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)
Cornell University (RJO, RZG, DCS)
Centers for Medicare and Medicaid Services (PJL)
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.
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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:
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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
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Hypotheses and Data Source
• We expect the number of preventive services used to be
influenced by:
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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
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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:
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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
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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
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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:
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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)
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Variables Used in Analyses of Predictors of Preventive
Services’ Use (Cont’d.)
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Ability to carry out daily activities, related to:
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Use of telephone
Housework (light and heavy studied separately)
Paying bills
Preparing meals
Shopping
(Analyses account for ability and desire to do these)
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Statistical Methods – Descriptive Analyses
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Descriptive analyses showed characteristics of the sample
members related to these variables.
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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)
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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.
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Results – Characteristics of the Full Sample (n =
11,158)
• Demographics and Socioeconomic status:
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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%
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Health Status of Respondents – Heart & Related Conditions
Diabetes
18.3%
Stroke
10.9%
Other heart problems
15.8%
Angina or CHD
12.9%
Myocardial infarction
14.1%
Hypertension
Hardening of arteries
0.0%
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58.0%
9.8%
10.0%
20.0%
30.0%
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40.0%
50.0%
60.0%
70.0%
Health Status of Respondents – Depression & Other MH Problems
Depressed all or most of last 12 months
5.4%
Psychiatric or MH problem
0.0%
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6.7%
1.0%
2.0%
3.0%
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4.0%
5.0%
6.0%
7.0%
8.0%
Health Status of Respondents – Musculoskeletal Problems
Paralysis
3.5%
Rheumatoid arthritis
9.4%
Broken hip
3.4%
Osteoporosis
0.0%
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16.5%
2.0%
4.0%
6.0%
8.0%
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10.0%
12.0%
14.0%
16.0%
18.0%
Health Status of Respondents – Cancer, COPD, Asthma, &
Emphysema
Other cancer
5.8%
Cancer related to screening test
14.2%
Emphysema, asthma, COPD
0.0%
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13.5%
2.0%
4.0%
6.0%
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8.0%
10.0%
12.0%
14.0%
16.0%
Perceived Health Status of Respondents
General health w as fair or poor
21.9%
General health w as good
32.8%
General health w as very good
29.1%
General health w as excellent
0.0%
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16.2%
5.0%
10.0%
15.0%
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20.0%
25.0%
30.0%
35.0%
Percent Who Received Each Type of Preventive
Service in Last 12 Months
Cholesterol Test
82.6%
Blood Pressure Check
94.8%
Flu Shot
67.9%
Eye Exam
62.1%
Pneumonia Shot
65.2%
Digital Rectal Exam (males only)
54.2%
PSA Test (males only)
69.6%
Pap Smear (females only)
36.3%
Mammogram (females only)
0.0%
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54.7%
10.0%
20.0%
30.0%
40.0%
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50.0%
60.0%
70.0%
80.0%
90.0%
100.0%
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:
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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)
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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:
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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%)
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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:
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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
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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.
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