The Usual Source of Care and Delivery of Preventive Services to Medicare Beneficiaries

1. The Usual Source of Care and Delivery of Preventive Services to Medicare Beneficiaries Hoangmai Pham, MD, MPH Deborah Schrag, MD, MPH* J. Lee Hargraves, PhD Peter B Bach, MD, MAPP** *Memorial Sloan Kettering Cancer Center ** Centers for Medicare and Medicaid Services Academy Health, June 2005

2. Does quality vary with physician characteristics? • Quality of care is suboptimal – across demographics, SES, conditions, communities • Evidence suggesting the influence of: • Physician sex, specialty, practice type for specific services or conditions • Definitively established associations can: • Direct quality assurance, quality improvement efforts • Affect patient or payer choice of physician

3. Study Objective • Assess associations between physician and practice characteristics, and the quality of preventive care their patients receive Physician characteristics Practice characteristics Preventive services

4. Methods – Data sources • 2000-01 Community Tracking Study Physician Survey • 12,406 respondents, 59% response rate • Clinically active physicians, PCPs oversampled • Nationally representative • Demographics, care setting, attitudes, practice behavior • Linked through performing UPINs, to • Medicare beneficiaries they treated in 2001, as captured by the 5% 2001 Carrier File

5. Methods – Populations • Physicians: • Assigning the usual source of care (USOC) physician • Physician billing for the plurality of a beneficiary’s evaluation and management visits • Ties broken by comparing total amount of paid claims • Limited to USOCs who were general internists or family/general pracitioners also responding to the CTS • Beneficiaries: • 65 years or older as of January 1, 2001 • Clinically eligible for at least one of six preventive services

6. Methods – Independent variables • Physician characteristics • Medical school site, Specialty, Board certification, Number of years in practice, Sex • Practice setting characteristics • Practice type, Urban vs. rural location • % revenue from Medicare, Medicaid, managed care • HIT to access treatment guidelines or to generate reminders

7. Methods – Outcome variables • Whether clinically eligible beneficiaries received each preventive services once • Diabetic care – Eye exams and Hemoglobin A1c testing • Cancer screening – Mammography and Colonoscopy/sigmoidoscopy • Vaccinations – Influenza and Pneumococcal

8. Methods – Analysis • Unit of analysis: Individual beneficiary • Logistic regression, applied CTS survey weights • Adjusted for • All other independent variables • Beneficiary age, sex, race, comorbidity score (Klabunde) • Median income in beneficiary’s zip code • % of county adult population with 12+ yrs education • % of beneficiary’s visits with USOC physician • Number of clinical radiologists per capita in MSA

9. Results – Physicians and Beneficiaries Physicians Beneficiaries • 5,914 diabetics eligible for eye exams and HbA1c • 6,928 women for mammograms • 17,525 eligible for colon cancer screening • 24,581 eligible for vaccinations

10. Results – Receipt of services

11. Results – Physician characteristics and Proportion of beneficiaries receiving preventive services *p<0.05, **p<0.01, ***p<0.001

12. Results – Practice characteristics and Proportion of beneficiaries receiving services *p<0.05, **p<0.01, ***p<0.001

13. Results – Physician characteristics and delivery of services, adjusted OR’s (95% CI)

14. Results – Practice characteristics and delivery of services, adjusted OR’s (95% CI)

15. Summary • Quality of preventive care is suboptimal across the board • Physician and practice characteristics associated with delivery of preventive services • Strongest associations were with practice level factors – revenue from Medicaid and practice type, less so availability of HIT • Medical school site, specialty, and board certification

16. Conclusions and Implications • Physician and practice factors account for a meaningful degree of the variation in quality of preventive care • Practice level factors appear particularly influential and should be considered, in addition to individual physician factors, in designing quality improvement interventions

18. Results – Physician characteristics and Proportion of beneficiaries receiving preventive services *p<0.05, **p<0.01, ***p<0.001