1. Using Demographic Data to Provide Patient-Centered Care: Why Data Collection is Important Romana Hasnain-Wynia, PhD Health Research and Educational Trust/AHA November 3, 2006

2. “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 Focus on data is good only insofar that we remember:

3. Health Care Should Be Safe Effective Patient-Centered Timely Efficient Equitable

4. Patient-Centered Care Incorporates respect for patients’ values, preferences, and expressed needs Is highly customized and incorporates cultural competence

5. Equitable Providing care that does not vary in quality because of personal characteristics such as gender, ethnicity, geographic location and socio-economic status

6. Disparities in Health Care STUDY CHARGE Assess the extent of racial and ethnic differences in healthcare that are not otherwise attributable to known factors such as access to care Evaluate potential sources of racial and ethnic disparities in healthcare, provide recommendations regarding interventions to eliminate healthcare disparities.

8. A National Problem African Americans are: –Less likely to have a kidney transplant, surgery for lung cancer, bypass surgery. –More likely to have a foot amputation. –More likely to die prematurely Latinos/Hispanics are: –Less likely to receive pain medications What about other groups? Chinese? Vietnamese Pakistanis? Nigerian? Somali? Haitian, etc….

9. Evidence of Racial and Ethnic Disparities in Healthcare Disparities consistently found across a wide range of disease areas and clinical services Disparities are found even when clinical factors, such as stage of disease presentation, co-morbidities, age, and severity of disease are taken into account

10. …..Continued Disparities are found across a range of clinical settings, including public and private hospitals, teaching and non-teaching hospitals, ambulatory care settings, etc… Disparities in care are associated with higher mortality among minorities (e.g., Bach et al., 1999; Peterson et al., 1997; Bennett et al., 1995)

11. Questions WHY and HOW disparities occur 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

12. CHANGING DEMOGRAPHICS: CHANGING NEEDS

13. Demographic Changes The U.S. population grew by 13% between 1990 and 2000. (Andrulis et al. 2003) Foreign born population living in the US increased by 44% to 28.4 million people during this period. (U.S. Census Bureau 2002). In 2000, the foreign born population comprised 10 percent of the total population, its highest since 1930. (U.S. Census Bureau 2002) Over 300 different languages are spoken in the U.S. and nearly 52 million people (19% of the U.S. population) speak a language other than English at home. (U.S. Census Bureau 2005)

14. Encounters with LEP Patients 80% of hospitals encounter patients with LEP frequently 43% daily, 20% weekly, 17% month HRET, 2006

15. Languages That 20% or More of Hospitals Encounter Frequently Spanish 93% Chinese 47% Vietnamese39% Japanese37% Korean 37% Russian37% German36% French31% Arabic26% Italian26% Laotian23% Hindi22% Polish 22% Tagalog21% Thai20% Source: HRET, 2006

16. Race/Ethnicity Data Why Collect It Current Practices Barriers

17. Why Collect Data? To monitor quality of care for all populations Target interventions appropriately to improve health care delivery

18. Equity Domain of “Equity” is not “top of mind” for senior administrative and clinical leaders. Disparities is “not our issue.” They happen “before” and “after” the hospital. Great concern that addressing disparities somehow acknowledges discrimination or otherwise bad behavior. Source: 42 key informant interviews: Bruce Siegel, MD, MPH Planning Grant for Robert Wood Johnson for Expecting Success, 2004

19. Equity Clinical Leadership N. Lurie, et al. Circulation (2005) 344 Cardiologists: -34% agree disparities exist overall -12% believe disparities exist in own hospital -5% believe disparities exist in own practice S. Taylor, et al. Annals of Thoracic Surgery (2005) 208 Cardiovascular Surgeons: -13% believe disparities occur often or very often -3% believe disparities occur often or very often in own practice

20. Why Collect Data On Patient Race/Ethnicity 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 Internal Factors

21. Why Collect Data continued… External Factors Reporting to the Joint Commission on Accreditation of Healthcare Organizations Reporting to CMS (payer, purchaser regulator, insurer, works through QIOs) State mandates

22. Current Practices: National Survey of Hospitals Who, When, and How: The Current State of Race, Ethnicity, and Primary Language Data Collection in Hospitals, 2004 CMWF

23. Nuts and Bolts of Data Collection Addressing Discomfort Categories Staff training Start the dialogue with the community before implementing systematic data collection on race/ethnicity/language

24. Recommendations For Standardization Who provides the information When to collect Which racial and ethnic categories to use Where and how data are stored Address Patients’ Concerns Provide Staff training

25. Common Barriers To Collecting Data Validity and reliability of data Legal concerns System/organizational barriers Appropriate categories Patients’ perceptions/language and culture Staff discomfort in explicitly asking patients to provide this information. *

26. A Project in Chicago

27. Using Health Information Technology to Provide Patient-Centered Care, Improve Quality and Reduce Disparities Valid measures of hospital and physician clinical performance Coordination of care Exchange of information between providers/practitioners and patients Improve safety

28. Project: Adding Race/Ethnicity and other Patient Demographic Information to Chicago Community Health Center Clinical Performance Information Systems The Partnership: -Health Research and Educational Trust -Alliance of Chicago Health Services -American Medical Association Funded by the Commonwealth Fund and the Robert Wood Johnson Foundation

29. American Medical Association Convened the Physician Consortium for Performance improvement, which aims to provide performance measurement resources to facilitate clinical quality improvement programs. The Consortium developed the Physician Performance Measurement Sets: Diabetes, Asthma, Coronary Artery Disease, Heart Failure, Hypertension, Prenatal Care, Prevention and Immunizations

30. Alliance of Chicago Health Services A group of community health centers with 24 clinical sites throughout Chicago serving 65,000 clients in 305,000 encounters annually. The Alliance was chosen by the Bureau of Primary Health Care to implement EHRs. The Alliance is integrating the Performance Measures into the EHRs and creating a data warehouse through funding from AHRQ.

31. ADVANCE

32. The project covers three critical areas in improving health care delivery: Adoption of health information technology (Electronic Health Record Systems) as a tool to monitor and improve quality of care. Patient Centered Care ( such as respect for patient values, preferences and needs, information/education, emotional support and involvement of family to remove fear and anxiety). Improving the quality of care for vulnerable populations through targeted interventions.

33. What Do We Mean by Linking Demographic Data to Clinical Data? Clinical Performance Measures will be linked with demographic data in the EHRs A.Will utilize the extract, transfer, and load software developed by General Electric. (Extraction will occur on a nightly basis.) B.The data will be loaded in a clinical data warehouse, which will be used to generate the clinical performance measure reports. C.The reporting process will include the transfer, linking, and aggregation of the patient demographic data with clinical data.

34. Goals: Standardize a process for collecting patient demographic data on patient race, ethnicity, language, health literacy (education), acculturation (years lived in the US), and socioeconomic status (family size, insurance, income). Link patient demographic data with national clinical performance measures in an electronic health record system. Show health care processes and outcomes for specific conditions stratified by key patient demographic information (to identify targeted opportunities for QI).

35. Adult Diabetes Performance Measures- Current System Captures the following: Performance Measure Provider Number Birth DateGender Hemoglobin A1c Lipid profile Fasting Total Cholesterol HDL-C LDL-C Triglycerides Influenza Vacc Foot Examination Dilated Retinal Eye Exam Smoking Aspirin Use

36. Adult Diabetes Performance Measures-New System Would Capture the following: Performance Measure Provider number BirthGender Race EthnicityLangEduc Years in US Fam Size Hemoglobin A1c Lipid profile Fasting Total Cholesterol HDL-C LDL-C Triglycerides Influenza Vacc Foot Examination Dilated Retinal Eye Exam Smoking Aspirin Use

37. Contributions IOM report, Crossing the Quality Chasm, calls for “national consensus on comprehensive standards for the definition, collection, coding, and exchange of clinical data.” IOM report, Unequal Treatment, calls for the collection and reporting of data on health care access and utilization by patients’ race, ethnicity, socioeconomic status, and where possible, primary language;

38. Benefits Standardize patient demographic data collection. Collect clinical performance measures. Link patient demographic data to clinical performance measures in an electronic health record system at clinical sites. This work speaks to the growing consensus that clinical quality improvement efforts should include key patient demographic data that allow for more targeted and efficient quality improvement interventions within health care organizations. In addition, this work will assess the feasibility of using electronic health record systems as a tool in quality improvement efforts in community health centers.