predictors of preventive services’ use among medicare beneficiaries ronald j. ozminkowski, ph.d....

Predictors of Preventive Services’ Use Among Medicare Beneficiaries

Ronald J. Ozminkowski, Ph.D.Ron Z. Goetzel, Ph,D.David Shechter, Ph.D.David C. Stapleton, Ph.D.Onur Baser, Ph.D.Pauline J. Lapin, M.H.S.

Thomson Medstat (RJO, RZG, DS,OB)Cornell University (RJO, RZG, DCS)Centers for Medicare and Medicaid Services (PJL)

2 Copyright 2004 Thomson Medstat Proprietary & Confidential

Background

• Clinical preventive services have been shown to prevent disease and promote early detection and treatment.

• Despite Medicare coverage, use of clinical preventive services has been less than optimal.

• Little is known about the factors that determine the use of preventive services among Medicare beneficiaries.

• Information on factors that predict the use of preventive services use among Medicare beneficiaries could inform policymakers of actions they might consider to promote appropriate use.


Background

• The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 provides Medicare reimbursement for an initial preventive physical exam (a.k.a the “Welcome to Medicare visit”) designed to review the health status of new Medicare beneficiaries.

• It is expected that this visit will yield an increase in the use of preventive services that Medicare pays for, including:

– Pneumococcal, influenza, hepatitis B vaccinations– Screening mammography– Screening pap smear and pelvic exam– Colorectal cancer screening tests– Prostate cancer screening tests– Glaucoma screening– Bone mass measurements


Hypotheses and Data Source

• We expect the number of preventive services used to be influenced by:

– Demographic and socioeconomic factors;– Health plan type;– Health status;– Underlying health risks;– Ability to take care of daily needs; and– Motivation to take care of oneself.

• The 2001 Medicare Current Beneficiary Survey (MCBS) supplied data to test these hypotheses.

– 11,158 respondents with non-missing data


Variables Used in Analyses of Predictors of Preventive Services’ Use

• The 2001 MCBS provided information on more variables expected to influence preventive services’ use than in other studies.

• Demographic and socioeconomic factors:– Gender– Race– Marital status– Employment status– Income– Education– Number of living children– Living alone or not– Place of residence (detached home, retirement community)– Availability of personal care services

• Health plan type:– HMO or not– Dually enrolled in Medicare and Medicaid or not


Variables Used in Analyses of Predictors of Preventive Services’ Use (Cont’d.)

• Health status measures– Having history of one or more of these conditions:

• Hardening of the arteries• Hypertension• Myocardial infarction• Angina or coronary heart disease• Other heart problems• Stroke• Diabetes• Rheumatoid arthritis• Psychiatric / mental health problems• Osteoporosis• Broken hip• Emphysema / asthma / COPD• Complete or partial paralysis• Cancer related to screening test of interest• Cancer not related to screening test of interest• Depression• Loss of general interest in life in last 12 months


Variables Used in Analyses of Screening Behavior (Cont’d.)

• Health status measures (Cont’d.):– General health status (excellent, very good, good, fair or poor)

• Health risks:– Smoking status (current smoker, former smoker)– Overweight– Obese– Drinking habits (heavy drinker vs. not)– Gets at least some weekly exercise– Does moderate, vigorous, or muscle-building exercise at least once / week

• Motivation:– Patient activation scale (available for 8,590 respondents, so used in some

analyses only)


• Ability to carry out daily activities, related to:– Use of telephone– Housework (light and heavy studied separately)– Paying bills– Preparing meals– Shopping

(Analyses account for ability and desire to do these)

Variables Used in Analyses of Predictors of Preventive Services’ Use (Cont’d.)


Statistical Methods – Descriptive Analyses

• Descriptive analyses showed characteristics of the sample members related to these variables.

• Descriptive analyses also showed relationships between these variables and the probability of having a:

– Low number of services (1 – 4)– Medium number of services (5 or 6)– High number of services (7)(in the past 12 months)


Statistical Methods – Multivariate Analyses

• Multinomial logistic regression analyses showed impact of each variable on the probability of having low, medium, or high numbers of preventive services, controlling for the impact of all other variables.

• Other analyses (available upon request), included:– Poisson count model analyses showing the marginal impact of each

variable on the number of services done in the previous 12 months (ranging from 0 – 7 possible services).

– Logistic regression analyses showing the impact of each variable on the probability of having each type of service done in the previous 12 months.

• All analyses were conducted in STATA and adjusted for the complex sampling process used for the MCBS.

• Results are nationally representative.


Results – Characteristics of the Full Sample (n = 11,158)

• Demographics and Socioeconomic status:– Female = 58.4%– African American Race = 7.7%– Never married = 3.2%– Currently employed = 12.1%– Low income ($0 to $25k) = 59.2%– Had no living children = 9.0%– Some college education or graduated college = 69.3%– Lives alone = 32.3%– Live in single family detached home = 70.9%

• Plan Type:– HMO members = 20.8%– Dually enrolled in Medicare and Medicaid = 9.4%


Health Status of Respondents – Heart & Related Conditions

9.8%

58.0%

14.1%

12.9%

15.8%

10.9%

18.3%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Hardening of arteries

Hypertension

Myocardial infarction

Angina or CHD

Other heart problems

Stroke

Diabetes


Health Status of Respondents – Depression & Other MH Problems

6.7%

5.4%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0%

Psychiatric or MH problem

Depressed all or most of last 12 months


Health Status of Respondents – Musculoskeletal Problems

16.5%

3.4%

9.4%

3.5%

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0%

Osteoporosis

Broken hip

Rheumatoid arthritis

Paralysis


Health Status of Respondents – Cancer, COPD, Asthma, &Emphysema

13.5%

14.2%

5.8%

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0%

Emphysema, asthma, COPD

Cancer related to screening test

Other cancer


Perceived Health Status of Respondents

16.2%

29.1%

32.8%

21.9%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0%

General health w as excellent

General health w as very good

General health w as good

General health w as fair or poor


Percent Who Received Each Type of Preventive Service in Last 12 Months

54.7%

36.3%

69.6%

54.2%

65.2%

62.1%

67.9%

94.8%

82.6%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%

Mammogram (females only)

Pap Smear (females only)

PSA Test (males only)

Digital Rectal Exam (males only)

Pneumonia Shot

Eye Exam

Flu Shot

Blood Pressure Check

Cholesterol Test


Results – Factors Associated With Having a High Number of Preventive Services in Full Sample

• The adjusted probability of having a high number of services (all 7) was significantly greater for:

– Those with children (14.1%) vs. those with no children (13.3%);– HMO members (14.7%) and FFS members (14.4%) vs. those dually

enrolled in Medicare and Medicaid (10.3%)– Those with the following conditions:

• Hardening of the arteries (17.4%) vs. not (13.7%)• Hypertension (14.7%) vs. not (13.0%)• Other heart problems (15.0%) vs. not (13.8%)• Diabetes (16.9%) vs. no diabetes (13.4%)• Osteoporosis (17.4%) vs. no osteoporosis (13.4%)• Emphysema, asthma, or COPD (16.1%) vs. none (13.7%)• Cancer related to the test of interest (17.3%) vs. not (13.5%)

– Those who participated in at least some weekly exercise (14.4%) vs. not (13.4%)

– Those who were more motivated to care for themselves (based on analysis of subsample who completed Patient Activation Scale questions)


Results – Factors Associated With Having a Low Number of Preventive Services in Full Sample

• The adjusted probability of having a low number of preventive services (1 – 4) was significantly greater for those who were:

– Females (42.3%) vs. males (34.2%);– African Americans (43.4%) vs. Other races (38.5%)– Currently employed (44.7%) vs. not (38.2%)– Lower income = $0 - $25k (42.8%) vs. high income (> $50k = 28.6%)– Dually enrolled in Medicare and Medicaid (42.2%) vs. FFS (39.9%) and HMO

(35.0%)– With excellent general health status (45.0%) vs. fair / poor (37.0%)– Had a broken hip (44.3%) vs. not (38.7%)– Heavy drinkers (50.3%) vs. not (38.8%)– Completely or partially paralyzed (43.1%) vs. not (38.7%)– Had difficulty shopping (44.1%) vs. not (38.4%)– Normally did not do shopping (44.1%) vs. shoppers (38.1%)– Had difficulty using a telephone (40.8%) vs. not (38.8%)


Implications

• Having a chronic condition was often associated with having more preventive services.

– Statistical significance may be due in part to large sample size.

• Outreach to promote the appropriate use of preventive services should be targeted to segments of the population with lower use, including:

– Females;– African Americans – Currently employed (cannot afford to stop working?)– Lower income– Dually enrolled in Medicare and Medicaid– Had a broken hip– Heavy drinkers

• Special arrangements may be need for some of these people:– Completely or partially paralyzed– Had difficulty shopping or who normally did not do shopping– Had difficulty using a telephone


Implications (Cont’d.)

• The new Medicare drug law provides Medicare reimbursement for an initial preventive physical exam designed to review the health status of new Medicare beneficiaries and promote the use of preventive services.

– It will be important to evaluate the impact of this visit on the use of preventive services among new beneficiaries.

• It is unlikely that a one-time visit will be sufficient to motive people to engage in these practices over time.

• Future research should identify, test and evaluate interventions targeting segments of the population where use is low, and methods to sustain appropriate use over time.

predictors of preventive services’ use among medicare beneficiaries ronald j. ozminkowski, ph.d....

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