Achieving Equitable Outcomes:Collecting Socio-Demographic Patient

Data in Health Care Settings

Joseph R. Betancourt, M.D., M.P.H.

Director, The Disparities Solutions CenterSenior Scientist, Institute for Health Policy

Director for Multicultural Education, Massachusetts General Hospital

Associate Professor of Medicine, Harvard Medical School

Outline

Disparities in Health and Health Care

Collecting Patient Demographics

Case Study of Mass General Hospital

– Collecting Race/Ethnicity Data

– Measuring and Monitoring Equity

– Developing Interventions

Diabetes-Related Death Rate, 2010

Deaths per 100,000 population

22.8

50.1

33.6

50.3

18.4

0

10

20

30

40

50

WHITE BLACK HISP/LTN AI/AN ASIAN/PI

What causes these Racial/Ethnic Disparities in Health?

Social Determinants

Access to Care

Health Care?

Racial/Ethnic Disparities inHealth Care

In patients with insurance…– Disparities based on race for:

Influenza vaccination (Gornick et al.)

Lung Ca Surgery (Bach et al.)

Renal Transplantation (Ayanian et al.)

Treatment of chest pain, cardiac catheterization, angioplasty, bypass (Harris et al, Ayanian et al., Peterson et al., Johson et al.)

Referral to cardiology specialist care (Schulman et al.)

Treatment of HIV/AIDS (Shapiro et al.)

Pain management (Todd et al.)

Disparities in Health Care 2002

Racial/Ethnic disparities found across a wide range of health care settings, disease areas, and clinical services, even when various confounders (SES, insurance) controlled for.

Many sources contribute to disparities—no one suspect, no one solution•Provider-Patient Communication

•Stereotyping

•Mistrust

IOM’s Unequal Treatmentwww.nap.edu

Recommendations

Increase awareness of existence of disparities

Address systems of care

– Support race/ethnicity data collection, quality improvement, evidence-based

guidelines, multidisciplinary teams, community outreach

– Improve workforce diversity

– Facilitate interpretation services

Provider education

– Health Disparities, Cultural Competence, Clinical Decisionmaking

Patient education (navigation, activation)

Research

– Promising strategies, Barriers to eliminating disparities

Quality Health Care

Health care should be

– Safe

– Effective

– Patient-centered

– Timely

– Efficient

– Equitable

Case Study:Achieving Equity

Massachusetts General Hospital

MGH Disparities Committee 2003

Underlying Principle

While data specific to disparities at MGH important, not

necessary to begin to take action given IOM Report

documented issue nationally

Charge

Identify and address disparities in health and health care

wherever they may exist at MGH– Subcommittees: Quality, Pt Experience, Education/Awareness

– Present plan and results to Board, Executive Council and other

hospital leadership regularly

Case Study:Achieving Equity at MGH

Data Collection

Data CollectionPerceived Challenges

Collection of information is illegal

Patients won’t want to provide information

Registrars won’t want to collect information (have history

of just deciding patient info)

Process will take too long, impede registration

Adapting IT systems to collect info costly

Uncertain how information will be used

Data Collection: TimelinePrior to 2003

Collected R/E data in 5 basic categories and preferred

language

Registrars asked basic questions

Little training or quality assurance

No preamble to collection of data

No campaign to inform patients of purpose

Information not linked to quality data

Data Collection: Timeline

2003Boston Mayor convenes Hosp CEO’s & Community Leaders

– Agree to effort to address disparities in health and health care– Boston hospitals to be required to collect race/ethnicity

2004Piloted new method of collection

– 3 models among 7000 patients (R/E, subgroup, language, education)– Metrics: Collects key info in timely fashion in way patients could understand

Registrars receive intense training and QA Process – Includes preamble, methods to respond to questions

City releases PR Poster CampaignMGH passes policy that all Quality Data will be stratified by race/ethnicity and language

Data Collection: Timeline2006MA Health Care Reform requires race/ethnicity, language, and highest level of education to be collectedMGH begins preparation of Disparities Dashboard

– Poster campaign series and website unveiled – Disparities questions incorporated in Quality Rounds– Patient Experience Survey Conducted– Multicultural Advisory Board Convened– Patient Satisfaction stratified by race/ethnicity, and language

2007MGH develops first Disparities DashboardDisparities found, interventions developed

2008MGH begins public reporting via web

Case Study:Achieving Equity at MGH

Measuring and Monitoring

Initial Disparities Dashboard Welcome and Purpose

– Definition of DisparitiesFocus on disparities in care

– Purpose of DashboardAnnual ReportEmbedded into Q and S Reporting

– Data and MeasurementHow race/ethnicity data collected

– Process, categoriesData Sources

– IDX, PATCOM, TSI, H-CAHPS survey data, medical record review (Core/NHQM)

Snapshot of diversity of MGH patients– Who they are and where they are seen

Initial Disparities Dashboard Measures

– Clinical quality indicatorsInpatient: National Hospital Core Measures

– AMI, CHF, CAP, SCIP

Outpatient: HEDIS Measures– Mammogram, Pap, CRC Screening

– Diabetes, Coronary Artery Disease

– Physician, Practice Linkage

– Patient Experiences with CarePress-Ganey Inpatient satisfaction by r/eResults of Quality RoundsResults of Minority Survey

– Communication with LEP patients

Disparities Dashboard Evolution (V2, V3) H-CAHPS Inpatient satisfaction by race/ethnicity

All-cause and ACS Admission by race/ethnicity

CHF Readmissions by race/ethnicity

Sentinel Measures– Mental Health

– Pain Mgmt in the ED

– Wait time for Renal Transplantation

– Orbit time for CABG

Patient Experience Summit– Interpreter Pilot Project

Cross-Cultural Communication Training Report

Public Reporting via external MGH Q/S Website

Disparities Dashboard Executive Summary– Green Light: Areas where care is equitable

National Hospital Quality MeasuresHEDIS Outpatient Measures (Main Campus)Pain Mgmt in the ED

– Orange Light: National disparities, areas to be exploredMental Health, Renal TransplantationAll cause and ACS Admissions (so far no disparities)CHF Readmissions (so far no disparities)Patient Experience (H-CAHPS subgroub differences)

– Red Light: Disparities found, action being takenDiabetes at community health centers

– Chelsea (Latino), Revere (Cambodian) Diabetes Project

Colonoscopy screening rates– Chelsea CRC Navigator Program (Latinos)

Case Study:Achieving Equity at MGH

Developing Interventions

The MGH Chelsea Diabetes Program

Chelsea: Large minority and immigrant community (Hispanic/Latino

primarily, but also Bosnian, Somali) about 3 miles from hospital.

MGH Chelsea Healthcare Center provides community based

care

MGH Chelsea Diabetes Program: A quality improvement /

disparities reduction program with 3 primary components:

• Telephone outreach to increase rate of HbA1c testing

• Individual coaching to address patients’ needs and concerns regarding

diabetes self-management to improve HbA1c

• Group education meeting ADA requirements

Diabetes Control Improving for All: Gap between Whites and Latinos Closing

24% 24%

20%

37%

34%

29%

0%

10%

20%

30%

40%

50%

2007 2008 2009

Year

% o

f P

atie

nts

wit

h P

oo

rly

Co

ntr

olle

d D

iab

etes

(H

bA

1c

> 8

) Whites

Latinos

* Chelsea Diabetes Management Program began in first quarter of 2007; in 2008 received Diabetes Coalition of MA Programs of Excellence Award

*

Monitoring Equity: Key Lessons Learned There may be initial resistance and concern

– Appropriate messaging, explanation of disparities, description of “work in progress”, blame-free approach is key

Not always as easy as it seems, but can be done

– Some data systems not easily connected; begin incrementally, build the system step-by-step; perfect not enemy of good

– Address basic methodological issues, don’t get bogged down by them

Need to expand measure set over time, innovate

– Sentinel measures; sub-group analysis of patient experience; errors

Mainstreaming essential

– Policies, champions make for success and culture change; needs to be owned by Quality and Safety; tailor to your needs

Looking towards the FutureBuilding Equitable Systems and Incentives

Race/ethnicity and other data collection is essential

Need to measure and monitor

20/80 Rule: Conditions of Focus

Asthma, Diabetes, CVD, CRC Screen, Mental Health

– South Asians and First Nation populations

Increase Capacity of Health Care Providers

Foster cultural competence of health care providers

Empower Patients

Support coaching and navigation activities

Summary

There is a significant body of evidence that has

identified racial/ethnic disparities in health care

Hospitals can play a major role in their elimination

through quality improvement; monitoring equity is key

Improving equity will improve the care not only of

minorities, but of all patients

Thank You

Joseph R. Betancourt, MD, MPH

jbetancourt@partners.org

www.mghdisparitiessolutions.org