mobility of elderly patients across healthcare institutions inês videira, inês jorge, iolanda...

Mobility of elderly patients across

healthcare institutions

Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer

Pires, Joana Ribeiro, Joana Vaz, Joana Fernandes, Joana Costa,

Joana Magalhães

Faculdade de Medicina da Universidade do

Porto

Introdução à Medicina

Class 10

2005/2006

Mobility of elderly patients across healthcare institutions

Presentation Summary

Introduction

Aim

Methods

Results/Discussion

Discussion Synthesis

Limitations - Bias


Introduction

Progress in Medicine and Informatics influences the development of health information systems

Wyatt, JC. Clinical Data Systems, part 1: Data and medical records. Lancet. 1994 Dec 3; 344 (8936): 1543-7

Medical information, present in medical records, helps decision making (sic)

Haux, R. Health information systems – past, present, future. Int J Med Inform. 2005 Sep 15


Organizing patients’ information is essential

Katehakis DG, Sfakianakis S,m Tsiknakis M, Orphanoudakis SC. An infrastructure for integrated electronic health record services: the role of XML (Extensible Markup Language). J Med Internet Res. 2001 Jan-Mar; 3(1): E7.

Communication between healthcare services influences the quality of the provided service

Introduction

Branger PJ, van’t Hooft A, Duisterhout JS, van der Lei J. A standardized message for supporting shared care. Proc Annu Symp Comput Appl Med Care. 1994;473-7


Patients’ data is spread in all the places where they have received clinical services

Katehakis DG, Sfakianakis S,m Tsiknakis M, Orphanoudakis SC. An infrastructure for integrated electronic health record services: the role of XML (Extensible Markup Language). J Med Internet Res. 2001 Jan-Mar; 3(1): E7.

Introduction

Elderly people demand much of health services [1], being the main consumers of the NHS [2]

[1] Scanaill CN, Carew S, Barralon P, Noury N, Lyons D, Lyons GM. A Review of Approaches to Mobility Telemonitoring of the Elderly in Their Living Environment. Ann Biomed Eng. 2006 Mar 21

[2] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210 6.


In Central and Northern Portugal, elderly people do not usually attend the doctor when facing a disease

Santana P. Ageing in Portugal: regional iniquities in health and healthcare. Soc Sci Med. 2000 Apr;50(7-8):1025-36.

Introduction

Effective care and treatment is required for this group [1], which may be enhanced with information systems

[1] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210 6.


Aim

To study elderly patients’ mobility

across healthcare institutions.


Study Classification

Observational: the observer only collects data,

without interference in the manipulation of variables Transversal: data is collected in a single moment

Retrospective: information refers to the previous

year Analysis Unit: all the individuals aged 65 years old

or over per household

Methods


Sample design

Random sample of elderly individuals out of the available population (elderly individuals with household phone numbers)

Methods

Target population: individuals aged 65 years old or over of Oporto’s region (Espinho, Gondomar, Matosinhos, Maia, Oporto, Paredes, Stª Maria da Feira, Trofa, Valongo, Vila do Conde, Vila Nova de Gaia) Available population: individuals aged 65 years old or over of Oporto’s region with household phone number starting with 22.


Methods Data collection

Random Digit Dialling - two stage random sample Telephone interviews

Questionnaire design The questionnaire included sociodemographic characteristics (age, sex, town)

Questions related to the aim of the study

Scale pilot - interview with seven subjects, in which the five questions were developed


Methods

The telephone number was randomly selected, using two computer generated directories for prefix and suffix

The following situations have been rejected: Non existent phone numbers

Non residential phone numbers

Within the valid households, these did not result into questionnaires:

Insufficient Age

Refused to Answer

100 questionnaires have been obtained within the time available for the telephone interviews


Methods

Statistic Issues

Simple frequency distribution - to show the characteristics of the subjects and their answers

Variance was calculated for every variable. Relations between variables were defined using, multiple response tables and compute variables Analyses performed with SPSS for Windows 13.0


Results

Table 1. Characterization of telephone calls (approximated percentages related to the total amount of telephone calls)

Of the 1892 telephone calls made, only 100 questionnaires were obtained response rate = 58%

Non-existent numbers 1226 (65%)

Non-residential telephone numbers 312 (16%)

Total amount of invalid telephone calls 1538 (81%)

Insufficient age 182 (10%)

Refused to answer 72 (4%)

Answered questionnaires 100 (5%)

Total amount of valid telephone calls 354 (19%)

Total amount of telephone calls 1892


Results

Sample Results: 65 women, 34 men and 1 missing

Mean number of age was 72,7 years

old

Ages between 65 and 90 years old


Results/Discussion

The mean number of different healthcare institutions visited in 2005 was 4.83, whether within the same type or across different types

111087654321

Total_institutions

30

25

20

15

10

5

0

Co

un

t

Figure 1. Bar chart showing the amount of people by number of healthcare institutions attended.


Mobility patterns: 41% attended at least

four different institutions

There is certain mobility among different types of institutions

Results/Discussion

Figure 2. Mobility pattern considering distinct types of institutions.

Linking medical institutions appears

to be a relevant issue

L,P,PhC,L,PhH,C,L,PhH,C,L,P,Ph

Mobility Pattern

25%

20%

15%

10%

5%

0%

Per

cen

t

6%7%

19%

22%


Figure 2. Number of healthcare institutions attended to within the same type and the corresponding amount of inquiries who visited them, in percentage (sample of 100 individuals)

Results/Discussion

People usually go to one medical institution per type.

0

1

2

3

4

5

Amount_visited

hospital centre lab priv_phisician pharmacy

Institution

0

20

40

60

Per

cen

t


Results/Discussion

Hospitals: 24% attended more than one

Pharmacies: 33% of the inquired individuals went to

more than one There is a certain mobility within the

same type of these medical institutions

Results/Discussion 42% of HSJ users establish

connections with other hospitals

HSJ should be primary linked to HSA, with a long term benefit for 5% of the elderly population

The second most relevant linkage should be HSJ-IPO (3%)Table 2. Existing relations between all the hospitals visited and the associated amount of elderly people.

Hospital pattern Cases (N)

HSJ…………………………………….. 24

Just HSJ………………………….

14

With others………………………

10

HSJ-HSA…………………..

5

Just HSJ-HSA……….

4

HSJ-HSA-Valongo….

1

HSJ-IPO……………………

3

Just HSJ-IPO...............

2

HSJ-IPO-Prelada.........

1

HSJ-Valongo……………….

2

Just HSJ-Valongo........

1

HSJ-Valongo-IPO.......

1

HSJ-Prelada...........................

2

Just HSJ-Prelada.........

1

HSJ-IPO-Prelada…….1


Results/Discussion

Figure – Mobility pattern focusing on number of different institutions per type

Mobility patterns: Most common: 1H,

1HC, 1PL, 0P, 1Ph

In an hypothetical priority list these institutions should be the first ones to be linked

2H 1C 1L 1P1Ph

0H 1C 1L 0P1Ph

1H 1C 1L 1P1Ph

1H 1C 0L 0P2Ph

1H 1C 1L 1P0Ph

0H 1C 0L 0P1Ph

1H 1C 1L 0P1Ph

Mobility Pattern 2

12%

10%

8%

6%

4%

2%

0%

Per

cen

t

4%

11%

3%3%

4%

3% 3%


Results/Discussion

Men and Women Women often go, in average, to more hospitals, health centres

and pharmacies

Men go, in average, to more private laboratories and physicians

Typical elderly individual – attends one medical institution per type

Hospitals Health Centres Private Laboratories Private Physicians Pharmacies

Men 0.76 0.71 0.97 0.79 1.41

Women 1.14 0.82 0.91 0.66 1.45

Both Genders 1.02 0.77 0.93 0.70 1.42

Table 3. Mean numbers of attended healthcare institutions, within the same type, by men and women separately and both genders together.


Discussion Synthesis

Patients’ mobility has been registered: More pronounced between different

types of healthcare institutions Less distinct among the same type of

medical institutions

Patients would indeed benefit from an information linkage between different types of healthcare institutions


Not every individual in target population owns a

household phone number

Restricted time period of interviews

Limitations - Bias

Some of the phone numbers starting with 22

include places out of the Oporto’s region

Data collected in one moment may not also reflect

the reality due to people’s memory lapses

Individuals that refuse to participate

mobility of elderly patients across healthcare institutions inês videira, inês jorge, iolanda...

Documents

mobility of elderly

elderly patients mobility

patients information

healthcare services

introduction elderly

health services

qual health care

mobility telemonitoring