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Download Technology Diffusion, Hospital Variation, and Racial Disparities Among Elderly Medicare Beneficiaries: 1989-2000 Peter W. Groeneveld, MD, MS Sara B. Laufer,

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Technology Diffusion, Hospital Variation, and Racial Disparities Among Elderly Medicare Beneficiaries: 1989-2000 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 Slide 2 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;349:1350-9. 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;335:1888-1896. Slide 3 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? Slide 4 Setting 20% random selection of elderly Medicare beneficiaries hospitalized between 1989-2000. 20% random selection of elderly Medicare beneficiaries hospitalized between 1989-2000. Medicare Provider Analysis and Review (MEDPAR) administrative records. Medicare Provider Analysis and Review (MEDPAR) administrative records. Slide 5 Selection Criteria for Procedures Performed in sufficient volume among the elderly throughout 1989-2000. Performed in sufficient volume among the elderly throughout 1989-2000. 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. Slide 6 Emerging Procedures and Their Indicator Diagnoses ProcedureIndicator Diagnoses (ICD-9) Replace aortic valvetissue 396.2,3,8; 424.1: Aortic valve disease 398.91: 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 414.01-5: 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 451.19: Deep phlebitisleg 453.8: Venous thrombosis Lumbar/LS spinal fusion 722.1,52: Lumbar disc displcmt./ degenrtn 724.00,02: Spinal stenosis 737.30: Idiopathic scoliosis 738.4: Spondylolisthesis Slide 7 Hospitalization with indicator diagnosis, 1989-2000. Hospitalization with indicator diagnosis, 1989-2000. 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 Slide 8 Multinomial Logit Model Logit (outcome) = 1 race + 2t year t + 3t race year t + 4 black9_20% + 5t black9_20% year t + 6 black>20% + 7t black>20% year t + k covariates + Logit (outcome) = 1 race + 2t year t + 3t race year t + 4 black9_20% + 5t black9_20% year t + 6 black>20% + 7t black>20% year t + k covariates + 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. Slide 9 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%) Slide 10 Which Patients are Admitted to Hospitals with >20% Black Inpatient Populations? % of whites/blacks admitted to hospitals with >20% black inpatient population Slide 11 Racial Disparity for Five Emerging Technologies 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Aortic Valve Replcmt IMA CABGDual-Chamb Pacer Vena Cava Interrpt L/LS Spine Fusion Odds ratio for blacks receiving procedure Slide 12 Procedure use at hospitals with >20% black inpatients Odds ratio for patients in hosp with >20% black inpatients compared to hosp with Comparison of Disparities at Hospitals with >20% or 20% or 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. Slide 17 END Slide 18 Procedure Rate Growth: 1989-1999 Procedures per 10,000 elderly Medicare Beneficiaries Slide 19 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.