The Usual Source of Care and Delivery of Preventive Services to Medicare Beneficiaries Academy Health, June 2005 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

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

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

Methods – Data sources  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

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

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

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

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

Results – Physicians and Beneficiaries PhysiciansBeneficiaries 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

Results – Receipt of services Eye ExamsHbA1cMammograms Colon cancer screening Influenza vaccination Pneumococcal vaccination Expected proportion 100% 10%, 20%100%10% Observed proportion Proportion in lowest income tercile Proportion in highest income tercile

Results – Physician characteristics and Proportion of beneficiaries receiving preventive services Diabetic Eye ExamHbA1cMammogram Colon cancer screening Influenza vaccination Pneumococcal vaccination General IM FP/GP 44.9* ***9.9*** * Certified Not certified *36.5**6.5*41.7*6.5** N Amer med grad Other FMG 43.0** **7.7*40.0***6.3** *p<0.05, **p<0.01, ***p<0.001

Results – Practice characteristics and Proportion of beneficiaries receiving services Diabetic Eye ExamHbA1cMammogram Colon cancer screening Influenza vaccination Pneumococcal vaccination Solo/2 46.9*52.3***42.5***8.4**44.6**7.0** Small group Med/large group Other practice Lowest Medicaid tercile Middle Medicaid tercile **43.3***7.8***44.4**6.8*** Highest Medicaid tercile 43.0*48.4***38.9*** ***6.4*** Have HIT No HIT45.4** ** *p<0.05, **p<0.01, ***p<0.001

Results – Physician characteristics and delivery of services, adjusted OR’s (95% CI) Diabetic Eye Exam HbA1cMammogram Colon cancer screening Influenza vaccination Pneumococcal vaccination Female 1.19 ( ) 0.96 ( ) 1.33 ( ) * 0.90 ( ( ) ** 0.98 ( ) FP/GP 0.81 ( ) * 1.11 ( ) 0.83 ( ) * 0.86 ( ) ** 1.08 ( ) 0.95 ( ) Board certified 1.12 ( ) 1.22 ( ) 1.34 ( ) * 1.27 ( ) * 1.08 ( ) 1.06 ( ) Other FMG 0.82 ( ) * 0.91 ( ) 0.78 ( ) * 0.92 ( ) 0.82 ( ) ** 0.74 ( ) *

Results – Practice characteristics and delivery of services, adjusted OR’s (95% CI) Diabetic Eye Exam HbA1cMammogram Colon cancer screening Influenza vaccination Pneumococcal vaccination Small group 1.12 ( ) 1.90 ( ) ** 1.13 ( ) 0.97 ( ) 1.01 ( ) 1.19 ( ) Med/large group 0.81 ( ) 1.91 ( ) ** 1.40 ( ) ** 1.12 ( ) 1.22 ( ) 1.16 ( ) Other practice 0.84 ( ) * 0.68 ( ) * 1.03 ( ) 0.91 ( ) 1.03 ( ) 1.21 ( ) * Middle Medicaid tercile 1.12 ( ) 0.74 ( ) ** 0.81 ( ) ** 0.87 ( ) ** 0.85 ( ) ** 0.76 ( ) *** Highest Medicaid tercile 1.04 ( ) 0.73 ( ) ** 0.76 ( ) ** 1.09 ( ) 0.77 ( ) *** 0.73 ( ) ** Have HIT 1.21 ( ) *** 1.13 ( ) 1.07 ( ) 0.96 ( ) 1.02 ( ) 1.21 ( ) **

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

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

Results – Physician characteristics and Proportion of beneficiaries receiving preventive services Diabetic Eye ExamHbA1cMammogram Colon cancer screening Influenza vaccination Pneumococcal vaccination Male Female * ***8.0 General IM FP/GP44.9* ***9.9*** * Certified Not certified *36.5**6.5*41.7*6.5** N Amer med grad Other FMG43.0** **7.7*40.0***6.3** *p<0.05, **p<0.01, ***p<0.001