1 Measurement Challenges in Reducing Disparities in Health Care Sheldon Greenfield, MD Executive Director University of California, Irvine Center for Health Policy Research 19 th National Conference on Chronic Disease Prevention and Control March1-3, 2005

2 NHDR “ But while Unequal Treatment demonstrates definitively that racial and ethnic disparities in health care exist, it does not measure the magnitude of the problem from a national perspective. The report also does not address disparities in access to health care or disparities related to socioeconomic position.”

3 “Rather than offer a series of snapshots of disparities from individual research studies, this report provides a comprehensive view of the scope and characteristics of differences in health care quality and access associated with patient race, ethnicity, income, education, and place of residence.”

4 National Healthcare Disparities Report Conceptual Framework Access to care Entry barriers Structural barriers Cultural barriers Use Costs Quality of Care Effectiveness Safety Timeliness Patient centeredness

5 Features of NHDR Comprehensive Multiple data sources Can interact with SES Longitudinal measures Merges access with quality Initial measures supported

6 NHDR Key Findings Inequality in quality persists Disparities come at a personal and societal price Differential access may lead to disparities in quality Opportunities to provide preventive care are frequently missed Knowledge of why disparities exist is limited Improvement is possible Data limitations hinder targeted improvement efforts

7 Disparities are Pervasive Across all dimensions of quality of health care including effectiveness, patient safety, timeliness, and patient centeredness. Across all dimensions of access to care including getting into the health care system, getting care within the health care system, patient perceptions of care, and health care utilization. Across many levels and types of care including preventive care, acute care, and chronic care.

8 Disparities are Pervasive (cont’d) Across many levels and types of care including cancer, diabetes, end stage renal disease, heart disease, and respiratory diseases. Across many care settings including primary care, dental care, mental health care, substance abuse treatment, emergency rooms, hospitals, and nursing homes. Within many subpopulations including women, children, elderly, persons with disabilities, residents of rural areas, and individuals with special health care needs.

9 Figure 2.2 Adults with diabetes who had all five recommended diabetic services in the past year, by race, ethnicity, and income,

10 In 2001, the proportion of adults with diabetes who received all five recommended diabetic services was lower among blacks compared with whites and among Hispanics compared with non-Hispanic whites (Figure 2.2). In 2000 and 2001, differences across income groups in the proportion of adults with diabetes who received all five services were not significant. In multivariate models controlling for age, gender, income, education, insurance, and residence location, blacks were 38% and Hispanics were 33% less likely than their respective comparison groups to receive all services in 2001.

11 Figure 3.7 Adults whose providers sometimes or never listen carefully to them by race, ethnicity, and income,

12 In 2001, the proportion of adults with providers who sometimes or never listen carefully was higher among API compared with white, Hispanic compared with non-Hispanic white, and poor, near poor, and middle income compared with high income adults; black-white differences were not noted. Between 2000 and 2001, rates of adults with providers who sometimes or never listen carefully did not change significantly among any groups. In multivariate models controlling for age, gender, income, education, insurance, and residence location, the difference between Hispanic and non-Hispanic whites is attenuated, but other differences persist. APIs are 73% more likely than whites to have providers who sometimes or never listen carefully. Compared with high income adults, poor, near poor, and middle income adults are 52%, 56%, and 37% more likely to have providers who sometimes or never listen carefully, respectively.

13 Interpretation Poor data sources Poor measures Individual measures unreliable Multiple solutions

14 Why aggregate Why aggregate? Individual measures are not reliable, well-behaved Aggregate scores easier for public, insurers, employers to use Aggregate scores are fairer to physicians (multiple ways to get a good score) Individual measures in aggregates can still be used (e.g. for quality improvement)

15 Creation of Aggregate Profile Score MeasureCorrelation with Total Annual HbA1c.41 Annual lipids.73 Annual urine microalbumin.30 Annual eye exam.43 Annual foot exam.39 HbA1c < 9%.44 LDL < 130 mg/dl.61 HDL OK.63 Triglycerides < 200 mg/dl.57 BP <140/90.18 Cronbach’s α =.78

16 Creation of Aggregate Profile Score Measure Correlation with Total Sum 5 process measures.62 HbA1c < 9%.45 LDL < 130 mg/dl.62 HDL OK.63 Triglycerides < 200 mg/dl.61 Cronbach’s α =.82

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18 Interpretation Poor data sources Poor measures Individual measures unreliable Multiple solutions

19 Conclusions Huge progress, but Better measures: (SES, quality) Better analysis Better data sources Better defined groups Put on firm financial footing