First, it is only through interview that the important dimension of subjective health cm be

taken into account. Second, it is only with the use of survey methods that measurement

can be made of iiiness that has never been presented for medicd treatment.

In lieu of an objective measurement of health status, which tends to be both

complex and expensive, the literanire tends to support counts of conditions as a variable

for measuring health status. The main weakness of this measure is that dl conditions are

equaiiy weighted. However, unless we have insight with respect to an alternative and

saperior scheme it may be best to use counts of conditions as a measure of health status.

In addition, it seems reasonable to also use perceived generd heaith status as a measure

fur need when trying to predict health care utilisation. One wodd expect that perceived

need wiil better help understand care-seeking and adherence to a medical regimen,

whereas evaluated or objective need would be more closely related to the kind and amount

of treatment one receives after presenting to the physician. l4

4.2 Measurine Socio-Economic Status.

Just as there is no standard measure of need, there is aiso no standard measure of

socio-economic s t a t ~ s . ~ Due to diniculty in obtaining individual measures of socio-

economic characteristics, many investigators have used census data to measure socio-

economic characteristics of the geographical area to develop geographic socio-economic

profiles. 5,48,6068 For instance, many -dies use census tracts to categorise socio-economic

levels based on rent, assuming that ceasus tracts are homogeneous with respect to socio-

economic factors. Such profiles, although they have been found to be good predictors of

residents' health status and hospitai use, have not been found to be predictive of physician

use. More specificdly, this method is not very precise and results in an underestunation of

the strength of the relationships between socio-economic status and the dependent variable

of interest .69

Socio-economic s ta tu is a complex concept. Most studies that have been based

on the individuai as the unit of andysis, such as the Canada Heaith Survey (CHS), have

used education, occupation or income as measures of socio-economic ta tus,^ or a

combination of these tl~ree.**'~ Although these variables are interrelated, each of them

reflects different ways in which social factors may influence health and heaith behaviours.

For example, employment status may alter the availability of time to use heaith care;

education could mean skills for acquinng dierent health knowledge; and income relates

to the capability to purchase goods and seMces (perhaps transportation to obtain care).

It has been argued that wage income is inversely related to use because of the

oppominity cost of lost work-the. 43.53,68,70 Taking the time to visit a physician may be

more costly for an individual eaming a high income than for an individual earning a lower

income. This may, in part, explain why the use of health services is higher among women

than men and among the low income groups than higher income groups. However, even

though time taken by those in a low income group may represent a lower dollar value than

those in a higher income group, the reai value of the dollar will ~ a r y . ~ ~ Another aspect

that may make access to care more dinicult for low-income groups is their inability to take

time off work without losing pay. Those in higher incorne groups are more Wely to be

paid on a salaried basis and may in tum find it easier to leave work to visit a physiciao and

are more iikely to be paid sick leave. A low-income worker who is paid an hourly-wage

will be more iikely to suffer an irnrnediate loss of eamings if she or he takes the time off to

visit a physician and therefore a greater threshold of illness will need to be reached for

uti~isation.~~

The innuence of any individual socio-economic variable is diffinilt to assess due to

multi-collinearity of the measured socio-economic factors. One study assessed the aspects

of socio-econornic status such as education, occupation and incorne using data fkom the

1979 CHS and found that of the three measures, incorne was consistently the best

correlate of health status? Occupational status was found to have the most inconsistent

relationship with health status. Education, however, was found to be the most stable

rneasure of socio-economic status." This stability cornes f?om the fact that the highest

education attained is usually quite early in Me. As a result, education has become the most

comonly used measure of socio-economic status. In a study set out to examine the

association between income, education, occupation and a set of risk factors for

cardiovascular disease, results showed that the relationship between measures of socio-

economic status and nsk factors was strongest for educatioq showing higher risk for

lower levels of education? in fact, after adjustment for age and time of survey, education

was the only measure that was significantly related to risk factors. The authors

hypothesised that education may protect against disease by duencing Mestyle

behaviours, pro blem-solving abiiities, and values." In addition, education may assist in

the acquisition of positive social skills and assets, and may provide Uwlation a g h t

adverse idluences. Aiso, education often provides the qualifications to acquire certain

occupations and income. Further, it is considered to be related to health outcornes

through its influence on lifestyle behaviours such as physical activity and the use of

tobacco and alcohol, and values such as the importance of preventive health behaviours.

Incorne is considered to provide access to medical care resources and good housing, less

exposure to a noxious environment, a good diet, good working conditions, and more

social amenities." Unlike occupation, idormation about incorne and education are both

obtained in a straightforward manner and are therefore, likely to be more accurate.

Help-seeking behaviour is part of a complex, dynamic process and varies

according to socio-economic status. In addition to economic variables, there are also

features of the delivery system and certain anitudùial and behavioural characteristics of the

lower income groups that may be important in determinhg the use of health tare." m e r

characteristics that have been shown to afFect the level and type of utilisation are age,

marital status, urban or rural residence, region of residence, prescription drug use, alcohol

consumption, smoking status, physical activity, immigration stafus, and employment

status.

5.0 Data and statistical techniques employed to explaidpredict utilisation of health services

The Limitations of using cross-sectional, household surveys such as the National

Population Health S w e y (NPHS) have been well-documented in past research. s,7o,n,74

Cross-sectional surveys provide information about the population at only one point in

t he . They suffer nom non-response or biased results fiom misunderstanding on the part

of the respondent, from the interviewer's own point of view, and from the design of the

questions.20 They are ürnited in their reliance on descriptions of self-reported syrnptoms

rather than diagnosis, which prevents linking reported utilisation to the presence of illness.

There is also the tendency to underreport illness and physician contacts due to problems of

recall, seasonai variations, and unique health condition^.^^^^^ This tendency, however, is

reduced when conditions are included on a checklist." It has been suggested that the

reporting of iliness and physician visits is systematically biased downwards due to the

social undesirability of being ill. However, it has also been found that over-reporting rnay

occur when recd is requested within a specified time frame in the past. That is, the

respondent tends to recali instances that occurred outside the penod specified and reports

them inside the period.77 In addition, longitudinal studies are able to use more subtle

rneasures of socio-economic status that may indicate greater social class differences than

expeaed from cross-sectionai studies.

A more accurate measure of utilisation, which does not rely on patient recall, are

administrative data, including physician records or the records of health facilities such as

hospitals and clinics. These records, however, are sometimes inaccessible, expensive and

diflïcult to extract. Although administrative data does provide utilisation data, and iinking

census information on individual socio-economic characteristics with utilisation data is

possible, it is not appropriate to use such data in this particular context. This study is

interested in the characteristics of non-use as well as use of heaith services and

administrative data contaios only records on individuais who make contact with the

system. Ln addition, information uniaiiy does not exist about visits for which there is no

billable item, such as blood pressure checks." Administrative data files provide little

information on the characteristics of users of the heaith care system and nothing about

those individuals who do not use the systern. Therefore, most studies exploring the

patterns of heaith care utilisation have been based on cross-sectionai social surveys such as

the National Health Interview Survey (NEUS), the Canada Heaith Survey (CHS), the

Ontario Health Survey (OHS) and the National Population Heaith Survey (NPHS). Such

large scaie surveys benefit from their size and representativeness, range of variables

included, and ability to introduce statistical controls to ident@ spurious findings." A

household survey is necessary in order to obtain relatively complete estirnates for large,

generai, geographicaiiy defined populations on the use and non-use of many or ail

senrices, as well as information on relationships between health status, health care

utilisation and demographic factors.

Because the probabilities of inclusion in such surveys dBer among households,

moa analyses are weighted to take into account these unequal probabilities. Observations

are usudiy weighted in accordance with the reciprocal of the sample inclusion

probabilities. In the studies using a cross-sectional social survey where use and non-use of

physician care and the volume of seMce consumed are exarnined, computer packages

such as SUDAAN (SUrvey Design And ~ ~ a l ~ s i s ) ~ are used to calculate standard errors,

appropriately, to account for the sampling weights of the survey as weli as the complex

sample designsgl SUDAAN takes into account the complex muiti-stage, cluster sarnphg

design used in surveys like the NPHS. Without considering the survey design, the

standard errors would be biased downwards. This study did not use software nich as

SUDAAN. Instead a Jackknife variance program designed by Statistics Canada for the

NPHS was used. This program wiii provide standard errors which are closer to the "tme

variance" than the estimates obtained fiom SUDAAN.

There are several useful statisticai techniques to assess the relationship between the

dependent and independent variables that take on several values. Most analyses of

utilisation data found in the literature have been performed using either discriminant

analysis, analysis of variance, or regression analysis to examine the independent

associations of several predictor variables on the primary dependent variable.

5.1 Discriminant analvsis.

Discriminant analysis is a multivariate technique that is sometimes used in the

examination of categorical dependent variables such as the use and non-use of health

s e ~ c e s . ' * ~ ' ~ It determines the ability of sets of variables to "discruninate" among

individuais belonging to dBerent categories of a given variable. The objective of

discriminant analyses is to form one or more Iinear combinations of variables that

maximise the statistical dinerence between two or more identifiable groups (users versus

non-users).* The weighted coefficients of the discriminant function are used to assess the

direction of the relation between the dependent and explanatory variables, the statistical

significance of these relationships, and their relative importance or the contribution of each

predictor variable to the discrimination.

5.2 Analvsia of variance [ANOVAI.

The ANOVA method tests if there are any Werences between three or more

groups. The hypothesis tested is that the means are equal for each group. The total

variation from the mean cm be divided into the variation explained by the independent

variables and the variation due to random error. The mean sum of squares of both types

of variation are taken to form what is called the F-ratio. If the nuli-hypothesis of equal

means is true, then the F-ratio will be close to unity. Using the ANOVA method to test

for significaoce assumes that the data are both normally distributed within the dEerent

classes of the variable and homoscedastic (the variance tends to be the same in al1 classes

of the variable).

5.3 Muiti~le linear renression.

Multiple linear regression relates one or more independent variables to a dependent

variable following a normal distribution. When the volume of use is treated as a

continuous variable (i.e., the number of physician visits by those who have already made at

least one visit), multiple linear regression is sometimes used to examine the volume of

services consurned. 1*8'24 Multiple regrasion analysis is an improvement over ANOVA Ui

that it allows a larger number of independent variables. Through multiple regression

techniques, it is possible to assess the relative individual importance of various determinant

factors, the magnitude and direction of their influence, and the extent of interaction effects

between certain independent variables.20 This is accomplished by comparing the observed

and predicted values under two models, one with and one without the variable in question.

When assessing utilisation, one should not assume equal variances of use rates

with respect to the population of observations. Ordinary least squares regression

techniques are robust when enor terms in the dependent variables are normally

distributed. However, because the dependent variables representing utilisation usudy

have discrete variable properties and have a skewed distribution, the use of other

multivariate approaches are more appropnate. Although measures of utilisation are

inherently discrete (count of doctors' visits), predicted fiactional values of the number of

visits can be interpreted as probabilities of utilisation." Some investigaton argue that

because visits are count variables with large numbers of individuals having no visits and

the remaining respondents very skewed in their use, more ideal models are Poisson and

negative binomial regression methods that deal with the problems of both no visits and the

skewed distribution of visits among users.' The Poisson distribution provides a mode1 for

the number of visits during a given period of tirne."" However it has been found in a

study comparing mdtivariate techniques, t hat Poisson techniques offers only marginal

gains over the standard l e s t squares technique.86

Whereas multiple linear regression relates one or more independent variables to a

continuous outcome variable following a conditional normal distribution, logistic

regression analyses relate one or more independent variables to a dichotomous outcome

variable following a binomial or Poisson distribution." Logistic regression is based on the

same principle as linear regression, the cornparison of observed values of the response

variable to predicted variables obtained from models with and without the variable in

question. A model of the following form might be considered:

where P is the probability of making a visit to a physician. However, since the right-hand

side could be less than O or greater than 1 for certain values of xi,. . . ,xk, predicted

probabilities of less than O or greater than 1 could be obtained, which is not possible.

Therefore, the probit, tobit or logit transformation of P is ofien used as the dependent

variable.

in some literature, the examination of the use and non-use of health services,

likelihood equations are sometimes estimated with the use of a probit regession rnodeL6'

The assumption of the probit analysis is that the critical level at which an individuai

decides to seek health care varies f?om individual to individuai and the distribution of these

critical levels is normal. To estimate the parameters, one can apply maximum-likelihood

methods.

One extension of the probit model was proposed by Tobin and concems not only

whether or not there is use but aiso how much is used." The approach is based on a

specification in which the dependent variable (the amount of use) is equated to a linear

combination of explanatory variables with unknown coefficients, provided that this linear

combination is positive; otherwise, the dependent variable takes a zero value. As in the

case of the probit analysis, Tobin suggests the maximum likelihood method to estimate the

unknown coefficients. The problem with applying the tobit model to volume of use is that

it makes a very strong assumption; that when the mean of the normal distribution

increases, a) the probability of use wiil increase and b) the mean use of those users will

increa~e.'~ The implication of this assumption is that the effect of income will be the sarne

on the probability of use and the volume of use. In other words the tobit model imposes

equivalent parameters for the usdnon-use and volume of use stages, whereas the two-

stage method allows an added dimension. Therefore. it is unclear whether the tobit model

is suitable for the andysis of health care ~tilisation.'~ A more general model would

estimate separately the relationship between income and the probability of at least one Msit

and then investigate the effect of income on volume of use."

Many researchers prefer a logit analysis to a probit analysis due to the complexity

of its theoretical background and the weakness of the nomality assumption it is based

85 on. Logit malysis makes the necessary monotonie transformation of the probability

more directly by descnbing odds in favour of use as a log-linear function. Therefore,

many analyses in the literature assessing the relationship between health care use and

socio-economic statu use weighted multivariate ordinal logistic regression analyses.534

The logit transformation logit(p) is defined as:

Unlike p, the logit transformation c m take on any value from -00 to +m. tf Iogit(p) is

modeiled as a linear funaion of the independent variables XI,. . .,% then the following

multiple logistic regression model is obtained:

Solving for p, the model c m be expressed as

a+P x +...+f3 u a+P x +...+p ?r p=[e I I k4k]/[l+e 1 1 k k ]

The adequacy of such a model cm be assessed by using the score chi-square test

statistic for the proportional odds assumption. The strength of association between an

independent variable and the dependent variable can be expressed in tems of an odds ratio

afler controliing for the other independent variables in the model. The odds ratio is the

chance that an individual with a particular characteristic wiil use a seMce divided by the

chance that an individual without that characteristic will use the service. Cumulative odds

ratios and 95% confidence intervals describe and summarise the nature and magnitude of

the association between use and socio-economic statu and other relevant variables?

Weighted stepwise logistic regression using maximum likelihood methods to

estimate regression coefficients are usudy used initially to model the effects of multiple

variables on the individual outcornes. Stepwise regression methods were developed to

identiS, good, but not necessarily the best, models with much less computing than is

required for all possible subsets regression. The fonvard and backward stepwise models

are identified sequentially by adding or deleting, respectively, the one variable that has the

greatest impact on the residual surn of squares. However, these stepwise regression

methods f d to take ulto account the effect that the addition or deletion of a variable can

have on the contributions of the other variables to the model. Thei-e is a method,

however, referred to as the stepwise procedure which is actuaiiy a combination of the

backwards and forwards procedures. Like the fonvard stepwise selection, it starts with no

independent variable and selects variables one at a tirne. However, there is an additional

step, similar to the backward stepwise procedure, in which aii variables in each equation

are checked again to see if they remaui significant f i e r the new variable has been entered.

In general, the stepwise procedure is accepted as being superior to the backward and

fonvard stepwise procedures. 86

The model's fit is usually assessed by using a score chi-square test statistic for the

intercept and covariates or by examining the G' statistic (-2 times the logarithm of the

likelihood-ratio statistic) which approlcimates the chi-square distribution with degrees of

fkeedom given by the number of cells minus the nurnber of parameters fitted." In addition

to the G ~ , several analogues to the linear regression R* have been proposed for logistic

regression. Hosmer and Lemeshow proposed a measure, (ItZL,, cast in terms of log-

kelihoods." This R ~ L is a proportional reduction in ~2 or a proportional reduction in the

absolute value of the log-likelihood measure. It indicates by how much the inclusion of

the independent variables in the mode1 improves the goodness of fit. The R ~ ~ , varies

between O and 1, where 1 is a mode1 that predicts the dependent variable with perfect

acniracy. The overail explanatory power of the models using cross-section data to

explain heaIth care utilisation have been typically

6.0 Summary of the Literature

Moa studies of health seMces utilisation have illustrated that the most important

determinant of use is the level of need in the population as represented by a person's

hedth status. Aithough many early Canadian studies cornparing data before and d e r the

introduction of a universal health care insurance system concluded that its implementation

led to an increase in the use of physician s e ~ c e s by low income groups relative to high

income groups, these studies failed to control for the heakh care needs of the population.

Nevertheless, more recent studies that have introduced indicators of need as an

explanatory variable tend to arrive at sirnilar results; that need is the most important

detenninant of health care utilisation. These studies draw the conclusion that Canada's

health care system has been successful in providing equal access to health care services.

However, few studies, when examining the differential use of pubiicly-insured primary

physician and specialist physician services, separate GPs and specialists into two dserent

types of utilisation, and no nationally representative study has been done dealing with tbis

issue. McIsaac et al. found that those in higher income groups were more likely to make

at least one specialist visit compared to those in lower income groups. Therefore it may

not be sutticient to raise use by those in Iower income groups to optimal Ievels, because

disparities by class in the difTerent types of health care received may still exist. The

primas, purpose of this thesis is to explain, in a nationaily representative sample, the role

of socio-economic status in the dflerential use of publicly-insured, primary and specialty

services in order to assess the extent to which Canada's universai health care systern is

successful at ensuring access to physician care on the basis of need rather than socio-

econornic status.

Chapter DI:

METEIODS

Data fiom the National Population Health Survey (NPHS) was selected to mode1

physician visits due to its nationally representative nature and its broad range of variables

such as those related to socio-economic status, health behaviour, measures of health

status, and measures of utilisation. This chapter descnbes the sample design, the

questiomaire design, the data collection methods, weighting procedures of the NPHS and

estimation techniques. Further, the independent and dependent variables will be described,

justification for their selection will be given, and expectations of the? influence will be

exp t ained.

1.0 Survey

In 199 1, it was recommended by the National Health Information Council that an

on-going national survey of the health of the Canadian population be conducted.* This

recommendation was made in view of the econornic and fiscal pressures on the Canadian

heaith care system and the cornmensurate need for information on health and the

determinants of health.

The NPHS was designed and implemented by Statistics Canada and began its first

12- month cycle of data collection in Iune 1994; it is to be repeated every two years. It is

a national, population-based survey designed to collect Somation related to the heaith of

the population. The primary purpose of the survey was to provide more comprehensive

information on the curent health status of Canadians and to increase understanding of the

relationship between health status and health care utilisation." One of the main objectives

of the NPHS is to provide panel data that will reflect the dynamic process of heaith md

ilhess. The w e y conduded in 1994 produced cross-sectional information, but

subsequent cycles of the suwey are stmctured to provide both cross-sectional and

longitudinal estimates.

The NPHS provides a range of data that can be used to examine hedth status and

health care needs across Canada. The questionnaire includes compoaents on health status,

use of health services, risk factors, and demograp hic and socio-economic characteristics.

1.1 Sam~Ie Desien.

With the exception of individuals residing on Canadian Forces Bases and Indian

reservations, and individuals in the Yukon, Northwest Temtoties and in some remote

areas in Ontario and Quebec, the nirvey was designed to be representative of the entire

population of Canada aged 12 and over. The excluded sub-populations are estimated to

account for less than 3% of the total population.

Many h e m surveys such as the 1990 Canadian Health Promotion Survey coilect

information on only one member of the household, while other nirveys, such as the 1990

Ontario Health Survey, i n t e ~ e w ail household members." The approach used in the

NPHS is a compromise between the one-member and the ail-member approaches. The

survey coiiects most Uiforrnation fiom a single household member, but also limited health-

related information for aii household members, including socio-economic characteristics,

health care utilisation, and chronic conditions. This approach dows for in-depth

questioning of the selected respondent, yields a disaggregated sample with respect to

household characterisùcs, and simplifies longitudinal fo l l~w-u~.~ '

The NPHS used the multi-purpose sampling methods developed for the redesign of

the Labour Force Survey (LFS). These methods provide household surveys with

clustered samples of dwellings, thereby making the design very cost-effective for the

listing and collection of data.g1 The basic design of the NPHS is a multi-stage stratified

sample of dwellings selected within clusters. Each province was divided into three

categories; major urban centres, urban towns and rural areas. Wthin the major urban

centres, clusters containing approximately 150 to 250 dwellings or households were

constituted and stratified by geograp hy a d o r socio-economic char act eristics. Six

clusters, usually Census Enmeration Areas (Eh), are selected eom each stratum using a

randomised probability-proportional-to-size (PPS) samphg scheme, where size is the

number of households. Towns and mrai areas in each province were stratified within

geographical areas by socio-econornic characteristics. Six clusters are chosen throughout

the sample design to aüow a one-sixth rotation of the sample every month for the LFS?

Due to the fact that only one member in each sample household is chosen at

random to become the longitudinal panel respondent, the chance of an individual being

included in the panel would be inversely related to the number of persons in that

household. The panel would therefore under-represent persons coming fiom large

households, typicdy parents and children since they have less chance of being chosen, and

over-represent persons coming from small households, often single people or the elderly.

Thus, to enhance the representativeness of the panel, a rejective technique was applied?

The rejeaive technique involved identifjing a portion of the sample households for

screening, and dropping households that did not have at least one member under age 25.

In order to compensate for the "rejected" part of the sample, the weights for those

households containing no youths or children were boosted by another multiplicative

weight adjustment.

1.2 Questionnaire desien and data collection method.

The survey was comprised of two interviewer-administered components. Almost

al1 respondents were initially contacted in person. Many of the i n t e ~ e w s began in person

and were completed on the telephone, either because the selected respondent was not

available at the t h e of the initial visit or because the long intemiew time prevented the

completion of the i n t e ~ e w in one contact. The total interview took an average of one

hour in each household. In al1 dwellings, some information about al1 household members

was obtained nom a knowledgeable household member, usuaiiy the person at home at the

time of the interviewer visit. Initial contacts with the sampled households were face-to-

face and aU information was gathered with Cornputer Assisted Interviewhg (CAI). CA1

dows the questionnaire to be customised to the respondent based on the data colleaed at

that tirne which is recorded directly ont0 a laptop computer. Each question is represented

by a screen on the computer. After the answer to each question is entered, the next

question appears automaticdy on the screen. On-screen prompts are shown when an

invalid enûy is recorded and thus immediate feedback is aven to the respondent ancilor

the interviewer to correct inconsistencies.

The fmt component of the NPHS, the general component, collected limited

information on all members of the household. The second component, the health

component, was a more in-depth survey, administered to one randomly selected member

of each surveyed household 12 years of age or older. The general component was

completed by 2',725 households, resulting in a response rate of 88.7% and the heaith

component was completed by 17,626 individuais resulting in a conditional response rate of

96.1%.

This study will use oniy data derived From the health component of the NPHS. By

limiting the analysis to the health component the sarnple sire is decreased nom 58.439, the

number of records available for analysis in the general component, to 17,626, the number

of records available for analysis in the health component. Including only the health

component of the NPHS for analysis was necessary as there are several important

variables included in the health component that are not included in the general component,

such as variables pertaining to health s ta tu and health behaviour. Ln addition, the health

component of the NPHS may have an advantage over the general component with respect

to the accuracy of the data collected. In order to avoid the high cost and extended time

requirements that would be involved in repeat phone calls to obtain idormation directly

from each respondent, approximately 55% of the information collected for the general

component was obtained from one household member. Such proxy reporting oniy

accounted for about 4% of the information obtained for the health component.

As a resuit of its complex design, it is recornmended that ail analyses using data

nom the health component use two sets of weights. Fûstly, because the probabilities of

inclusion in the NPHS differed arnong households it was necessary to weight observations

for the purpose of data rnalysis. Therefore, observations were weighted in accordance

with the reciprocal of the sample inciusion probabilities. Second, each respondent is

assigned a weight to reflect the number of people in Canada that she/he represents. This

weighting factor is based on the inverse probability of selecting one specified member of

the household. The sum of these weights was the total non-institutionalised population of

Canada over the age of 12, which was approximately 24 million people in 1994.

Therefore when applying this weighting factor, the sample size essentidy becarne 24

million. When analysing data belonging to such a large sample size, small merences in

utilisation by different socio-economic groups of individuals become highly signuicant and

difncult to interpret. A method has been suggested by Statistics Canada that simplifies

model-building and interpretation of results; this method is used in the data analyses of this

study.'' The method consists of rescahg the weights on the records so that the average

weight is one. The rescaling was accomplished by using a weight equal to the original

weight divided by the average of the original weights for the individuals contribuhg to

the estimator in question.g0 Using these new weights d o w s the results produced by SAS

to be more manageable wbile still taking into account the unequal probabilities of

selection. These weights were used only in the rnodel-building process. Once the best

mode1 was selected the models were run again using the weights provided with the NPHS

data by Statistics Canada.

2.0 Dependent Variables

The main dependent variables are the number of GP and specialist visits and were

based on the responses to the following questions included in the NPHS: "In the past 12

months, how many times have you seen or tdked with a) a general praditioner/fdy

physician? b) another medical doctor (such as a surgeon, ailergist, gynaecologist,

psychiatnst, etc.)?" Because these questions ask if the respondent has seen talked to a

health professional, some of the visits may include telephone consultations. To calculate

use differentids for each factor, the outcome was analysed in two stages. The first

analysis yielded the proportion of users and non-users of primary care services. That is,

the population with no reported GP (or specialist) visits in the past 12 months was

compared with the group having reported one or more visits to a GP (or specialist). In the

second part of the analysis the subgroup of those who had one or more GP visits was

M e r divided to compare those having made 1-5 visits with those having made 6 or more

visits. The first stage of the analysis examines the influence of independent variables on

the variation between dierent groups in the probability of making at least one contact

during a specifled period. Those who have made at least one contact to a health care

practitioner have made access to the health care system. The second stage examines how

the same set of independent variables explains the volume of use or frequency of use

arnong those who have made at least one contact. In other words, the h s t stage of the

model is a mesure of the propensity to make use of hedth care services, the second stage

of the model is a measure of the intensity of use and overail utilisation of physician

services is equal to the propensity mdtiplied by the intensity of use. W~th respect to the

utilisation of specialist services, however, there are two types of analyses; the one

described above and the one that models specialist utilisation controlling for GP

utilisation. This is done by includuig a variable representing the predicted probability of

persons making six or more visits to a general practitioner which is a proxy for the

propensity to be referred due to " persistence" .

As was discussed in Chapter II, the decision to model those having made 1-5 visits

compareci with those having made 6 or more visits arose nom the observation that there

are a large nurnber of individuals who have made no visits and the rernaining respondents

are very skewed in theii use. Figure 1 displays the shape of the distribution for contacts

with GPs during a 12 month period. It is evident tiom the long tail to the right that a very

s m d proportion of people have made multiple visits. Further, those who use health care

seMces on a fiequent basis have been shown to have very different characteristics fiom

those who access the healtb care systern less frequently.' Therefore, it is logical to model

these two groups separately. The decision to divide the number of visits at those who

made 1-5 visits and those who made 6 or more visits was based on previous research and

the authors' observation that approlrimately 20% of the population made 6 or more visits

to a GP or speciaiist.' The highlight document of the Ontario Health Survey also used this

nit-point. An alternative method to deal with the positively skewed distributions of the

dependent variable is to take the natural logarithms of the amal number of visits.

However, this wouid destroy the meaningfulness of the unit of analysis (physician visits)."

The sensitivity of the results will be tested for at different nit-points (Le., 1-4 and

1-6 visits). That is, the second stage of each of the GP and specialist models will be remn

cornparhg those having made 1-4 (and 1-6) visits Mth those having made 5 or more (and

7 or more) visits. The results of this sensitivity analysis will be assessed to see if varying

the selected cut-point affects the final conclusions of the study.

3.0 Independent Variables

A brief description of the independent variables is given in Appendix 1. The

behavioural mode1 of health service utilisation, discussed in Section 3 of Chapter II,

provided a basis for selecting variables for modelling use by groups with different income

and education levels. The model outlines the different factors which help to determine the

health care that people receive and will serve as a guide in the selection of significant

variables to include in a model of physician utilisation. This behavioural model of health

s e ~ c e utilisation has been the most frequently used model to analyse the decision to seek

care and the volume of care used and has formed the basis for much of the empincal

iiterature over the 1st 20 years. 19,26,38,89 Independent variables which are believed to have

an e f f i on each outcome are divided into the four sets of factors proposed by the

behaviourai model: 1) Predisposing, 2) Enabling, 3) Need, and 4) Health Behaviour.

3.1 Predis~osing factors and physician utilisation.

Predisposing variables reflect the fact that some individuals have a greater

propensity to use seMces than do other individu al^.^' Predisposing variables can be

classified as either demograp hic characteristics (age, marital status, and w hether there are

any childreo in the household) or social structure characteristics (education and

immigration status). According to the model, individuals with different demographic or

social structure characteristics bave different types and arnounts of illness, resulting in

diEerent patterns of health services utilisation.

It is expected that the age of an individuai will be an important determinant of

physician utilisation." In particular, it seems reasonable to believe that the decision to

seek care and the volume of use wiil increase with advancing age due to the tendency for

physiological health to deteriorate over time. However, although age is primarily a

predisposing variable, it also has a need component and therefore, after adjusting for

health status, age may not have as great an effect on physician utilisation as one would

expect.*

The effect of education on physician utilisation is expected to be positive due to

the probability that the value of maintainhg or improvhg one's stock of health increases

with education. In addition, more highly educated individuals may be more informed

about the Canadian health care system and possess greater interactive skills which will

d o w them a higher level of access. This higher level of access is expected to be especiaily

evident when analyshg those specialist seMces that require the referral of a primary care

physician. Counter to this theory, it has also been argued that those with higher education

are more likely to possess the knowledge that aliows them to treat themselves and make

use of preventive services, resulting in a negative association between education and

physician use." According to Grossrnan's human capital rnode~,~' demand for health care

is derived fiom the dernand for health where health is viewed as an investment commodity

with the r e t m to investment being the increased arnount of heaithy time available for

work or leisure activities. The demand for medical care cm be seen to depend in part

upon one's income and education. Education is a proxy for knowledge and efficiency in

the use of information in combining own time and medicai goods and services to produce

gross investment. Increases in education lowers the irnplicit cost of investments in health

capital (the price effect, which increases the quantity demanded) while the improvement in

productive efficiency via a scale effect lowers the demand for medicai services. Assurning

the demand for health capital is elastic, those with higher education will demand more

medical services than those with lower education attainment.

Immigration status which has been associated with socio-economic status is also

expected to be a determinant in the use of heakh care services5 Although much of the

literature has found that recent immigrants have higher morbidity and lower self-rated

heaith status, it seerns reasonable to expect that recent immigrants to Canada wilI be less

likely to use health care seMces than those bom in Canada or more established

immigrants, due to possible language barriers, cultural differences in patterns of s e ~ c e

use, and Uflfamiiléuity with the Canadian heaith care ~ ~ s t e r n . * ' ~

Marriage has been found to be positively associated with health; however, once

income is controlled for, this effect often becomes in~ i~n i f i can t .~~ This suggests that much

of the positive effect of marriage on health is due to the higher incomes among those

married or living in common-law situations." Mamied and cornmon-law individuals, as

wel as those who have young children in their care, are expeaed to consume more health

care services than single individuals or those without young dependent children due to an

increased need to maintain their normal econornic roles and household roles. 8.a In

addition, married individu&, or those who are living in common-law situations rnay be

more likely to be motivated by a partner to seek care when syrnptoms become apparent.

3.2 Enabline factors and ~hysician utilisation

Enabling characteristics in the model reflect the fact that while the individual may

be predisposed to use health services, she or he will not use these seMces unless able to

do so!' Enabling variables can be classified as either farnily resources (income adequacy,

employment status and having a regular source of care) or comrnunity resources

(urban/rural and region in which one lives). See Appendix 3 for derivation of the variable

income adequacy. According to the model, if there are insufficient farnily or cornmunity

resources to enable the individuai to use health services then the individual will be less

likely to use those services.

The main objectives of Canada's universai heaith care system emphasise that the

utilisation of health care seMces be according to need rather than income or place of

residence. Under a universal health system, direct out-of-pocket costs are elimuiated and

therefore, unless there are indirect influences, utilisation should be independent of

economic factors. However, income has been argued to affect the utilisation of heakh

care services io a number of "non-enabling" ways. Lower income groups generdy have

poorer hedth and in mm use a higher proportion of health care. Therefore, one would

expect a negative relationship between income and the use of heaith care services. Also

supporting this negative relationship is the hypothesis that income is inversely related to

use due to the oppominity cost of lost work time.j3 That is, it is possible that the

consumption of health care seMces is more costly for an individuai earning a high income

than it is for an individual ea-g a low income. In tum, one would expea the use of

health seMces to be higher arnong lower income groups than it would be among higher

income groups. However, evea though the length of tirne taken by persons with lower

income represents a lower nominal value than those with higher income, the real value of

the dollar of the individual may be higher for low income individuals than for higher

income individuals. According to this hypothesis, a positive relationship between income

and health care utilisation is possible. Furthemore, the mesure of health status used may

not capture all dimensions of need; it is therefore possible that persons in lower income

groups will exhibit a greater propensity to seek care than those in higher income groups.

The NPHS provides a variable that enables the statistical adjustment of income to account

for Merences in family size as it is kely to impact economic purchasing power and

socio-economic status (see Appendix 3).

It is expected that availability of health care improves as the size of the community

in which the individual resides increase~.~ That is, individuals who tive in urban areas d

be more Likely to seek health care and consume a greater volume of health care due to Iess

travel the , greater abiiity to reach services, and a greater physiciadpatient ratio. This

pattern is expected to be most apparent when anaiysing specialised services, which tend to

be located in &an areas.

Regional Merences in utilisation of health care sewices are expected to exist in

both type of s e ~ c e and volume of services consumed, with poorer regions having less

access to care. In particular, previous research has found that there is a signincantly

greater probability for consulting a physician in Ontario and British Columbia perhaps

because these provinces have the greatest physician to population ratio!'

It has been shown that there are substantial health difEerences between the

employed and the unemployed, with the latter reporting more health probierns and making

more visits to physicians than the employed." Aside ftom health differences unemployed

individuals are anticipated to exhibit a greater propensity to seek treatment and consume

more care than their employed counterparts because employment status can be viewed as

a substitute for opportunity costs that are incurred when health care is consumed. The

dollar value of time lost when visiting a physician is lower for an individuai who is not

working than it is for an individual who would otherwise be eanllng money during that

tirne.

Access has sometimes been measured in tenns of whether or not an individual

identifies with a regular GP.~' Having a regular medical doctor has been found to be an

important correlate of h e m care utilisation. 24,41,78 Whether having a regular GP irnproves

efficiency or promotes better quality care has not been a widely researched issue; however,

it is hypothesised that the degree to which persons are considered to have a reguiar f d y

physician affects such outcornes as the use of physician services, the receipt of

recommended preventive service^,^' and the use of waik-in clinics and hospital emergency

departrnents.

3.3 Variables in di catin^ need.

The behavioural mode1 asserts that even in the presence of the appropriate levels

of predisposing and enabling characteristics, individu& must perceive some need for using

physician s e ~ c e s ? It is expected that the factors most strongiy related to physician

utilisation, both primary and specialist care, wiii be those representing need for medicai

care represented by health status. Health statu will be controlied for by using perceived

health relative to other persons of comparable age and the number of health problems (see

Appendix 4 for a description of this variable). Self-perceived health status has been shown

to be the most important deteminant of both GP and referred seMces use.35 Although

these measures of health status do no? include a professionai, objective evaluation of need,

the number of chronic diseases may, in part, represent idormation obtained fiom a

physician about the health problems of an individuaL3'

3.4 Health Behaviour.

Several health behaviours were considered: the smoking status of the respondent,

the smoking status of other household members (to include the effect of passive smoking

exposure), the number of alcoholic drinks consumed per week, and a physical activity

index.

The association between lifestyle and health is weii-known. Lifestyies consisting

of negative health behaviour display a definite socio-economic gradient. For instance, the

percentage of smokers is higher in less educated and lower incorne g r o ~ ~ s . ~ ~ ~ '

Furthemore, those in higher educated and higher income groups tend to be more involved

in regular physicai exercise, which in tum, reduces the risk of ihess and premature

death?% However, the effects of these different heaith behaviours on health care

utilisation are unclear. It couid be argued that those who are concemed with maintaining

and improving their health stock and engage in positive health behaviours will be healthier

and therefore less likely to seek care. An alternative argument however, is that seeking

hedth care, to a certain extent, is a means of maintaining and improving the value of

health aock. Thus, it is possible that individuals who engage in positive heaith behaviour

will be more likely to consume hedth care setvices than those who do not.

3.5 GP utilisation as an inde~endent variable.

When modelling the utilisation of specialist services, the inclusion of a variable

representing the predicted probability of persons making six or more visits to a GP has

been found to be ~ignifcant.~ In Canada, access to many specialised health care services

requires a referral fiom a GP. It seems reasonable, therefore, to expect a positive

association between the probability of consulting a specialist and the probability of

consulting a GP. Assuming such a relationship exists, any significant results indicating

differential access to specialist care utilisation by socio-economic status may be in fact due

to diffierential access to GP s e ~ c e s . Therefore it is important when assessing the

utilisation of specialist care to include a variable representing access to primary care.

Once controlling for Werential access to GPs by socio-economic status by the inclusion

of this variable, a positive gradient is expected, that is, greater specialist utilisation as

socioeconomic status rises f ier controlliag for GP utilisation. It is expected that this

retationship will not be as strong when GP visits are not controlled for. The mode1 of

specialist utilisation will be examined both with and without controlling for GP utilisation.

Due to the correlation berneen the explanatory variable GP visits and the dependent

variable specialist visits, it may not be appropriate to apply ordinary logisitic regression.

The specialist equation postulates that specialist visits are detennùied in part, by whether

or not one makes a visit to a GP because a specialist visit usualiy requires a visit to a GP

first (i.e. the probability of making a GP visit is a risk factor for making specialia visits).

Applying logistic regression to the equation may result in inconsistent estimates due to the

likely correlation between the stochastic explanatory variable GP and the independent

variable. A more appropriate method of obtainîng consistent estimates is Instnimental

Variable Estimation or a two-staged least squares approach.lOO This method involves first

estimating the determinants of GP visits and substituthg the predicted values for the

'amal' values of the GP visits into the equation estimating the determinants of specialist

visits with GP visits as a separate independent variable. Therefore, modelling the

probability of seeing a specialist included a variable representing the predicted probability

of persons making six or more visits to a generai practitioner which was estimated by

instrumentai variable estimation.

4.0 Analysis

The data fiom the NPHS was provided by Statistics Canada to the Data Library at

the University of Toronto and was downloaded to a personal cornputer for anaiysis using

the statistical software program SAS. Due to the fact that the NPHS is based upon a

complex design with stratification and multiple stages of selection and unequal

probabilities of selection of respondents, the variances that are calculated by statistical

packages such as SAS may be incorrectw Therefore, in order to account for the complex

muiti-stage, cluster sampling design used in the NPHS, it is necessary to obtain actual

variance estimates for the specific variables used which are othenvise unreleaseable due to

confidentiality reasons. The exact coefficients of variation are obtained via an exact

variance program, developed by Statistics Canada, which uses a technique called

'Tackkninng". This technique involves dividing the records on the microdata files into

subgroups (or replicates) and determining the variation in the estimates fiom repiicate to

replicate.90 Although SAS allows sampiing weights to be incorporated in the analyses, the

variances that are produced often do not take into account the stratified and clustered

nature of the design properly, whereas the exact variance program would.

AU "not-stated responses were replaced with the median response, calculated

using the SAS procedure W A R I A T E . The number of "not-stated" responses to the

survey was very Iow. For all questions used in this study, fewer than 1% were in the not-

stated category, with the exception of the physical activity index and incorne adequacy

which were both around the 4% level. Further details concerning missing values are

contained in Appendk 2. Females and males were analysed separately. It is useful to

assess the ciifferences in physician utilisation between females and males instead of

averaging results for both genders. Females are expected to use more physician seMces

than d e s due to visits unreIated to disease such as reproductive health. In addition, their

use of physician services may ciiffer by other factors such as socio-economic status.'l

Examùiing physician utilisation according to sex allows an examination of gender-specific

socioeconornic-utilisation patterns which is not be possible when analyshg the behaviour

of females and males cornbineci.

uitialiy four moads were formed. Two compared the population of GP and

specialist users (one or more visits) with non-users; the other mode1 looked at the

subgroup of users and compared those with 1-5 reported GP and specialist visits to those

with six or more visits. Further, the specialist models were also nui without controhg

for GP visits.

The analysis began with a univariate analysis of each variable. Variables were

examined for statistical significance in contingency tables with each of the GP use and

specialist use outcomes, versus the different levels of each independent variable. The

weighted SAS procedure FREQ was used to obtain the likelihood ratio chi-square to test

the hypothesis of no association between the independent variable and outcorne. The

weighted non-linear relationship between the probability of making a visit and the

independent variables was transformed into a linear relationship between the logit of the

probability of making a visit and the predictors with the logit of the probability as the

response variable. Further analyses of each variable were performed with the use of the

SAS procedure LOGISTIC. Each independent variable was modelled separately with GP

use and speciaiist use outcomes, to yield the estimated coefficient, the estimated standard

error, the univariate Wald statistic, and the unadjusted odds ratios (obtained by raising the

estirnated coefficient to exponents)." The 95% confidence intervais for the odds ratio

were caldated and examined to determine if they contained one.

Multivariate logistic modelling was undertaken for each of the four models. Ody

the variables that were found to be sigdicant at the p<.25 in the univariate analysis were

selected for inclusion in the rnultivariate analysis. Age was forced into al1 models based on

a priori expectatioos concerning its relationship between incidence of The models

initialiy were fit using stepwise regressiong7 with a cut-off for inclusion of pC.05 using the

Wald aatistic." The Wald statistic for each variable was exarnined and each estimated

coefficient was compared with the coefficient fiom the univariate model containing only

that variable. Coefficients were estimated using maximum likelihood estimation., which

provides consistent and unbiased estimates. Once the model-building process was

complete, the final SAS programs were sent to Statistics Canada to be nin using exact

variances. It was necessary for Statistics Canada to run the final models for the anaiysis

because the actual variance estimates for specific variables are not releasable to the public

due to confidentiality reasons.

4.1 Goodness-of-fit.

The overd goodness-of-fit of the regression models was evaluated in two ways.

Firstly by the G~ statistic, which is equal to -2 times the logarithm of the likelihood-ratio

statistic. The output of the SAS logistic procedure provides the G~ statistic associated

with the model and can be used to carry out a likelihood ratio test for any variable. The

likelihood ratio test, whicb is similar to an F-test in O.L.S., measures the overail

sigmficance of the model by comparing the G* associated with the model that includes the

variable in question and the G~ associated with the model that does not include the

variable in question. Due to the large sample size, the Merence between these two -210g

likelihoods will be approximately distributed as a chi square statistic ( X 2 ) with degrees of

fkeedom equal to the dinerence in the nurnber of estimated parameters in the two models

(under the nul1 hypothesis that the variable has no effect on visits). Variables that did not

contribute to the model based on these cnteria were eliminated and a new model was fit."

Therefore, overall model fit was assessed by the statistical significance of each additional

or removed parameter tested by the likelihood ratio test, which is the difference of the

maximised loglikelihood statistics for any two models. The ha1 models include only the

statistically biologically signincant variables and were found significant at p<. 05.

Secondly, a generalised coefficient of determination, R*, was caiculated for each

model to evaluate the goodness of fit. This rneasure was developed by Cox and ~ne l l '~ ' :

R~=I- @(0)/L(f3)}"

where L(0) is the iikelihood of the intercepts-only mode1 L(P) is the likeiihood of the

specified model and n is the sarnple sizee.1' R* indicates how much better the dependent

variable can be predicted fkom the independent variables than the dependent variable could

be predicted without the information about the independent variable^.^' Higher values for

R~ indicate a p a t e r level of explanatory power for the estimated equation. It is expected

that only a s d proportion of variance in physician visits be explained as this is typical of

studies attempting to explain patterns of physicians ~tilisat.ion.~~*~~ A typical R* for such a

study ranges from 6 to 1 5.

Table 2 contains the G* and the adjusted c coefficients for each model.

Cbapter IV: RESULTS

1.0 Descriptive Statistics for Physician Utiiisation

The results are presented separately for the usdnon-use of seMces and the

frequent use and non-frequent use of GP and specialist services. There were 18 341

people over 12 years of age surveyed for the health component of the NPHS. The

conditional response rate for the heaith compoaeot of the survey was 96.1%, resulting in

1 7 626 individuals (9 568 females and 8 058 males) available for this analysis. As seen in

Table 2 this was equivalent to a population of 12.2 million females and 11.8 million males

over the age of 12 in Canada in 1994. There were 99.7% females and 99.8% males with

cornplete information on GP visits and 99.9% females and 99.9% males with complete

information on specialist visits.

Table 2 displays the mean and median numbers of visits, the percentage of

Canadians making no visits, at least one visit and at least 6 visits to GPs and specialists.

The mean number of visits for Canadians over the age of 12 was 6.11. Approxirnately

77% of the population had at least one self-reported visits to a GP in the previous 12

months. Females made more visits to GPs than males. The mean number of visits to GPs

was 7.10 for women (median=2) and 4.94 for men (rnedian=l). In the previous year,

82.66% of females and 7 1.63% of males experienced one or more GP visit. Of those who

visited a GP in the previous year, 26.74% of females and 1 7.94% of males made 6 or more

visits. Femaies aiso made more visits to specialists than males. The mean nurnber of visits

to a specialist was 1.86 (rnedian4) for females and 1.56 for males (median=û). There

were 3 1.98% of females and 20.13% of males who reported having made at least 1 visit to

a specialist in the past year. Of these, 1 6.8 1 % of femaies and 1 3.06% of males made six

or more visits. Although these figures have not yet been adjusted for dflerences in the

age distributions between females and males, they suggest that women report making

greater use of health care services, primary and specialist. As cari be seen from Figure 3,

on average males make use of specialist services less than females; however, they seem to

use them more intensely. That is, of those who visited a specialist, the mean number of

visits were greater for men then for women, 7.8 versus 5.58 visits. The proportion of

females and males making at least one visit to a GP and the proportion of females and

males making at least one visit to a specialist, controllhg for age and sex, is displayed in

Figures 2 and 3. It is expected that during the childbearing years (1 5-44), females will use

more health care services than males due to visits unrelated to disease, such as

reproductive health. As seen in Figure 2, it is between these ages that the merence in

utilisation of physician services between females and males is the greatest. Of M e r

interest, as show in Figures 2 and 3, under the age of 65 females reporting at least one

visit to a GP and specialist are consistently greater than males. However, after the age of

65 males consistently report making at least one visit more than females. This pattern is

even more apparent when examining the percentage of the population reporthg one or

more visits to a specialist in Figure 3.

Table 3 displays the Goodness-of-Fit measures; the -21og likelihood (G*) and the

Coefficient of Determination (R2=). The low levels of explanatory power are cornrnon for

studies of this type and are not of major concern.

2.0 The Utilisation of GP services

2.1 At Least One Visit to a GP (Non-use Versus Use)

The characteristics associated with having made at least one visit to a GP in a one-

year period and the adjusted and unadjusted odds ratios for females, males, and both sexes

are displayed in Tables 4, 5, and 6 respectively. The first column in Tables 4, 5, and 6

represent the unadjusted percentage of females and males in each group with one or more

visits to a GP in the past 12 months. These percentages can be compared with the overall

percent, displayed in Table 2, to determine if the group is above or below the average rate

of use by the baseline group.

2.11 Variables indicating need.

The results suggest that the medical needs of individuals, as measured by the

number of health problems and perceived health status, significantly increase the

propensity to make at least one visit to a GP in a year. That is, the largest gradients of

visit fiequemies (measured by the odds ratios), occur for the variables representing

medical need. Increasing numbers of health problems and poorer perceived health status

show a strong positive association with having made at least one visit to a GP. The

adjusted odds ratios for wornen aad men with four or more health problems having made

at least one GP visit compared to those women and men with no health problems, were

1.95 and 2.45, respectively as shown in Tables 4 and 5. Furthemore, there was a clear

relationship between decreasing levels of self-reported health status and making at least

one visit to a GP. Women and men with poor perceived health status were rnuch more

likely than those who rated their health as excellent to have made at least I visit (0R=2.28

for women and OR4.44 for men, as shown in Tables 4 and 5).

2.12 Predis~osine Variables.

Predidably, with advancing age, the proportion of those making at least one visit

to a GP increased for both females and males. However, after controlling for other

variables in the model, this gradient became less apparent, with the middle age group (45-

64 years) being the least likely group to make one visit to a GP.

Females and males with post-secondary education were more likely to make use of

GP seMces thau those without post-secondary education. The unadjusted proportions for

those with less than a completed high schooi education making at least one GP visit were

8 1% for women and 71% for men, compared with 83% of women and 73% of men having

completed at least some post-secondary education. Once adjusted for other variables in

the model, the estimated odds ratio between the two most extreme levels of education

attainment for men having made at least one GP visit was 1.3 1 and for women was 1-45

Single males and femaies were less liely to become users of primary care seMces

in the past year than those who were currently married and those who were widowed or

divorced (adjusted OR=.73 for males). Widowed or divorced females were signincantly

more likely to make at least one visit to a GP in the past year than were those females who

were presently married or had never been married (OR=1.2 1).

There was no significant ciifference in the probability of individuais making at least

one visit to a GP by income. 77.72% of those in the lowest income level made at least one

GP visit compared to 77.76% in the highest income group (not shown).

2.13 Enabiine variables.

Both before and after adjusting for other variables in the model females and males

from Quebec were sigdicantiy less likely than those in any other region to make use of

primary care services. Compared to males living in Ontario, males from Quebec had an

odds ratio of .47 compared to Ontarian males. Males from Ontario were the most tikely

to make one GP visit when compared to males living elsewhere in Canada.

Those living in an urban community were more likely to make use of GP seMces

than those living in a rural community (adjusted OR4.42 for femaies and males

combineci). Women and men who responded "yes7' to having a regular medical doctor

were more likely to have made at least one visit to a GP ( O R 4 19, OR=3.28).

2.14 Health behaviour.

Both females and males reporting non-smokers residing in the household were

sigmficantly more likely to see a GP.

For fernales, but not for maies, the number of aicoholic drinks consumed per week

was sigdicantiy associated with making at least one visit to a GP. Females consuming

betweea 1 and 1 1 drinks in a week were 1.2 times more likely to visit a GP in the past 12

rnonths than femaies coasuming no aicohol in a week.

Although most of the variables that were found to be sigmficant at the pC.05 level

were the same for females and males, there were some that were difTerent. For instance,

there was no significant merence between females in dif5erent age categories making at

least one visit to a GP. A fernale's working status was not a significant determinant of

making a visit to a GP, whereas those males, who did not work in the Fast year were more

likely to rnake at least one visit to a GP than those who were working at the time of the

survey (adjusted OR= 1.26).

2.2 At least Six Visits to a GP Mon-freauent Use vs. Freauent Use)

The characteristics associated with having made at least six visits to a GP in a one

year period and the adjusted and unadjusted odds ratios for females, males, and both sexes

are displayed in Tables 7, 8, and 9 respectively. The tirst column in Tables 7, 8, and 9

represent the unadjusted percentage of females and males in each group with six or more

visits to a GP in the past 12 months.

2.21 Variables in di catin^ need.

The number of heaith problems and poorer perceived health status again displayed

the strongest association with being more likely to make six or more visits to a GP in a

one year penod for both females and males. Femdes with four or more heaith problems

had an odds ratio of 1.65 compared to females with no health problems. For males with

four or more health problems, the odds ratio compared to males with no health problems

was 4.25. Self-rated health status displayed a much stronger relationship with the

probability of making six or more visits than it did with the probability of making at least

one visit to a GP, for both females and males. Those females who perceived their heaith

as poor had an adjusted odds ratio of 1 1-89 compared to females who perceived their

health as excellent. Males who reported their health status as poor had an odds ratio for

making six or more GP visits of 12.40 compared to males who regarded their health as

excellent.

2.22 Predis~osine variables.

For males but not for females, increasing age was associated with being more

likely to make six or more visits to a GP afler adjustment for need and the other

characteristics in Table 8. Males who were 75 years or older had an adjusted odds ratio of

2.3 3 compared with males in the 12-24 year age group. However, the absolute proportion

of females and males over the age of 75 making six or more visits was quite similar, 40%

for females and 37% for males, indicating that the merence is probably due to females

consuming a higher volume of services during the chiid-bearing years.

The absolute proportion of femaies making at least six visits to a GP suggests that

females with a lower attained level of education are more likely to use GP seMces than

those with higher attained education levels; 29% of females with less than a high school

education compared with 22% of females with post-secondary education. However, once

adjusted for other factors in the table, females in the lowest education group were slightly

less iikely to make six or more visits to a GP than those with post-secondary educatioq

the latter, having an odds ratio of 1.12.

Femaies with young chiidren were more likely to make six or more visits with an

odds ratio of 1.26 compared to females without children residing in the household.

2.23 Enablin~r variables.

Whereas varying income groups displayed no dflerence in the probability of

making at least one visit to a GP, this was not the case for persons making fiequent use of

GP services. There were 33% females and 25% males in the low income groups making

six or more visits to a GP compared with 19% and 15% in the highest income group. In

generai, higher income levels, holding other things constant, were associated with being

less likely to make six or more visits to a GP. Aiter adjusting for the other sigdcant

variables in the mode1 there were some signincant dBerences amoog income groups in the

probability of making at least six visits to a GP. Females and males in the three highest

levels of income were less likely to make six or more visits to a GP in the past year.

As was the result for the probability of making at lest one visit to a GP, Quebec

males and females were the least Uely to be high utilisers of GP services, with those from

British Columbia being the most likely to be high utiiisers. Females and males with a

regular medicd doctor were more likely to make six or more visits to a GP with females

havhg an adjusted odds ratio of 1.62 and 2.16 for males.

2.24 Health bebaviour.

Whereas females consuming 1-1 1 alcoholic drinks per week were more likely to

make at least one visit to a GP in the past year, females and males combined consuming 1-

11 drinks were less likely to make 6 or more visits to a GP (OR=.84 and O.R=.79 for

females and males respectively). For femaies and males combined, there was a sigrilficant

gradient with respect to the amount of alcohol consumed.

3.0 The Utilisation of Specialist Services

3.1 At Least One Visit to a Swcialist CUse Venus Non-use)

The characteristics associated with having made at least one visit to a specialist in

a one year period and the adjusted and unadjusted odds ratios for females, males, and both

sexes are displayed in Tables 10, 1 1, and 12 respectively. The fira column in Tables 10,

11, and 12 represent the unadjusted percentage of fernales and males in each group with

one or more visits to a specialist in the past 12 months.

3.1 1 Variables indicatine need.

Jua as in the analyses of making at lest one visit and making six or more visits to

a GP, increasing nurnbers of health problems and poorer perceived health were associated

with being more likely to have made at least one speciaiist visit. The variable representing

the predicted probability of making at least six visits to a GP did not show a significant

effect on the iikelihood of visiting a specialist.

3.12 Predis~osine variables.

Increasing age was associated with an increasing Wrelihood of havhg seen a

specialist for males but not for females. However, unlike the analysis of six or more visits

to a GP, the results of this analysis indicated that the proportions of femaies and males

over 75 making at least one visit to a specialist quite different (28% vs 3 6%).

Females and males in the highest education level were more likely to see a

specialist than those with the lowest level of education attained. Compared to those not

having completed high school, females with a post-secondary education had an odds ratio

of 1 -86 and males had an odds ratio of 1 -39.

3.13 Enabline variables.

Although the absolute proportion of both males and females seeing a specialist was

quite similar arnongst different income groups, after controlling for need and other

characteristics, a positive relationship between income and seeing a specialist is evident.

Twenty-seven percent of fernales in the Iowest income group made at least one visit to a

specialist compared with 30% of fernales and males in the highest incorne group. After

controllhg for other variables, individuals making at least one visit to a specialist displayed

a gradient, with high income individuals compared with low income individuals having an

odds ratio of 1.69 of seeing a specialist at least once. This is exactly the inverse of the

relationship noted earlier for the probability of seeing a GP six or more times during the

Y=r*

It was expected, that the relationship between socio-economic statu and specialist

utilisation would be stronger once the probabTty of making fiequent use of primary care

seMces was controlled for. However, as can be seen 60m Tables 10 to 15 the predicted

probability of GP visits was not a significant factor in determining the probability of

making a visit to the specialist. Tables 19% 19b and 19c display the effect of education

and income on visits to specialists with and without controlling for GP visits. From these

tables there is no difïerence in the direction or sign<ficance of the effect of socio-economic

status once GP visits are controlled for.

In the analyses of utilisation of GP services, individuals residing in Quebec had a

lower likelihood of using GP services; however, in the analyses of the utilisation of

specialist services, femaies and males from Quebec were the most likely to make at least

one visit to a speciaiist compared with those residing elsewhere in Canada. Individuais

residuig in British Columbia were the least likely to visit a specidist. Individuals residing

in an urban community were significantiy more likely to consume health care s e ~ c e s

(OR=1.45). Males who had a regdar medical doctor were more likely to make at l e s t

one visit to a specialist, with an odds ratio of 1.63. However, femafes with a regular

medical doctor were slightly less likely to make sut or more visits to a specialist, witb an

adjusted odds ratio o f . 7 1.

3.14 Heaith behaviour.

Males reporthg consumhg 1 - 1 1 more alcoholic drinks in a week were more Likely

to see a specialist (OR=!. 18). Males reporting to be inactive were significantly less likely

to see a specialist compared to those males reporting to be active (OR=.80).

3.2 Six or More Visits to a Speciafist (Non-Freauent Use Versus Freauent Use)

The characteristics associated with having made at least six visits to a specialist in

a one-year period and the adjusted and unadjusted odds ratios for females, males, and both

sexes are displayed in Tables 13, 14, and 15 respectively. The fïrst colurnn in Tables 13,

14, and 15 represent the unadjusted percentage of females and males in each group with

six or more visits to a specialist in the past 12 months.

3.21 Variables indicatine need.

Poorer perceived heaith stahis was associated with males and females being more

kely to use specialist seMces more fiequently. However, contrary to the other three

models, the number of health problems was not sigruficantly associated with the

probability of making at least six visits to a specialist. Those with a regular medical doctor

were sigdicantly more likely to make six or more visits (females OR=2.12 and males

OR=3.75). The predicted probability of making at least 6 visits to a GP was not a

sigruticant factor in explaining the eequent utilisation of specialist services with the

exception of the mode1 combining females and males. Females and males having made sÏx

or more visits to a GP were over two times more iikely to have made at least six visits to a

specialist (adjusted OR=2.43).

3.22 Predisposine variables.

hcreasing age was significantly associated with males but not females being less

likely to make six or more visits to a specialist. M e r adjustment, males 75 years or older

had an odds ratio of 0.21 compared to males between the ages of 12 and 24.

Females having at lest completed high school were more tikely to consume a high

volume of specialist services than those having attained a lower level of education.

Men with young children residing in the household had an odds ratio of 0.42

compared with those men without young children, whereas femdes with children under

age 12 residing in the household were more likely to make six or more visits to a specialist

(OR= 1.49) than those without young children.

3.23 Enabline variables.

Contrary to the fïndings for the probability of making at least one speciaiist visit,

the income group to which one belongs and the province in which one resides had no

significant effect on whether one consumes a high volume of speciaiist services.

Females living in an urban community were sigmficantly more likely to consume a

higher volume of specialist visits (OR= 1 .19).

3.24 Health behaviour.

Inactive females displayed a greater propensity to consume a hi& volume of

specialist seMces than active individuals ( O R 4 -32). Females and mdes r e p o h g to be

inactive were sigdicmtiy more likely to visit a specialist 6 or more h e s than those

reporting to be inactive (O.R=1.29). Non-smoking fernales were less likely to make 6 or

more visits to a specialist than those femaies reporting to smoke daily (O.R=.83).

3.25 Seasitivitv Andvsis.

The sensitivity of the results were tested for different cut-points for the models

explaining the probability of making at least six visits to a physician. The analysis was

r e m to mode1 both the probability of making at least 5 visits and at least 7 visits to see if

varying the selected cut-point af5ected the final conclusions of the study. Appendices 5

through 9, display the odds ratios for the probability of making at least 5, 6 (baseline) or 7

visits to GPs or specialists. When comparing the results of the probability of making at

least 5 and 7 visits to the baseline, it is apparent that neither the direction nor the

mapitude of the resultant odds ratios Vary substantially.

4.0 Factors Related to Having a Reguiar General Practitioner

Table 16 displays a univariate analysis of factors that have been shown in the

Literature to be associated with having a regular medical doctor. It was found that 13% of

ail respondents lacked a regularly-visited GP. Those in lower income groups were found

to be more likely than those belonging to higher income groups to lack a regular GP. As

would be expected, Canadians with a greater number of health problerns and poorer health

status were more likely to report having a regular medical doctor. It then follows, due to

the positive relationship between income and healtb, that those with lower income would

be more likely to have a regular medical doaor. However, fiom Table 16 it can be seen

that the opposite is m e . There was a gradient effect for femaies and males; those with

lower incornes were less Iikely to have a regdar doctor than those in higher income

groups. This f i n h g is interesting and begs the question that the inclusion of this variable

(having or not having a regular medicai doaor) may hide the impact of income on the

utilisation of health care services.

Chapter IV: DISCUSSION

This study has described Merences in the utilisation of generai practitioner and

specialist seMces by females and males with varying socio-demographic attributes. Its

primary objective was to explain in a nationally representative sample, the role of socio-

economic statu in the differential use of publicly-insured, primary and specialist s e ~ c e s

in order to assess the extent to which Canada's universal health care system guarantees

socio-economic equity in the use of physician services. The results of this study are

comparable to the hdings nom the 1990 Ontario Health Survey (OHS) that lower incorne

groups are more likely to make frequent use of prirnary health care and less likely to make

use of specialist health care than higher socio-econornic groups.5 However, there were

some important ciifferences found between the two studies which need to be addressed.

1.0 Socio-Economic Status and Access to Physician Senices

A universai, publicly-finded medical insurance program was justified on the

grounds that al1 Canadians should have access to health care seMces on the basis of need

rather than economic status. For the purposes of this thesis, access is defined as physician

utilisation in accordance with need, as measured by self-perceived health status and the

number of health problems. Equal access is said to be achieved when income is no longer

a disadvantage in the utilisation of physician seMces or when there is no positive socio-

economic gradient between income and utilisation for a given level of need. Access to

health services continues to be a major policy goal based on the assumption that improved

access to health care WU lead to improved health ~tatus.'~ In theory, universal health

coverage should result in health care utilisation being unrelated to socio-economic status

and being determineci instead by health need. However, though financial barriers may not

impede equd access to primary hedth care in Canada, resuits from this study suggest that

difFerentiaIs in the use of physician services penist.

The factors found to be moa consistently related to physician utilisation, for both

primas, and specialist care, were the indicators of heaith need. Self-perceived heaith

status was strongly related not only to access to prirnary care and specialist care but aiso

to the frequency of their use. The number of self-reported health problems was also

strongiy related to the use and tieguency of use of primary care and to the use of specialist

services. By and large, these results agree with most Canadian studies whose results

indicate that need is the most important determinant of health care utilisation.

Table 17 displays a summary of the effect of income and education on visits to

GPs and specialists. Wtth regard to the association between income and physician

utilisation, the findings confirm the results of McIsaac et al. that there was no difference

by household income for either females or males in the probability of making at least one

visit to a general practitioner during a one-year period. The fact that the use of primary

care services is independent of incorne supports recent iiterature in the contention that

under Canada's universal health care system, economic status plays no direct role in

influencing the decision to seek care from a general pra~titioner.'*'*~ However, it should

be noted that socio-econornic status is significantly negatively correlated with having a

regular medical doaor which is, in tum, related to the decision to make a visit to a

p hysicim.

When exatnining factors associated with making fiequent use of p r i m q care

services. the results of this study. again, confirm the findiigs nom the OHS data that

females and males in high incorne households were less likely to make six or more visits to

a general practitioner, compared to those in low income households. It could be argued

that this gradient is evidence for the inequity in the distribution of physician services in

favour of low income groups; that the weil-off members of society are disadvantaged in

their use of services. A more iikely explmation, however, is that the measures of health

status used in this study failed to capture al1 dimensions of need. Because need is

inversely associated with income, it is not surprising that individuals in low income groups

were more likely to use primary care seMces on a fiequent basis. This result may also

suggest that the opportunity cost incurred when an individual visits a general practitioner

is significant and inversely related to the fiequent use of primary care. Taking the time to

visit a physician may be more costly for an individual eamlng a high income than for one

earning a low income. Therefore, one might exped the use of health services to be higher

among lower incorne groups than it would be among higher income groups due to the

opportunity cost of lost work time.

In most instances, the effect of education on physician utilisation was significant

and positive. Females and males with at least a high school education were more likely to

d e use of physician seMces and were more iïkely to use these seMces on a fiequent

basis than were those not having at least a high school education. This result was

expected due to the likelihood that as one's level of education increases so does the value

of rnaintaining or improving one's stock of health4 Referrhg back to Grossrnan's modei,

education is a proxy for knowledge and efficiency in the use of information and in

combining one's own time and medicai semices to produce gross inve~tment.'~ As one's

education increases the implicit cost of investments in health capital decreases. Assumuig

the demand for heaith capital is elastic, those with higher education wiil dernand more

medical services than those with lower education attainment. In addition., more highly

educated individuals may be more informed about the Canadian health care system and

possess greater interactive skills which will aiiow thern a higher level of access. This

higher level of access was especiaily evident in the anaiysis of specialist seMces where

individuais with post-secondary education and higher incomes were more Wtely to make at

les t one visit to a specialist. These results suggest that perhaps those of higher socio-

economic status are more knowledgeable or have different attitudes about the benefits that

can be reaiised by accessing specialist care. The positive effect of education on physician

utilisation agrees with Grossman's mode1 of the demand for heaith. That is, those with

higher education will demand more services.

The fact that socio-economic status was found to be an important factor in

receiving a referrai to a specialist has implications regardhg equity in access to specialist

care, cost and the appropriateness of the referral decision. In Canada, as in most

countries, before a patient sees a specialist, such as a gynaecologist, psychiatrist,

rheumatologist, or dermatologist, a referrai from a primary care physician is required. In

order to substantiate that Canada's heaith case system has been somewhat successfid in

achieving the equitable distribution of physician services among different socio-economic

groups, the "ideal" health care system should reveal that health status measures are the

main determinants of referral. However, studies have shown that patient preferences or

expectatioos play an important role in the disparity of the use of specialist services

between those of high and low socio-economic tat tus.^^ It is possible, then, that those

with higher levels of education and higher socio-economic status can benefit ftom the

health care system more effectively than those of low socio-economic status, even when

the system employs universal coverage.

The fact that "patient wishes" has been found :O be the most important factor

idluencing decisions by GPs to refer for consultation with a ~ ~ e c i a l i s t ~ ~ is a possible

explanation for the Merences in the utilisation of specialist seMces by socio-economic

status. Due to the probability that the l e s educated or poor may be less able to express

their need for care, they rnay be less likely than the educated middle class to gain entry to

specialist services.' Furthermore, those of higher socio-econornic status may have

different attitudes about the benefits that cm be realised by accessing specialist care and

may in tum be more motivated to seek opportunities by requesting specifk kinds of

physician visits. If speciaiised seMces are essential to maintainhg and enhancing the

stock of health, then it follows that socio-ecoaomic advantage enables an increased

capacity to produce and sustain positive hem.

The finding that the effect of education on physician utilisation was positive was

somewhat Werent f?om the result of McIsaac et al.' who found that the effect of

education was negative for fiequent primary health care utilisation but positive for

specialist health care utilisation. This may be due to the fact that this study includes a

variable indicating the extent to which one identifies with a regular medical doaor. The

level of education attained is negatively correlated with havhg a regular medical doctor

which is in turn positively related to utilisation and therefore may hide the impact of

education. The importance of including a variable representing the extent to which one

identifies with a reguiar medicd doctor is discussed below.

When modelling the utilisation of specialist services, it was expected that the

predicted probability of persons making six or more visits to a general practitioner be an

important factor in deterrnining use. McIsaac et al. found a variable representing the

probability of making at least 6 visits to a GP to be positive and sigruficant. Individuals

who visited GPs more kequently also had more specialist Msits over and above the other

detemiinants of use. McIsaac et al. concluded that this result was not surpnsing as the

most significant factors contributing to the probability of making at least six visits to a

general practitioner were those variables indicating need. These results however, may

contain biased estimates as a two-stageà ieast squares method was not used to control for

GP utilisation in the models explaining specialist utilisation. For cornparison purposes, the

models explaining specialist utilisation of the present study were run with and without

using a two-staged least squares method to control for GP utilisation. The analysis

without using this method resulted in similar findings to those of McIsaac et al. When the

two-staged least squares method was employed, the parameter estimate associated with

GP utilisation was found to be positive but insignificant. That is, after adjusting for the

endogeneity between GP and specialist utilisation and controlling for the socio-economic,

demograp hic and health need detenninants of specialist utilisation, greater exposure to a

GP does not in itself result in more refends to specialists. The inconsistency between

these results suggests that the simple application of multiple regression may result in

biased coefficient estimates. The more appropriate results are those which adjust for the

potential bias by entering the predicted probability of GP utilisation into the specialist

utilisation model.

The lack of significance of the predicted probability of making fiequent visits to a

GP on specialist utilisation is ditficuit to interpret. One would expect since a referral to a

specialist usuaiiy occurs through a GP, that GP visits would be a nsk factor for seeing a

speciaiist. A possible explanation may lie in the fact that for most groups of people, the

probability of a large number of GP visits (greater than 6) is quite srnall. Using logistic

regression to model fkequent GP utilisation wili predict that few people make at least 6

visits to a GP in one year. Taking this idormation and inserting it into the model

explaining specialist utilisation may decrease the ability to detect any correlation between a

high nwnber of visits and the probability of seeing a specialist.

2.0 Other Factors

One of the most striking findings of this study concerns the patterns of utilisation

with respect to province. M e r adjusting for other variables in the mode1 females and

males residing in Quebec were consistently the lest iikely to visit a general practitioner at

least once and at least six times. However, once specialist seMces were examined this

trend became the reverse. Individuals residing in Quebec were found to be the most likely

to make use of specialist services. Although it is beyond the scope of this thesis, one

explanation for this result is a possible uneven geographical distribution of, and hence

access to, primary care and specialist physicians. Another reason may be the extent to

which physician seMces are "open7' or "closed" in Quebec compared to other provinces.

The observed innuence of the province in which one resides on the different types of

physician utilisation requires an investigation of the geographic distribution of physicians

in Canada.

As was anticipated the remlts suggest that the access to heaith care improves as

the size of the cornrnunity in which the individual resides increases.' In most instances,

rural respondents were more likely to have access barriers to obtaining primary and

speciaiist care seMces than their urban counterparts. Individuals who Live in urban areas

will be more likely to seek health care and consume a greater volume of physician services

perhaps due to less travel tirne, greater ability to reach services, and a greater

physiciadpatient ratio." Surpnsingly, this pattern was no more apparent when analyshg

speciaiised seMces which tend to be located in urban areas. An analysis of the supply of

physicians in relation to the medical needs of Canadians rnight document a maldistribution

which would suggest a need to implement policies designed to achieve a more equitable

geographic distribution of health care professionals.

The association between lifestyle factors and physician utilisation, nich as

smoking, alcohol consumption and physical activity, can in part, be due to the effect these

habits have on health. Smoking, dcohol consumption, and lack of physical activity are

well-known risk factors for many diseases as weU as for pain in general. However, the

relationship between health behaviour is not as straightfonvard as it may seem. It can be

argued that those who are concemed with maintainhg and improving their health stock

and engage in positive health behaviour wiIi be more likely to consume heaith care senices

than those who do not. This study offen mixed results about the effects of health

behaviour on physician utilisation. In some instances, negative health behaviour displayed

a signtficant and positive association with the utilisation of physician s e ~ c e s . Females

consuming between 1 and I I drinks per week were less Likely to visit a general

practitioner or specialist at least once and more likely to visit a general practitioner at least

six times in the past year. However, males consuming between 1 and I I dnnks in a week

were less likely to make fiequent use of primary care seMces but were more likely to

make use of specialist senrices. Females and maies residing in a household with at least

one smoker were less likely to visit a general practitioner. Females and males reporting to

be inactive exhibited a greater propensity to become frequent users of GP seMces and

specialist services whereas inactive males were the least likely to visit a specialist.

Being married, divorced, widowed or living in a cornmon-law situation al1 had the

effêct of increasing the Iikelihood of making at least one visit to primary care physician.

Further, females with children under the age of 12 residing in the household were more

likely to become fiequent users of primary care and specialist services, whereas males

Living with young chiidren were less likely to be fiequent users of physician services. It

has been suggested that when women use medical care, some of the benefits may a e c t

the rest of the familY." These extemalities may be greater for females than for males

because of women's roies as mothers and providers of non-medicai health care. For

instance, when wornen use medical care the information they receive rnay later be applied

to the entire f d Y . "

It was anticipated that recent immigrants would be less tikely to use health care

seMces than those bom in Canada or more established immigrants due to possible

language barriers, cultural dinerences in patterns of service use, and UnfSuniliarity with the

Canadian heaith care system. However, the results of this shidy found immigration status

not to be of major importance in explaining variation in visits to a physician during one

year except for the mode1 explaining the probability of males making fiequent use of GP

services. Recent male immigrants were significantly less likely to make at least six visits to

a GP within the last year.

3.0 The Impact of having a Regular Medical Physician

The extent to which one identifies with a regular medical doctor has been found to

display a strong positive association with health care utilisation. Therefore, examinhg the

extent to which those individuals with and those without a regular physician differ in their

utilisation of health care services is important because it relates directly to issues of equity

in the distribution of medical resources. In fact, whether or not people have a regular

source of primary care has been commonly used as a measure of access and has been used

as an indicator of whether an individuai has a source of continuity of Although the

objectives of this study do not address the issue of whether having a regular medical

doaor prornotes better quality of care, it did find that lacking a regular medical doctor

identifies a group that is less likely to receive prirnary care.

With the exception of the probability for females making at least one visit to a

specialist, having a regular medical doctor has been found to be a significant variable. It

has also been found that those with a regular physician receive significantly more care than

those without, a hd'rng that corresponds to the rnajority of the literature on this t ~ ~ i c . ~ ~ '

An important factor that has been shown to be very strongly associated with

having a regular physician is the prevalence of chronic health problems and poor health

status in general. 28*4' It has been suggested that the relationship between having a

regularly-visited physician and higher health care utilisation is most probabiy one of cause

and effect. That is, those with poor health status will normally find a regular physician and

those with a regular physician will normally receive more care. However, d e r controllhg

for health status and other variables in the rnodel, having a regular doctor remained a

strong si@cant factor in determining whether or not one will make use of pnmary care

services.

It was estimated from the survey data that about 87% of individuals identify with a

regular medical doctor. This is a very high proportion of Canadians; however, in certain

socio-demographic groups, there is a much srnalier proportion of individuais reporting to

have a regular physician. For instance, lacking a regular medical doctor has been

associated with low income. Although it has been found that many of the individuals

reporting that they did not have a regular medical doctor did not feel it necessary to have

one, these individuals may be at greater risk for not receiving the care they need.41

Therefore it has been suggested that health care reform advocating a system linkuig

individuais to a reguiar source of care would be effective in promothg access to

appropriate care and recommended health care s e ~ c e s . ~ " ' Included in some of the

proposals for the restnicturing of primary medical care in Canada is patient rostering to

specific farnily physicians and developing additional primary access points to health care.

Under rostering, patients would be formally registered with a general practitioner or health

care organisations who would provide access to continuous "round-the-clock" care and

ensure that the patient receives al1 necessary medical services. One of the goals of this

new system is to create a more stable relationship between patients and their generd

practitioners, thereby increasing receipt of preventive medical services and decreasing the

use of the emergency department for primary care.

The results of this study tend to agree with the iiterature suggesthg that

individuals idenwng with a regular medical doctor have better access to prirnary care

than those not ident@ng with one. In addition, the findings contribute to the literature by

demonstrating that after controllhg for demographic variables, socio-economic variables

and for variables indicating need, having a reguiar doctor was not oniy positively

associated with access to primary care services but aiso to specialist care services. That is,

those with a regular physician were more likely to receive care requiring a refend than

those who did not iden* with a reguiar physician.

4.0 Strengths and Limitations

Some strengths and limitations of this study deserve mention and should be kept in

mind when interpreting the results. Many of the strengths of the study stem fkom the

advantages associated with ushg data fiom the NPHS. The study design and sampling

methods of the NPHS were well-planned. Its sample is weighted, random and

representative of Canadians over the age of 12, thereby making it possible to address

issues at the national level in the assessrnent of the effects of predisposing, enabhg and

need characteristics of health care utilisation. As a result of its large sample size, adequate

power is provided to give reliable estimates for the variables of interest. The NPHS

contains a range of variables that cm be used to examine health status and health care

needs across Canada. However, in testing a large database such as the NPHS, multiple-

hypothesis testing c m result in spurious hdings and incorrect conclusions. This study

attempted to minimise this problem by choosing variables for analyses on the basis of the

literatwe review and the behavioural mode1 of health care utilisation. Furthemore, a

method involving rescaled weights was used when selecting variables for the multivariate

anaiysis. This method has been recornrnended by Statistics As explained in

Chapter III, section 1.3, the rescaled weights allowed the results to be more manageable

than if the onginal weights had been used in the model-building stage.

Many of the limitations associated with using a cross-sectional, household w e y

such as the NPHS are discussed in Section 5 of Chapter 3. In a cross-sectional survey

such as the NPHS, relationships between variables can be made with a calculable Ievel of

confidence but inferences as to causation should be made with caution. There is an

inability to examine longitudinal patterns for the outcornes measured. For instance, causal

inferences codd not be drawn about health status and the use of physician services. The

use of longitudinal data would greatly enhance interpretations of aii causal mechanisms

operating. The redtant odds ratios are usefid in comparing the relative importance of

each of the factors in the mode1 in determinhg physician use. However, the value of the

adjusted odds ratios should not be comidered quanftatively accurate outside the model.'O1

The relatively small proportion of variance explained in physician visits as seen by the

s d R~ values, in this analysis is probably attributable to the problems associated with

cross-sectional data. The study relied on self-reports rather than independent measures of

health and tùnctional status. Physician visits were examined retrospectively, and the

nature of the visit could not be determined.

As weii, the sarnpling strategy used in the study focused on household dwellîngs

and excluded specific populations, such as the homeless, native people living on

reservations and those in institutions. Although these excluded populations represent ody

a smd proportion of the total population of Canada, it is these populations that are more

likely to be poor and have difficulty accessing primary and specialist services. For instance

the institutionalised population of the country, is a group that includes seniors' residences,

nursing homes, psychiatrie institutions, prisons, hostels and hospitals. These represent

groups with significantly higher risk and lower socio-economic stahis. Taking these

omissions into account, the actual rate of physician use may be higher however, the

purpose of this analysis was to iden* factors related to use rather than the absolute rates.

AIthough the meanire of self-rated health status has been shown to be a very good

prediaor of physician use it does involve a fair arnount of rneasurement error. Individuals

will undoubtedly use different definitions of health status by different socio-economic

g r o ~ p s . ' ~ ~ ' While the use of comprehensive measures based on self-report controls for

this somewhat there may be a bias operating in this study. In future studies of socio-

econornic status and heaith it may be preferential to question respondents as to their

understanding of ' health' .

This study did not take into consideration the effect of interaction terms on

physician utilisation. It has been argued that because physician utilisation is a fundon of

three types of variables need, enabling and predisposing, pbysician utilisation is predided

only if ail three factors are present. This implies a three-way interaction among the

predictors. Since the effect of the three predictors are not additive, a non-additive

statistical mode1 should be used to properly represent health service use." Such a mode1

can be accomplished by uicluding product terms as predidors in the multivariate analysis.

AIthough the inclusion of interaction terms can facilitate greater understanding of

relationships and can provide a statistically significant increase in predictive accuracy their

use are uniikely to produce large increases in explanatory power.'9

Furthemore, there are several disadvantages involved with using interaction terms.

Their use increases sigrufïcance occurring by chance alone (Le. inflates the alpha level),

reduces the degrees of keedom leading to restrictions in the sensitivity of significance

tests, leads to multicolhearity and potential confounding of interactive effects with non-

linear effects? There are other ways to improve prediction and understanding without

the use of interaction terms for instance, reporting separate analyses for different types of

utilisation and including additional predictor variables. The purpose of this analysis was to

explain Merences in physician utilisation by different socio-economic groups not to

predict fiiture utilisation. Therefore, the low levels of explanatory power, cornmon for

studies of this type are aot of major concem.

5.0 Poücy Implications

In recent years, health care reform has become one of the top pnorities of both the

federal and provincial governments in Canada. In the last few decades heaith expenditures

have increased disproportionately in relation to other components of govemment

expenditure. Provinces are docating as much as 30% of their total budget to heaith

care." In addition to fiscal pressures, the organisation of Canada's health care system has

been cnticised for providing a lower intensity of services, with a corresponding reduction

in the quality of care and for lacking the ability to 'foilow patients' rendering it dinicult to

respond to their needs. It is this increased concem for the govenunent's fiscal flexibility

and for the cost-effedveness of Canada's health care senrices that has prompted health

care policy-maken to undertake significant restnrcturing of the Canadian health care

system. With an emerging emphasis on restraining costs, policy-makers are attempting to

develop alternative methods for health-care delivery and physician remuneration that wiil

enable them to be less "voIume-dnven". Changes in the way in which primary care

physicians are reimbursed will have the potentiai for sigruficant impact on the use of and

access to primary care and specialty services. Proposais include patient rostering to

specific famiy physicians and developing additional primary access points to health care.

However, because patterns of use of primary care may difFer by socio-economic status,

the impact of primary care refom rnay be greater on those with lower income and

education. Therefore, it is important to assess current patterns of primary care utilisation,

and access to referred secondary or specialised health care services, so that the impact of

these changes on the health of the population can be understood. This analysis, iike that

of McIsaac et al., suggests that there is an equitable situation regarding the use of GP

services in Canada. This is based upon the fact that income does not contnbute to the

variance that can be explained in the measure of GP utilisation. Further, need

characteristics are the principal contributors to this explained variance. The exception

here is the signincant impact on physician utilisation of identifyuig with a regular medicai

doctor.

Results from this study indicate that those individuals identifjmg with a regular

medical doctor, even &er controüing for health status are more likely to receive primary

and specialist care than those without a regular doctor. Regardless of the reason why

people Iack a regular medical doctor, this implies that health poiicy that links an individual

to a physician might be effective in promoting access than one that does not.

6.0 Future Research

There are some interesthg questions beyond the scope of this study that might be

addressed in future research. The results of this study found that lacking a regular medical

doctor identifies a group that is less likely to receive primary care. It seems reasonable to

assume that those with poor health status will normally find a regular physician and those

with a reguiar physician will normally receive more care. However, even after controlling

for health status and other variables in the model, having a regular doctor rernained a

strong s i d c a n t factor in determinhg whether or not one will make use of primary care

and specialist care services. If one is interested in who is at nsk for not obtaioing needed

care, the reason for lacking a regular medical doctor should be evaluated M e r .

In the sense that physician utilisation depends on both supply and demand of heaith

services, it is important to include a variable representhg patient demand. It seems

reasonable to assume that individuais will have different demands for health care for a

given level of need. It therefore follows that unequal utilisation rnay not be entirely

inequitable. For example demand for physician care may Vary because some individuals

prefer to take the risks associated with not seeking care. It may, therefore, be necessary

to iden* other variables that are aiding, or suppressing the relationship betweea socio-

economic status and p hysician utilisation such as heait h beliefs, attitudes or preoccupation

with health. Such variables are needed to measure the tendency for increased attention to

health matters.

The fact that socio-economic status was found to be an important factor in

receiving a referrai to a specialist has implications regarding equity in access to speciaiist

care, cost and the appropriateness of the referrai decision. The role of primary care

physicians as gatekeepers to ensure appropriate use of specialist care is necessary.

Specialist care should be organised to serve those with the greatest health needs. If

individuals in higher socio-econornic groups are inappropriately seeking referrals to

specialists (especiaily for primary care), then closer monitoring of the referral process is

needed. Policies should be designed to reduce inequitable effects and unnecessary use of

speciaiist care and to ensure that the Iower and middle socio-economic groups have good

access to specialist care and are not underserviced. In order to gain insight to the factors

affecting refends a system whereby use is linked to particular doctors would be ideal.

Furthemore, it may be helpfbi to examine types of specialist utilisation to h d out whether

or not the inequality of use by socio-emnomic groups lies withio certain types of

specialists.

Chapter V: CONCLUSION

The primary purpose of this thesis was to examine the role of socio-economic

status in the differential use of primary and specialist care, in order to assess the extent to

which Canada's universal health care system parantees socio-economic equity in the use

of physician services. In theory, universai health care coverage should result in both

primary and specialist heaith care utilisation, being unrelated to socio-econornic status.

The results of this thesis support the literature in its finding of a positive relationship

between health need and the use of primary care seMces under a universal publicly-funded

health care system Health needs, as defined by number of heakh problems and self-

perceived health status, were the most important determinants of GP and specialist use.

However, even after adjusting for factors representing need there remained some

significant difrences in the utilisation of physician seMces between socio-econornic

groups.

There were two measures of socio-economic stahis used in the anaiysis: education

and income. The level of education attained was significantly associated with the use of

self-referred primary care services, with more highly educated Canadians being siightiy

more likely to make at least one visit to a GP. However, the use of primary care seMces

displayed no significant dserences by income. Once non-primary heaith seMces that

usuaiiy require a referral from a primary care physician were considered, significant

ciifferences in utilisation by both income and education were found. Despite universal

health care, Canadians with lower incomes and education are less likely to visit specialists

than those with moderate or high incomes and a higher education, even after adjustments

for need. There are several possible interpretations of this fhding, al1 of which have

Merent implications. However, the fact remains that in the event that these specialist

services are necessary to restore function or enhance heakh status, those of lower socio-

economic status may be accessing a different quality of care than those belonging to higher

socio-economic groups.

in addition to variables indicating need and socio-economic status, an important

variable in determining physician utilisation is whether or not one identifies with a regular

medicai doaor. The resdts of this thesis agree with the Literature suggesting that

Canadians who i d e n e with a regular medical doctor have better access to primary care

than those without. Although the issue of whether having a regular medical doaor

promotes better quality of care was not dealt with in this thesis, it did find that lacking a

regular medical doctor identifies a group that is less likely to receive primary care, even

after adjusting for need.

Equality of opportunity provided by the national health insurance program in

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significant dinerence in their use by incorne. However, disparities by class in the amount

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Figure 2. Percentage of the populathn reportrng one or more d i t s ta a general pract#&ner in the preceding p a r by sex and age gmup

Figure 3. Percentage of aie poplafion repotting one or more vbits fo a speciarrst h the p d i n g year &y sex and age goup

Femal Ma les

Table 1. A summary of studies of the Use of Physician Services

DATA HOW WAS NEED CONTROLLED FOR?

GPS AND SPECIALISTS SEPARATED?

Enterline et al. 1973%

Houvehold swvey dritti 1 969- 1972

Nol controlled A shifi in physician utilisation from persons in higher income to Iowa income p u p s a f k the introduction of medicare

Beck, 1973~' Administrative data 1963- 1968

Not çontrolled YES Although accessibility hcis increased with univerirril health insurance, low incorne goups still have fewer contricts with physicitui than higher income groups

Badgely et d. 1967

Siuvey &ta Not conirolled YES Although trcçessibility htw increcwed with the induction of u n i v d hecilth cure insurance, higher income wd eductition groups are referred more frequently to specialisls

Linked household interview datu to OHIP &ta 1974

Self-risscsscd hwlth status Higher income groups have tr gratter volume of specialist encounters thun lower inçome proups

- -

Househald survey dm 1974

1985 Genertil Social Swvey (GSS)

CHS 1 978ff 9

Illness, long-tenn illness, selected syrnptoms tuid disiibility

NO

YES

No sigrdicrint differençe in physicirin utilisation by incorne plroup

No relutionship b e t w m income md probability of having w d primruy çtue services; those with highcr levels of

Use is detzrmined by mcdiçal nced, those of 1owt.r SES WJ more çwe thm higher SES

Broyles et d, 1983''

use of'int:diçution, # of accidents, # of hrrilth problems tuid prcvious illncss

Roos and Mustard, 1 997'"

CHS 1978179

OHS 1990

1990 OHS tuid

1990 NHlS

Claims payment data, 1992

Ontario

County in Nonvay

Chibrio tuid USA

Winnipeg

use of medication, # of accidents, # of hetilth ~robiems atid ~reviouv illness

Sclf-assessed hcalth status, # of liealth problems

Self-assessed health status, psychological distress, chronic diseasc, # of events the last 6 nionths with cold, influenza, etc.

E S

Not controlled

Use is detennined by need, volume of use is deaendent on SES

YES

Use is Iargely detennined hy medical n d , low income groups less likely to visit ~pecialists

Health s h t u was the most important detenninant of physician use, regardless of type of service but found a higher rate of referral with higher education level

Consistent inverse relationship bctween Visity and income

GPs providc more ciue to lower income groups while specialists provide the m e mount of cue to low incomc and high incarne groups

TABLE 2

Visits to Canadian Pbysicians in a 12 month period by Malu and Femaies 12 years or older

-.

Males Fernales ALL

NPHS Respondents Canadian Population

General Practitioners Mean Visits (Median) %No Visits %At Least 1 Visit %6 or More ~is i t s '

Specialists Mean Visits (Median) %No Visits %At Least 1 Visit %6 or More ~isits '

1.72 (O) 73 -85% 26.15% 15.39%

* For those having made at ieast 1 visit

TABLE 2

Goodness o f Fit o f Measures -2 log likelihood (G') and Coenicient of Determination (R')

Model

Probability of females rnaking at least 1 visit to a GP

Probability of males making at least 1 visit to a GP

Probability of males making at least 1 1 9671 ( p=0.0001 1 -1 1

P value G~ ~djusted~ '

81 06

861 2 - - . - - - -

Probability of females and males making at least 1 visit to a GP

Probability of females making at least 6 visits to a GP

Probability of males making at least 6 visits to a GP

Probability of females and males rnaking at least 6 visits to a GP

Probability of fernales making at least 1 visit to a s~ecialist

p=O.OOOl

p=O.OOOl

p=0.0001

p=O.OOOl

p=0.0001

1

171 42

8250

4703

1 3049

6020

visit to a specialist Probability of females and males

p=O.OOOl

p=O.OOOl

-1 5

.19

-20

.19

.12

making at least 1 visit to a specialist Probability of females making at least 6

.12

-1 7

15896

visits to a specialist Probability of males making at least 6

visits io a s~ecialist

2208

Probability of females and males making at least 6 visits to a specialist

p=O.OOOl

1257

.10

p=O.OOOl

3229

-1 O

p=0.0001 .O9

p=O.OOOl .O9

Table 4. Factors reiuted to one or more visits tu a GP, camparing mers wiih non-users for FemuIes

L

Variable *one or more unadjusteci odds **adjusted 95% CI ..------ v i i

__CI_---- .. ratio -- - ____._________ odds ratio Education no high school high schml comp1eted some post-secondary post-secr,ndary completd A s 12-24 25 -44 45 -64 65-74 75 or older Health Status excellent very good g d fàir Poor No. of reported health pro blems no problems 1-3 4 or more Regular medicd doctor no Y= Community rural urban Marital Status married/common-law Single Widowed/Divorced Number of Alcohoiic Drinks O 1-1 1 12+ not staîed Household member smokes Y= no Province Ontario Quebec Maritime Prairie British Columbia 83.57 -85

"adjusted for aii other variables in table "*ail frequendes are weighted to represenî Canadian population

Table 5. Factors reloied - to one or more visits to a GP. comparing urers w i t i o r Males Variable *one or more unadjusted odds **adjusteci 95% CI

ns-(vq P.

ratio odds ratio - Education no high schwl htgh school completed some post-secondary pst-secondary wmpleted Age 12-24 25-44 45-64 65-74 75 or older Health Status excellent ves. good fkir good P"or No. of reported health problems no problems 1-3 4 or more Reguiar medical doctor no

Y= Comrnunity rural urban Marital Status nxî.rried/comrnon-law Suigle Widowed/Divorced Working Status currentty working not currently working did not work in past year not applicable Household member smokes Y S no Province Ontano Quebec Maritime Prairie British Columbia "adjusted for al1 other variables in table '"ail freqaencies are weighted to reprwent Canadian popdation

Table 6. Factors related tu one or more visifs tu a GP, compating users with non-users for Fernotes and Males Combined I ...L1I

Variable *one or more unadjusted odds **adjusted 95% CI --.----

visit$%) ratio __- odds ratio Education no high school high schml completed some post-secondary post-secondary compIeted Age 12-24 25-44 45-64 65-74 75 or older Health Status excelient very good good fàir g d

Poor No. of reported health prob lems no problems 1 -3 4 or more Regular medical doctor no Y= Community d urban Working Status currentiy workmg not currently woriung did not work past year not applicable Household member smokes Y== no Province Ontario Quebec Maritime Prairie Bnnsh Columbia 80.15 -94 -77 ( 0.68,0.88 ) "adjusted for al1 other variables in table "al1 frequencies are weighted to represent Canadian population

Table 7. Factors related tca six or more M'si& to a GP for Fernales Variable *six o r more unadjusted odds **adjusted 95% CI

visits(%) ratio odds ratio Education no high school 29.18 1 .O0 1 .O0 high schml cumpleted 27.14 -90 1.20 ( 0.95, 1.52 ) s m e post-secondary 27.0 1 -90 1.2 1 ( 0.99, 1.47 ) post-secondary completed 22.00 -68 1.12 ( 0.88, 1.43 ) Age 12-24 23 .56 1 .O0 1 .O0 25-44 25.62 1.12 1.16 ( 0.91, 1.48 ) 45-64 25 .O4 1 .O8 .95 ( 0.73, 1.24 ) 65-74 33.7 1 1.65 1.16 ( 0.87, 1-54 ) 75 or older 39.86 2.15 1.19 ( 0.89, 1.59 ) Income Adequacy 1" quintile 33.44 1 .O0 1 .O0

quintile 3 7.46 1.19 1.14 ( 0.85, 1.54 ) 3" quintile 27.52 -76 .82 ( 0.63, 1 .O8 ) 4"' quintile 23.73 .62 .79 ( 0.59, 1.05 ) 5& m e 18.99 -47 -70 ( 0.49, 0.99 ) Health Status excellent 13.67 1 .O0 1 .O0 VerY good 20.17 1-60 1.48 ( 1.18, 1.85 ) ! P d 3 1.58 2.9 1 2.63 ( 2.10, 3.29 ) fi3i.r 52.97 7.11 5 .58 ( 4.20, 7.39 ) Poor 72 -42 16.6 1 11.89 ( 7.54, 18 -74 ) No. of reported health problems no problems 22.64 1 .O0 1 .O0 1 -3 21-71 -95 -80 ( 0.61, 1.04) 4 or more 46.03 2.9 1 1.65 ( 1.23, 2.80 ) Regular medical docto r no 14.24 1 .O0 1 .O0 Y S 27.60 2.30 1.62 ( 1-10, 2.39 ) Community rural 29.30 1-00 1 .O0 urban 24.18 .77 -9 1 (0.75, 1-10) Children under age 12 no 26.20 1 .O0 1 ,O0 Y S 27.95 1 .O9 1.26 ( 1 .04, 1.52 ) Number of Alcoholic Drinks O 29.24 1 .O0 1 .O0 1-1 1 21.58 6 7 -84 ( 0.71, 0.98 ) 12+ 30.72 1 .O7 1.30 ( 0.90, 1.86 ) not stated 8.63 -23 .29 ( 0.05, 1.91 ) Province Ontano 29.08 1 .O0 1-00 Quebec 15.83 -46 -56 ( 0.36, 0.87 ) Maritime 3 1.23 1.11 1.21 ( 0.78, 1.85 ) Prairie 28.72 -98 1.16 ( 0.76, 1.77 ) British Columbia 33.74 "adjusted for al1 other variables in table "dl frequencies are wcighted to represent Canadian popuiation

Table 8. Factors related fo six or more visits to a GP for Males Variable "six or more unadjusted odds * "adjwted %@/O CI

visits(%) ratio odds ratio

Age 1 2-24 25-44 45-64 65-74 75 or older Income Adequacy 1" qumtile 2' quuitile 3" quumle 4& q u i d e 5" qyintile Health Status excellent very good fàir Poor No. of health probs. no problems 1 -3 4 or more Reg. medical doctor no Y= Community rural urban Children under age 12 no Y= Immigration Status Canadian bom 1 O+ years < 10 years Working Status currently workmg not currentfy working did not work past 12 mos not applicable Number of Alc. Drinks O 1-1 1 12+ not stated *adjarted for ail other variables in table "dl frequencies are weighted to represent Canadian population

Table 8, continued Variable *six or more unadjusteci odds **adjusteâ 95% CI

visits(%) ratio odds ratio Province Ontario 18.44 1 .O0 1 -00 Quebec 12.62 -64 -59 ( 0.35, 0.96 ) Maritime 2 1.60 1 -22 1.05 ( 0.70, 1.58 ) Prairie 19.79 1 .O9 1 .O 1 ( 0.67, 1.52 ) British Columbia 20.85 1.17 1. 14 ( 0.86, 1 4 q ) "adjusted for dl otber variables in table * *di frequendes are weighted to represen t Canadian population

Table 9. Factors reIated to six or more vis* to a GP for both Males a d F m I a Combined Variable *sir or more unadjusteci odds ^*adjusted 95% CI

vi~its(~/~) ratio odds ratio overali rate Education no high school high school completed

Age 12-24 25 -44 45-64 65-74 75 or older Income Adequacy 1" quintile 2d quimile 3" guintile 4& -le 5'h m e Health Status excellent =sr

kir Poor No. of health probs no problems 1-3 4 or more Regular medical doctor

Frequency of smoking dady occasionally not at all Children under age 12 no Y= Number of Aic. Drinks O 1-1 1 12+ not stated Physical Acîiviîy Index Active Moderate M v e *adjusted for ali other variables in table **aU frequencies are weighted to represent Canadian population

Table 9. contimed Variable *one or more unadjusted odds ** adjusted 95Y0

visits(%) ratio odds ratio Province Ontario 24.54 1 .O0 1 .O0 Quebec 14.5 1 .53 .O0 ( 0.43,0.84 ) Maritime 27.30 1.16 1.18 ( 0.86, 1.62 ) Prairie 25 -00 1 .O3 1.17 ( 0.85, 1.59 ) British Columbia 28.10 1.20 1.39 ( 1.09, 1.79 ) "adjusted for dl other variables in table **au frequencies are weighted to represent Canadian population

I l l

TaMe 10. Factors relateci to one or more visits to a speciuIist. rompring wers with non-users by FemcrIcp Variabte *one or more unadjusteci * 'adjusteai 95% confidence

visits(%) odds ratio odds ratio internai Education no hi& school high school completed some post-secondary post-secondary comp leted Age 12-24 25-44 45-64 65-74 75 or older Income Adequacy 1' quintùe 2" quintile 3d gumtile 4& quintile 5" quuitile Health Status excellent =si gOOd fair Fcx'= No. of reported health probs. no problerns 1 -3 4 or more Six or more GP visitsk** 1 -5 6 or more Regdar medical doctor no Y= Community rural urban Number of dcoholic drinks O 1-1 1 12+ not stated Province Ontario Quebec Mantune Prairie British Columbia *adjrutecl for alI other variables in table **ail frequenaes are weighfed to represent Canadian population "'This is the predicted probability of makhg 6 or more visits to a GP derived using irutr. variable estimation

Table 11. Factors related to one or more visits fo a specialist. cornpuring users with non-users by Mat' Variable *one or more unadjusteâ **adjusted 95% confidence

Visits(%) odds ratio odds ratio intemal Education no hi& school high school completed some post-secondary post-secondary completed Age 12-24 25-44 45-65 65-74 75 or older Income Adequacy 1" quintile 2' quinide 3" quintile

qtmûle 9" quintile Health Status excellent verY good good fâir Pmr No. of reported health probs. no problems 1 -3 4 or mort= Sir or more GP visits*** 1-5 6 or more Regdar medical doctor no Y= Physical Activity Index Active Moderate Inactive Number of alc. drinks O 1-1 1 12+ not stated Province Ontario Quebec Maritime Prairie British Columbia 17 -49 -72 -68 ( -66, .71 ) "adjusted for al1 otber variables in table "ail frequencies are weighted to represent Canadian popdation "*This is the predii*d pmbabüity of rnakhg 6 or more virib to a GP derived using instr. variable estimation

Table 12. Factors relaed to one or more visits to a speciolist. comparing users with - . non-users by Femaîes and M a h Variable *one or more unadjusteci ""adjusted 95% Ci .--p.

v i s i t s ( O I ) -- odds ratio odds ratio Education no high school high school cornpleted some post-secondary post-sec. cmpleted

Income Adequacy 1" guintile 2" quhtile 3" quintile 4h quintile 5& quuitile Hedth Status

l'oor No. of heaith probs. no problems 1 -3 4 or more Six or more GP visitse** 1 -5 6 or more Working Status currently workmg not currently work.lng did not work in past year not applicable Community

urban No. alcoholic drinks O 1-1 1 12+ not stated Province Ontario Quebec Maritime Prairie British Columbia ( -66, .76 ) "adjusted for al1 other variables in table

frequencies are weighted to mpresent Canadian papolation

114

Table 13. Factors reiated to six or more visits to a specialist for Femafes Variable "SU or moce unadjusted ""adjasted 95% CI

visits(*/o) odds ratio odds ratio Education no high schml 13-12 1 .O0 1 .O0 high school completed 15 -42 1.2 1 1 - 1 1 ( .89, 1.40 ) some post-seconciary 2 1.09 1.77 1.5 1 ( 1.37, 1.67 ) pst-secondary completal 15.59 1.22 1-26 ( 1 - 1 1 ? 1-43 ) Age 12-24 13.02 1 .O0 1 .O0 25-44 22.64 1.96 1.32 ( 1.21, 1.56 ) 45-64 1 1.73 .89 .73 ( -60, -89 ) 65-74 13.37 1 .O3 -77 ( .63, -95 ) 75 or older 12.78 .98 .77 ( -58, 1-01 ) Health Status excellent 12.08 1 .O0 1 .O0 VerY good 17.30 1.52 1.48 ( 1.29, 1.69 )

14.89 1.27 1.29 ( l.107 1.50 ) kir 20.14 1.84 1.80 ( 1.25,2.61 ) Poor 38.02 4.46 3 -54 ( 1-77? 7.10 ) Six or more GP visits 1-5 visits 1 1.35 1 .O0 1 .O0 6 or more visits 25.18 2.63 2.20 ( -78, 6.17 ) Regular medical doctor no 11.12 1 .O0 1 .O0 Y s 17.43 1.69 2.12 ( 1.43, 3.16 ) Community cufaI 15.79 1 .O0 1 .O0 urban 14.55 -9 1 1.19 ( 1.09, 1.29 ) Children under age 12 no 13.37 1 .O0 1 .O0 Y s 24.1 O 2.06 1.49 ( 1.36, 1-64 ) Physical Activity Active 12.7 1 1 .O0 1 .O0 Moderate 12.3 1 .96 .87 ( .79, .97 ) inactive 18.99 1.6 1 1.32 ( 1.21, 1.44 ) Smoking Frequency da il^ 19.50 1 .O0 1 .O0 occasionally 22.67 1.21 1.73 ( 1.36, 2.19 ) not at all 15.53 -76 -83 ( .78, -89 ) "adjasted for al1 other variables in table **al1 frequencies are weighted to repment Canadian population ""This is the predicted probabitity of malring 6 or more vUits to a GP derived asing instr. variable estimation

Table 14. Factors relared to six or more vîsits to a specialist for Malcs Variable *six OC more unadjusted **adjusted 95%CI

visits(%) odds ratio odds ratio Age 12-24 15 .O5 1 .O0 1 .O0 25-44 12 -25 -79 .75 ( .607 -94 ) 45-64 15.06 1 .O0 -63 ( -48, .82 ) 65-74 9.33 .5 8 -28 ( -20, .40 ) 75 or older 1 1.67 -75 .2 1 ( -11, -41 ) Health Status excellent 6.95 1 .O0 1 .O0 very good 1 1.39 1.72 1.81 ( 1.26,2.58 ) good 12.59 1.93 2.29 ( 1.46, 3.59 ) fàir 20.57 3 -47 3. 13 ( 1.64. 5.97 ) Poor 26.9 1 4.93 3.1 1 ( .94, 10.24 ) Six or more GP visits 1-5 visits 8.19 1 -00 1 .O0 6 or more visits 20.60 2.9 1 3.32 ( .30. 37.29 ) Regular medical doctor no 7.55 1 .O0 1 .O0 Y s 13 .56 1.92 3 -75 ( 2.24,6.30 ) Children under age 12 no 14.48 1 .O0 1 .O0 _yes 8.33 .54 -42 ( -33, 3 3 )

"adjusted for ail other variables in table "aii frequencies are weighted to represent Canadian population "*This is the predicted probability of making 6 or more visits to a GP derived using instr. variable es timatioa

Table 15. Factors reltzted to six or more M'sits to a speciaiist for F d m and Males combued Variable "six or more unadjusted **adjusted 95% confidence

visits(%) odds ratio odds ratio interval .... -

Overali rate 15.5 1 Education no high school high school completed some post-secondary post-secondary completed Age 1 2-24 25-44 45-64 65-74 75 or older HeaIth Status exceUent very good

Fair Poor SU or more GP visits 1-5 visits 6 or more visits Community rural h a n Reguiar medical doctor no Y= Working Status currently working not currently worlang did not work in past year not applicable Physical Activiîy Active Moderate Inactive Children under age 12 no yes 19.73 1.49 *adjuted for al1 other variables in table "ail freqaencies are weighted to represent Canadian population "*This is tbe predicted probabiüty of making 6 or more visits to a GP derived using instr. variable estimation

Table 16. Factors related to h m s a replar medicui zlll.LIlli doctor Variable % having a % having a ./O having a

regular medical regular medicai regular medical doctor l(fernales1 doctor (males) doctor @ I l

__..*.--- - - - - - - - - - - - - . - * - - . - - . . - - * . . .--CI-- ----------- ---_ __*-*.* .--. -.--.-.-.------ -.. .--...-.-- Overali rate 90.41 82.8 1 86.93 No. of reported health problems no problems 1-3 4 or more fiealth Status aceIIent very g d fkir eoor Income Adequacy 1" quùitile 85.98 75.36 8 1.79 2" quintile 86.5 1 81.97 84.77 3" q d e 90.49 82.6 1 87.29 4h cpntùe 91.35 82.92 87.05 5& quintile 93.74 85.44 89.47 Education no high school 90.85 86.44 88.84 high school cmpleted 9 1.48 83 -90 88.29 some post-secondaty 90.17 81.20 85.95 post-secondaq completed 89.16 78.74 84.33

Table 17. Surnmary of the efect of education and incorne on visits to a GP und Specialisl

-- -

21 visits to a 2 6 visits to a GP 2 1 visits to a 2 6visits to a GP specialist specialist

Education Femaies + + + not signifiant Males + not significant + not signifiant Al1 + + + not signifiant Income Females not sipificant - + not significant Males not sipificant - + not sipificant Al1 not signifieant - + Jificant

Table 18b. Stcmmary of the rew lts from the bivariate a~ïalysis:

21 visits to a GP 2 6 visits to a GP *> 1 visits to a **> 1 visits to *2 6 visits to a **> 6 visits to a specialist a specialist specialist spccialist .............................................................................................................................................................................................. ............................................. ........................................ ..........*..............................,... .......m.........*.....,.....,.

Education no high school 1 .O0 not sig. 1 .O0 1 .O0 1 .O0 not sig. high school completed .96 not sig. 1.37 1.15 .87 not sig. some post-secondary 1 .O7 not sig . 1,24 1.13 1.34 not sig. post-secondary completed 1 .O8 not sig. 1.28 1.14 .96 not sig. Income Adequacy 1 st quintile not sig. 1 .O0 1 .O0 1 .O0 1 .O0 not sig. 2nd quintile not sig. 1 .O4 .75 .8 1 .42 not sig. 3rd quintile not sig. .7 1 1 .O6 .93 .46 not sig. 4th quintile not sig. .54 1.12 .94 .50 not sig. 5th quintile not sig. .5 1 1.28 1 .O5 .63 not sig.

* controlling for GP visits using instrumental variable estimation ** without controlling for GP visits

Table 19c. The d e c t ~Leducatiori arid hrcome mi visifs to GPs ..........-- and A>eciafist,s - h y b -.

rl v z t m 6 visits to a GP *2 1 visits to a * * Z 1 visits to *t 6 visits to a **z- specialist a specialist specialist specialist ................................................................................................................................................................................ ......................................... ...................................... .............................................. ...........,.,,,,,......,..*.....

Education no high school 1 .O0 1 .O0 1 .O0 1 .O0 1 .O0 1 .O0 high school completed 1.17 1.1 1 1.38*** 1,38*** 1 .O1 9 9 some post-secondary 1,39*** 1.15 1.63*** 1.65*** 1.43*** 1.45*** post-secondary completed 1.46*** 1 .O3 1.73*** 1 .go*** 1.18 1.1 1 Income Adequacy 1 st quintile not sig. 1 .O0 1 .O0 1 ,O0 not sig. not sig. 2nd quintile not sig. 1.14 1.01 -97 not sig. not sig. 3rd quintile not sig. -82 1.16 1.10 not sig. not sig. 4th quintile not sig. ,73*** 1.27*** 1.19 not sig. not sig. 9 not m si . 1.54*** not sig. A * controlling for GP visits using instrumental variable estimation ** without controlling for GP visits * ** significant pC.05

D ~ S C ~ D ~ ~ O Q of indeoendent variables -. .. . . .

Variable Description Predisposing Education

Immigration status

Marital status

C hildren

Enabling Income adequacy

Employment status

Regular Medical Doctor Need Heaith Status

Nurnber of heaith problems

Health Behaviour Household smokers

Alcohol consumption

high school aot completed, high school completed, some post- secondary, post-secondary completed

Canadian-bom, an immigrant of 10 or more years, and immigrant of Iess than 10 years

rnarried/comrnon-law, single, widowed/divorced

Whether or not there are any children under the age of 12 in the household

Derived by the NPHS the variable incorne adequacy consists of five discrete categories based on household income and the size of the househoId

currently working, not curredy working and did not work in Past Year

Ontario, Quebec, Atlantic provinces, Prairie provinces and British Columbia Based on the question: Do you have a regular medical doctor?

Perceived health relative to other persons of comparable age; excellent, very good, good, fair or poor

Respondents were asked about 20 difEerent chronic health problems with the opporhuiity to volunteer cther conditions not listed

asked if anyone smokes regularly inside the house

the number of alcohoIic drinks per week (O, 1 - 1 1, 12+)

Phvsical Activitv Index active, moderatelv active. inactive (see below for detaiis)

Appendix 2. Variables with 'not-stated' responses

Variable Number of 'not Percentage of responses stated' responses ‘net-stated'

Regular medical doctor 1 .O 1 Marital status

Smoker in household Immigration status

Number of specialist visits Number of health problems

Level of education Number of GP visits

Weekly alcohol consumption Employment status Incorne adequacy

Appendix 3. Definition of the Variable Incorne Adeqoacy

Quintile Description Household Sue

1"' < $10,000 1-4 persons < $15,000 5 or more persons

2" 10,000-14,999 1-2 persons 10,000- 19,999 3-4 persons 1 5,000-29,999 5 or more persons

3d 15,000-29,999 1-2 persons 20,000-3 9,999 3-4 persons 30,000-59,999 5 or more

4& 30,000-59,999 1-2 persons 40,000-79,999 3-4 persons 60,000-79,999 5 or more persons

5th 60,000 or more 1-2 persons 80,000 or more 3 or more persons

Appendix 4.

The variable representing number of health problem was derived nom the responses to the foilowing questions inchideci in the NPHS:

Do you have any food allerges diagnosed by a heaith professionai?

other allergies usthma rheurnatism back pro blems (excludirtg arthritis) high bloodpressure migraine heuabches chronic bronchitis simszt is diabetes epilepsy heart dzsease cancer stomach or intestinal ulcers urinary incontinence acne reqrriring medications prescribed (ages 12-29) A Izheimers (ages 18 and older) Cataracts (ages 18 and older) Ghcorna (ages 18 and older) Any other long-tenn conditions

I n e ~ o f m a R i n r t feaxt 6 or 7 visils, r e q e c t i v i v a GPjor bath sexes .___

Variable 1-4 Vwits 1-5 visits 1-6 visits _____C_CCI__II__-***~----------

Education no high school 1 .O0 1 .O0 1 .O0 high school completed 1.13 1-11 1 .O9 some post-secondary 1.12 1.15 1.20 pst-secondary cornpieteci 1 .OS 1.03 1 .O5

Income Adequacy la quinîile zd quiatiie 3" quintile #' qyintiie 5' quinîile Health Status excellent very good g@ fair Poor No. of reported health probs. no problems 1-3 4 or more Regufar medical doctor no yes Community Nfal uban Freqaeacy of smoking daily occasionalfy not at ail Children under age 12 no Y S Number of Aicoholic Drinks O 1-1 1 123. not stated Physical Activity index Active Moderate Inactive Province Onrario Quebec Maritime Prairie British Columbia 1.37 1.39 1.38 -

7 h e ~ r n a k i n ~ s i t . s , r e m to a GPfor fendes Variaùte 1-4 visits 1-5 nsits 1 4 visits Eâucation no high school high school completed some post-semndary post-secondary completed Alle 12-24 25-44 45-64 65-74 75 or older Income Adequacy 1% quintile

quintile 3" qyintile 4& quintiie 5' quintiie Heaith Status excellent v good

fair Poo= No. of reportcd heaith problems no problems 1 -3 4 or more Regular medical doctor no Y S Commnnity rural urban Chiidren under age 12 no Y S Number of Alcoholic Drinks O 1-1 1 124- not stated Province Ontario Quebec Maritime Prairie British Columbia 1.39 1.45 1.34

A r o k b i l i t y of maRing at a GP for males Variable 1-5 visas 1-6 mts

Age 12-24 25-44 45-64 65-74 75 or older incorne Adeq~acy 1' quintile 2"d quintile 3" quintile 4"' quintile 5" quintile Healtb Statiis excellent very l w d

fair €'c'or N a of reported health problems no probtems 1-3 4 or more

Commanity rural urban Children nnder age 12 no Y= Immigration Status Cariadian bom 10+ years < 10years Working Statua currently worlcing not currently working did not work past 12 months not applicable -44 -46 -69 Number of Alcohotic Drinks O 1-1 1 12+ not stated Province Ontario Quebec Maritime Praïxie British Columbia 1.21 1. 14 1.35

~ o b a b i & o J m a R i n g or 7 v i s i l s , v e l y . to a - specralrsfjor females Variable 14 visits 1-5 visits 1-6 visitJ

Edacation no high school 1 .O0 1 .O0 1 .O0 high school completed 1 .O5 1.11 1.28 some post-secondary 1.39 1.5 1 I .52 post-secondary completed 1.36 1.26 1.35 Age 12-24 25-44 45-64 65-74 75 or older Heaïth Statas excellent very good good fair Poor S u or more GP visits 1-5 Visits 6 or more visits Regular medical doctor no Y=

Chiidren under age 12 no Y= Physical Activity Active Moderate LM* Smoking Frequency daily occasionaiiy not at al1

a r o b a b i l i - le& visils, r e ~ e c t i e ~ r mdes Variable 1-4 visits 1-5 Visits 1-6 visits

4F 12-24 1 .O0 1 .O0 1.00 25-14 -78 -75 3 5 45-64 -71 -63 .79 65-74 -37 -28 .52 75 or older -29 .2 1 .36 Health Statas excellent 1.00 1 .O0 1 .O0 veV 1.29 1.81 1-25 POd 1.77 2.29 1.40 fair 2.16 3.13 2.70 Poor 2.79 3.11 2.37 Sis or more GP visiîs 1-5 Visits 1 .O0 1 .O0 1 .O0 6 or more visits 2 . U 3.32 2.50 Regnlar medical doctor no 1 .O0 1 .O0 1 .O0 Y= 3 -96 3.75 3.66 Children ander age 12 no 1 .O0 1 .O0 1 .O0 yes .37 -52 -42

IMAGE NALUATION TEST TARGET (QA-3)

APPLIED IMAGE . lnc 1653 East Main Street - -. . Rochester. NY 14609 USA -- -- - - Phone: 71 Wl82-0300 =-a Fax: 716i286-5989