community care coordination performance measures · 2013-06-24 · many parties were involved in...

Community Care Coordination Performance Measures

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COMMUNITY CARE COORDINATION PERFORMANCE MEASURES

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Advancing Quality Improvement Efforts Through the Use of Standardized COMMUNITY CARE COORDINATION PERFORMANCE MEASURES

Many parties were involved in the success of the NIH-Community Care Coordination Performance Measures (NIH-CCCPM) study and in the preparation of this Technical Report.

The National Institutes of Health (NIH) provided funding for this project through the American Recovery & Reinvestment Act of 2009, Grant Award No. 1RC2MD004781-01. Within NIH, the project was possible through the administration and support of the National Institute on Minority Health and Health Disparities (NIMHD).

In particular, we thank Irene Dankwa-Mullan MD, MPH, Director, NIMHD Office of Innovation and Program Coordination. We are grateful that Dr. Dankwa-Mullan included this study as one of the unique health innovations in her portfolio. We also appreciate the leadership and support of NIMHD Director John Ruffin, PhD, and Rick Berzon, DrPH, Program Officer, Office of Innovation and Program Coordination, who provided input during the project’s implementation.

Technical Expert Panel member support was essential and was greatly appreciated. Members include: Co-Chairs, Veronica Nieva, PhD and Sarah Redding, MD, and the following other members, Wendy L. Gary, MHA; Denise Levis Hewson, RN, BSN, MSPH; Melanie Moyer Swan, MPH, PMP; Mary Overall, BS, MSN; Dan Rubin, MPP; Jan L. Ruma, MEd, CFRE; and Judith Warren, MPH.

Thanks are offered to the Community Study Sites, their leadership and the local personnel involved. In particular, we would like to thank, Sarah Redding, MD MPH and Mark Redding, MD, FAAP (Ohio – Community Health Access Project); Sherry E. Gray, MA and Susie Dittman, MHA, (Indiana – Rural and Urban Access to Health); Tom Hoover, RN MBA-HCM and Jean Stilwell, MA, (Nebraska – Lincoln E. D. Connections); James Walton, DO, MBA, Adam Chabira, MHA, and Steven Walton, MBA (Texas – Baylor Community Care), and Christine Sison, MS and Greg Bergner, MD (California – Access El Dorado).

Prepared by: Westat.

Reprinting and Distribution: This document may be used and reprinted with permission from Westat. Contact: Brenda A. Leath, MHSA, PMP by sending an email request to [email protected].

Suggested Citation: Leath, B., Mardon, R., Atkinson, D., Johnson, M., Smith, S., Rajapaksa, S., Kilian, T., Gary, L., & Darden, M. (2012). NIH-Community Care Coordination Performance Measures (NIH-CCCPM) Project Technical Report on Project: Standardizing Community Care Coordination Measures Linked to Improvements in Quality of Life and Health Outcomes Among Vulnerable Populations. Prepared by Westat under the American Recovery & Reinvestment Act of 2009, National Institute on Minority Health and Health Disparities, National Insti-tutes of Health Grant Award No. 1RC2MD004781-01.

ACKNOWLEDGEMENTS

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FOREWORD

Established in 1963, Westat has a rich history of conducting evidence-based research. In the health-care arena, Westat works to help inform the cost effectiveness of treatment, improve care delivery, and reduce costs. Many of such efforts involve improving outcomes for vulnerable populations who face health disparities.

Many of Westat’s current and previous engagements helped inform and enrich the NIH-Community Care Coordination Performance Measures (NIH-CCCPM) study. This includes Westat’s role in implementing and monitoring the Health Innovation Exchange for the Agency for Healthcare Research and Quality (AHRQ) and the company’s involvement in the national Community Care Coordination Learning Network (CCCLN).

The NIH-CCCPM study is a distillation of some of the best features of Westat’s work. Through its community-based participatory research (CBPR) design, a multi-disciplinary team of study members agreed on transparency in sharing information about service delivery and care. Everyone helped identify and track performance measures that could be standardized across venues and populations. Yet, the team also acknowledged and learned from site differences – cultural and linguistic, management design, services offered and people being served.

The study can help demonstrate how standardized performance measures, combined with evidence-based care in a community care coordination environment can result in a positive return on investment. Outcomes can include greater health literacy, better self-care, improved health and quality of life for patients and lowered costs for systems and communities. Studies such as these can also help advance national plans toward health disparities reduction and improvement of the availability of quality health services for all, in a timely, efficient, responsive, and coordinated nationwide system of care.

We want to thank all those involved with this study – funder, colleagues, study participants, site personnel, and other stakeholders. We hope to continue working with you in support of healthcare delivery improvements with positive outcomes for all.

BRENDA A. LEATH, MHSA, PMP RUSS MARDON, PHDBrenda A. Leath, MHSA, PMP Russ Mardon, PhDProject Director/Co-Principal Investigator Co-Principal Investigator

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Chapter Page

Acknowledgements iForeword iiExecutive Summary vi

1 Introduction 1What You Will Find in This Report 1Intended Audience 2Some Frequently Used Terms 2

Health Disparities, Social Determinants of Health, Vulnerable Populations 2 Care Coordination and Community Care Coordination 2 Pathways Community HUB Model 3 Medical Home 3 Community-Based Participatory Research (CBPR) 4

How the NIH-CCCPM Study Project Evolved From Earlier Efforts 4Relationship to Federal Efforts 4 NIH, NIMHD and ARRA “Grand Opportunity” Grants 5 HHS 2011 Action Plan to Reduce Racial and Ethnic Health Disparities 5 Affordable Care Act and Accountable Care Organizations 5

2 Key Players: Participating Organizations 7

National Institute on Minority Health and Health Disparities (NIMHD) 8Westat 8Technical Expert Panel 8Matrix Knowledge Group 9Study Sites 9

Community Health Access Project 9 Rural and Urban Access to Health 10 Baylor Community Care 10 Lincoln E. D. Connections 10 Access El Dorado 11

TABLE OF CONTENTS

Chapter Page

3 Project Design and Implementation 13

Project Objectives and Methodology 14

Objectives 14 Methodology – Community Based Participatory Research (CBPR) 14

Activities 15

Site Selection 15 Conceptual Model, Selecting, Defining and Refining Performance Measures 15 Engagement of Data Research Associates 16 Gaining Permissions to Access Records and Participants 16 Testing the Measures, Protocols and Processes 16 Collecting Client Services Data 17 Administering and Collecting Patient/Client Feedback 17 Data Cleaning and Analysis 18

4 Findings and Results 19

Part 1. Performance Measures for Community Care Coordination 20Part 2. Results From the Quantitative Data 21Results – Sites’ Use of the Community Care Coordination Performance Measures 23Part 3. Results From the Qualitative Data 28Study Site Managers: Comments, Perspectives on Study Participation 28

Theme 1: Site Operations Continued as Usual 28 Theme 2: There are Benefits to Participation in a National Study 28 Theme 3: Study Findings Mirror Our Local Analysis and Add to the Evidence Base 29

Theme 4: The Study Provided Numerous Other Benefits 29

Study Sites’ Future Interest and Recommendations for Next Steps 30

Chapter Page

5 Implications and Conclusions 31

Study Accomplishments 32Key Lessons Learned/Take Home Messages 32

Implications for Importance to Community Care Coordination Organizations 32 Implications for Research Community 33Moving Forward 33

Study Sites Additional Efforts – Expanding Capacity 33 Dissemination 34

In Conclusion 35

Appendix

HUB Snapshots 37

Community Health Access Project 38 Rural and Urban Access to Health 39 Baylor Community Care 40 Lincoln E.D. Connections 41 Access El Dorado 38

Endnote Citations 43

Tables

1 List of Performance measures for community care coordination including measurement domains, pathways components, and measure names 20

2 Client characteristics by site 223 Additional client characteristics by site 22Figures

1 Community hub: Medical home pathway 42 Geographic dispersion of study sites 93 Health care referral completion 244 Social or support services referral completion 255 Client overall health status with past 2 months 27

“There is measure in all things”Horace, Satires

Roman lyric poet & satirist (65 BC – 8 BC)

During the last decade, national interest in performance measurement for healthcare services as well as other industry sectors has grown exponentially in response to a number of political, economic, and legislative imperatives. There are many ‘voices,’ including public constituents, payers, Federal and municipal entities who are calling for reforms and “demanding an explicit measurement of individual and system quality measures. There are tremendous pressures and expectations to accurately measure individual physician (or a system of care) performance.” In this regard, there is a prevailing assumption that community care networks have an important contribution to make to health care reform and quality improvement efforts—and do so with measurable outcomes in ways that are cost effective. However, more scientific and evidenced-based data are needed to support this claim.

This Technical Report contains an overview of the NIH-Community Care Coordination Performance Measures (NIH-CCCPM) research study, led by Westat, which focused on performance measurement development and data collection methodologies for primary health care services delivered in geographically diverse community settings. Written with a content orientation for community-based service providers, potential funders, and local and regional stakeholders, this report is designed to share information about the community care coordination performance measures that have been developed. The narrative highlights the reasons why these measures are important as well as their relevance for local and regional provider networks. An overview of the methodological processes deployed in developing the project’s performance measures such as how measurement tools for each variable (including a consumer satisfaction survey) were designed, tested, then beta-tested and deployed is provided in the report. Suggestions for utilization of the measures by community-based organizations similar to the ones in our study are outlined.

A nationally recognized patient navigation services program (The Pathways Community HUB Model) founded by Drs. Mark and Sarah Redding of the Community Health Access Project in Mansfield, Ohio, served as a guiding interpretive presence and framed the basic research design. One of the challenges facing the study team mirrored those of other participatory research projects with similar site diversity was taking a common model and implementing it into an array of vastly different settings, while adhering to the fidelity of the model. Our report highlights the geographical variances in pilot sites and how this is reflective of strategies for disparities reduction.

The collaborative site-based study team acknowledged varying degree of gains in organizational capacity resulting from information exchanges between participating partners, Westat corporate team members and a national Technical Expert Panel (TEP) of advisors and stakeholders. Insights from our TEP offer a glimpse into external perspectives from experts and stakeholders.

Melanie Moyer Swan, MPH, PMP, Program Manager, ECRI, National Guideline Clearinghouse, National Quality Measures Clearinghouse “The recent literature is beginning to evidence an increasing interest in care coordination . . . that the trend is identifiable on a national scale and can be viewed as emerging over the past two to three years.”

Wendy L. Gary, MHA, PGCM, CMQ/OE, Vice President, Quality, Safety and Innovations Division, Delmarva Foundation for Medical Care “Initiatives like this study are ‘needed for health care reform’, not replacing an initiative, but it’s a philosophical movement, and paradigm shift.”

Executive Summary

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Groundbreaking projects such as NIH-CCCPM hold vast potential to help shape the national dialog on healthcare reform and finance policy. The effort is congruent with NIH’s focus on eliminating health disparities—particularly as it relates to vulnerable populations, diseases, and health outcomes. Ultimately, a major purpose of the CCCPM project is to add to the body of work in health disparities and care coordination in a way that will help to bring about a comprehensive, viable, and sustainable performance measurement system. It is envisioned that organizations will embrace the report and relate the experience to their environments in terms of how they might be able to replicate what we’ve done.

The framework emanating from the CCCPM dissemination plan can be utilized as a roadmap for other research initiatives and by stakeholders involved in planning culturally competent strategies for healthcare delivery and partnership development. Since socioeconomic, geographical, and related societal determinates have a bearing on the efficacy of community care networks, it is envisioned that initiatives such as the CCCPM project can be transformative in bringing about needed reforms in the healthcare industry. Hopefully, the professional community, who will take a lead in performance measure development/implementation and the governing and funding bodies who support them, and, critically, the consumers of services will benefit from the work that we do.

For additional information about the NIH-CCCPM study, or to learn more about how to implement a project of this type in your own organization or community, please contact The Center for Pathways Community Care Coordination (CPCCC) at the Rockville Institute for the Advancement of Social Science Research (Rockville Institute) through email at [email protected].

For additional information about the NIH-CCCPM study, or to learn more about how to implement a project of this type in your own organization or community, please contact The Center for Pathways Community Care Coordination (CPCCC) at the Rockville Institute for the Advancement of Social Science Research (Rockville Institute) through email at [email protected].

The Introduction describes the intended audience and how the report is structured. It provides a glossary of some frequently used terms. It summarizes how the study project evolved from previous efforts and how the project is in alignment with national efforts to reduce health disparities and improve health outcomes and well-being. The Key Players: Participating Organizations section summarizes the parties involved in the study project. Study objectives and methodology are described in the Project Design

and Implementation section that also summarizes the key project activities. This section includes input from the study site managers – including successes and challenges, as well as suggestions regard-ing any enhancements, where warranted. The Findings and Results section provides a summary of data collected and provides personalized reflections and perceptions from the study sites about their participation in the study as well as recommendations for next steps. In addition, actual results and findings derived from the study methodology are presented in this section. The Implications and

Conclusions section describes how the study process and results contribute to the field of standardizing performance measures for community care coordination – particularly for underserved populations. The Appendix provides summary “snapshots” for each study site.

What You Will Find in This Report

INTRODUCTION:

2 Community Care Coordination Performance Measures

Intended Audience The Technical Report is developed primarily for community-based service providers, potential funders, and local and regional stakeholders. Others who work in different types of health care related settings and organizations may also find it useful.

Some Frequently Used TermsBelow is a brief explanation of some of the terms and how they are used in this report.

Health Disparities, Social Determinants of Health, Vulnerable Populations

The Healthy People 2020 initiative defines a health disparity as “a particular type of health difference that is closely linked with social, economic and/or environmental disadvantage. Health disparities adversely affect groups of people who have systematically experienced greater obstacles to health based on their racial or ethnic group; religion; socioeconomic status; gender; age; mental health; cognitive,

sensory, or physical disability; sexual orientation or gender identity; geographic location; or other characteristics historically linked to discrimination or exclusion.2

According to the World Health Organization, “the social determinants of health are the conditions in which people are born, grow, live, work and age, including the health system. These circumstances are shaped by the distribution of money, power and resources at global, national and local levels. The social determinants of health are mostly responsible for health inequities – the unfair and avoidable differences in health status.”3

Vulnerable populations are defined by race/ethnicity, socioeconomic status, geography, gender, age, disability sta-tus, risk status related to sex and gender, and among other populations identified as at-risk for health disparities.4

Interrelationship of these Factors. The interrelationships between an individual’s personal characteristics and his or her socioeconomic conditions are complex and often influence health status. As an example, if a person does not have a high school diploma (an individual characteristic), he may be more likely to have a low-paying job (a socioeconomic condition) that does not offer health insurance. Without health insurance, the person may not have access to the health care he needs. Thus, the person in this example is vulnerable to poor health outcomes.

Care Coordination and Community Care Coordination

Health care in the United States is often fragmented – many patients receive attention only for individual health conditions rather than for their overall health. In response to this fragmentation, care coordination is seen as a way to help improve health care outcomes and quality of life.

There are many definitions of the term, “care coordination.” We will use the following: “Care coordination is the deliberate organization of patient care activities between two or more participants (including the patient) involved in a patient’s care to facilitate the appropriate delivery of health care services.”5

Community care coordination works to help address health disparities and (often) the social determinants of health. Community care coordination processes include:

• Identifying and engaging individuals within their community/home setting; • Assessing their health and social needs; and • Connecting them to the health and/or social services they need.

3Introduction: The NIH-CCCPM Technical Report

INTRODUCTION

Community care coordination includes helping individuals navigate and overcome barriers they encounter between their home and a wide range of institutional structures, such as clinics, hospitals, and human service agencies (e.g., public assistance, transportation services, and medical assistance). Community care coordination embraces a holistic approach to addressing the physical, social, and behavioral determinants of health. Collectively, these are integral to health care interventions needed to achieve personalized care and improved outcomes.6

Pathways Community HUB Model

Designed to produce healthy outcomes using community care coordination, the Pathways Community HUB Model (hereinafter “Pathways HUB Model”) was developed by physicians Sarah and Mark Redding of the Community Health Access Project (CHAP) in Mansfield, Ohio. Using individualized care pathways, the Pathways HUB Model employs community health workers (CHWs) who connect at-risk individuals to care that works (“evidence-based care”). The approach includes step-by-step actions for resolving problems and tracking outcomes as part of the process.

Pathway. “Basically, a pathway is a measurement tool or metric focused on achievable outcomes,” explains Sarah Redding. Pathways can address education, depression, prenatal care, housing, and more. An individual may have many pathways. A pathway is only complete when an identified problem is solved. For illustration purposes, here is a “Common Structure” for a pathway, derived from “Connecting Those at Risk to Care.”8

• Initiation Step: Defines the problem and target population. Examples: high-risk pregnancy, asthma in poor control, lack of medical home.• Action Step 1. Provide standardized education to the client/family regarding the problem identified.• Action Step 2. Identify and develop a plan to eliminate identified barriers to receiving services related to the problem.• Action Step 3. Assist client/family in identifying qualified provider or agency to resolve identified problem. This may include scheduling appointment, arranging transportation, submitting forms, etc.• Action Step 4. Confirm that referral appointment was kept and appropriate services provided. In some cases, confirm services (medications, therapies, etc.) meet national guidelines. Assist client with followup recommendations and compliance with treatment plan.• Completion Step (must be measurable outcome). Confirm resolution or significant improvement of identified problem (e.g., normal birth weight, control of diabetes, immunizations up to date) OR Confirm that client is receiving an evidence-based service proven effective in resolving or improving the identified problem (e.g., smoking cessation program).

HUB or Community HUB. The Pathways Community HUB Model promotes timely, efficient care coordination through use of a community HUB. A community HUB is a centralized data collection site for tracking and monitoring health and social services across agencies involved in providing care to the target population. Use of a HUB can help prevent service duplication and improve efficiency.9

Medical Home

The primary care and patient-centered medical home is a promising model for transforming the organization and delivery of primary care. Key features of medical homes include team-based care, a robust care coordination and care management capacity, patient-centered care with strong support for self-management of health, an emphasis on access and relationships, the use of clinical data to proactively plan care and manage populations, and a sys-tems-based approach to quality and safety. To followup on the description of Pathways, the following schematic depicts a “Medical Home” Pathway. This is one of the pathways for which data was collected in the NIH-CCCPM study. See Figure 1.


Community-Based Participatory Research

Community-Based Participatory Research (CBPR) is a collaborative approach to research that equitably involves all partners in the research process and recognizes the unique strengths that each brings. It has the aim of combining knowledge with action and achieving social change to improve health outcomes and eliminate health disparities. According to AHRQ, conventional approaches to research in low-income and minority communities lack the kind of collabo-ration and communication afforded through CBPR.

How the NIH-CCCPM Study Project Evolved From Earlier EffortsThe NIH-CCCPM study draws from Westat’s involvement in the Community Care Coordination Learning Network (CCCLN)13 and its Scorecard Project.14

These provided an underlying foundation for the NIH-CCCPM study.

With a focus on the Pathways HUB Model, the CCCLN was launched in 2008 by the Agency for Healthcare Research and Quality (AHRQ), an entity within the U.S. Department of Health and Human Services (HHS). Designed to bring communities together to adopt care coordination models that can reduce health disparities, the CCCLN provided learning and networking opportunities for a network consisting of 16 community HUBs in 10 states.

CCCLN members came together to create a scorecard prototype to standardize data collection and reporting on the community level. They developed two measures (Connection to Ongoing Primary Care and Connection to at least one Social Service). These measures were put into use by a variety of CCCLN-related providers and helped inform the development of performance measures for the NIH-CCCPM study.

The CCCLN began its vital work early on as a distinct entity under the management of AHRQ. CCCLN’s groundbreaking legacy later served as the framework for what is now known as the Center for Pathways Community Care Coordination (CPCCC) that operates at the Rockville Institute for the Advancement of Social Science Research (Rockville Institute). The five sites in the NIH-CCCPM study were all members of the CCCLN and are continuing as members of the CPCCC.4

Relationship to Federal EffortsSeveral agencies at the Federal level are working toward improving health outcomes for the Nation’s vulnerable populations. These include HHS and, within HHS, the National Institutes of Health (NIH) and the National Institute on Minority Health and Health Disparities (NIMHD). The NIH-CCCPM study aligns with the purpose and many of the efforts of these entities. Below we summarize a few examples of this alignment of purpose.

Figure 1. Community hub: Medical home pathway

5Introduction: The NIH-CCCPM Technical Report

INTRODUCTION

NIH, NIMHD and ARRA “Grand Opportunity” Grants

In 2009, the American Recovery and Reinvestment Act (ARRA) provided funding that enabled NIH to create the “Grand Opportunities” (“GO”) grants program. The “GO” grant program supports high-impact ideas to advance research, stimulate future growth and investments, and advance public health and healthcare delivery. Of more than 2,500 applicants for these funds, the NIH-CCCPM project was one of 382 that achieved funding. With its focus on health disparities and vulnerable communities, the NIH-CCCPM project was one of only eleven grants awarded through NIMHD’s “Social Determinants of Health Initiative” portion of the GO Grants.17

HHS 2011 Action Plan to Reduce Racial and Ethnic Health Disparities

In its 2011 “Action Plan to Reduce Racial and Ethnic Health Disparities,” HHS indicates that expanding health care access, data collection, and the use of evidence-based interventions will contribute to health equity for vulnerable populations.18 One of the strategies of the plan is to reduce disparities in access to primary care services and care coordination.

Affordable Care Act and Accountable Care Organizations

Signed into law in March 2010, the Affordable Care Act (ACA) mainly addresses the problem of the high number of uninsured in the United States. The ACA also seeds efforts to reform health care.19 The Accountable Care Organization (ACO) is one service delivery and financial reform concept promoted in this legislation. An ACO is a tightly linked group of providers working together to share accountability for the quality and cost of care they provide to a defined population of patients. Care coordination, performance measures and accountability are only a few of the concepts that are shared by the ACO and this NIH-CCCPM study.20

Information about the key entities involved in the NIH-CCCPM study is summarized below. This is followed by additional information about the study sites. The listing is not meant to depict a hierarchical order of importance. As is inherent in CBPR, all parties were actively and equitably engaged in this study.

Participating Organizations

KEY PLAYERS:


National Institute on Minority Health and Health Disparities (NIMHD)Within the NIH, NIMHD promotes minority health, conducts and supports research, training, research infrastructure, fosters emerging programs, disseminates information, and reaches out to minority and other communities impacted by health disparities. NIMHD, formerly the National Center on Minority Health and Health Disparities, is the funding agency for the NIH-CCCPM grant.21

WestatEstablished in 1963, Westat’s work includes research, evaluation, statistical surveys, and policy analysis. Westat has an extensive multi-sector research portfolio serving the health and human services, education, transportation, and energy infrastructure industries. The company has been the lead contract agency in many large-scale studies sponsored by NIH, AHRQ, and other health and human services agencies.22

The Westat NIH-CCCPM Project Director and Co-Principal Investigator for this study was Brenda A. Leath, MHSA, PMP. Russ Mardon, PhD, served as Co-Principal Investigator. The study Evaluation Expert was Donna Durant Atkinson, PhD. Sushama Rajapaksa, MA. was the NIH-CCCPM Project Manager. Maurice C. Johnson, Jr., MPH, served as Measurement Development & Testing Coordinator and Scott Smith, PhD, was a Westat data analyst with the study effort. Lisa C. Gary, PhD is a Westat Public Health Scientist and Madeline L. Darden, MSW, served as an external consultant on the project.

Data Research Associates (DRAs) operated from the various study sites and their role was vital to the study methodology and implementation. DRAs working on the NIH-CCCPM study included Anne Seifert, MEd (Ohio), Jane McGinnis, MBA (Nebraska) and Trudy C. Kilian, MS (California), Steven Walton, MBA (Texas), Meghan M. O’Quinn, MHA (Texas), Mayowa Ijagbemi (Texas), and Natalie Jackson (Indiana).

Technical Expert PanelThe NIH-CCCPM study established a TEP made up of stakeholders and experts selected to represent a diversity of perspectives and backgrounds. Convening the TEP was important to help ensure transparency and provided an opportunity to receive many stakeholders’ input throughout the study process. Held at regular intervals, TEP meetings helped foster communication among a broad base of participants (described below) and facilitate an exchange of lessons learned and emerging best practices.

For the NIH-CCCPM study, the TEP co-chairs are Veronica Nieva, PhD and Sarah A. Redding, MD, MPH. Dr. Nieva is a Westat Vice President and serves as the study’s Corporate Monitor & Senior Project Advisor. Dr. Redding is Director of the Community Health Access Project (CHAP) in Mansfield, Ohio and is the Co-Founder of CHAP’s Pathways Community HUB Model.

In addition to health care services, other disciplines represented within the TEP include quality improvement, strategic planning, managed care, research, and policy analysis. In addition to CHAP and Westat, organizations represented in the TEP are the Delmarva Foundation for Medical Care, Community Care of North Carolina, the National Quality Measures Clearinghouse, the Central Oklahoma Project Access Program, CHOICE Regional Health Network of Washington, the Toledo-Lucas County CareNet Hospital Council of Northwest Ohio and Healthcare Access Now.

9Key Players: Participating Organizations

KEY PLAYERS

Matrix Knowledge GroupThe study project’s information technology contractor is Matrix Knowledge Group. Matrix designed and devel-oped the study’s electronic data collection/reporting tool. They designed and managed the project web portal in collaboration with Westat management. The portal was used for data transfer (uploads/downloads) and as a resource for study team members. The portal also featured performance graphic and tabular data displays with multiple levels of comparison and detail.23

Study SitesGoing from East to West, the five sites that participated in the study are Community Health Access Project (CHAP), Rural and Urban Access to Health (RUAH), Baylor Community Care (BCC), Lincoln E. D. Connections (LEDC), and Access El Dorado (ACCEL). The map below, Figure 2, shows the geographic dispersion of the study sites. The section that follows provides more details about the sites. The rationale for site selection is provided in the Project Design and Implementation Section of this report. The Appendix also provides more information about each study site.

Sources of Information about the Sites. Several parts of this document reference information about the study sites and include comments from study site personnel. Such information was derived from a number of documents as well as directly from communications with study site personnel. Because the sources of information were so numerous and varied, citations for each statement about the sites are not provided herein, but are available upon request.

Community Health Access Project

The Community Health Access Project (CHAP) is a nonprofit organi-zation that was started in Mansfield, Ohio in 1999 by physicians Mark and Sarah Redding. CHAP’s mission is “To eliminate health and social disparities in our community by find-ing those at risk, connecting them to care and measuring the outcomes. We believe all communities can be transformed through the work of community health workers and the creation of community HUBs – an ac-countable care coordination delivery system.”

In Richland and Knox counties in Ohio, with a focus on low-income, Medicaid eligible populations, each year CHAP serves approximately 1,200 pregnant and post-partum women and children ages 0-3. CHAP’s co-founders also provide technical assistance across the nation in the development and implementation of programs and services that are in alignment with the Pathways HUB Model. Partnerships. While CHAP was the sole party that provided access to the data and patients interviewed for this study, CHAP’s work regularly involves collaboration with various community stakeholders. The partners involved de-pend upon the Pathway(s) or other projects that are the focus of a particular effort. For instance in their development of Pathways within the Children’s Community Health Access Initiative, CHAP collaborated with more than 70 different health and social service agencies across Richland County.

Figure 2. Map of the Pilot Site Geographical Locations


Rural And Urban Access To Health

Established in 2000, Rural and Urban Access to Health (RUAH), is a collaborative program sponsored by St. Vincent Health, which is Indiana’s largest healthcare employer. Main goals of RUAH include increased access to medical and social services and reduced inappropriate care.

RUAH provides safety net services in eight counties in central Indiana. In Madison County, where the NIH-CCCPM study took place, approximately 1,400 persons are served annually. While the community is predominantly White and non-Hispanic, RUAH serves a more diverse clientele, with an over-representation of Hispanic/Latino participants.

Partnerships. Organizations that participated in the study and provided access to data are Saint John’s Hospital, St. Vincent Health Information System Team, the Madison County Community Hub, and the United Way Community Access Network. RUAH is managed by St. Vincent Health. Eight of St. Vincent’s hospitals are members of RUAH, with two of these being in Madison County. Baylor Community Care

Baylor Community Care (BCC) served as a study site in the Dallas-Fort Worth “metroplex” area of Texas. BCC is a project of the Baylor Health Care System – a system that served more than 2.8 million people in 2011.

BCC seeks to provide quality healthcare and a compassionate medical home to patients and families that do not have access to a primary care physician. A primary goal is that underserved patients will experience fewer health disparities and require less frequent utilization of hospital services.

In 2011-2012, the community care navigation program worked with 1,200 patients, and successfully connected 806 patients to a medical home. The BCC clinics that become medical homes for these patients served 12,000 patients. Of all sites, this community’s demographics were the most racially and ethnically diverse, with 65.3 percent of the population being White and 27.5 percent being of Hispanic or Latino origin.

Partnerships. The Baylor Health Care System was the sole party that provided access to the data and patients interviewed for this study. The BCC program operates within four Baylor hospital campuses and 10 clinics. Many of these clinics are operated in association with community-based service providers as well as Baylor-employed staff. Baylor-paid CHWs that staff the BCC also work very closely with community providers in helping patients access and retain needed healthcare and barrier relief needs. Lincoln E. D. Connections

Lincoln E. D. Connections (LEDC or “ED Connections”) is a collaborative program of two hospital-based systems in Lincoln, Nebraska – BryanLGH and Saint Elizabeth Regional Medical Center. BryanLGH, the successor to Lincoln General Hospital, is a not-for-profit, locally owned healthcare organization with two acute-care facilities and several outpatient clinics. The organization is undergoing a name change to Bryan Medical Center, in September 2012. Saint Elizabeth Regional Medical Center is a nonprofit, faith-based medical center and member of Catholic Health Initiatives, the third largest Catholic healthcare system in the country with a presence in 19 states.

Initiated in 2005, the purpose of ED Connections is to serve the community’s most vulnerable patients who repeatedly use the emergency department (ED) for non-emergency purposes. The primary goal of the program is to eliminate barriers to health care, such as transportation, medication costs, financial difficulties.

Approximately 4,500 individuals qualify for enrollment annually. Annually, approximately 500 to 600 are served. Within Lincoln’s predominantly White population, the majority of current participants, as of this writing, are White women age 25 – 45.

11Key Players: Participating Organizations

KEY PLAYERS

Partnerships. Organizations that participated in the study and provided access to data include the aforemen-tioned two hospital systems. De-identified patient data came from both hospitals for the purposes of this study. Oversight of the LEDC program is provided by a community advisory council and the program is directly super-vised by both ED Directors of the hospitals. LEDC regularly collaborates with more than 45 community social ser-vice agencies and medical providers. These include Lancaster County Medical Society, Center for People in Need, People’s Health Center, Matt Talbot Kitchen, Lancaster County Health Department and many other agencies, local pharmacies, and private health care providers. Access El Dorado

Access El Dorado, popularly known as ACCEL, is a community-wide collaborative among public and private agencies in predominantly rural El Dorado County California. Formed in 2004, ACCEL’s mission is to (1) seek to create healthier communities, especially within vulnerable populations, (2) identify specific barriers (especially access!) to a healthy community and (3) develop systematic improvements that include all partners and serve the entire community.

In 2011, over 1,200 patients of all ages were served across seven Pathways. While persons of Hispanic or Latino origin are characteristic of 12.3 percent of the county’s population, they are over-represented in ACCEL’s clientele.

Partnerships. Collaborative partners who participated in the study and provided access to data include ACCEL’s health collaborative members – the El Dorado County Health and Services Agency’s Public Health and Mental Health Divisions, Barton Healthcare System and Marshall Medical Center (as well as their affiliated medical pro-viders and rural clinics), El Dorado County Community Health Center (a Federally Qualified Health Clinic), Shingle Springs Health and Wellness Center (formerly Shingle Springs Tribal Health Program). One other member of the collaborative, Western Sierra Medical Center, was too new to the collaborative to be able to provide data or pa-tients for the study.

This section summarizes how the study project was designed and implemented. Key activities are discussed. A summary of how some of the study’s administrative and technical challenges were ad-dressed is provided as well.

PROJECT DESIGN AND IMPLEMENTATION


Project Objectives and Methodology

Objectives

Four major objectives for this project were to:

Refine the conceptual framework for the Pathways HUB Model and identify relevant measurement domains for assessing quality and outcomes. Draft detailed specifications for selected care coordination quality and outcomes measures. Assess the relevance, feasibility, validity and reliability of the measures through a pilot test at five pilot sites. Finalize the measure specifications and develop documentation, data collection, and reporting tools to facilitate their use.

Methodology - Community Based Participatory Research (CBPR)The CBPR methods used in the NIH-CCCPM project incorporated the knowledge and experience of the Westat project staff, the TEP, the study site personnel and the DRAs that collected data and interviewed patients. This “CBPR Team” acted as a real-world “learning laboratory.” This team approach helped ensure that the performance measures created were relevant to the community and that the use of standardized performance measures could be implemented in diverse community settings.

Transparency. The CBPR approach helped ensure that the study activities were transparent to key stakeholders. Monthly teleconferences were held with Westat, study sites, and DRAs. Twice monthly teleconferences were held with the DRAs and the Westat project team. In-person meetings were also held several times during the study.

Learning and Sharing through the CBPR Process. These interactions provided a collaborative forum in which to learn about and monitor the status of work in progress, to highlight areas of concern for timely action, and to update the completion status of scheduled activities. Participant feedback and reciprocal dialog was a fundamental component. Such learning and sharing opportunities were helpful in gaining insight into such issues as:

15PROJECT DESIGN AND IMPLEMENTATION

PROJECT DESIGN

Timely approval process - It is necessary to understand variations in Institutional Review Board, data use and business associate agreement requirements, across settings (i.e., hospitals, healthcare networks). Across sites, this involved different timeframes and procedures to secure necessary approvals protecting patient privacy and ensuring security of information sharing.

Building consensus - The development of clear definitions and specifications for each measure need to be through a systematic approach that is understood and applied uniformly, but also in consideration of site differences. Timely approval of patient surveys - Surveys to assess patient experience are a critical study component. Collecting time sensitive data - The need for time sensitivity in data collection is important, particularly among programs having shorter patient encounter timeframes.

ActivitiesBelow is a list of the key activities conducted during the study. The narrative that follows summarizes some of these activities and provides input from the study sites.

Site selection; Creating the conceptual model, selecting, defining, and refining performance measures; Hiring, training, deployment, and coordination of DRAs; Gaining institutional/agency permissions for access to participants and their data; Developing performance measure definitions and data collection protocols; Development of an electronic data collection tool and web portal; Developing the Patient/Client Survey and its administration protocol; Testing data collection instruments and processes; Collecting data; and Cleaning and analyzing data.

Site SelectionNIH-CCCPM study site selection was based on a number of factors. All sites were already collaborators with Westat through their involvement in the CCCLN. Each of the sites had adapted some facets of the Pathways HUB Model and each had a central HUB or a leading project/program that coordinated their pathways. The sites were spread across the United States, were in both rural and urban settings, and were managed by different types of entities. Furthermore, with the exception that each site served vulnerable populations, care coordination methods, pathway definitions and participant characteristics were not the same. This diversity was intentional, leading to a better view of how performance measures might fit over a broad spectrum of venues, processes, and populations.

Conceptual Model, Selecting, Defining and Refining Performance MeasuresA care coordination conceptual model was completed. It outlined processes that were common across most pathways – such as enrollment, participation, completion of involvement, and documentation of outcomes.

Subsequently, the Westat project team drafted detailed measure specifications, in collaboration with other CBPR team members. The intention was to identify pathway domains (dimensions of performance) and draft performance measures that were relevant, applicable, and in common use across multiple study sites.


It was important to ensure that the measures, protocols and processes were scientifically sound. Literature reviews of previous measures and measure definitions, data collection, and patient survey efforts were conducted. Consultation with subject matter experts and other key stakeholders helped inform this step. The participation of the sites in the measure selection process was essential. The measures had to be operationally feasible, relevant, and of interest and value. In considering particular measures, the sites considered whether they already captured the data related to the measure, if not, could they envision ways to capture it and/or could they envision ways to improve how they capture such data. They were asked to consider if the data were worth capturing. That is, did it help inform their service delivery system/costs/outcomes/other metrics?

Standardization of metrics across sites has always been perceived to be difficult—a premise confirmed by this effort. Below are some comments from study site managers regarding this process.

“Based on the way our services are provided, defining ‘enrollment,’ selecting an enrollment date and defining ‘Pathway completion,’ was challenging.”

“If you had asked me what I thought the biggest realization would be is that it would be really challenging to establish metrics across different sites. And, frankly, that was confirmed.”

Reaching consensus on aspects of care coordination that should be integral to any program required looking into how a measure could be uniformly applied. This required objectivity across the project team. This helped ensure that such elements would be identified for measure development regardless of their implementation in participating sites.

Engagement of Data Research AssociatesFive Data Research Associates (DRAs) were engaged – one for each site. They helped refine the data collection processes and collected information from participant records as well as from Patient/Client Surveys. They entered the data into the study’s electronic database. The DRAs also helped provide local insights as part of the CBPR team process.

In addition to the aforementioned monthly conference calls, several in-person training, networking, and information sharing sessions were held with the DRAs. Westat-provided training included regulations and practices regarding data security and privacy protection. DRAs were also required to meet any local privacy and security requirements.

Study Site Contributions to DRA Success. Coordination of activities was managed by Westat, but the activities concerning data collection or access to patients had to be managed in accordance with the operations of each site. Consequently, each DRA met often with one or more study site stakeholders.

At all sites, the DRA was provided wide access to information and benefitted from knowledgeable and supportive study site assistance. Study site personnel helped the DRA understand how to use local documentation systems and helped clarify terms and processes. In the sites that participated in the Patient/Client Survey, local personnel also helped locate current contact information for the potential interviewee and helped with other logistics.

Gaining Permissions to Access Records and ParticipantsFor each site, officials had to approve DRA access to patient data and to patients. Site managers noted that strong coordination is needed between study managers and entities from which permissions were to be obtained (e.g., research councils, Institutional Review Boards).

There are differences in how each entity determines such authorizations. The timing of obtaining permissions and the particular process for doing so resulted in one of the sites not being able to participate in the Patient/Client Survey part of the study. As the site manager put it, “Hospitals need to see everything clearly defined, ‘everybody’s ducks in a row at the onset.”

17PROJECT DESIGN AND IMPLEMENTATION

PROJECT DESIGN

Testing the Measures, Protocols and ProcessesUpon being oriented to the drafted data collection protocols, the DRAs tried out the intended methods for accomplishing the tasks. The focus was on determining whether the tools and procedures would correspond to how business was normally conducted at the study sites. The DRAs also tested the process of saving data to the study database and uploading them to the project web portal.Feedback from the data collectors (DRAs) and the data “owners” (the sites) on the processes and instruments were considered in revising the instruments and protocols. Other CBPR team member input was also considered – including that from Westat personnel and the TEP.

Collecting Client Services DataIn their regular operations, sites used both paper-based and electronic data collection instruments to record and monitor service delivery. As noted earlier, DRAs had to learn how to use these tools. In some cases, several different databases had to be accessed in order to obtain information for the study.

Most sites agreed that it wasn’t always possible to collect complete data due to “human error” issues, as one site manager put it, At times, data were missing, incomplete or inconsistent in the files from which the DRA was extracting information. As another site manager put it, “This process helped show us areas where we need to tighten up.”

Different Measures in Different Sites. The types of services data that were routinely collected varied across study sites. Fewer overall records were collected for certain performance measures since some sites could not report services data for all of the performance measures.

“We did not participate in some of the mea-sures because our program does not collect that information. For instance, we aren’t paid for reducing ED use, so we do not track it,” said one site manager.

However, a study site manager acknowl-edged that that sites were not expected to use measures and methods that wouldn’t fit with their programs, in order to participate in the study. “They didn’t tell us to re-do our program,” he said.

Administering and Collecting Patient/Client FeedbackGathering input from participants or their parents (in the case of minors) was important. A report entitled “Transforming Patient Engagement,” had this to say about the value of such surveys:

“First, there is no better measure of patient engagement than assessing individual patients’ experiences with their care. We know from research that better patient experience yields better health outcomes, and experience surveys are the best tools we have for assessing the impact of care for the highest-need, highest-cost patients.”25

The CBPR approach helped immensely in the creation of the Patient Surveys. For example, CBPR team members helped devise ways to shorten the initial Patient/Client Survey, to enhance relevance based on operations at the sites and to develop different modes of survey administration. CBPR team members also helped identify the need for a Spanish-language survey.

Reaching Survey Candidates. One site noted that the number of completed Patient/Client Surveys was relatively small, and they suggested this outcome was due to the difficulty with reaching potential interviewees. The population served was transient, with many potential interviewees moving in and out of the area. Many only had cell phones, but couldn’t afford to use cell phone minutes on a call to complete the survey. To protect client privacy, if an interviewee was not reached, a callback number was not provided. This might have resulted in fewer responses. Also, when a DRA made a call, the respondent might not have recognized the number or might have noted it as a “blocked call.” This might have reduced the response rate.

Survey Responses – Possible Site-Specific Differences. Some sites felt that the particular ways that they conduct business might have affected Patient/Client Survey results. For instance, the survey asked to rate the help they received from the community care coordination program. Some sites were concerned that interviewees may not have been aware which provider helped them.

Our short service delivery period and the often chaotic setting in which patients are served may have affected our Patient/Client Survey responses. Huge challenges are inherent in the discharge process. We’re just one of many talking to the patient, and so they may not remember the guidance our CHWs are trying to provide,” indicated one site manager.

Another site manager related that patients are not always aware of their HUB as providing them with services. They are more aware of the individual service provider within the HUB (clinic, public health department, etc.) and identified with that provider’s staff.

Data Cleaning and AnalysisOnce data collection began, the critically intense phase of “data cleaning” was initiated. Westat team members looked at the data collected, noted discrepancies and missing fields, queried the DRAs, and completed other “logic checks.” The resultant information was compiled and analyzed as described in the next section.

The Findings and Results section provides quantitative data on the demographics of the clients served in this study and on the implementation of the performance measures by the study sites. The data sources for the quantitative section include a survey of clients served as well as nonsurvey data from institutional databases on client services utilization, which often include basic client background information e.g., age. All data were de-identified. In addition, this section provides an overview of quali-tative information which reflects the perspectives of the study sites on the study implementation and areas for future study. Before the discussion of quantitative and qualitative results, we first present the list of community care coordination performance measures which should be shared with the public (Table 1). This list of measures is one of the primary outputs from this study.

FINDINGS AND RESULTS


Part 1. Performance Measures for Community Care CoordinationTable 1. Community Care Coordination Measurement Domains, Pathways Components, and Measures

Measurement Domain Pathways Component Measure Name (Data Source)

Enrollment Services Enrolling in Community Care Coordination

Timeliness of Contacting, Screening, and Enrolling Prospective Clients (Non-Survey)

Appropriate coordination of health care

Identifying and Reducing Barriers to Care

Developing and Maintaining a Care Coordination Plan (Non-Survey)

Health Care Referral Scheduling (Non-Survey)

Health Care Referral Completion (Non-Survey)

Client Received Needed Help form CHW to Coordinate Health Services (Survey: Q3b)

Client Received CHW Help Getting Medicine (Survey: Q7)

Appropriate coordination of support services

Identifying and Reducing Barriers to Care

Developing and Maintaining a Care Coordination Plan (Non-Survey)

Social or Support Services Referral Scheduling (Non-Survey)

Social or Support Services Referral Completion (Non-Survey)

Client Received Needed Help form CHW to Coordinate Social or Support Services (Survey: 12b)

Evidence-based processes of care

Confirming the Delivery of Evidence-Based Care Pathways Completions (Non-Survey)

Obtaining needed support services

Confirming the Delivery of Evidence-Based Care Pathways Completions (Non-Survey)

Health outcomes Documenting Outcomes Pathways Completions (Non-Survey)

Utilization/cost savings Documenting Outcomes Emergency Department (ED) Use (Non-Survey)

Emergency Department (ED) Visits Post Care Coordination Completion (Non-Survey)

Hospitalization Post Care Coordination Completion (Non-Survey)

Client experience of care coordination Cross-cutting Client Satisfaction With Health Care Coordination

by CHW (Survey: Q4)

Client Satisfaction With Social Support Services Care Coordination (Survey: Q13)

Frequency of Communication Between the Client and His/Her CHW (Survey: Q15)

Client’s Recommendation of His/Her CHW (Survey: Q16)

Client’s Empowerment to Coordinate Health Care Services (Survey: Q19)

Client Empowerment to Coordinate Social or Support Services (Survey: Q20)

21FINDINGS AND RESULTS


Part 2. Results From the Quantitative DataThe diversity among sites is evident in the wide array of clients represented in the data (Tables 2 and 3). Males account for more than one-half (55.6%) of clients. More than one-third of clients are under the age of 18 (42.3%); 20.8 percent range in age from 50 to 65. Close to 15 percent of clients are Black/African-American (14.4%) and 10 percent (10.2%) are solely of Hispanic/Latino or Spanish origin. Furthermore, English is the primary language of three-quarters of clients (75.4%). In particular, a significant proportion of sociodemographic data are unknown. One site only began collecting this data half way through the project while several other sites never consistently collected this information.

Measurement Domain Pathways Component Measure Name (Data Source)

Cultural competence Cross-cutting CHW’s Consideration of Client’s Values and Beliefs (Survey: Q17)

Delay in Receipt of Services due to Client’s Communication or Cultural Problems with Service Provider (Survey: Q18)

Shared decision making Cross-cutting Documentation of Client Participation in Care Coordination Plan Development (Non-Survey)

Client Awareness of Care Coordination Plan Development (Survey: Q1)

CHW Engages Client in Care Coordination Plan Development (Survey: Q2)

Health-related quality of life Cross-cutting Client’s Self Rated Health (Survey: Q8)

Client’s Report of Unhealthy Days for Physical Health (Survey: Q9)

Client’s Report of Unhealthy Days for Mental Health (Survey: Q10)

Client’s Report of Unhealthy Days for Usual Activity (Survey: Q11))


Table 2. Client characteristics by site

Four of the five sites collected survey data using three different administration modes—mail, telephone, and in-person—resulting in 208 complete surveys. The overall response rate across all participating sites was 48.5 percent. The numbers of completed surveys by mode were: 27.2 percent mail, 62.2 percent telephone, and 9.9 percent in-person administration. Three surveys were administered in Spanish and the remaining surveys were administered in English. There were almost as many adult surveys (54.3%) completed as there were surveys completed by a family member or legal guardian for their children who received services.

SITE

Characteristic Site A Site B Site C Site D Site E Total

Number of Clients 765 616 140 371 600 2,492

Age

0 to less than 1 229 0 0 0 2 231

1-18 382 0 8 11 5 406

19-29 19 1 21 8 87 136

30-49 69 0 69 1 282 421

50-64 58 0 27 0 199 284

65 and Over 4 0 2 0 22 28

Unknown 4 615 13 351 3 986

Gender

Male 367 356 61 240 87 1111

Female 392 229 79 130 57 887

Unknown 6 31 0 1 456 494

Race/Ethnicity

Black or African American 0 16 24 153 48 241

Hispanic/Latino 135 11 4 2 18 170

White 309 534 96 190 49 1178

Other 27 2 13 26 15 83

Unknown 294 53 3 0 470 820



Table 3. Additional client characteristics by site

Results – Sites’ Use of the Community Care Coordination Performance MeasuresEnrollment Services Domain Timeliness of Contacting, Screening, and Enrolling Prospective Clients (3 sites collected data)This measure assesses the timeliness of contacting, screening, and enrolling clients into community care coordination when prospective clients come to the attention of the care coordination organization from external sources. More than half (56.8%) of prospective clients were contacted, screening, and enrolled within 14 days of being referred to the care coordination organization, while an additional 11 percent of prospective clients were enrolled within 60 days of referral. Conversely, almost one-third (32.2%) of clients were never enrolled in care coordination. Of those not enrolled in a care coordination, more than half (59.4%) were contacted by a CHW, but refused services.

Appropriate Coordination of Health Care Domain

Developing and Maintaining a Care Coordination PlanA comprehensive care coordination plan specifies and prioritizes actions for achieving the desired health endpoint, including connections to needed health care services, and connections to needed social or support services. The care coordination plan should be developed in conjunction with the client on a timely basis after enrollment, and updated regularly thereafter. This measure is included in both the Appropriate Coordination of Health Care domain and the Appropriate Coordination of Support Services domain since a comprehensive care coordination plan addresses both health care and social or support service needs.We experienced multiple challenges measuring the development and maintenance of a care coordination plan. Initial review of the data during the collection period revealed few records complying with these activities. Follow up with data collection staff uncovered that many sites reported care plans under development, yet did not actively document this task—a requirement per measure specifications. Other sites did not do formal care coordination planning as part of their normal process. As a result there were insufficient pilot test data to report on this measure.

SITE

Characteristic Site A Site B Site C Site D Site E Total

Number of Clients 765 616 140 371 600 2492

English as Primary Language

Yes 628 614 140 371 125 1878

Insurance Status

Medicaid 292 13 22 366 1 694

Uninsured 0 272 93 1 0 366

Other 108 36 25 4 42 215

Unknown 365 295 0 0 557 1217

Income (Household)

100% FPL 0 256 126 104 0 486

Greater than 100% FPL but no more than 200% FPL

0 41 13 264 0 318

Unknown 765 319 1 3 600 1688


HealthCare Referral Scheduling (4 sites collected data) The health care referral scheduling measure indicates the time it takes from when a referral is made to the time that the health care provider is contacted and the appointment is placed on their calendar. A large majority (86.9%) of referrals were scheduled within seven days. The rate of referral scheduling within seven days was higher for primary care and developmental screening referrals, and lower for mental/behavioral health care and other specialty care. In part this difference is due to differences in how sites schedule referrals. Of the 81 cli-

ents not scheduled for a referral, 50 were unreachable af-ter initial contact; there were insufficient records for 19 other potential clients.

Health Care Referral Completion (4 sites collected data)A referral is completed when the indicated health care service is delivered. For services that require multiple visits such as prenatal care, we consider the referral to be completed at the time of the first visit to the health care provider. The number of referrals for this measure differed from the number for the referral scheduling measure because some health care services

do not require appointments, and because the measurement time periods were different in the pilot test to allow sufficient time for referrals to be completed. More than 40 percent of referrals (40.8%, n = 1,157) were completed within 14 days and nearly two-thirds were completed within 30 days (Figure 3). Most of these completed referrals were for primary care visits. The completion rates were lower for mental and behavioral health services as well as other types of specialty care. Of the 101 clients who did not complete their referral, more than half (58.4%) did not appear for a scheduled appointment. This measure highlighted a documentation challenge for some of the sites. The measure specifi-cation requires confirmation from the health care provider to demonstrate the completion of the referral. Yet in practice, some sites relied on client confirmation.

Survey itemsTwo of the measures in this domain were estimated from the client survey. One of these measures is entitled Client Received Needed Help from CHW to Coordinate Health Services. This measure is based on clients who reported needing help coordinating health care services. According to the survey results, more than 6 in 10 (61.7%, n = 201) respondents needed health care in the past 2 months. Of those respondents, fewer than half needed help coordinating their care (40.5%, n = 121). Out of this number, CHWs helped coordinate healthcare services for the overwhelming majority of those in need (93.8%, n = 48). The second survey measure was Client Received CHW Health Getting Medicine. During the previous two months, just less than half (43.6%, n=204) of respondents were prescribed medicine other than vitamins. Only 22.7 percent (n = 88) needed help getting the medicine. A majority (72.2%, n = 18) of those respondents received needed help from their CHW getting their prescription filled.

Appropriate Coordination of Support Services Domain

Developing and Maintaining a Care Coordination PlanAs mentioned in the Appropriate Coordination of Health Care section, there were insufficient pilot test data to report on this measure.

Social or Support Services Referral Scheduling (2 sites collected data) The social or support services referral scheduling measure indicates the time it takes from when a referral is made to the time that the service provider is contacted and the appointment is placed on their calendar. Many social or support service providers do not require appointments so this measure is not applicable to those services. Of the social or support services where an appointment was necessary, an overwhelming majority (99.3%; n = 457) of them were scheduled within seven days of initial contact. Two sites were included in this

41%

22%

14% 8%7% 9%

HeHealalthcare Referral Completion (Nu(Number of referrals = 11187187))

Number Completed Within 14DaysNumber Completed Within 30DaysNumber Completed Within 45DaysNumber Completed Within 60DaysNumber Completed Later 60 DaysNumber Not Completed

Figure 3. Healthcare referral completion



measure; however, one site accounted for a large proportion of records (98.2%). In particular, this site had a specific Pathway that many of their clients in their program were eligible for – obtaining health insurance.Social or Support Services Referral Completion (3 sites collected data)

Although two sites collected scheduling data, three sites collected completion data. Only one in four cli-ents (27.7% n=573) accessed social services within four-teen days after a referral, while an additional 20 percent received the service within 30 days. Still, more than three-fourths (75.3%) of social services referrals were ultimately completed (Figure 4). Many of the care coordination organiza-tions provide social or support services themselves. The rate of completion for these internal referrals, which made up the majority of the referrals, was higher with half of the referrals completed within 30 days. The completion rate for referrals to external service providers was lower, with only 40 percent

completed within 30 days, and one-third not completed at all. The most common reason for failure to complete referrals for social or support services was loss of contact with the client (48.4%).The most common social or support service referrals were for health insurance enrollment, for which 55 percent of the referrals were completed within 30 days, and parent education services, for which 42 percent of the refer-rals were completed within 30 days.

Survey itemsThere was one survey measure in this domain, Client Received Needed Help from CHW to Coordinate Social or Support Services. To be eligible for this measure, the client must have reported needing health coordinating so-cial or support services. Close to half of respondents (45.0%, n = 202) needed social or support services in the past two months. Of those who needed social or support services, three in four (74.2%, n=89) also needed help coordinating those services. CHWs provided help coordinating social or support services for a majority (92.3%, n = 65) of those respondents who reported needing it.

Evidence-Based Processes of Care Domain

Pathways Completions (4 sites collected data)The Pathways Completions measure is the sole measure in three domains: Evidence-Based Processes of Care, Obtaining Needed Support Services, and Health Outcomes. While a conceptually simple measure, its versatility lies in the robustness of the Pathways Model itself. A Pathway is any structured workflow that guides the deliv-ery of care coordination services aimed at achieving a specific health outcome or process goal. A Pathway must have specified client or patient eligibility criteria, a defined initiation step, appropriate intermediate steps and milestones, and a verifiable completion criterion indicating the completion of that Pathway. Depending upon the type of Pathway, its completion may represent the delivery of an evidence-based health care service (e.g., connecting a client to a medical home or ensuring that a client is up to date on immunizations), the connection to a needed social or support service (e.g., parent education or family planning services) or the achievement of a defined health outcome (e.g., a healthy birthweight baby).

Of the nearly 2,000 Pathways initiated (1,929), 86.2 percent were completed. The completion rate was lower for some Pathways such health insurance enrollment, connection to mental health/substance abuse services, and the medical home Pathway, while it was higher for the well-child checkup and the parent education Pathways. The average duration of completed Pathways also varied greatly ranging from 12.7 days (Newborn visit) to 279.4 days (Other Healthcare). The most common reason for non-complete Pathways was that the client was non-compliant or lost to follow-up (8.3% of non-completed Pathways).

28% 20%

16% 6%5%

25%

Social or Suppport Services Referral CCompletion

Number of RReferrals = 678

Number Completed Within 14 Days




Number Completed Later than 60 Days

Number Not Completed

Figure 4. Social or support services referral completion


Obtaining Needed Support Services DomainPathways Completions (4 sites collected data)See the Evidence-Based Processes of Care domain.

Health Outcomes Domain

Pathways Completions (4 sites collected data)See the Evidence-Based Processes of Care domain.

Utilization/Cost Savings DomainEmergency Department (ED) UseEmergency Department (ED) Visits Post Care Coordination CompletionHospitalization Post Care Coordination Completion

We collected limited data from one site on Emergency Department (ED) use, and visits to an ED or hospitaliza-tion within 90 days of post care coordination completion. Other sites were not able to field these measures be-cause of difficulties collecting the necessary data on utilization of these services. Two sites were not affiliated with a hospital system and, therefore, would have needed to put in place data sharing agreements to get the data, and they were unable to do this for this study. Two institutions had access to ED and hospital data yet did not have the necessary time and/or resources to gather data. A key factor was the lack of synergy between care coordination sites and their corresponding hospitals data systems.

Survey itemsAlthough there are no survey measures which analyzed utilization/cost savings, the survey did provide questions which provide information relevant to this domain. More than one in three (42.2%, n = 45) respondents who received help coordinating their health care services visited the emergency department (ED) in their past two months. The last time respondents visited the ED in their past two months, nearly four in five (89.5%; n = 19) believed it was for an emergency (based on self-reported data). It is possible that trained health professionals may conclude that some of these ED visits were for a non-emergency concern.

Client Experience of Care Coordination Domain

Survey itemsThere were six survey measures in this domain.

• One measure was Client Satisfaction with Health Care Coordination. An overwhelming majority (97.9%; n = 48) of respondents were either ‘Satisfied’ or ‘Very satisfied’ with the coordination of their health care by their CHW. • All of the respondents (n = 54) reported being ‘Satisfied’ or ‘Very satisfied’ on the Client Satisfaction with Social or Support Services Coordination measure. • A large majority (86.1%) of respondents were ‘Definitely’ willing to recommend their CHW to friends and family. • With respect to Frequency of Communication Between the Client and His/Her CHW, almost nine in ten (87.9%, n = 198) respondents were either ‘Always’ or ‘Usually’ able to get in touch with their CHW when they needed to, although 10.6 percent were either ‘Never’ or ‘Rarely’ able to do so. • Approximately half of respondents reported feeling Empowerment to Coordinate Health Care Services (53.2%, n = 203) or Social or Support Services (53.0%, n = 202) after spending at least two months with their CHW.



Cultural Competence Domain

Survey itemsThere were two survey measures in this domain. A large majority of respondents (91.4%, n = 196) believed their CHW Always, Usually, or Sometimes thought about their beliefs, values, and traditions when working with them. A full 79.1 percent responded ‘Always’ on this measure. Another measure of cultural competence is the CHW’s ability to identify and address cultural or language barriers their clients may encounter in their interaction with health care or social or support service providers. During the past two months, only a small portion (2.0%, n = 202) of respondents reported a Delay in the Receipt of Services due to Client Communication or Cultural Problems with Service Providers.

Shared Decision Making Domain

Documentation of Client Participation in Care Coordination Plan DevelopmentSimilar to the Developing and Maintaining a Care Coordination Plan measure, we experienced challenges collecting the Documentation of Client Participation in Care Coordination Plan Development measure. In part this was because four out of the five care coordination sites did not routinely document client participation in care coordination plan development. Also, some of the clients were long-time clients who may have had an initial care coordination plan developed in the past. Because of these measurement difficulties, we changed the specification of this measure in the final measure set to reflect only new clients to measure their participation in their initial care plan development.

Survey itemsThere were two survey measures in this domain. The first was Client Awareness of Care Coordination Plan Development. Approximately 6 in 10 respondents (58.7%) were aware that their CHW developed a plan for them; and additional 2.4% believed someone else with the program had done so. A large majority (91.7%) of respondents thought their CHW used their ideas when developing their care coordination plan, reflecting high scores on the measure CHW Engages Client in Care Coordination Plan Development.

Health-Related Quality of Life Domain

Survey itemsTo assess health-related quality of life, we use the Centers for Disease Control and Prevention (CDC) “Health Days” measures. A large number (82.5%) of respondents self-reported their health status as either “Excellent,” “Very Good,” or ‘Good’ (Figure 5). Furthermore, nearly two-thirds of respondents (63.5%) did not have any unhealthy physical or mental days in the previous two months. On average, respondents who reported at least one unhealthy physical or mental day in the past two months suffered 14.0 physically unhealthy days and 24.1 mentally unhealthy days. By comparison, the CDC in 2008 reported a national average of 3.6 physically unhealthy and 3.4 mentally unhealthy days in the past 30 days. Of the 32 respondents who suffered at least 1

day of poor mental health in their previous 2 months, 21 also suffered at least 1 day of poor physical health during the same period of time.

More than one in four adults (28.3 %) and one in ten children (10.5%) reported at least one day in the past 60 they were unable to do their usual activities such as self-care, work, or recreation at least one day in the past two months reported with an average of 15.78 and 5.2 days lost, respectively. Nationally, only 5.5 percent of adults and 7.3 percent of children reported a limitation of activity. In sum, pilot test respondents were more likely to report at least one mentally or physically unhealthy day, more unhealthy days, and be unable to do their usual activities compared to national norms.1

54%

28%18%

Client Overall Health Status WithinPast 2 Months

(N = 206)

Excellent or Very Good V

Good

Fair or Poor

Figure 5. Client overall health status within past 2 months


Part 3. Results From the Qualitative DataStudy Site Managers: Comments, Perspectives on Study ParticipationComments about the findings, the benefits of being involved, and suggested study improvements are provided in this section. Recommendations for improving study design or for moving to the next step of standardizing performance measures are discussed as well. The comments revealed four main themes.

Site Operations Continued as Usual; There are Benefits to Participation in a National Study; Study Findings Mirror Our Local Analysis and Add to the Evidence Base; and The Study Provided Numerous Other Benefits.

Theme 1: Site Operations Continued as UsualAccording to interviews with study site managers, being involved in the study had no major impact on how each site conducted its normal operations. Business went on “as usual,” once the Program obtained clearances so that DRAs could access data and talk to patients (or their parents/caregivers, in the case of minors).

Theme 2: There are Benefits to Participation in a National StudyStudy sites indicated that being involved in a national study, especially an NIH study, could help build credibility and support growth. Selected site manager comments are provided below.

“Being one of the five study sites allowed us to gain national recognition for the work that we do. This is not always possible for programs such as ours that are located in small and rural communities.”“The fact that (our site) was involved in this national study was mentioned in every single grant application that we wrote,” said the site manager. “It helped highlight the fact that, “(our site), a relatively small operation in this small, rural county, can still make a very important impact in the health care frontier.”

“We’re hoping that this study will generate interest among national and local funders to help us spotlight the need for funding of crisis and barrier relief.”

“We’re proud of the fact that we were able to help define some of these elements. We were grateful to participate in this NIH rigorous, groundbreaking study and want to help drive this kind of effort forward.”



Theme 3: Study Findings Mirror Our Local Analysis and Add to the Evidence BaseAll sites are already using performance measures. Most sites indicated the analysis of the data collected from the study resonated with their own measurement tracking and evaluation outcomes.

“What I’ve seen so far is consistent with our internal results, in terms of reduction in ED visits for people in the program,” reported one site manager.

“When I saw the initial results from the non-survey data collection, I was pleasantly surprised to see that it reflected similar outcome results as those we tallied through our local data analysis”, said another site manager.

One site also noted that having more data, resonating with local findings, is definitely a benefit.

“There is always a benefit of having more data to look for patterns, understand and adapt best practices and convince funders and other stakeholders of the worth of a particular effort.”

Some study sites were pleasantly surprised at the volume of Patient/Client Survey responses and “how recep-tive folks were to the survey.”

Theme 4: The Study Provided Numerous Other BenefitsOne site indicated that being involved in the study helped them expand the number of pathways they provide and the geographic areas they served.

“Being involved in the study helped us determine to expand the Pathways project. It helped us move our actual Pathway development forward more quickly than we might have and spread it to different communities,” the site official stated.

Another site used the impetus of the study to complete plans for revising how they collect data.

The biggest benefit from the program was “recognizing the need to improve our tracking and reporting,” stated the site manager. The site subsequently created a new database to replace their spreadsheet system that was becoming inadequate.

Another site recognized the benefit of having a third party review their processes and documentation and dis-cuss the data entries and patient communication procedures with staff. The site manager indicated this helped their program identify “where we need to tighten up, within or between agencies, in relation to our training and our workflows.”

The collegiality, problem-solving and information sharing aspects of the study were positively acknowledged by one site manager, in particular.

Being involved in the teleconferences and on-site meetings were helpful, as well – having a chance to meet other sites facing the same issues, indicated a site manager. It was helpful to hear how different sites are “selling” care coordination. For example, one of the sites associated health care coverage with specific services that may not otherwise been paid to create a monetary value their collaborative was able to bring.

Study Sites’ Future Interest and Recommendations for Next StepsAll study sites are interested in pursuing additional efforts for standardizing care coordination performance measures. This includes continuing with an ongoing collaboration with the Rockville Institute’s Center for Pathways Community Care Coordination.

The study sites viewed the participatory nature of project as viable and productive relative to accomplishing the project’s objectives. Their responses acknowledged a varying degree of gains in organizational capacity resulting from participating in the study and the information exchanges between the CBPR team (including participating partners, Westat corporate team members and the TEP).

One of the most prevalent challenges cited was a lack of sufficient time to do more of the actual data collection subsequent to performance measure development/selection. However, most attendees deemed the performance measure development process to be noteworthy as clearly evidenced by its rigor and conformity to contractual expectations.

Many site managers reported that they thought having a longer data collection period could be helpful. Another common remark was that including ways to measure “return on investment” (ROI) should be looked at. These sentiments are reflected in the statements below.

“Having more data to look at and use to convince funders this is worthwhile would be helpful. Developing ways to state that this implementation would help – for example if a site is doing particularly well or if an approach is working (well) in multiple areas, that certainly builds for credibility. Having cost-benefit data would have been helpful,” said one site manager.

“For us, having cost benefit data would be helpful to justify value of care coordination, where [at this] time we’re trying to do more with less. Hard data, ROI or think about different ways we can sell care coordination to our funders or stakeholders is always helpful. Having a longer data collection period would be helpful,” the site manager suggested.

Opening up the study to a broader range of participants would be useful, according to one site manager. Extending the study period or expanding the study measure definitions would be helpful, as well, noted several site managers.

Continuing to refine the measures or expanding the measures would provide additional helpful information for community-based programs, as noted by several site managers. In order to obtain greater amounts of data per measure, clustering measures in relation to the types of services or types of sites conducting the work were recommendations by some.

The Implications and Conclusions section reflects study accomplishments and summarizes implications for community care coordination providers and stakeholders as well as the research community. It describes how the study process and results contribute to the field of standardizing performance measures for community care coordination – particularly for underserved populations. This section also describes efforts “moving forward” – what study sites are doing or planning in relation to enhancing their own impact in this field and a discussion about dissemination of this report.

IMPLICATIONS AND CONCLUSIONS


Study AccomplishmentsThe NIH-CCCPM project was a pilot study to develop and test new performance measures in community care coordination. The project was supportive of current health reform efforts and federal initiatives to reduce health disparities by improving health outcomes for at-risk populations.

The study involved a small number of diverse community-based sites. Among the elements of diversity were their size, location, setting, and pathways used. Common threads were their focus on community care coordination and use of or adaptation of the Pathways HUB Model. While more work is needed in this area, the results of this project have demonstrated the feasibility of performing data collection activities across diverse sites.

The project has addressed the lack of performance measures in community care coordination. The study’s use of CBPR and other scientific-based approaches to mesure development is a major contribution to the field of care coordination. Further, through this effort, we have assessed, to some extent, the usefulness of the measures in helping to informlocal quality improvement activities.

The project has implications that go far beyond the five partner sites because of the network outreach and expansion capabilities. Spanning out in concentric circles, the NIH-CCCPM project can have a major impact in terms of presence and visibility of the initiative.

Key points that we focused on in the study and in this report include:

Performance measurement is an essential ingredient for improving quality and reducing disparities. Communities working in collaboration with research institutions can help translate science around care coordination processes into real world practice. Use of performance measures can help identify key information that may be useful in creating alternative payment options for care coordination services.

Key Lessons Learned/Take Home Messages

Implications for Importance to Community Care Coordination Organizations Although community-based care coordination organizations are diverse with respect to populations served, service delivery and care coordination models, organizational structures, and leadership styles, a common value that is shared by these organizations is the commitment to quality improvement and providing clients with high quality services. The implementation of a performance measurement system is feasible in community care coordination organizations with minimal disruption in their daily work efforts. Community care coordination organizations already document, track, collect and analyze data for a number of purposes and these ongoing efforts are the stepping stones for building a standardized performance measurement system. The success of the NIH-CCCPM project demonstrates that community care coordination organizations

can contribute to a project of national significance where uniform data collection and participation in the development of standardized performance measures were required.

33IMPLICATIONS AND CONCLUSIONS


As a result of these accomplishments, community care coordination organizations have expanded their portfolios to include being research collaborators and innovators in service delivery. This experience adds to their collective credibility and perhaps expands opportunities for future funding sources, future collaborations such as participation in the CCCLN and long-term sustainability.

Implications for Research CommunityThe NIH-CCCPM project and its reported results, analysis and discussion in this report can benefit the research community in many ways.

The project contributed to the science of performance measurement by developing standardized metrics in community care coordination.

Using innovative CBPR principles and strategies, the researchers and community-based providers engaged in collaborative processes designed to define core elements of care coordination for systematic measurement. For example, we used a consensus process to identify essential domains (dimensions of performance) of the community care coordination. Through pilot testing the metrics across multiple sites, we assessed feasibility and provided a basis for benchmarking performance both within individual care coordination programs and across care coordination programs in multiple communities. The project team produced documentation tools that could help track outcomes-based care coordination services and performance-based financing of care coordination.

Moving ForwardWe hope this preliminary research study will facilitate adoption and implementation of performance measure development for community care coordination networks. Moreover, we envision that it will lead to further research and learning that will inform practice and build capacities in local communities.

Specifically, implementation of a demonstration study with a longer study timeline would enable further testing of the measures to assess:

The reliability and validity of the measures; The utility of the measures in improving service quality; and The utility of the measures in assessing patient experience.

The strengthening of care at the community level is an important element of the NIH-CCCPM effort. Community care networks have an important contribution to make to the healthcare reform and quality improvement efforts – and do so with measurable outcomes in ways that are cost effective.

Study Sites Additional Efforts – Expanding CapacityStudy sites are engaged in many efforts, several of which are in alignment with the NIH-CCCPM Project. They are expanding community care coordination services, broadening their geographic focus, analyzing participant needs differently, improving the way they track and evaluate data, continuing and expanding alliances and adding collaborative information technology tools. The summaries below represent only a few of the more recent activities of the study sites.


Community Health Access Project. CHAP is currently involved in helping the state of Ohio replicate the Pathways Community HUB Model for Medicaid beneficiaries in Appalachia. Ohio officials said the model was selected because it demonstrates improved outcomes and reduced costs.

“This initiative fits perfectly with the governor’s objectives to improve care coordination for vulnerable Ohioans, said Director Greg Moody of the Governor’s Office of Health Transformation. “This initiative fits perfectly with the governor’s objectives to improve care coordination for vulnerable Ohioans and to pay for value, not volume, in healthcare.”

Michigan Pathways to Better Health is another new venture that expands the reach of the CHAP Model. The Michigan Public Health Institute, partnering with the Michigan Department of Community Health and the Community Health Access Project received a grant award of $14,145,784 to enable the integration of community health workers (CHWs) into primary care teams in three Michigan counties. This “Pathways Community HUB” model will decrease hospitalizations and emergency department visits by improving adherence to therapy, improving ac-cess to primary care and increasing use of preventive care and support services. Over a 3-year period, the Michigan Public Health Institute will train over 231 people and hire 87 people to serve as community health work-ers, providing care self-management coaching, care navigation services, and care coordination services.

Rural And Urban Access To Health. During the course of the study, RUAH grew from one healthcare pathway (medication assistance) to providing five additional pathways. Additionally, RUAH created new reports to reflect the change from an activity-based model to an outcome-based model. Another effort is the development of human-interest stories and data to demonstrate RUAH services cost benefit for both reduced expenses, and improved health status.

Baylor Community Care. The Program Manager indicated that BCC is looking to expand the use of Community Health Workers in community care coordination roles. “This includes whether that’s facilitating transitional care like they do in the program we focused on in this study, or whether that’s expanding their use in chronic disease education and self-management training like we do in another of our programs.”

Lincoln E. D. Connections. Lincoln E. D. Connections is implementing Cluster Based Planning – a national behavioral health/substance abuse model that includes tracking resources according to diagnosis. According to the Program Manager, LEDC has incorporated this model, including its “wrap around” (behavioral/physical) feature into their pathway(s).

Access El Dorado. In September 2011, ACCEL was selected to become one of 15 best-practice examples in the use and integration of technology to improve health and healthcare for its residents. The collaborative received a $350,000 Model eHealth grant award from the University of California, Davis and the California Telehealth Network (CTN). The funds will be used to acquire eHealth technologies and telehealth equipment, provide training and manage the connection with the broadband system that CTN is now establishing around the state.

DisseminationThis Technical Report serves as a key component of the NIH-CCCPM research project’s overall dissemination plan. Dissemination is the process of communicating research findings to stakeholders so that the evidence can be used for change. Dissemination is also an important step for increasing the knowledge base in both research and practice communities. An overarching goal of the NIH-CCCPM dissemination planning was to ensure that the development, preservation, management, and documentation of project purpose, methodology, and outcomes were maintained and shared with the community. The NIH-CCCPM project’s contributions to the research litera-ture and to the development of innovative data collection tools, and other products form a framework to support ongoing learning and capacity-building in community care coordination.

35IMPLICATIONS AND CONCLUSIONS


As a result of the CBPR framework for this project, the dissemination planning process was designed to be collaborative and to help impact and influence service planning for potential users and current beneficiaries of medical and social services, as well as increase opportunities for partnership development among community care coordination organizations. In this vein, the NIH-CCCPM technical report will be distributed to key stakeholders in-cluding an expanded network of local and national community care coordination providers, health care providers, consumers, policymakers, professional associations, and researchers. Stakeholders will have the opportunity to review the study findings and perhaps adopt some of key performance measures to their organizations or inform other organizations about these efforts.

The dissemination plan is vastly important. The framework emanating from the CCCPM dissemination plan can be utilized as a roadmap for other research initiatives and by stakeholders involved in planning culturally competent strategies for healthcare delivery and partnership development. Hopefully, the professional community, who will take a lead in performance measure development/implementation, and the governing and funding bodies, who support them, and, critically, the potential users and beneficiaries of services will benefit from the work that we do.

In ConclusionIn a climate of increasing scrutiny, systemic reforms and fiscal constraints, the public and private health sector is being required to provide evidence for the effectiveness of its interventions and the achievement of enhanced quality of life outcomes for the community. An inherent challenge is to obtain and present this evidence while acknowledging the substantial role played by the social and environmental determinants of health. The NIH-CCCPM project supports current health reform efforts to reduce health disparities by improving health outcomes for at-risk populations. In this regard, the grant award provided an opportunity to build upon the Westat research collaborative team’s prior work with the CCCLN.

In light of the short time frame allocated for the study, the NIH-CCCPM project was charged with the daunting task of creating new, and newly validated, measures for assessing the impact of community-based care coordination on health and well-being—in addition to beginning to build an evidence base. Our study underscored the premise that to achieve an authentic participatory research approach, and viable quality data, project stakeholders need to be ‘partners’ in the process of developing performance indicators. This configuration must be undergirded by sound research methodology, study protocols, and appropriate data collection systems.

This project established a foundation for broader investigative study on the utility of the performance measures to assess progress made in quality improvement and disparities reduction efforts. Furthermore, the results of this project addressed the dearth of performance measures available for use by community-based care coordina-tion programs. These measures will continue to be essential in quality improvement efforts for community care coordination. The unique application of CBPR methods to the development of performance measures will increase the likelihood of the adoption of community care coordination performance measures in the field. By engaging community-based care coordination organizations in this project and study existing care coordination resources (such as the Pathways Community HUB Mode, the scientific community will have a better understanding of what works with those who need help the most. Given a dearth of literature in this regard, more scientific and evidenced-based data is needed to support such claims. It is important to conduct in-depth research on what makes the best systems successful and disseminate what is learned. Since socioeconomic, geographical, and related societal determinates have a bearing on the efficacy of community care networks, it is envisioned that initiatives such as the NIH-CCCPM project can be transformative in bringing about needed reforms in the healthcare industry.

This is a summary of some of characteristics of the NIH-CCCPM study project sites. Descriptions are primarily limited to those services provided as part of their involvement in community care coordination. Each of the sites also provides many other services and carries out many other activities.

APPENDIX


Community Health Access ProjectThe Community Health Access Project (CHAP) is a nonprofit organization that was started in Mansfield, Ohio in 1999 by Mark Redding, MD, and Sarah Redding, MD. CHAP’s mission is “To eliminate health and social disparities in our community by finding those at risk, connecting them to care and measuring the outcomes. We believe all communities can be transformed through the work of community health workers and the creation of community HUBs – an accountable care coordination delivery system.”

Numbers Served. CHAP serves approximately 1,200 individuals, annually – 600 each in Richland and Knox Counties. Clients include pregnant and postpartum women and children from age 0 to 3, with an emphasis on Medicaid eligible populations.

Outcome Measures. Key outcome measures include the program’s impact on birth weights, prenatal visits and miscarriages. Data from more than 300 clients shows a 30 percent reduction in the risk for low-weight births in Richland County and the number of at-risk pregnant women served increased from 19 to 146 in 1 year, a level that has been maintained over 3 years.

Budget, Staff and Funding. Currently, the budget for Richland and Knox County combined, is approximately $800,000. This supports the following staff – Executive Director, COO/Fiscal Director and six full-time equivalent Community Health Workers. Volunteer personnel, including Mark Redding, MD, serve advisory and support capacities. About 40-45 percent of the program comes from payments for meeting benchmark interventions and outcomes. Funding comes from Medicaid managed care and state-funded maternal and child health programs, state grants, United Way, and foundations.

Community and Patient Dynamics. Because the NIH-CCCPM project focused on Richland County, community characteristics are reported for that jurisdiction. The County is rural in nature, with a predominantly White population (87.9%). The highest percentage of racial minorities are Blacks (9.4%) followed by Asians (.7%). Only 1.5 percent of the population is of Hispanic/Latino origin.

Richland County has more children without insurance than any metropolitan county in Ohio. In addition to health-related needs, according to the CHAP CEO, Sarah Redding, MD., transportation, housing, jobs, and a “steady food supply” are problems for residents of the County and the situation seems to have worsened over the last several years.

Mark Redding, MD, FAAP,Co-Founder, CHAP(419) 525-2555

Sarah Redding , MD, MPH,Director, CHAP(419) 525-2555

FOR MORE INFORMATION

Community Health Access Project, 35 North Park Street, Suite 132 Mansfield, Ohio 44902http://www.chap-ohio.net

39APPENDIX

APPENDIX

Rural and Urban Access to HealthEstablished in 2000, Rural and Urban Access to Health (RUAH), is a collaborative program sponsored by St. Vincent Health, which is Indiana’s largest healthcare employer. RUAH provides safety net services in eight counties in central Indiana.

The Purpose of RUAH is to connect friends, family and neighbors to a comprehensive, integrated delivery network of health, human, and social services resulting in improved access and removal of barriers to needed resources. Main goals of the program include increased access to medical and social services and reduced inappropriate care. The program employs field-based workers to coordinate and integrate care, provide outreach and education, and facilitate access to healthcare and prescription drugs for the growing at-risk population.

Numbers Served. In Madison County, where the NIH-CCCPM study took place, approximately 1,400 persons are served annually.

Outcome Measures. Key outcome measures include the program’s impact on chronic disease management and ED utilization. In fiscal year 2010, RUAH assisted 5,695 clients with 9,412 referrals to local health, human, and social service agencies. RUAH medication coordinators assisted community members in accessing 10,867 low/no cost medications valued at $5,524,459.

Budget, Staff and Funding. The cost of running the eight-county program is estimated at $1.2 million annually, as of November 2011. Costs include salaries and a monthly fee for the prescription assistance software. Staffing includes a director; a coordinator for all access workers; an operations manager, language access workers (who organize all of the training, assessment, and process improvement initiatives); 15 health access workers; and a large number of volunteers. Funding is primarily achieved through the parent organization, St. Vincent Health, through its local healthcare ministries. Each participating hospital is responsible for paying access workers.

Community and Patient Dynamics. While RUAH operates in eight counties, for purposes of this report, commu-nity characteristics are derived from Madison County, as this was the jurisdiction used for the NIH-CCCPM study. The County has a predominantly White population (89.1%) with 8.4 percent of the community being Black, and .4 percent being either Asian or Alaska Native/American Indian. Hispanic/Latinos of any race represent just 3.4 percent of the population.

The majority of RUAH participants are uninsured, underinsured and/or low income (under 200% FPL). There is an overrepresentation of Hispanic/Latino participants compared to the community. The patient population also includes migrants, persons with limited or no English proficiency, and transients. RUAH System Director, Sherry Gray, indicates that several medical, social, and financial problems are faced by community members. These include the inability to get a doctor or medication, no insurance, lack of access or connection to social ser-vices, insufficient funds for visits or co-payments, transportation, and (outside of the ED) access to medical care, particularly specialty care.

Sherry E. Gray, MA,System Director(317) 583-3211

Susie Dittman, MHA,Operations Facilitator(317) 583-3213


Rural and Urban Access to Health (RUAH) | St. Vincent Health, 10330 N. Meridian St., Suite 415 Indianapolis, IN 46290http://www.stvincent.org/Community-Connections/Programs/Advocacy-Support-Programs/ Rural-and-Urban-Access-to-Health.aspx


Baylor Community CareThe Baylor Health Care System served more than 2.8 million people in 2011; Baylor Community Care (BCC) is a project of that system. BCC served as a study site in the Dallas-Fort Worth “metroplex” area of Texas. BCC seeks to provide quality health care and a compassionate medical home to patients and families that do not have access to a primary care physician. A primary goal is that underserved patients will experience less health disparities and require less frequent utilization of hospital services.

Community Health Workers (CHWs) are deployed within four of Baylor’s hospitals to identify uninsured patients who require ongoing care following discharge. They provide health education, health system navigation and patient advocacy, including connections to medical home clinics in the BCC network.

Numbers Served. In 2011-2012, the community care navigation program worked with 1,200 patients, and successfully connected 806 patients to a medical home. The BCC clinics that become medical homes for these patients served 12,000 patients.

Outcome Measures. Director Adam Chabira indicates, “We connect at a little over 50 percent of patients to medical homes within 14 days of discharge.” Once patients started using the medical clinics, 17 percent had fewer and shorter hospital stays.

Budget, Staff and Funding. The budget for the program (FY 2012-2013) is approximately $6.5 million, with $5.7 million coming from the Baylor Health Care System and the remainder coming from grants and in-kind services (such as the overhead at the clinics). The budget including expenses for the 10 community clinics and community care navigation staff at four of the Baylor hospitals. Staffing includes 14 full-time equivalent physicians and nurse practitioners and 10 to 12 community health workers, four of which are community navigators. The program also uses volunteers in various capacities.

Community and Patient Dynamics. BCC serves the 12 county Dallas-Fort Worth Arlington Metropolitan Statistical Area (MSA). The 2010 Census indicates that 65.3 percent of the population was White, 15.1 percent were African-American, 5.4 percent were Asian, 0.7 percent was American Indian or Alaska Native, and .1 percent was Native Hawaiian or Other Pacific Islander. Hispanic or Latino origin was a characteristic of 27.5 percent of the population. In this MSA, 14 percent of residents lacked insurance according to 2006-2010 American Fact Finder data.

Most BCC participants are low-income and are uninsured. Transportation, money for co-payments or prescriptions, and access to specialty care are significant problems for BCC clients, according to Director Chabira.

Adam Chabira, MHA,Director, BCC(972) 860-8681

James Walton, DO, MBA,VP of Network Performance for Accountable Care Baylor Health Care System(214) 265-3726


Baylor Community Care Baylor | Health Care System8080 North Central Expressway, Suite 1700, LB83 Dallas, TX 75206

41APPENDIX

APPENDIX

Lincoln E.D. ConnectionsLincoln E. D. Connections (LEDC) is a collaborative program of Lincoln Nebraska’s Bryan Medical Center and Saint Elizabeth Regional Medical Center. Initiated in 2005, the purpose of ED Connections is to serve the community’s most vulnerable patients who repeatedly use the emergency department (ED) for nonemergency purposes. The primary goal of the program is to eliminate barriers to health care, such as transportation, medication costs, financial difficulties, Limited English Proficiency, and difficulties navigating health systems.

ED Connections case managers work with clients in developing a personal care plan designed to meet the most immediate needs of the client first. Services are provided typically over a 3- to 12-month period, during which participants might follow one or more different pathways.

Numbers Served. Annually, approximately 4,500 individuals qualify for enrollment and approximately 500 to 600 are served.

Outcome Measures. LEDC participants demonstrate less nonemergent ED use, attain enrollment in medical homes, attain prescription medication assistance, and report improved self-care and health functioning. For clients in FY2011, the project reports: 100 percent were enrolled in medical homes, 81 percent kept their first appointment with the physician, 85 percent received prescription assistance (over a 3-year period, saving patients more than $34,000 in drug costs), and 67 percent reported improved self-care and overall health.

Budget, Staff and Funding. Annual program costs are approximately $265,000, primarily covering the salaries and benefits of case managers. Each hospital employs one social worker and one registered nurse as case managers. Each case manager handles roughly 30 clients at a time. Operational overhead is covered by the two hospital systems. About $15,000 annually is needed to provide minimum barrier relief including medication assistance, help with co-pays, housing assistance, utility bills, and transportation to medical appointments and other emergency needs. These funds have come from private donations or grants secured by the hospital foundations.

Community and Patient Dynamics. For the LEDC program that was part of the NIH-CCCPM study, the patients are primarily from the City of Lincoln, Nebraska, the state capitol. According to 2010 census data, the racial makeup of the city was 86.0 percent White, 3.8 percent African American, .8 percent Native American, 3.8 percent Asian, 0.1 percent Islander, and 3.0 percent from two or more races. Hispanic or Latino of any race was 6.3 percent of the population.

Approximately 80 percent of LEDC clients have behavioral health or substance abuse issues. In addition, 70 percent of those served are uninsured or underinsured and one-fourth is homeless. Currently, the majority of clients are predominantly White women age 25 – 45. Health-related needs and gaps include access to medical care, insurance co-pays, prescription medication assistance and access to specialty care, including mental health treatment. Other barriers to care, according to the LEDC Program Director, Tom Hoover, are lack of transportation, housing, sufficient food supplies, and childcare.

Tom Hoover, RN MBA-HCMLEDC Program Manager(402) 481-4165(402) 219-5205

Jean Stilwell, M.A.,Resource Development Coordinator(402) 219-7051


Bryan Medical Center & Saint Elizabeth Regional Medical Center Emergency Departments2300 South 16th St., Lincoln, NE 68502www.bryanlgh.com and www.saintelizabethonline.com

Lincoln E. D. Connections


Access El DoradoAccess El Dorado, popularly known as ACCEL, is a community-wide collaborative among public and private agencies in El Dorado County California. Formed in 2004, ACCEL’s mission is to (1) seek to create healthier communities, especially within vulnerable populations, (2) identify specific barriers (especially access!) to a healthy community and (3) develop systematic improvements that include all partners and serve their entire community.

Among its initiatives are seven cross-agency care pathways using community health workers to help low-income individuals and families obtain health insurance, navigate the health care system, access appropriate medical and mental health services, and learn related self-care behaviors.

Numbers Served. In 2011, over 1,200 patients were served across seven pathways.

Outcome Measures. Key outcome measures include the program’s impact on newborn andwell-child visits to primary care physicians, immunizations, mental health pediatric consultations and access to specialty consultations, as well as obtaining and retaining health insurance. Since the program’s inception, more than 6,600 previously uninsured children have obtained coverage. More than 3,300 children have been helped with connections to healthcare resources. Establishment of a medical home, achieved by 86 percent of the children referred for that need, resulted in a 43 percent reduction in subsequent Emergency Department costs.

Budget, Staff and Funding. The minimum annual budget is approximately $250,000. This covers a full-time pro-gram director, hourly stipends for two physician champions, a part-time supervising health education coordinator, and two bilingual community workers. It also covers licensing and maintenance costs (but not upgrades/changes) for ACCEL’s web-based care coordination system. ACCEL funding has come from multiple sources including AC-CEL partner contributions, First Five, foundations, and grants.

Community and Patient Dynamics. El Dorado County, California is located in the east-central region of the state. A primarily rural county, two major community areas, the Western Slope and South Lake Tahoe are bisected by the Sierra Nevada mountain range. Race and ethnic data for the county (2011) reflect 90.4 percent White, 3.7 per-cent Asian, 1.4 percent American Indian and Alaska Native, .9 percent African-American, and 3.3 percent of the population reporting two or more races. Persons of Hispanic or Latino origin are characteristic of 12.3 percent of the population.

Similar to other rural areas, El Dorado County residents often suffer disproportionately from chronic illness and overall poor health. Other problems El Dorado County residents face is having no insurance or being underinsured, having no primary care physician, and limited access to necessary dental, behavioral health, mental health, and specialty services. Additional barriers to care for ACCEL patients include transportation, food security, home-lessness, and communication gaps (i.e., Internet access, cell phone minutes). Access to culturally competent resources is also a problem.

Christine Sison, MS.,Program ManagerAccess El Dorado (ACCEL)[email protected]

Greg Bergner, MD,ACCEL Physician [email protected]


County of El Dorado, Department of Health Services – Public Health Division670 Placerville Drive; Suite 1B Placerville, CA 95667http://www.acceledc.org

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ENDNOTE CITATIONS1 United Healthcare Services, Inc. (2007). The measurement of health care performance: A primer from the Council On Medical Specialty Societies. Chicago, IL: Council on Medical Specialty Societies/ United Healthcare Services, Inc.2 U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. (N.D.). Disparities (Paragraph 5, Healthy People 2020). Washington, DC: Author. Available at http:// healthypeople.gov/2020/about/Disparities About.aspx. (Accessed 8/12/12).3 World Health Organization. (2009). Social determinants of health. Available at http://www.cdc.gov/minorityhealth/OMHHE.html. (Accessed 8/19/12).4 Centers for Disease Control and Prevention, Office of Minority Health and Health Equity. (2012). Mission. About CDC’s Office of Minority Health & Health Equity (OMHHE). Available at http://www. cdc.gov/minorityhealth/OMHHE.html. (Accessed 8/19/12).5 McDonald, K.M., Schultz, E., Albin, L., Pineda, N., Lonhart, J., Sundaram, V., Smith-Spangler, C., Brustrom, J., and Malcolm, E. (2011). Chapter 2. What is care coordination? In Care coordination measures atlas. Rockville, MD: Agency for Healthcare Research and Quality. Available at http://www.ahrq.gov/qual/careatlas/ careatlas2.htm. (Accessed 8/19/12).6 Center for Pathways Community Care Coordination, Rockville Institute. (N.D.). Defining community care coordination. Available at http://www.rockvilleinstitute.org/CPCCC/mission.asp. (Accessed 8/19/12).7 Agency for Healthcare Research and Quality. (2011). Feature story: Community hubs ensure better care for the most vulnerable. Available at http://www.ahrq.gov/research/jun11/0611RA1.htm. (Accessed 8/19/12).8 Health Care Innovations Exchange. (N.D.). Connecting those at risk to care. Available at www.innovations.ahrq.gov/ articles.aspx.9 Community Health Access Project. (N.D.). Chapter 4. The community setting (p. 18). Pathways: Building a community outcome production model. (p. 18). Mansfield, OH: Author. Available at http://jfs.ohio.gov/ohp/bcps/OHMedAdvComm/ documents/072104_mcac_Handouts.pdf. (Accessed 8/19/12).10 U.S. Department of Health and Human Services. (2011). Roadmap to better care transitions and fewer readmissions.Available at http://www.healthcare.gov/compare/partner-ship-for-patients/ safety/transitions.html.11 National Institutes of Health, Office of Behavioral and Social Sciences Research. (N.D.). Community-based participatory research. Available at http://obssr.od.nih.gov/scientific_areas/ methodology/community_based_participatory_research/index. aspx. (Accessed 8/18/12).12 Federal Register. (2002, June 21). Federal Register Notice: Department of Health and Human Services. Agency for Healthcare Research and Quality. Request for suggestions on community- based participatory research. 67(120), 42262-42264. Available at http://archive.ahrq.gov/fund/fr/fr062102.htm. (Accessed 8/19/12).13 Health Care Innovations Exchange. (2012). Community Care Coordination Learning Network. Available at http://www. innovations.ahrq.gov/innovations_quality-tools.aspx?taxlink=&find =Community+Care+Coordination+Learning+Network ( Accessed 8/19/12).14 Agency for Healthcare Research and Quality. (2010). Community Care Coordination Score Card: Raising the bar across communities (slide Presentation from AHRQ 2010 Annual Conference). Available at http://www.ahrq.gov/about/annualconf10/gray_overall_ reddington_smith/Over-all.HTM. (Accessed 8/19/12).

15 Center for Pathways Community Care Coordination, Rockville Institute. (2012). Center for Pathways Community Care Coordination. Available at http://www.rockvilleinstitute.org/ CPCCC/Index.asp. (Access 8/17/12).16 National Institutes of Health. (N.D.). NIH ARRA funding: Summary of ARRA-specific funding opportunities. Available at http://report. nih.gov/recovery/NIH_ARRA_Funding.pdf. (Accessed 8/19/12).17 National Advisory Council on Minority Health and Health Disparities. (2010). Minutes of February 23, 2010, meeting (p.4). Available at www.nimhd.nih.gov/about_ncmhd/advise.asp.

18 U.S. Department of Health and Human Services. (N.D.). HHS action plan to reduce racial and ethnic health disparities. A nation free of disparities in health and health care. Available at minorityhealth.hhs.gov/npa/files/Plans/HHS/HHS_Plan_complete.pdf.19 U.S. Department of Health and Human Services. (N.D.). Read the law (Affordable Care Act). Available at http://www.healthcare.gov/ law/full/. (Accessed on 08/19/12).20 Engelberg Center for Health Care Reform at the Brookings Institute and Dartmouth Institute for Health Policy and Clinical Practice. (2011). Accountable care organization toolkit. Available at https:// xteam.brookings.edu/ bdacoln/Documents/ACO%20Toolkit%20 January%202011.pdf. (Accessed 8/08/12).21 National Institutes of Health. (N.D.). Project information. Available at http://projectreporter.nih.gov/project_infodetailscfm?aid=794199 9&icde=0. (Accessed 8/17/12).22 Westat. (2012). www.Westat.com.23 Matrix Knowledge. (2012). www.matrixknowledge.co.uk.24 This study used the classification of “domains” as depicted in the National Quality Measures Clearinghouse (NQMC). The classification of measures into domains within NQMC is based on a number of rationales regarding dimensions of performance related to clinical health care delivery and population health within which measures can be developed. Domain descriptions are available at http://www.qualitymeasures.ahrq.gov/about/ domainframework.aspx. (Accessed 8/19/12).25 Patient-Centered Primary Care Collaborative. (2010). Transforming patient engagement: Health IT in the patient centered medical home. A compendium of resources from the Patient Engagement task force of the Patient-Centered Primary Care Collaborative. (p. 5). Available at www.pcpcc.net/files/pep-report.pdf. (Accessed 8/17/12).26 Series of telephone interviews, calls, and electronic communications with five study sites in the NIH-CCCPM project. Dates from July 10 through August 15, 2012. Conducted by Trudy C. Kilian and Madeline Darden.27 Michigan Public Health Institute. (2012). Model eHealth Community Awards announced. Available at www.mphi.org%2ffiles%2fnewsev ents%2fCMSAwardJune2012.pdf. (Accessed 8/12/12).

28 California Telehealth Network. (N.D.). Model eHealth Community Awards announced: 15 Communities receive funding for eHealth development. Available at http://www.caltelehealth.org/post/ model-ehealth-community-awards-announced. (Accessed on 08/17/12).

Community Care Coordination Performance Measures