Agenda Creating Equity Dashboards to Monitor Racial, Ethnic and - - PDF document

Creating Equity Dashboards to Monitor Racial, Ethnic and Linguistic Disparities in Health Care

Lessons from the Disparities Leadership Program

Alexander R. Green, M.D., M.P.H. Associate Director, The Disparities Solutions Center

Senior Scientist, Mongan Institute for Health Policy Associate Professor of Medicine, Harvard Medical School Tuesday, March 12, 2013 10:45 AM-12:15 PM

Agenda

• Welcome, brief overview of the field, and the

MGH DSC experience – Dr. Alexander Green

• Alameda County Medical Center –
• Dr. Mini Swift
• University of Chicago Medicine and

Biological Sciences – Brenda Battle DSC Background and Mission (est. 2005)

The Disparities Solutions Center is dedicated to developing and implementing strategies to eliminate racial and ethnic disparities in health care locally, regionally, and nationally. We aim to serve as an agent of change by:

 Translating existing and ongoing research on strategies to eliminate disparities into policy and practice.  Developing and evaluating customized solutions to address disparities.  Providing education and leadership training to expand the community of skilled individuals dedicated to eliminating disparities.

DSC Model:

Collect Data Identify/Report Implement Solutions Evaluate Strategic Planning

Initial Dashboard Measures

• Clinical quality indicators

– Inpatient: 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 Care

– Press-Ganey Inpatient satisfaction by race/ethnicity – Results of Quality Rounds and Minority Survey

• Communication with LEP patients

Dashboard Evolution

• H-CAHPS Inpatient satisfaction by race/ethnicity
• All-cause and ACS Admission by race/ethnicity
• CHF Readmissions by race/ethnicity
• ‘Sentinel measures’ of disparities

– Pain Mgmt in the ED – Wait time for Renal Transplantation – Mental Health

• Patient Experience Summit

– Interpreter Pilot Project

• Cross-Cultural Communication Training Report

Disparities Dashboard Executive Summary

– Green Light: Areas where care is equitable

• Almost all National Hospital Quality Measures
• Almost all HEDIS Outpatient Measures improvement
• More linkage to PCPs

– Orange Light: Disparities with gaps narrowing

• Colonoscopy screening rates

– Chelsea CRC Navigator Program (Latinos)

• Breast cancer screening for refugees and immigrants

– Chelsea Komen Breast Cancer Program for Refugees

– Red Light: New areas of disparities, more work needed

• Impact of limited-English proficiency (LEP) on patient safety
• Patient Experience (H-CAHPS/CG-CAHPS)
• Difference in readmission rates by race

Accreditation, Quality Measures, and Reform

 Joint Commission: Disparities/cultural competence standards 2010-11  NCQA: Multicultural Recognition and new standards  National Quality Forum: Released cultural competence quality measures,

developing disparities measures, incorporating into MAP

 Health Care Reform has multiple provisions addressing disparities

The Disparities Leadership Program

 Develop cadre of leaders in health care equipped with

– Knowledge of disparities, root causes, research-to-date – Cutting-edge QI strategies for identifying/addressing disparities – Leadership skills to implement and transform organizations

 Assist individuals and organizations to:

– Create a strategic plan to address disparities, or – Advance or improve an ongoing project, and – Be prepared to meet new standards and regulations from the JC, NCQA, and health care reform, etc.

Disparities Leadership Program Alumni

190 participants 89 organizations

• 44 hospitals
• 19 health plans
• 17 community health centers
• 1 hospital trade organization
• 1 federal government agency
• 1 city government agency
• 6 professional organizations

Representation from 28 states, along with the Commonwealth of Puerto Rico and Switzerland

DLP participants hail from 28 states, the Commonwealth of Puerto Rico, and Switzerland

For More Information the Disparities Leadership Program

www.mghdisparitiessolutions.org Contact: Aswita Tan-McGrory, MBA, MSPH Deputy Director atanmcgrory@partners.org 617-643-2916

Measuring Equity: Lessons Learned

• U. Mini B. Swift MD MPH FACP

Alameda Health Systems

“To measure is to know”…“If you cannot measure it, you cannot improve it” Lord Kelvin, William Thompson, 1824‐1907 Process Measures: Standardized, there should be no variation. ‐‐No variation found that is not related to small sample size ‐‐ Small sample sizes. Measure over time Perfect Care Roll‐up

Core Measures Results

Perspective Measures: How well do we serve all patients? ‐ 1st Qtr improved interpreter access = ↑ satisfaction in Asian sub group ‐ Opportunity: Asian 10% less satisfied with “Communication about Medicines”

Patient Experience Results Determining What to Measure

Overloaded with "priority projects " Take an equity in operations approach Provide new perspective on strategic priorities

– Process Measures:

• Core Measures

– Perspective Measures

• Patient Experience

– Outcome Measures

• Reducing Admission for Chronic

Disease Patients

Road Blocks

Accurate Data Collection ‐Use established metrics ‐Compare internal and external demographic data collect ‐ REaL Registration Education Campaign Limitations of Electronic Medical Granularity, Storage and Reporting ‐ Partner with IT and Patient Business Services ‐Community partnership to leverage buying power ‐Leverage national focus ‐Advocate power of Disparities Solutions Center & Leadership Program

Creating Equity Dashboards to Monitor Racial, Ethnic and Linguistic Disparities in Health Care: Lessons from the Disparities Leadership Program

DiversityRx Workshop Brenda A. Battle, BSN, MBA

March 12, 2013

Policy Statement

• Data stratified by race, ethnicity, language, gender, age and payer, will inform patient-centered care,

culturally and linguistically competent care and services, and help to decrease health disparities/inequities. Timely, valid, and representative data collection is essential to the provision of quality and equitable care. Purpose of Policy

• The purpose of this policy is to extend beyond collecting data on patient’s race, ethnicity, language,

gender, age and payer for compliance reasons; it is to enable the use of this data to understand the health care needs of the populations served by BJH and to provide data to support our ability to plan and customize programs and interventions to meet the needs of these populations, and to implement targeted, meaningful solutions to provide safe, quality care and improve health care outcomes.

Data Stratification Policy

20 Dashboards | 21 Dashboards |

Dashboard - readmissions

Gender Cas es Readmit Rate Denom Cas es 30 Day Readmit Cas es % 30 Day Readmit Male 18,810 18,279 3,324 18.18 F emale 22,908 22,428 3,806 16.97

Gender: Age:

Age Category Cas es Readmit Rate Denom Cas es 30 Day Readmit Cas es % 30 Day Readmit 1-17 years 290 290 19 6.55 18-30 years 5,843 5,800 862 14.86 31-50 years 10,931 10,789 1,836 17.02 51-64 years 12,265 11,956 2,325 19.45 >65 years 12,374 11,859 2,088 17.61

Race:

Race Cas es Readmit Rate Denom Cas es 30 Day Readmit Cas es % 30 Day Readmit Black 14,587 14,304 2,711 18.95 Multiracial 118 118 21 17.80 Native american/es kimo 371 365 60 16.44 Other 614 583 67 11.49 White 26,005 25,314 4,268 16.86

Payor:

Hos pital Cas es Readmit Rate Denom Cases 30 Day Readmit Cas es % 30 Day Readmit Managed Care Readmits 13,361 13,072 2,111 16.15 Medicaid Readmits 8,523 8,403 1,553 18.48 Medicare Readmits 16,041 15,485 2,988 19.30

Equity indicators in clinical effectiveness – Harm events - Patient safety indicators (BSI, pressure ulcer, catheter-associated UTI, etc.) – Care transition/care coordination – hospital readmissions – Key external quality indicators – Other ambulatory care sensitive conditions

Creating the intersection between quality, safety and equity

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Creating regression models that incorporates predictive variables to help identify a patient profile for 30-day readmissions, including indicators such as:

• Patient demographics
• Diagnosis
• Co-morbid conditions
• Primary Care MD
• Medications
• # of Previous Admissions
• Social determinants of health such as environment i.e., literacy levels, family

support, environmental factors, etc. Evaluate data based on:

• Consistent patient population focus
• Consistent timeframes

Predicting

23 Dashboards |

• Community Health Needs Assessment – Community

Benefit

• Clinical effectiveness
• Patient experience

Targeting interventions toward populations

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Audience Questions and Answers