Technology Diffusion, Hospital Variation, and Racial Disparities Among Elderly Medicare Beneficiaries: Peter W. Groeneveld, MD, MS Sara B. Laufer, MA Alan M. Garber, MD, PhD CDEHA Center on the Demography and Economics of Health and Aging

Healthcare Disparities and Geographic Variation Racial disparities in medical procedure use may partially be explained by “small area” geographic differences in procedure availability. Racial disparities in medical procedure use may partially be explained by “small area” geographic differences in procedure availability. Explained 95% of the difference in knee replacement rates between white and latina women.* Explained 95% of the difference in knee replacement rates between white and latina women.* Within localities, there are large differences in technology utilization rates among hospitals. † Within localities, there are large differences in technology utilization rates among hospitals. † *Skinner J, et al. Racial, ethnic, and geographic disparities in rates of knee arthroplasty among Medicare patients. N Engl J Med 2003;349: †Selby JV, et al. Variation among hospitals in coronary-angiography practices and outcomes after myocardial infarction in a large health maintenance organization. N Engl J Med. 1996;335:

Research Questions Do differences in major medical procedure rates among hospitals help explain racial disparity in healthcare? Do differences in major medical procedure rates among hospitals help explain racial disparity in healthcare? Do hospitals with larger black inpatient populations provide more/less equal care? Do hospitals with larger black inpatient populations provide more/less equal care? As medical technologies diffuse through the marketplace, do racial disparities decrease? As medical technologies diffuse through the marketplace, do racial disparities decrease?

Setting 20% random selection of elderly Medicare beneficiaries hospitalized between % random selection of elderly Medicare beneficiaries hospitalized between Medicare Provider Analysis and Review (MEDPAR) administrative records. Medicare Provider Analysis and Review (MEDPAR) administrative records.

Selection Criteria for Procedures Performed in sufficient volume among the elderly throughout Performed in sufficient volume among the elderly throughout Substantial growth in volume and in number of hospitals offering procedure during the 1990s. Substantial growth in volume and in number of hospitals offering procedure during the 1990s. Performed in inpatient setting. Performed in inpatient setting. Influenced DRG assignment. Influenced DRG assignment.

Emerging Procedures and Their Indicator Diagnoses ProcedureIndicator Diagnoses (ICD-9) Replace aortic valve–tissue 396.2,3,8; 424.1: Aortic valve disease : Rheumatic heart failure Internal mammary artery coronary bypass grafting 410.4,7: Myocardial infarction 411.1: Intermediate coronary syndrome 412: Old myocardial infarction 413.9: Angina pectoris : Coronary atherosclerosis 414.9: Chronic ischemic heart disease Dual-chamber pacemaker 426.0,1: Atrioventricular block 427.8: Cardiac dysrhythmias Vena cava interruption 415.1,11,19: Pulmonary embolism/ infarct : Deep phlebitis—leg 453.8: Venous thrombosis Lumbar/LS spinal fusion 722.1,52: Lumbar disc displcmt./ degenrtn ,02: Spinal stenosis : Idiopathic scoliosis 738.4: Spondylolisthesis

Hospitalization with indicator diagnosis, Hospitalization with indicator diagnosis, Linked to subsequent hospitalizations within 90 day period. Linked to subsequent hospitalizations within 90 day period. Outcomes: Outcomes: –Procedure within 90 days of admission or –Death prior to 90 days without procedure or –Survive 90 days without procedure. Cohort Formation / Outcomes

Multinomial Logit Model Logit (outcome) = β 1 race + β 2t year t + β 3t race year t + β 4 black9_20% + β 5t black9_20% year t + β 6 black>20% + β 7t black>20% year t + γ k covariates + ε Logit (outcome) = β 1 race + β 2t year t + β 3t race year t + β 4 black9_20% + β 5t black9_20% year t + β 6 black>20% + β 7t black>20% year t + γ k covariates + ε Covariates: sex, age, zip code-level income/education, Charlson comorbidity, academic hospital Covariates: sex, age, zip code-level income/education, Charlson comorbidity, academic hospital Standard errors adjusted for data clustering by hospital and ZIP code. Standard errors adjusted for data clustering by hospital and ZIP code.

Sub-cohorts Candidates for...NBlacks Aortic Valve Replacement (tissue valve) 198,05212,636 (6%) IMA-CABG 1,371,92289,249 (7%) Dual Chamber Pacemaker 354,16530,786 (9%) IVC Filter 229,30621,367 (9%) Lumbar/Lumbosacral Spinal Fusion 195,5078,933 (5%)

Which Patients are Admitted to Hospitals with >20% Black Inpatient Populations? % of whites/blacks admitted to hospitals with >20% black inpatient population

Racial Disparity for Five Emerging Technologies Aortic Valve Replcmt IMA CABGDual-Chamb Pacer Vena Cava Interrpt L/LS Spine Fusion Odds ratio for blacks receiving procedure

Procedure use at hospitals with >20% black inpatients Odds ratio for patients in hosp with >20% black inpatients compared to hosp with <9% black inpatients WhiteBlackWhiteBlackWhiteBlackWhiteBlackWhiteBlack Aortic Valve Replcmt IMA CABGDual-Chamb Pacer Vena Cava Interrpt L/LS Spine Fusion

Comparison of Disparities at Hospitals with >20% or 20% or <9% Black Inpatients p=0.01 p=0.005 p<0.001 p= Black <9% Black >20% Black <9% Black >20% Black <9% Black >20% Black <9% Black >20% Black <9% Black >20% Aortic Valve Replcmt IMA CABGDual-Chamb Pacer Vena Cava Interrpt L/LS Spine Fusion Odds ratio for blacks compared to whites in hosps with 20% black inpatients

Conclusions Hospitals with larger black inpatient populations had generally lower procedure rates for their patients. Hospitals with larger black inpatient populations had generally lower procedure rates for their patients. These hospitals also had greater levels of racial disparity. These hospitals also had greater levels of racial disparity. Substantial racial disparities persisted in the use of several emerging medical technologies during the 1990s. Substantial racial disparities persisted in the use of several emerging medical technologies during the 1990s.

Limitations Administrative data were insufficiently detailed to determine who met definitive procedural criteria. Administrative data were insufficiently detailed to determine who met definitive procedural criteria. Possible that systematic differences exist between the accuracy and detail of MEDPAR records for whites and blacks. Possible that systematic differences exist between the accuracy and detail of MEDPAR records for whites and blacks.

Implications The quality and innovativeness of care provided by hospitals with >20% black inpatient populations is critical to the provision of more equal healthcare. The quality and innovativeness of care provided by hospitals with >20% black inpatient populations is critical to the provision of more equal healthcare. Policy initiatives to improve racial disparities in healthcare should concentrate on the mediating role of these hospitals. Policy initiatives to improve racial disparities in healthcare should concentrate on the mediating role of these hospitals.

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Procedure Rate Growth: Procedures per 10,000 elderly Medicare Beneficiaries

Covariates Race (black or white). Race (black or white). Sex, age, ZIP-code-level race-specific income/education, urban location. Sex, age, ZIP-code-level race-specific income/education, urban location. Charlson comorbidity index. Charlson comorbidity index. Black inpatient population (%) of center in which patient hospitalized. Black inpatient population (%) of center in which patient hospitalized.