USING RACE AND ETHNICITY DATA AS TOOLS FOR QUALITY IMPROVEMENT

1. USING RACE AND ETHNICITY DATA AS TOOLS FOR QUALITY IMPROVEMENT Romana Hasnain-Wynia, PhD GIH PHONE CONFERENCE JUNE 7, 2005

2. What We Don’t Know • Why and Howdisparities occur - Quality of care hindered because of bias and prejudice - Quality of care hindered because of communication, language, or cultural barriers • Which interventions are effective at reducing or eliminating disparities • What proportion of observed disparities are amenable to improvements in health care • How to collect relevant data respectfully -- and when

3. Why HCOs Should Collect Data On Patient Race/Ethnicity And Language Internal Factors • Valid and reliable data are fundamental building blocks for identifying differences in care and developing targeted interventions. • Being responsive to communities: Pressing community health problems such as disparities in care can be addressed more effectively if health care organizations and health professionals build the trust of the community by documenting accomplishments. • Link race and ethnicity information to quality measures to examine disparities and undertake targeted interventions • Ensure the adequacy of interpreter services, patient information materials, and cultural competency training for staff

4. External Factors • Federal and state reporting requirements e.g. CMS has implemented policies to use race and ethnicity data for quality improvement purposes, under Medicare + Choice managed care plans are required to identify racial and ethnic disparities in clinical practice • Accreditation the Joint Commission on the Accreditation of Healthcare Organizations and the National Committee for Quality Assurance may require race/ethnicity data collection

5. Focus on data is good only insofar that we remember: “It is not the data, it is what you do with it” -------Maryland Hospital Indicator Project “ We can not manage what we can not measure.” ---David Kindig, M.D., M.P.H., University of Wisconsin School of Medicine

6. Patient Experiences with the Health Care System Percent who say that they have felt that a doctor judged them unfairly or treated them with disrespect because of …. Kaiser Family Foundation Survey of Race, Ethnicity, and Medical Care, October 1999

7. Results Hospitals that did not collect data on race and ethnicity were asked why. • Sixty-seven percent felt is was unnecessary • No reliable system for data collection (18%) • Lack of a good classification system (15%) • Data too costly to maintain (7%) • Data would be unreliable (7%) • Not authorized by the hospital though it was legally (7%) • Prohibited by law or external regulation (4%)

8. Barriers to Collecting Data • Resource limitations • Categorization • Staff training • Validity and reliability of • data • Legal concerns • System/organizational barriers • Patients’ perceptions/language • and culture

9. Other Health Care Organizations • Medical Group Practices • Less likely to collect race/ethnicity information than hospitals • 75% didn’t collect data because they thought it was unnecessary or • That the collection was potentially disturbing to patients. • (Nerenz, et al. 2003). • Health Plans • Health plans do not routinely capture information on race/ethnicity • of their members and do not assess quality of care stratified by race • and ethnicity (Nerenz, et al. 2002) • AHIP notes that collection of data by health plans is fragmented. • AHIP and RWJ study found that 74% of plans that responded to a • survey collect information on enrollment. • Health plans cite same barriers to data collection

10. Study Questions • How do people feel about being asked about their race and ethnicity? • Do attitudes change when they know the rationale for collecting this data? (e.g., desire to measure quality of care and ultimately reduce disparities)? • Do people prefer an open-ended format versus choosing from a list of options? *This pilot study was conducted at Northwestern University (NU) School of Medicine/ Northwestern Memorial Hospital (NMH). NU/NMH site Principal Investigator, David W. Baker, MD, MPH

11. Most Patients Agreed That It Was Important to Collect Race/Ethnicity Data “It is important for hospitals & clinics to collect information from patients about their race or ethnic background.” Would you say that you: Strongly Agree 43% Somewhat Agree 37% Unsure 6% Somewhat Disagree 10% Strongly Disagree 4% NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH

12. Even Stronger Support that Hospitals Should Examine Differences in Quality “It is important for hospitals & clinics to conduct studies to make sure that all patients get the same high quality care regardless of their race or ethnic background.” .” Would you say that you: Strongly Agree 93% Somewhat Agree 4% Unsure 2% Somewhat Disagree 1% NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH

13. Significant Concerns About How This Data Might Be Used “How concerned would you be that this data could be used to discriminate against patients? Not concerned at all 34% A little concerned 15% Somewhat concerned 20% Very concerned 31% 14% said somewhat/much less likely to go to a hospital/clinic that collected race/ethnicity data. NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH

14. Thoughts • Open-ended questions appear to work well. • Minimal time required to answer. • Still, many patients uncomfortable. • Separate question about Latino/Hispanic? • Need to include questions on language barriers. • No validation yet of back-end coding. • Implementation/evaluation planned for NMH. NU/NMH pilot study, site Principal Investigator: David W.Baker, MD, MPH

15. The Case For A Uniform Framework • Eliminate current fragmentation in data systems within and across HCOs • Can serve as a tool for organizations to achieve comparability • Can increase efficiency and accuracy and reduce redundancy and costs • Provide a solid foundation for targeting quality of care initiatives and reduce disparities. • By linking clinical data with race/ethnicity and language, HCOs • would be able to track the care process and develop interventions that target quality improvement efforts for their most vulnerable populations.

16. What Do We Need? • Reliable Race, Ethnicity and Language Data • National Performance Measures • Electronic Health Record Systems • What Do We Have: • Health Plans—HEDIS quality measures • Hospitals---CMS quality measures • Ambulatory Care Setting-Ambulatory Care Performance measures

17. Improving Quality For All Reduces Disparities The gap between blacks and whites in the adequacy of hemodialysis dose decreased from 10% to 3%. The gap between female and male patients decreased from 23% to 9%. Source:   Sehgal, Impact of Quality Improvement efforts on Race and Sex Disparities in Hemodialysis. JAMA, Volume 289(8). Feb 26, 2003.996–1000.

18. Project Goals • Measure disparities in inpatient quality of care for three conditions (Acute Myocardial Infarction, Heart Failure, Pneumonia). • Assess hospital response to reporting these data (through case studies) • Assess the feasibility of implementing the Uniform Framework for collecting race, ethnicity, and primary language data at Northwestern Memorial Hospital

19. Project Team • Health Research and Educational Trust: • Principal Investigator (PI), Romana Hasnain-Wynia, PhD • Project Coordinator, Debbie Pierce • Northwestern Memorial Hospital: • Co-PI, David Baker MD, MPH • Co-Investigator, Joe Feinglass, PhD • Henry Ford Health System: • Co-PI, David Nerenz, PhD • Massachusetts General Hospital: • Co-PI, Joel Weissman, PhD

20. Background • Hospital Quality Alliance • One of many efforts in CMS’s overall Hospital Quality Initiative to foster hospital quality improvement through a variety of quality measurement and improvement opportunities. • 3,793 hospitals are participating as of May 5, 2005. • Focus on three conditions • Acute Myocardial Infarction • Heart Failure • Pneumonia • Ten Measures • Derived from evidence in the medical literature and tested extensively in the hospital setting. • http://www.cms.hhs.gov/quality/hospital/

21. University Health System Consortium (UHC) • UHC is an alliance of academic health centers in the United States aimed at improving performance levels in clinical, operational, and financial areas. • UHC is collecting the quality measures for the three conditions with patient race and ethnicity information for 123 hospitals. • UHC is conducting analyses of these 123 hospitals for this project. • We are currently in the midst of data analyses.

22. Initial Analysis • Looked at data from 89 hospitals • (time frame: Quarter 3 2002- Quarter 1 2004) • Total Admissions, 118, 279 • We examined mean rates and median times (in minutes for continuous measures) for each of the quality measures. • In preliminary analyses, found differences in mean rates and median times for measures requiring personal interaction with patients.

23. Further Analyses Showed: • There are substantial disparities ACROSS hospitals for all the measures. Those hospitals serving a high percentage of minority patients do worse on all the measures…they are the poorer quality hospitals based on these indicator. • Next: • Examine disparities across hosp more carefully controlling for clustering etc.. • Examine disparities within hosp • Discuss the policy levers for both • Will present at AcademyHealth in Boston end of June.

24. LET ME POINT OUT THAT…. • This work wouldn’t have been possible without race and ethnicity data • OR without national performance measures which are uniformly collected • EMR would make this endeavor easier but not all hospitals are there yet…..

25. Closing Comments • We have made headway but have a long way to go… • Where next—pushing the envelop a bit • Better data on patient demographics (not just r/e) • Ability to link these data to performance measures in multiple settings (health plan, hosp, ambulatory care) to REALLY look at processes of care and health outcomes to truly target interventions at the clearest points of vulnerability • Movement to a National Health Information Technology system EMR