1. The Role of Consumer Knowledge on the Demand for Preventive Health Care Among the Elderly Stephen T. Parente, Ph.D., Project HOPE Center for Health Affairs and Johns Hopkins University David S. Salkever, Ph.D., Johns Hopkins University and NBER Joan DaVanzo, Ph.D., The Lewin Group (Formerly of the Barents Group, LLC) Research sponsored by the Health Care Financing Administration, (Contract #500-95-0057/Task Order 2)

2. Presentation Overview Study Objectives Supporting Literature Modeling Approach Estimation Results Policy Implications Next Steps

3. Study Objectives Develop an economic model to of demand to estimate the direct effect of information on the preventive service utilization. Identify the effect of income, education and insurance coverage, controlling for information effects. Estimate the benefits of a fully informed non- institutionalized population. Identify characteristics of a ‘knowledgeable’ Medicare beneficiary.

4. Literature Supporting Research Role of consumer information on medical care demand Arrow (1963): Patients rely on providers and insurers to act as their agents. Pauly & Satterthwaite (1981): First empirical analysis of the role of consumer information’s indirect effect on demand. Kenkel (1990): Estimated the direct effect of information on medical visit demand. Hsieh and Lin (1997): Estimate effect of information on preventive services in Taiwan.

5. Literature Supporting Research Knowledge of Health Services and Health Insurance Benefits McCall et al (1986): Medicare beneficiaries in six States have a low level of knowledge of Medicare benefits and supplemental policies.. Issacs (1996); Blendon et al, (1997): Significant misunderstanding among the general population regarding managed care and entitlement programs. Barents/Project HOPE/Westat (1998): General probability sample of 1996 Medicare non- institutionalized beneficiaries suggests people learning principally by experience.

6. Unexplored Areas The direct effect of knowledge (not information) on the demand for Preventive Services in the Medicare population. The impact of recent change in preventive care benefit design on the use of preventive care. The direct effect of Medicare program knowledge on curative medical care utilization and cost. The $120 Million (Medicare +Choice) question: Will better informed beneficiaries have different in their health care use, cost, health status, and satisfaction than uninformed beneficiaries?

7. Modeling Approach Model the demand for influenza vaccination and mammography screening among Medicare beneficiaries (both were covered benefits as of 1992). Use a two part model of demand Treat beneficiary knowledge of the preventive care benefit as endogenous. Use IV estimation with instrument(s) for beneficiary knowledge of the benefit.

8. Two Part Demand Model for Preventive Care –Eq. 1: K i = a 0 + a 1 X i + u i –Eq. 2: D i = b 0 + b 1 Y i + b 2 K i + v i K i = knowledge of beneficiary I X i = vector of patient characteristics relevant to obtaining K D i = preventive service demand (0,1) Y i = beneficiary attributes u i and v i random error terms Eq. #2 provides a reduced form demand expression

9. Data: Medicare Current Beneficiary Survey (MCBS) Panel survey of (~14,000) beneficiaries offered every year since 1991. Household interview that occurs in three rounds annually. Self-report survey data is linked to Medicare claims data for the non-Medicare risk HMO population. Provides: cost and use information (including drug use), SES, health status, functional status.

10. Data Used for this analysis -1 1996 calendar year MCBS population Three rounds of combined data: –Round 16: Cost and Use, Medicare claims for all 1996 attached. –Round 17: Includes supplemental questionnaire regarding beneficiaries ‘information needs’. –Round 18: Includes supplemental questionnaire on specific Medicare benefit and program knowledge.

11. Data Used for this Analysis -2 Selected a subset of non-institutionalized elderly. (N=9735 all, 5601 women) Dependent Variables: –Mammography screening use (for women): 1=yes, 0=no –Flu shot: 1=yes, 0= no Explanatory Variables (e.g., benefit knowledge): –True (1) or false (0), Medicare covers flu shot /mammography? Control Variables (demand shifters): –Income, Education, Network effects –Insurance (supplemental, dual eligibility) –SES, Health status, functional status

12. Data Used for this Analysis -3 Key Instrumental Variable for Benefit Knowledge: –Combined score of Medicare program quiz questions: ‘A physician who accepts assignment can not charge whatever they want’? ‘You have the right to appeal a decision made by Medicare regarding a covered benefit’? ‘Physical exams are a covered Medicare expense’? 21.5% got all three right. Second Instrument: –Correct Knowledge of the ‘other’ preventive care benefit.

13. Descriptive Statistics of Key Variables Flu Shot:MeanSTD –Use:64.9% (0.477) –Correct Knowledge:76.4%(0.425) Mammogram (women only) –Use:39.4%(0.489) –Correct Knowledge66.2% (0.473) Program Rules21.5%(0.411) –women only19.9%(0.399)

14. First Stage Results-1 Flu Shot Benefit Knowledge

15. First Stage Results-2 Mammography Benefit Knowledge

16. Second Stage Results-1 Flu Shot Use

17. Second Stage Results-2 Mammography Screening Use

18. Key Findings Knowledge of a preventive care benefit appears to have the greatest impact on demand. Income, supplemental coverage and education level have a positive impact on the demand for services. Mixed results regarding race. Black beneficiaries less likely to get a flu shot, but there is not a similar finding for mammography. May reflect an interaction between race and gender.

19. Policy Implications If all non-institutionalized beneficiaries were knowledgeable about prevent care benefits: –1.5 million for beneficiaries immunized (9.1% increase) –~1 million more females screened (14.7% increase) Per beneficiary annual cost-saving for flu shot is $1.64 to $9.03 depending on health status. Medicare will spend $3 per year on beneficiaries for consumer education. Medicare’s goal of increasing preventive service use further will depend on the marginal cost of reaching one more beneficiary.

20. Next Steps Control for impact of prior use of services on knowledge. Compare results from 2SLS to bivariate probit results. Examine effect of knowledge on health care utilization and cost. Develop new instruments for Medicare +Choice analysis using the MCBS.

21. Solicitation for Future Instruments to be included in MCBS Supplement Current list includes: –Most people covered by Medicare can choose among different kinds of health insurance plans within Medicare (T/F). –Medicare by itself doesn=t pay for all of [your/(SP=s)] health care expenses. –The government is trying to force some people on Medicare to join HMOs even if they don=t want to. –People can complain to Medicare about their HMOs or supplemental plans if they are not satisfied with them. –HMOs that cover people on Medicare often cover more health services, like prescribed medicines, than Medicare by itself. –If (you/SP) join(s) an HMO that covers people on Medicare, (you/SP) will have fewer benefits than if (you/SP) just had Medicare by itself. –If (you/SP) join(s) an HMO that covers people on Medicare, (you are/SP is) allowed to drop out only during certain times of the year and still be covered by Medicare.