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The American Journal of Managed Care September 2015
Do Patient or Provider Characteristics Impact Management of Diabetes?
Erin S. LeBlanc, MD, MPH; A. Gabriela Rosales, MS; Sumesh Kachroo, PhD; Jayanti Mukherjee, PhD; Kristine L. Funk, MS; and Gregory A. Nichols, PhD
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S. Yousuf Zafar, MD, MHS; Fumiko Chino, MD; Peter A. Ubel, MD; Christel Rushing, MS; Gregory Samsa, PhD; Ivy Altomare, MD; Jonathan Nicolla, MBA; Deborah Schrag, MD; James A. Tulsky, MD; Amy P. Abernethy, MD, PhD; and Jeffery M. Peppercorn, MD, MPH
Building Upon the Strong Foundation of National Healthcare Quality
Charles N. Kahn III, MPH, President and CEO, Federation of American Hospitals
Improving Partnerships Between Health Plans and Medical Groups
Howard Beckman, MD, FACP, FAACH; Patricia Healey, MPH; and Dana Gelb Safran, ScD
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Innovative Approach to Patient-Centered Care Coordination in Primary Care Practices
Robin Clarke, MD, MSHS; Nazleen Bharmal, MD, PhD; Paul Di Capua, MD, MBA; Chi-Hong Tseng, PhD; Carol M. Mangione, MD, MSPH; Brian Mittman, PhD; and Samuel A. Skootsky, MD
Developing Evidence That Is Fit for Purpose: A Framework for Payer and Research Dialogue
Rajeev K. Sabharwal, MPH; Jennifer S. Graff, PharmD; Erin Holve, PhD, MPH, MPP; and Robert W. Dubois, MD, PhD
Predicting Adherence Trajectory Using Initial Patterns of Medication Filling
Jessica M. Franklin, PhD; Alexis A. Krumme, MS; William H. Shrank, MD, MSHS; Olga S. Matlin, PhD; Troyen A. Brennan, MD, JD, MPH; and Niteesh K. Choudhry, MD, PhD
Reply to "Transforming Oncology Care": Advancing Value, Accessing Innovation
Rebecca Paradis, MPA
Payer Source Influence on Effectiveness of Lifestyle Medicine Programs
Joseph Vogelgesang, BS; David Drozek, DO; Masato Nakazawa, PhD; Jay H. Shubrook, DO
High-Risk Centers and the Benefits for Lower-Risk Transplants
Schelomo Marmor, PhD, MPH; James W. Begun, PhD; Jean Abraham, PhD; and Beth A. Virnig, PhD, MPH
Targeting a High-Risk Group for Fall Prevention: Strategies for Health Plans
Lee A. Jennings, MD, MSHS; David B. Reuben, MD; Sung-Bou Kim, MPhil; Emmett Keeler, PhD; Carol P. Roth, RN, MPH; David S. Zingmond, MD, PhD; Neil S. Wenger, MD, MPH; and David A. Ganz, MD, PhD
Socioeconomic Disparities Across Ethnicities: An Application to Cervical Cancer Screening
Brendan Walsh, PhD; and Ciaran O'Neill, PhD

Innovative Approach to Patient-Centered Care Coordination in Primary Care Practices

Robin Clarke, MD, MSHS; Nazleen Bharmal, MD, PhD; Paul Di Capua, MD, MBA; Chi-Hong Tseng, PhD; Carol M. Mangione, MD, MSPH; Brian Mittman, PhD; and Samuel A. Skootsky, MD
Description of a program embedding nonlicensed care coordinators in primary care practices including training, interventions, and the effect of the program on emergency department visits.

Objectives: Although care coordination is an essential component of the patient-centered medical home structure, current case manager models have limited usefulness to population health because they typically serve a small group of patients defined based on disease or utilization. Our objective was to support our health system’s population health by implementing and evaluating a program that embedded nonlicensed coordinators within our primary care practices to support physicians in executing care plans and communicating with patients.

Study Design: Matched case-control differences-in-differences.

Methods: Comprehensive care coordinators (CCC) were introduced into 14 of the system’s 28 practice sites in 2 waves. After a structured training program, CCCs identified, engaged, and intervened among patients within the practice in conjunction with practice primary care providers. We counted and broadly coded CCC activities that were documented in the intervention database. We examined the impact of CCC intervention on emergency department (ED) utilization at the practice level using a negative binomial multivariate regression model controlling for age, gender, and medical complexity.

Results: CCCs touched 10,500 unique patients over a 1-year period. CCC interventions included execution of care (38%), coordination of transitions (32%), self-management support/link to community resources (15%), monitor and follow-up (10%), and patient assessment (1%). The CCC intervention group had a 20% greater reduction in its prepost ED visit rate compared with the control group (P <.0001).

Conclusions: Our CCC intervention demonstrated a significant reduction in ED visits by focusing on the centrality of the primary care provider and practice. Our model may serve as a cost-effective and scalable alternative for care coordination in primary care.
Am J Manag Care. 2015;21(9):623-630
Take-Away Points
We implemented and evaluated a program that augmented the primary care practice’s role as the medical home by embedding nonlicensed personnel to coordinate care. Our comprehensive care coordinators (CCCs) were trained within our system, were co-located with the primary care physicians, served patients from all payers, and received support from centrally based licensed personnel. 
  • In 1 year, CCCs touched nearly 14,000 unique patients, primarily executing the physician’s plan of care or coordinating transitions. 
  • We found a 20% year-over-year greater reduction in emergency department visits among the patient population attributed to the 14 practices with CCCs compared with 14 practices without.
The passage of the Affordable Care Act (ACA) reinforced primary care practice redesign as the main element for providing optimal population health.1 This redesign takes many forms, but the term “patient-centered medical home” (PCMH) has come to describe the ideal practice.2-4 The PCMH is central to healthcare reform, with national organizations (eg, National Committee for Quality Assurance, URAC) having certified thousands of practices as PCMHs and some state programs providing financial rewards for acquiring certifications.5-7 However, the last decade of experience demonstrates that PCMH transformation is difficult, disruptive, and expensive.6,8 Although PCMH demonstrations have shown improved outcomes, real-world applications of PCMH practice redesign have inconsistently improved quality and utilization metrics.9-12 Our University of California at Los Angeles health system (UCLA Health), consisting of over 28 primary care practice sites, developed a transformation model to implement practice redesign swiftly and broadly across our network. Our approach included aspects from many PCMH domains, centering on an innovative approach for coordinating patient care.
Care coordination is a core component of the PCMH model13 and was one of the “7 Joint Principles” promulgated by the primary care societies.14 Most of the literature on PCMH care coordination describes programs oriented around patients who are high-risk utilizers, have specific medical conditions, or are discharged from the hospital.15-19 These programs are frequently delivered from an external administrative unit separated from the primary care ambulatory practice, such as by the patient’s health plan, a health maintenance organization (HMO), or an intensive ambulatory practice.20,21 Care coordination models without a tight linkage to primary care did not meet our health system’s priorities of providing population-based care management that strengthens the patient–primary care physician (PCP) relationship.
In our PCMH model, a comprehensive care coordinator (CCC) is embedded in each practice with the flexible job role of providing additional support to any patient who needs it within the practice’s panel. Some have proposed this role as part of the PCMH model, and we innovatively filled this role with nonlicensed staff instead of case managers, social workers, or counselors.22 These CCCs extend PCPs’ reach by addressing barriers to coordinated care through short- and long-term relationships with patients. Our CCCs act more as patient navigators than health coaches, as the emerging literature differentiates the roles of nonlicensed personnel.23,24 In contrast to typical navigators, CCCs perform this function as part of the care team by reviewing the electronic medical record (EMR) system and executing care plans. Our care coordination model prioritizes higher-need patients with unmet medical or social needs, but moves away from empaneling patients solely by disease or risk of future utilization. Whereas UCLA Health has population-based capitation and risk-sharing contracts, many patients are in traditional fee-for-service plans and the CCCs support patients irrespective of insurance type.
In this paper, we describe the structure of our care coordination program, including the CCC’s training, typical work flow, and number and types of interventions delivered over 1 year. We hypothesized that providing care coordination through embedded, nonlicensed personnel to a broad and heterogeneous group of patients would allow our practices to deliver more complete primary care. We tested this hypothesis by examining emergency department (ED) utilization between practices with and without a CCC.

Program Description
We embedded 1 CCC per practice in 14 of the 28 primary care sites within UCLA Health. CCCs were not required to have specific healthcare training or licensure; instead, we sought prior experience functioning in complex organizations, acting independently to solve problems, and participating within busy teams. Many had been medical assistants, military medic or corpsman, emergency medical technicians, or community health workers.
Because they did not have formal licensure and training, 2 types of support were provided to promote effective and high-quality patient care. First, the CCCs completed approximately 40 hours of initial training under a case manager and licensed social workers. The curriculum included topics on problem solving, patient engagement, post acute–care planning, socio-behavioral risk assessment, physician communication, community resources, and health plan navigation. This introduction was reinforced through new CCCs shadowing a veteran for 2 weeks and then through case-based problem solving at biweekly, 2-hour CCC conferences. The second source of support for CCCs was a centralized team of more highly trained personnel that consisted of an RN program director, a nurse case manager and a licensed clinical social worker. These individuals were available telephonically to answer complex questions, provide consultation for complex case management needs, or to perform medical interventions, such as home visits, that require licensure and training. We had a ratio of approximately 1 licensed personnel to 7 CCCs.
CCCs identified patients in need of coordination (patient identification), engaged in outreach to patients (patient engagement), and performed 1 or more interventions usually during a time frame of the next several days to weeks depending on the need (Figure 1). While all patients within the practice’s panel qualified for a CCC intervention, 3 categories of patients were identified to receive targeted efforts: patients recently in an acute care setting (ED or hospital), patients with high utilization rates or high-risk scores, and patients directly referred by the primary care provider. CCCs identified patients in these categories through regular automated reports and registries, structured huddles with the care team, or informal communication with PCPs. Each practice integrated its CCC into the PCMH team in different ways, but at minimum, the main touch point was a CCC–PCP daily huddle with CCCs followed by coordination with the practice’s front- and back-office staff (electronically or in-person) to define each patient’s needs. CCCs reached out to patients directly, either by phone or in person, reviewed the patient’s medical record, and performed an informal assessment of barriers to care. Based on this assessment, CCCs performed 1 or more interventions in the following categories: coordination of transitions, execution of care plan, monitoring and follow-up between visits, linkage to community resources, and/or patient assessment. The decision to “discharge” a patient from the CCC’s list was made by the PCP–CCC dyad, not by centrally defined criteria. CCCs documented in an internally developed online Patient Care Coordination System (PCCS); initially, PCCS was not linked to UCLA’s EMR, but subsequently, copies of PCCS documents were automatically ported over.
Setting and Implementation
Among the primary care practices within UCLA Health, most are traditional community-based practices with full-time clinicians; only 3 are academic with trainees. These practices include family medicine, internal medicine, internal medicine-pediatric, and geriatric physicians. The number of PCPs in these practices ranged from 3 to 11; however, to ensure co-location, 1 CCC was embedded in each practice. CCCs were introduced into the intervention sites in 2 waves: wave 1 consisted of 5 practices starting in May 2012 and wave 2 consisted of 9 practices starting in November 2012. The first wave was considered a 6-month pilot phase that helped shape the implementation process and the CCC work flow for the second wave. The control sites were the remaining 14 practices, which did not receive a CCC.
Program Evaluation and Analysis
We tabulated the total number of CCC “touches” and unique patients touched in the PCCS documentation system from May 2012 to July 2013. A CCC touch was defined as an encounter that a) contributed to the development and/or implementation of a plan of care for a patient or family and b) was documented in PCCS. A coding system to categorize CCC touches was adapted from a systematic review of care coordination published by the Agency for Healthcare Research & Quality,25 literature on case management, discussions with CCCs, and an exploratory review of the PCCS database. Touches were then classified into 5 broad categories based on manual review of the first full year of PCCS records for the wave-1 practices. Five coders, in total, coded all touches with a high inter-rater reliability (κ = 0.89).
We evaluated the impact of the CCC intervention on ED utilization at the practice level. Although CCCs were available to all patients, we restricted the population used for the evaluation to patients for whom we had full data capture of ED visits: patients in the HMO insurance plan delegated to our medical group. ED visits were identified through encounters at our hospitals’ EDs or through paid claims for visits at external facilities. A visit-based attribution rule was used to assign a patient to a PCP, so only patients with at least 1 PCP visit during either the pre- or post time periods were included.
We limited our evaluation to wave-2 practices compared with the 14 control practices that did not have a CCC. The wave-1 practices were not included on account of several differences from the other practices: wave 1’s mean age was statistically higher as it included our only geriatrics practice, the time period for wave 1 was different, and wave 1 was seen as a pilot. ED visit rates were calculated for the intervention and control sites based on the 12 months prior to and after the introduction of CCCs into the practices. A negative binomial multivariate regression model was used to test the effect of being in a CCC practice on ED utilization. The models controlled for baseline ED visit rate, age, gender, and risk adjustment factor score (RAF)—a payment modifier used by CMS and a marker of medical complexity. Significance was based on P <.05. We also calculated the cost savings for payers accounted by any averted ED visits.
We received UCLA Institutional Review Board exemption for this quality improvement study.

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