Reducing Disparities:

1. Reducing Disparities: The Importance of Collecting Standardized Data on Patient Race, Ethnicity and Language Aligning Forces for Quality National Program Office

2. Why are we here? • Understand the role of standardized R/E/L data collection in reducing disparities • Identify and consider the key decision points to successfully implement standardized R/E/L data collection in your organization • Obtain knowledge and tools to train staff on the standardized collection of R/E/L data

3. What will we cover today? • Building blocks toward equitable care • National health care disparities • Increasing attention R/E/L data • Linking R/E/L data to quality • Using data to drive improvements • Key Decision Points • Changes at the organizational level • Nuts and Bolts • Tools to train your staff

4. What are disparities in health care quality? “Racial and ethnic minorities tend to receive a lower quality of healthcare than non-minorities” Less likely to receive: Cancer screening Cardiovascular therapy Kidney dialysis Transplants Curative surgery for lung cancer Hip and knee replacement  Pain medicines in the ER

5. Growing U.S. minority population Population Projections, 2010 to 2050 Source: U.S. Census Bureau, 2009 National Population Projections (Supplemental) 4. Projections of the Population by Sex, Race, and Hispanic Origin for the United States: 2010 to 2050

6. Increasing legislative and regulatory attention to R/E/L • American Recovery and Reinvestment Act of 2009 • Hospitals and providers will need to collect R/E/L data to be eligible for “meaningful use” incentive payments • Race/Ethnicity follow Office of Management and Budget guidelines • Patient Protection and Affordable Care Act of 2010 • Health programs receiving federal money are required to collect R/E/L data • NCQA Patient-Centered Medical Home Standards • Points toward recognition earned by collecting and analyzing R/E/L data • Revised Joint Commission standards • Expanded requirements related to the collection of patient language data • New requirement to collect patient-level data on race and ethnicity

7. Office of Management and BudgetRace and ethnicity categories Race • Black • White • Asian • American Indian/Alaska Native • Native Hawaiian/ Pacific Islander Ethnicity • Hispanic • Not Hispanic

8. Identifying and addressing disparitiesThree steps • Standardized collection of self-reported R/E/L data • Categories are standardized • Patient self-reports • Stratification and analysis of performance measures • Compare patients within an organization • Consolidate data to identify community-level trends • Use of stratified data to identify and develop quality improvement interventions targeted to specific patient populations

9. National CABG rates Rate per 1,000 Medicare enrollees Jha, NEJM, 2005

10. Diabetes OutcomesBetter Health Greater Cleveland http://www.betterhealthcleveland.org/Analysis/Conditions/Diabetes.aspx

11. Using R/E/L data to drive improvement Massachusetts General Hospital Chelsea Diabetes Project • Identified disparity between white and Latino patients in diabetes control and recommended care • Created culturally competent Diabetes Management Program • Improved mean HbA1c values for all patients, reduced gap between white and Latino patients • Increased overall number of patients with HbA1c test within past 9 months and eliminated disparity Source: Disparities Solution Center at MGH http://dx.confex.com/dx/8/webprogram/Paper2024.html

12. How else can you use R/E/L datawithin your organization? • Provide more patient-centered care • Develop cultural competency training for staff • Compare utilization of health services among different patients • Compare patient satisfaction with care provided among different patients • Target marketing materials to specific patient populations • Capture changes in demographic trends

13. What needs to happen withinyour organization? • Develop the capacity and infrastructure to collect standardized race, ethnicity and language information from all patients • This will affect: • Registration system and processes • Staff training and workflow • Patient communications • How data are used to monitor quality

14. Key Decision Points in Standardizing Patient Race, Ethnicity and Language Data Collection

15. Key decision points to consider • Where are data currently collected? • Who needs to be engaged? • What registration system and IT modifications need to be made? • How will staff be trained?

16. Where are data collected? • When scheduling/registering an office visit • Face-to-face • Written registration forms • Telephone • Upon admission or registration at the hospital • Face-to-face • Telephone registration • All points of entry (inpatient, outpatient, emergency department, cardiac catheterization lab, etc.) • “Downstream effect” – Registries and other databases Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

17. Who needs to be engaged? • Senior Leadership • Information Technology staff • Registration/Admissions staff • Quality Improvement • Interpreter Services • Clinicians • Patient Advocacy/Diversity Team • Community Relations/Marketing Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

18. What registration system and IT modifications need to be made? • Will you need add data fields to accommodate new categories? • Will you use granular categories? • Can patients choose more than one race? • Will you collect both spoken and written language? • What is your system’s capacity to add a field? • Can the change be made ‘in-house’ and house-wide? • What departments need to be involved to make changes to the system? • Is there a need to create combined R/E categories? • Will these fields be hard stops?

19. How will staff be trained? Who needs to be trained? Who will provide training? How will the training be implemented? Role-playing? Handouts/scripts? Screen content? Will data be monitored after the training? How will you monitor staff? Will feedback be given? Will registrars see how data is used? 19

20. Anticipating staff concerns • Patients will get angry • It’s illegal • Patients will get angry • We don’t need to collect this information • Patients will get angry • I’m uncomfortable asking these questions • Patients will get angry • It will take too much time • Patients will get angry

21. Nuts and Bolts of Collecting Patient Race, Ethnicity and Language Data: Staff Training

22. Purpose of this training • We are implementing a standardized method of collecting race, ethnicity and language (R/E/L) data as self-reported by patients or their caregivers. • You are key to ensuring that all data are collected consistently, accurately, professionally, and completely.

23. Learning Objectives • After this training session you will be able to: • Describe the reasons for standardizing the collection of patient R/E/L • Use scripts to ask each patient to self-identify his/her R/E/L • Address patient questions and concerns

24. What is standardized data collection? • Standardized categories across the organization • Patient self-reports race, ethnicity and language • No more “eyeballing” the patient • Data is collected from all patients

25. Why collect standardized R/E/L data? • We can ensure adequate interpreter services, patient information materials, cultural competency training for staff. • We can link patient race, ethnicity and language data with clinical information to improve quality and examine any health care disparities. • We can use quality improvement tools/techniques to address any health care disparities. • By collecting this information, we can ensure that all patients receive high-quality care.

26. “….but we already collect this information!” • That may be true, but studies examining R/E/L data collection in hospitals and ambulatory practices show: • In many organizations that currently collect R/E/L data, not everyone is doing a good job. • Many registrars collect the information by observing the patient and guessing. Allowing the patient to self-identify will lead to more accurate and reliable data.

27. Challenging assumptions – guess their race

28. How will the registration process change? These are the recommended questions—your organization may choose to revise this list. Letting your patients know Ethnicity Race Preferred written and spoken language

29. Recommended script for letting patients know “We want to make sure that all our patients get the best care possible. We would like you to tell us your racial/ethnic background and preferred language so that we can review the treatment that all patients receive and make sure that everyone gets the highest quality care.” This is a recommended script —your organization may choose to use a different or revised script. Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

30. Recommended script for ethnicity “First, do you consider yourself Hispanic or Latino?” • Yes • No • Declined • Unavailable This is a recommended script —your organization may choose to use a different or revised script, or use different categories. If applicable, you can include a screen shot that will show registration staff any changes to the computer screen that staff see during registration Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

31. Ethnicity definitions Hispanic or Latino: Person of Cuban, Mexican, Puerto Rican, South or Central American decent, regardless of race. Non-Hispanic or Latino: Person not of Hispanic or Latino ethnicity. Declined*: Patient is unwilling to provide an answer to the ethnicity question or cannot identify him/herself as Hispanic or Not Hispanic. Unavailable*: Patient is physically unable to respond. Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

32. Recommended script for race “Which category best describes your race?” • American Indian/Alaska Native • Asian • Black/African American • Native Hawaiian/Other Pacific Islander • White • Declined • Unavailable • Some other race This is a recommended script —your organization may choose to use a different or revised script, or use different categories. Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

33. Race definitions American Indian or Alaska Native: Person having origins in any of the original peoples of North and South America (including Central America) and maintains tribal affiliation. Asian: Person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent. Black or African American: Person having origins in any of the black racial groups of Africa. Native Hawaiian or Other Pacific Islander: Person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. White: A person having origins in any of the original peoples of Europe, the Middle East, or North Africa. Some Other Race*: A person who does not self-identify with any of the OMB race categories. Declined*: Patient is unwilling to choose a race category or cannot identify him/herself with one of the listed races. Unavailable*: Patient is physically unable to respond. * This symbol indicates a modification we have made to the OMB recommendations Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 27, 2011

34. “What language do you feel most comfortable speaking with your doctor or nurse?” English Spanish Other Declined Unavailable “What language do you feel most comfortable reading medical or health care instructions?” English Spanish Other Declined Unavailable Recommended script for patient’s preferred language If your organization is going to use different questions, you can use that text on this slide. Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

35. Preferred spoken: the language a patient feels most comfortable speaking with their doctor or nurse Preferred written: the language a patient feels most comfortable reading medical or health care instructions Declined: A person who is unwilling to state a language preference. Unavailable: Patient is physically unable to respond. Language definitions If your organization will not ask preferred written language, you can remove that text from this slide.

36. “I Speak” Poster 36 Source: Cambridge Health Alliance (Cambridge, MA)

37. What do patients think? • Most patients (80%) think hospitals and clinics should be collecting data. • Most patients (97%) also think it’s important for hospitals and clinics to examine differences in quality. • Some patients are concerned about how the data will be used. Baker, DW, et al. Patients’ Attitudes toward Health Care Providers Collecting Information about Their Race and Ethnicity. Journal of General Internal Medicine. Volume 20 (10): 895 – 900. August 2005.

38. Letting your patients know Wall Posters Can be displayed in: • Registration areas • Waiting rooms

39. Addressing patient concerns Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

40. Addressing patient concerns Source: HRET Toolkit, http://www.hretdisparities.org/ accessed on Sept 16, 2009

41. Acknowledgements This presentation was adapted from the Health Research and Educational Trust Disparities Toolkit as part of the Aligning Forces for Quality (AF4Q) initiative, supported by the Robert Wood Johnson Foundation.