Racial/Ethnic Disparities in Quality of Ambulatory Care for Chronic Physical Health Conditions: T he effects of physici

1. Racial/Ethnic Disparities in Quality of Ambulatory Care for Chronic Physical Health Conditions: The effects of physician and care setting characteristics Sponsored by The Robert Wood Johnson Foundation, New Connections Program Academy Health Conference June 2008 Rhonda BeLue PhD The Pennsylvania State University

2. Overview • Background • Rationale • Study Objectives • Methods • Data • Measures • Analysis • Results • Conclusions and Implications

3. Background

4. Background : Disparities in Health Care Quality • Racial/Ethnic inequities in exist in multiple domains of quantity and quality of care: safety, timeliness, effectiveness, efficiency, equity, and patient-centeredness • (Aaron 2003, Aaron 2003, Kirby 2006, IOM, Mayberry 2006, Ma 2005, Weisfeld 2005).

5. Background • Disparities exist across a wide variety of treatments for multiple conditions: including treatment for CVD, Heart failure and diabetes (IOM, Unequal Treatment). • It is believed that poor quality of care for ethnic minorities is linked to poor health care outcomes. (Lavizzo-Mourey 2005)

6. Background • In fact, it has been shown that improvements in quality of care for all US consumers are necessary (Asch 2006). • Wide variation also exists in racial disparities across geographic lines and care settings • (Baiker 2005, Baiker 2004, Wennberg 2006) Bach 2004, 2005).

7. Background • Despite the documented existence of inequities in healthcare quality, more work is needed to understand and test strategies to improve the quality of healthcare for ethnic minority populations (Beach 2006).

8. Background • African Americans are more likely to see health care providers in facilities with inadequate recourses and by providers with lesser credentials than facilities where whites receive care (Epstein 2004, Bach 2004). • African Americans are also likely to have poorer continuity of care largely due to lack of regular site of care.

9. African Americans are more likely to be seen in hospital clinics and community health centers where the chances of seeing the same provider across visits are low (Doescher 2001).

10. Background Peter Bach et al (2004) found that elderly Blacks and Whites are treated at racially homogeneous facilities that are either largely White or African American.

11. Background • Elderly blacks receive care at facilities which: • 1) provided more charity care • 2) had higher percentage of revenue from Medicaid • 3) were more likely to practice in a low-income neighborhood and • 4) were less likely to be board certified in their primary specialty. • 5) Physicians treating mostly white patients were more likely to indicate that they could confidently provide quality care and access to referrals, specialty care, and ancillary services

12. Rationale • Understanding the characteristics of health care facilities can inform interventions and policy making related to consumer access to care and choice of health care setting, resource management and allocation in settings that treat racial/ethnic minorities receive care

13. Contribution • This study adds to the literature by investigating the relationship between healthcare setting context and quality of care received for chronic conditions in adults ages 18 and older. • Diabetes will be used as an illustration for this presentation

14. Objectives Assess: • 1) racial/ethnic differences in the characteristics of the facilities where racial and ethnic minorities receive care • 2)The relationship between quality of care for diabetes and characteristics of the care setting

15. Conceptual Framework: The Chronic Care Model • Summarizes the basic elements for improving care in health systems at the community, organization, practice and patient levels. • Community characteristics: resources and policies • Health system characteristics: clinical information systems, design and delivery system • Provider characteristics: prepared and proactive • Patient characteristics: activated patient

16. Methods

17. Data and Sample • The 2005 National Ambulatory Medical Care Survey (NAMCS) were used for this investigation. • NAMCS uses a multistage stratified probability sample of patient visits in ambulatory care settings to enable nationally • NAMCS is designed obtain objective information about ambulatory medical care services in the United States • Whites, Blacks, and Hispanics aged 40 and older with Diabetes • Several other ACS conditions were explored

18. Measurement

19. Patients with conditions (diabetes) of interest were identified via ICD9 code (as indicated by the NAMCS diagnosis variable) and confirmed by physician report. • First, second and third diagnoses were included • Checked against physician report

20. Measures: Facility and Physician Characteristics Facility Solo or group practice Ownership Lab Testing available Difficulty with referrals EMR % of revenue Claims submitted electronically Physician: Employment status Does email consults Telephone consults Hospital visits Time spent with patient

21. Measures: Patient Characteristics • Demographics: age, gender, insurance status • Comorbid illnesses: bmi, total number of chronic conditions, number of medications • Number of visits in the past 12 months • Number of Medications

22. Measures: Dependent Variables • Quality measure(s) were derived based on measures from: • The National Quality Measures Clearing House • Selected measures relevant to ambulatory care settings

23. Quality indicators were calculated as the percentage of visits in which the patient received appropriate quality of care divided by the total number of visits.

24. Diabetes Quality Outcome • Ambulatory care management of diabetes measure • Diabetes • Process: • % of patients who received a HA1c test • *Should be taken every 3 months, especially in those with poor glycemic control

25. Analytic Strategy

26. Analytic Strategy: Aim 1 • Chi-square tests using Stata survey procedures were employed to examine the relationship between race/ethnicity and care setting characteristics

27. Analytic Strategy: Aim 2 • Logistic regression analyses were employed to examine the relationship between race, provider and facility characteristics and quality indicator controlling for patient demographic and health status indicators • Sample/design weights were incorporated • GEE for parameter estimation • Assessed moderation-within race/ethnicity models • Bonferroni adjustment for multiple comparisons • Modeled the probability of receiving HGBA

28. Results

29. Sample Characteristics • Sample represents a total of 15858 patient encounters among those over 40, • % of patient encounters among those with diabetes (weighted): • N=3078 diabetics • White: 11.5% • Black: 18.9% • Latino/a: 16.8%

30. Race and Outcome Measures

31. Diabetes • Among those who have diabetes, approximately at any encounter: • 13.9% of whites receive an HA1c screening • 7.4% of blacks receive an HA1c screening • 8.4% of Latino/as receive an HA1c screening • Significant at P<0.001

32. Results Aim 1

33. Results: Aim 2-Whites • More that 50% or revenue from Medicare- • OR = 0.24 ( 0.1, 0.5) • Difficulty Referring to Medicaid – • OR=0.35 ( 0.2, 0.7)

34. Results: Aim 2-Blacks • Seen in a solo practice : • OR = 1.8(1.7,2.1) • More that 50% or revenue from Medicare- : • OR = 0.4(0.1,0.7) • On Site Lab: • OR= 5.7(1.5,7.2)

35. Results: Aim 2-Latinos • Seen in a solo practice : • OR = 2.1(1.6,2.7) • On Site Lab: • OR= 1.5(1.5,7.2)

36. Limitations • Cross-sectional data • Lack of financial data to accurately asses level of resources • Need of composite score or better interpretation of what facility characteristics mean • Patient preferences for care setting • Combine several years to increase N for minority groups and to allow for more comparisons

37. Conclusions • Future health services and quality initiatives may benefit from focusing on improving resources in care settings in order to improve quality and treatment of chronic conditions in racial and ethnic minorities

38. Acknowledgements • The Robert Wood Johnson Foundation, New Connections Program • Dr. Debra J. Perez • Dr. Margarita Alegria • Junior Investigator Forum Colleagues