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Using Demographic Data to Provide Patient-Centered Care: Why Data Collection is Important

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Using Demographic Data to Provide Patient-Centered Care: Why Data Collection is Important

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    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

    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

    15. Languages That 20% or More of Hospitals Encounter Frequently

    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

    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

    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 72% collect Over 50% collect by eyeball 52% collect primary language (we are analyzing data from a language survey) 28% see drawbacks to colleting data 31% use for QI72% collect Over 50% collect by eyeball 52% collect primary language (we are analyzing data from a language survey) 28% see drawbacks to colleting data 31% use for QI

    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

    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

    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:

    36. Adult Diabetes Performance Measures-New System Would Capture the following:

    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.

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