Eliminating Health Care Disparities: Why and How

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Understand why hospitals must take the lead in eliminating disparities in care …

Understand why hospitals must take the lead in eliminating disparities in care
Learn about the various dimensions of health care disparities. This presentation provides a background on the factors contributing to health care disparities, the ways in which race, ethnicity and language (REaL) data may be applied to improve health equity, as well as strategies through which to enhance the collection of REaL data.

Authors: Bohr D, Bostick N

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  • We’ll return to these 3 action steps near the end of the presentation in order to suggest some concrete, doable next steps for your consideration.
  • As you are well aware, the population of Robeson County is extremely diverse, with a large portion of the population consisting of Native Americans and African Americans.
  • Address how, unlike many urban areas, ethnicity and accompanying language considerations, may be less of an issue for SRMC. Ask the Health Disparities Taskforce if this is something to consider moving forward.
  • You know your health statistics better than we do, of course; the next set of slides is to illustrate the point that we recommend that all medical centers know there population health data as well as the major conditions treated in their facility, which is derived from your discharge data. For example, we understand that CHF and Diabetes are major conditions in your area.
  • ACA—requiring enhanced demographic data collection; HCAPS scores and Value-based purchasing. In NY state, Medicaid Redesign Team Disparities Group…
  • Recent study in Annals of Emergency Medicine looked at professional interpreters in the Emergency Dept. “Professional Interpreters in ER Need Training More Than Experience.” Found that 2% of errors with potential clinical consequences for professional interpreters that received at least 100 hours of training. This is contrasted with 12% of errors with potential clinical consequences for professional interpreters that received less than 100 hours of training.
  • In addition to knowing the health statistics in your community, you can begin the journey by collecting Race, Ethnicity and Primary Language or REAL data. The next series of slides will give you a taste of the training that HRET does with admitting or registration staff for the purpose of helping to ensure that Race, Ethnicity and Primary Language data are collected in a respectful manner and that the admitting and registration staff feel comfortable collecting this information.
  • Miscommunication with these populations is associated with excessive utilization of diagnostic tests.
  • So, we went through the Response Matrix, which is part of our training for admitting staff, fairly quickly. Let’s recap again some top FAQs. We’ll go through these fairly quickly, too.
  • Now let’s turn our attention to using these data to make a difference. If these data are not use to increase the medical center’s understanding of whether there are differences in outcome for different sets of patients, then the organization is missing a tremendous opportunity.
  • to address quality differentials. In a bit, we’ll provide highlights from a few case studies to illustrate how this can be done.Example of culturally-tailored intervention: For Hispanics, four culture-related processes highly relevant for health interventions and outcomes include acculturation, family functioning, familism, and culturally related stress. We need to gain a better understanding of how such culture-related factors contribute to risk for and protection from disease and problematic health behaviors and how these cultural factors influence responses to interventions. A better understanding of the impact of these factors can help us refine interventions and make them more effective as well as design interventions that can address multiple disorders that have common root causes.
  • This is a simple example of what some organizations call an “Equity Dashboard.” It’s just the
  • So, how to begin this journey…

Transcript

  • 1. TRANSFORMING HEALTH CARE THROUGH RESEARCH AND EDUCATION June 2012 Deborah Bohr, MPH Andy Bostick, MA, MPP Eliminating Health Care Disparities: Why and How
  • 2. Session Objectives • Understand why hospitals must take the lead in eliminating disparities in care • Learn about the various dimensions of health care disparities • Review health facts for Robeson County • Explore strategies for collecting REaL data • Learn how to use REaL data to reduce health care disparities and improve health equity
  • 3. BACKGROUND ON HEALTH CARE DISPARITIES
  • 4. Elements of Quality Health Care • Safe • Effective • Patient-Centered • Timely • Efficient • Equitable
  • 5. STEEEP Examples IOM Domain Examples Safe Central Line infections Timely Radiology turn-around times Effective Appropriate discharge meds Efficient Average length of stay Equitable ??? Patient Centered Patient/employee satisfaction
  • 6. Disparities in Health Care • Systematic review of a large body of research found significant variation in the rates of medical procedures by race, even when insurance status, income, age, and severity of conditions were comparable • Findings indicated that minority patients were less likely to be given appropriate cardiac medications or to undergo bypass surgery, and are less likely to receive kidney dialysis or transplants. Conversely, minority patients were more likely to receive such as lower limb amputations for diabetes and other conditions.
  • 7. Disparities in Health Care • Disparities still exist: • African Americans received substandard care relative to Whites for 41% of quality measures • Asians and American Indians and Alaska Natives received substandard care relative to Whites for about 30% of quality measures • Hispanics received substandard care relative to non-Hispanic Whites for 39% of measures
  • 8. Causes of Health Care Disparities • Poor provider-patient communication • Patient mistrust • Stereotyping and bias • Access to evidence-based practice
  • 9. National Call to Action to Eliminate Health Care Disparities • Joint effort of the American College of Healthcare Executives, American Hospital Association, Association of American Medical Colleges, Catholic Health Association of the United States, and National Association of Public Hospitals and Health Systems to eliminate health care disparities • Goals include: • Increase the collection of race, ethnicity and language preference data • Increase cultural competency training for clinicians and support staff • Increase diversity in governance and management
  • 10. ROBESON COUNTY POPULATION FACTS
  • 11. Robeson County Population Composition 29.00% 24.30% 38.40% 0.70% 0.10% 2.50% 2010 Racial Demographic Data White African American/Black American Indian and Alaska Native Asian Native Hawaiian and Other Pacific Islander Two or more races
  • 12. Robeson County Population Composition 8.1% 91.9% 2010 Ethnic Demographic Data Hispanic or Latino Non-Hispanic
  • 13. Racial Differences in Health Care Access From NC Center for Health Statistics
  • 14. Racial Differences in Chronic Disease Incidence From NC Center for Health Statistics
  • 15. Racial Differences in Mortality Rates From NC Center for Health Statistics
  • 16. WHY ADDRESS HEALTH CARE DISPARITIES?
  • 17. Ethical Case • All medical centers and their staff want to provide the same quality of care to ALL their patients
  • 18. Business Case • Quality differentials can affect HCAHPS Scores, which has implications for hospital revenue under value-based purchasing and pay-for- performance models • Disparities in care can be costly to hospitals as they contribute to the following: • Extended length of stay • Preventable re-admissions • Hospital-acquired conditions
  • 19. Risk Management Case • Medical errors • Poor or inadequate informed consent • Discounting pain and suffering through miscommunication • Failure to recognize or take into account the patient’s cultural, religious, or ethnic beliefs
  • 20. Legal Case • Section 4302 of the Affordable Care Act of 2010 • Medicare Improvements for Patients and Providers Act of 2008 • Title VI of the Civil Rights Act of 1964 • Section 504 of the Rehabilitation Act of 1973 • Title II of the Americans with Disabilities Act of 1990
  • 21. Quality Case • SAFETY • Communication difficulties may lead to misdiagnosis and inappropriate treatment and limit the process of truly informed consent • EFFECTIVENESS • Minority patients tend to receive fewer key diagnostic and therapeutic procedures • PATIENT CENTEREDNESS • Minority patients are more likely feel they will receive unequal treatment and are less satisfied with quality of care they receive • TIMELINESS • Minority and LEP patients receive less timely care which may lead to differences in quality
  • 22. Accreditation and Regulation Case • Joint Commission • National Quality Forum • Community benefit and not-for-profit status
  • 23. Current Realities, however… • Sociocultural barriers: • Language and nonverbal communication • Health practices and beliefs • Role of family members in health care decision-making • Patient knowledge and expectations of health system
  • 24. Beginning the Journey… The quest to eliminate health care disparities begins with the following: • Leadership buy-in • Understanding the health needs of the communities you serve • Incorporating this goal into your overall quality improvement and strategic plans
  • 25. REDUCING DISPARITIES THROUGH THE USE OF REAL DATA
  • 26. What is REaL data? • REaL data refers to the following patient demographic information: • Race • Ethnicity • Primary Language
  • 27. Why Define Race? The purpose of defining race is to provide common language to promote uniformity and comparability for the collection and reporting of race and ethnicity.
  • 28. What is Race? “ (Race) reflects self-identification by persons according to the race or races with which they most closely identify. These categories are sociopolitical constructs and should not be interpreted as being scientific or anthropological in nature. Furthermore, the race categories have both racial and national-group origins.” (Source: National Center for Education Statistics Institute of Education Services; http://nces.edu)
  • 29. OMB Race Categories • The Race Categories are: • American Indian or Alaska Native • Asian • African American or Black • Native Hawaiian or Other Pacific Islander • White
  • 30. Useful, if not Perfect • The OMB Categories are not perfect. The race and ethnic categories were developed by the federal government to be able to monitor and help prevent discrimination in housing, education and other areas. • The U.S. Census uses these categories to track the rapidly changing demographics in the U.S.
  • 31. OMB Race Categories Defined• American Indian or Alaskan Native: a person having origins in any of the original people of North and South America (including Central America) and who maintains tribal affiliation or community attachment. • Asian: A person having origins in any of the original peoples of Far East, Southeast Asia or Indian subcontinent, including for example, Cambodia, China, India, Japan, Ko rea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
  • 32. OMB Race Categories • African American or Black: A person having origins in any of the black racial groups of Africa. • Native Hawaiian or Other Pacific Islander: A person having origins in Hawaii or Pacific Islands not specified in the Asian racial category, e.g., Micronesia, Fiji, Tahiti
  • 33. OMB Race Categories • White: A person having origins in any of the original peoples of Europe, the Middle East or North Africa. HRET modification—Added Category: • Multiracial: A person having origins in more than one of the above categories. (Some organizations allow the coding of up to 3 races.) • Declined • Unavailable (patient incapacitated)
  • 34. What is Ethnicity? Ethnicity is a term which represents social groups with a shared history, sense of identity, geography, and cultural roots which may occur despite racial difference.
  • 35. Defining Ethnicity • Consider Puerto Ricans as an example of an ethnicity. Many Puerto Ricans represent various races. • Ethnicity shapes a group's culture - the food, language, music, and customs. • For many patients, nationality or heritage are synonymous with ethnicity.
  • 36. Why We Need Subpopulation Data • Race is a broad category. For example, Native Hawaiians and Other Pacific Islanders comprise more than 25 diverse groups with various historical backgrounds, languages, and cultural traditions. • Research has documented different health risks and health status within smaller population groups, e.g., Puerto Rican individuals versus Honduran individuals. Researchers need data on subgroups or ethnicity.
  • 37. Ethnic Categories within Race• American Indian or Alaskan Native • Hopi, Navaho, Cree, Lumbee • African American/Black • Ethiopian, Kenyan, Dominican, Haiti an, etc. • White • European, Middle Eastern, Israeli, French, Irish, North African
  • 38. Ethnic Categories within Race • Native Hawaiian or Other Pacific Islander • Polynesian, Samoan, Fijian, etc. • Asian • Asian Indian, Thai, Korean, Pakistani, etc. • Multi-ethnic/Multiple, Unavailable, Declined
  • 39. English Proficiency • How would you rate your ability to speak English? • Excellent, very good, good, fair, poor? • Some hospitals collect these data via drop- down screens like race and ethnicity by registration or admitting staff
  • 40. Language Preference Questions • What language do you feel most comfortable speaking? • In what language would you prefer to receive written materials? • For minors, ask these questions of parents or guardians • These data are recorded via drop-down screens like race and ethnicity by registration/admitting staff
  • 41. Language Preference Tools
  • 42. Language Preference Tools • “I-Speak” cards and point-to posters help staff determine language preferences of LEP individuals (A Patient-centered Guide to Implementing Language Services Across Services in Healthcare Organizations, www.omhrc.gov/Assets/ pdf/Checked/HC-LSIG.pdf)
  • 43. Deaf and Hard of Hearing Populations • Effective communication is equally important in this population; miscommunication can lead to misdiagnosis or delayed treatment. • Many can speak even though they cannot hear. • People who are deaf or hard of hearing use a variety of ways to communicate.
  • 44. Deaf and Hard of Hearing Populations • Hospitals must provide a variety of services and aids, depending on abilities of the person: • Sign language interpreters (various) • Oral interpreters • Cued speech interpreters • CART—Computer Assisted Real- time Transcription
  • 45. COLLECTING REAL DATA
  • 46. Explaining Why to the Patient • Sample scripts are provided in subsequent slides: • Community responsiveness • Quality of care • Cultural competence • A combination of the above
  • 47. Community Responsiveness Rationale We want to know your race, ethnicity, and preferred language to help us develop services to meet the needs of all the populations we serve.
  • 48. Quality of Care Rationale We want to make sure that all of our patients get the best possible care. We would like to ask you to tell us your race, ethnicity, and preferred language so that we can review the treatment that all patients receive and make sure that everyone gets the highest quality of care.
  • 49. Cultural Competence Rationale We want to know the race, ethnicity and preferred language of each of our patients to help us provide care that is respectful of everyone’s cultural background.
  • 50. Combination Rationale We would like to know your race, ethnicity and preferred language. This will help us in a couple of ways. It will help us… and … . (For example, it will help us provide care that respects your cultural background and will help ensure that we provide the most appropriate care and services to all our patients.)
  • 51. Handling Patient Responses • Some patients will question why they are being asked for their ethnicity and race. • They will have questions and comments. • We want you to feel comfortable answering whatever questions patients ask.
  • 52. Patient Response Matrix • The Patient Response Matrix is based on actual patient responses other hospitals have received to race/ethnicity questions. • The matrix is intended to be used as a tool to help you respond in the best possible manner. • You may have more examples to add and incorporate into the training of new staff in coming months.
  • 53. Patient Responses—Routine Patient Response Suggested Response Hints Code “I'm American" “Would you like to use an additional term for race that is listed on this card?” “I can code American as well (for ethnicity).” As patient self- identifies "Can't you tell by looking at me?" “Well, usually I can. But sometimes I'm wrong, so we think it is better to let people tell us.” As patient self- identifies "I don’t know. What are the responses? “Please look at this card--you can say white, Black or Africa- American, Latino or Hispanic, Asian, American Indian or Alaska Native, Pacific Islander or Native Hawaiian, some other race or any combination of these.“ As patient self- identifies "I was born in Nigeria, but I've really lived here all my life. What should I say?" “Nigerian is great—we’ll list that as your country of origin as well as your ethnicity.” “Could you also state your race as listed on this card?” As patient self- identifies
  • 54. Patient Responses—Routine Code Hispanic If patient declines to list a separate race, code Preferred Not to Answer in Race slot. Code Hispanic “The federal government has designated Hispanic as an ethnicity. I will record Hispanic as your ethnicity. Do you also want to list as race, as described on this card?” Thank you.” “Why isn’t Hispanic a race?” I am Latino/Latina/Puerto Rican Up to 3 races“Many people are multi-racial and you can provide me with up to three races that you see on this card.” I am more than one race— how many can I list.” N/A “Administrators will see these data and researchers may use non-patient identified data for their studies. No one else will see these data.” “How will this information be used?” CodeHintsSuggested ResponsePatient Response
  • 55. Returning Patients with Incomplete Data Patient Response Suggested Response Code Hint A patient returning for care with the “Preferred Not to Answer” code. None—skip the race and ethnicity questions N/A—already coded Don’t ask again A patient returning for care with the “UN” or "Unable to provide information" code. Proceed to ask for the information per routine
  • 56. Tougher Questions Patient Response Suggested Response Code Hint "I'm Human“ “Would you prefer not to answer? If so, that is fine.” Preferred Not to Answer or Declined Do not say Refused "It's none of your Business" “I'll put down that you prefer not to answer, which is fine.” “ “ "Why do you care? We're all human beings“ “Well, it is important for our organization to know all of the different populations we treat in order to provide the most appropriate services and the most individualized care.” “ DON'T SAY: I'll just code as a refusal “
  • 57. Tougher Questions Patient Response Suggested Response Code Hint What do you mean this is part of your patient- centered care approach? “Everyone is unique and we want to be sure that we know as much about you as possible in order to individualize your care.” If patient declines further information, code Preferred Not To Answer or Declined "Who looks at this?" “The only people who see this information are registration staff, administrators for the hospital and the people involved in quality improvement and oversight.” “ "Are you trying to find out if I'm a US citizen?“ “No. Definitely not. Also, you should know that the confidentiality of what you say is protected by law.” “
  • 58. Top FAQs • Why are data being collected about race, ethnicity and language? • This information helps us understand the various patient populations we serve. We want to provide the best care to all our patients. • It is also required by agencies that oversee the care hospitals provide.
  • 59. Top FAQs • How will data on race, ethnicity and language affect my care? • Your care will meet the highest patient care standards. Information about race and ethnicity will help us… this answer will depend on the rationale that the organization selects.
  • 60. Top FAQs • I am an American citizen; why are race, ethnicity and preferred language being asked? • This information helps us to better understand our various patient populations, provide more culturally competent care, and comply with federal, state and accrediting agencies.
  • 61. Top FAQs • What is the difference between race and ethnicity? • Race reflects self-identification by persons according to the race or races with which they most closely identify. Ethnicity is a term which represents social groups with a shared history, sense of identity, geography and cultural roots which may occur despite racial differences.
  • 62. Top FAQs • Why aren’t more races listed? • A federal working group came up with the list to meet the needs of 30 very diverse federal agencies. The rationale was to have a relatively short list of races and to allow for a much greater list of ethnicities to recognize unique religious, cultural and geographic characteristics.
  • 63. Top FAQs • What is the difference between “Hispanic” and “Latino?” • There is no difference. OMB accepts Hispanic or Latino. However, for ease of coding our organization has chosen Hispanic. If patient responds “Latino,” code as “Hispanic.”
  • 64. Top FAQs • Why isn’t Hispanic a race? • The Federal government decided that some individuals of the White, Indian (North, Central and South American), and Black races would consider themselves Hispanic because they speak a common language (Spanish) and have a common cultural heritage or ethnicity. It was decided to consider Hispanic an ethnicity, rather than a race. However, many individuals will self-identify their race as Hispanic.
  • 65. Top FAQs • Why is “Pakistani” considered Asian and not Middle Eastern? • There is no Middle Eastern race in order to limit the number of different races. This illustrates the importance of collecting ethnicity information as well as race information. Identifying “Pakistani” as the ethnicity tells us much more than “Asian” as a race.
  • 66. Monitoring Progress • Your supervisor will meet with you as a group or one-on-one to ask: • how your patients are responding to be asking their race and ethnicity, and • how you feel the process is working—what’s working and what could be improved.
  • 67. Monitoring Progress • Your supervisor will also be monitoring the number of Unknowns to determine if some staff are having more difficulty than others obtaining race, ethnicity and preferred language.
  • 68. SRMC’S DATA COLLECTION PRACTICES
  • 69. Physician Services Data Collection
  • 70. Medical Center Data Collection
  • 71. Home Health/Hospice Data Collection
  • 72. UTILIZING REAL DATA TO REDUCE DISPARITIES
  • 73. Tailoring Interventions • If disparities in outcomes are discovered, design culturally-tailored interventions
  • 74. Monitoring Quality of Care Outcomes REaL data should be used to measure the following quality differentials: • Clinical outcomes • Patient satisfaction • Process measures
  • 75. Sample Dashboard: Colorectal Cancer Incidence Rate by Race/Ethnicity Cases per 100,000 population From Santium Hospital
  • 76. Sample Hospital Equity Report From RWJF
  • 77. Other Sample Dashboard Topics • Hospital Quality Alliance Measures (Process Measures): • AMI, HF, Pneumonia, SCIP, HCAHPS • NQF-endorsed Standards for Serious Reportable Events • AHRQ measures • Cardiovascular, Cancer Outcomes* * Where many medical centers start
  • 78. CASE STUDIES
  • 79. Montefiore Medical Center Objective Interventions Standardize REaL collection Train registration staff and modify Information systems Improve AMI & CHF care for all Montefiore patients Patient and provider centered materials, improvement methods Evaluate quality of care by demographic group Monthly reporting of AMI and CHF measures by demographic group; data analyzed by Quality Dept. Improve communication with post- discharge providers CHF-specific discharge planning
  • 80. New York-Presbyterian OVERVIEW: Serves predominantly Hispanic community with high rates of asthma, diabetes, heart disease and depression. ACTIONS: Established work group to improve care coordination and culture competency through 4 strategies: 1) Patient-centered medical homes focused on diabetes, CHF, asthma and depression; 2) Centralization of call center functions such as scheduling, test results, and follow-up for 7 outpatient sites; 3) Employment of bilingual and bicultural community health workers and navigators in medical homes and in emergency departments; and 4)Implemented 4-hour training program to build workforce better able to address linguistic, culture and health literacy needs . Physicians receive training with patient-based cross-cultural care, which assists with cultural competency and communication with patients and families. Physicians become more aware of their patients and their own perceptions. RESULTS: As of May 2011, 600 employees rec’d cultural competency training. Collaborative helped decrease # ED visits for ambulatory-sensitive condition by 9.2 %
  • 81. Baylor Office of Health Equity OVERVIEW: Baylor’s Office of Health Equity (OHE) aims to reduce variation in health outcomes among it diverse patient populations. Diabetes is a severe epidemic & more than 2X as likely to occur in minority populations. REaL data analysis indicated disparities in diabetes management within Baylor’s primary care practices. ACTIONS: OHE developed a Diabetes Equity Project (DEP) to reduce disparities in diabetes care and outcomes in nearby Hispanic com- munities. Enrollment began 9/09. Steps taken: 1) Community health worker recruitment and training, 2) Building on local clinic partnerships & integrating community health workers into Baylor’s overall care coordination strategy, and 4) developing electronic diabetes registry to track patient metrics and facilitate disease management communication between community health workers and primary care clinicians. RESULTS: > 800 patients enrolled; A1C values improving, suggesting sustainable diabetes control can be achieved for participants who previously had poor control by augmenting “usual care” with community health worker-led patient education & advocacy.
  • 82. Communication Suggestions • Community leaders & community meetings • Hospital Newsletters • Local newspaper articles, TV news • Targeted brochures to local households • Posters, table-top signs in Admitting • Laminated cards for registrants to hand out • On medical center Web site • Community focus groups
  • 83. Using REaL—Leading Practices 1. Use equity dashboard to report org’l performance 2. Inform & customize language translation services 3. Review performance indicators such as LOS, admissions and avoidable readmissions 4. Review process of care measures 5. Review outcomes of care 6. Analyze provision of certain preventive care 7. Analyze patient satisfaction scores
  • 84. Getting Started What Leadership Can Do: • Understand your own attitudes and skills— start with self-assessment tool • Engage the communities you serve & understand your community’s needs • Standardize REaL data collection • Work with outside experts to begin to analyze process and outcome data on 1 diagnosis, e.g., cardiovascular care, stratified by race once REaL data collection in place
  • 85. Resources • Massachusetts General Hospital Disparities Solutions Center • http://www2.massgeneral.org/disparities solution/guide.html • Expecting Success: Excellence in Cardiac Care • http://www.rwj.org/pr/product.jsp?id=36180 • HRET Disparities Toolkit • http://www.hretdisparities.org/ • RWJF- Creating Health Equity Reports • http://www.rwjf.org/pr/product.jsp?id=29173 • Hospitals in Pursuit of Excellence • http://www.hpoe.org
  • 86. QUESTIONS?
  • 87. Contact Us • Deborah Bohr • dbohr@aha.org • Andy Bostick • nbostick@aha.org