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The American Journal of Managed Care January 2015
Disease-Modifying Therapy and Hospitalization Risk in Heart Failure Patients
Fadia T. Shaya, PhD, MPH; Ian M. Breunig, PhD; and Mandeep R. Mehra, MD, FACC, FACP, FRCP
Frequency and Costs of Hospital Transfers for Ambulatory Care-Sensitive Conditions
R. Neal Axon, MD, MSCR; Mulugeta Gebregziabher, PhD; Janet Craig, PhD, RN; Jingwen Zhang, MS; Patrick Mauldin, PhD; and William P. Moran, MD, MS
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A. Mark Fendrick, MD, and Michael E. Chernew, PhD Co-Editors-in-Chief, The American Journal of Managed Care
Value-Based Insurance Design: Benefits Beyond Cost and Utilization
Teresa B. Gibson, PhD; J. Ross Maclean, MD; Michael E. Chernew, PhD; A. Mark Fendrick, MD; and Colin Baigel, MBChB
Changing Physician Behavior: What Works?
Fargol Mostofian, BHSc; Cynthiya Ruban, BSc; Nicole Simunovic, MSc; and Mohit Bhandari, MD, PhD, FRCSC
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Raina M. Merchant, MD, MSHP; Kristen Finne, BA; Barbara Lardy, MPH; German Veselovskiy, MPP; Casey Korba, MS; Gregg S. Margolis, NREMT-P, PhD; and Nicole Lurie, MD, MSPH
Relationship of Diabetes Complications Severity to Healthcare Utilization and Costs Among Medicare Advantage Beneficiaries
Leslie Hazel-Fernandez, PhD, MPH; Yong Li, PhD; Damion Nero, PhD; Chad Moretz, ScD; S. Lane Slabaugh, PharmD, MBA; Yunus Meah, PharmD; Jean Baltz, MMSc, MSW; Nick C. Patel, PharmD, PhD; and Jonathan R. Bouchard, MS, RPh
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Mollie Shulan, MD; and Kelly Gao
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Medical Homes: Cost Effects of Utilization by Chronically Ill Patients
Jason Neal, MA; Ravi Chawla, MBA; Christine M. Colombo, MBA; Richard L. Snyder, MD; and Somesh Nigam, PhD
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Rashid Kazerooni, PharmD, BCPS; Joseph B. Nguyen, PharmD, BCPS; Mark Bounthavong, PharmD, MPH; Michael H. Tran, PharmD, BCPS; and Nermeen Madkour, PharmD, CSP
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Medical Homes: Cost Effects of Utilization by Chronically Ill Patients

Jason Neal, MA; Ravi Chawla, MBA; Christine M. Colombo, MBA; Richard L. Snyder, MD; and Somesh Nigam, PhD
A longitudinal case-control design was used to evaluate the effects of the patient-centered medical home model on medical costs and utilization among chronically ill patients.
The impact of primary care practices adopting the patient-centered medical home (PCMH) model is analyzed by comparing per member per month (PMPM) costs and utilization among commercial HMO members with chronic illnesses in PCMH and non-PCHM practices in the Philadelphia area. Transforming primary care practices to conform to the PCMH model has shown early promise in reducing costs and improving outcomes, and chronically ill patients’ frequent contact with the healthcare system and costly care make them ideal targets for such health system reforms.

Study Design and Methods
The impact of the PCMH model on PMPM costs was analyzed using a generalized linear regression model to adjust for age, gender, and baseline cost. The impact of the PCMH model on utilization per 1000 rates was analyzed with the Poisson regression model, adjusting for baseline differences in age, gender, and risk score.

After accounting for differences at baseline, PCMH practices achieved lower total, inpatient, and specialist PMPM costs, as well as lower relative utilization of hospital admissions and specialist visits.

These findings suggest that policy makers should maintain or expand incentives to adopt PCMH reforms and that targeting chronically ill patients may be the most effective way to leverage the benefits of PCMH adoption.

Am J Manag Care. 2015;21(1):e51-e61
Chronically ill patients enrolled in nonpediatric primary care practices that adopted the patient-centered medical home (PCMH) model had lower total, inpatient, and specialist per member per month costs compared with non-PCMH practices after adjusting for baseline characteristics.
  • PCMH cost reductions appear to have been driven by lower utilization rates of hospital admissions and specialist visits.
  • Inpatient admissions per 1000 patients were significantly lower for chronically ill patients in PCMH practices in each of the 3 program years analyzed.
Despite extensive evidence that quality primary care has the effect of improving health and controlling costs,1,2 the field is described as facing a crisis. One oft-cited source of the problem is the current fee-for-service reimbursement system, which does not adequately compensate the “cognitive” services that lie at the core of primary care.3 The American College of Physicians (ACP) position paper distinguishes “cognitive” from procedural-driven services, and refers to the evaluation and management of patients by primary care physicians.3 The fee-for-service reimbursement model is credited in part with driving medical school graduates to enter better compensated specialty fields, creating the potential for a shortage in primary care practitioners.4,5

Other concerned voices note that beyond the debate about an adequate supply of doctors, there is a need for primary care practitioners to take a more proactive role in the coordination of care across multiple sites and providers.6 Poor coordination of care, as can occur when a patient lacks a usual source of care, has been shown to lead to increased costs, diminished care quality, reduction of access to preventive services, and increased usage of high-intensity care.1,7

This relationship is of particular concern for the treatment of chronically ill patients. Primary care doctors are encountering increasingly complex patients, with the average family practice office encounter addressing 2.7 medical problems.8 This complexity has very real implications for costs in the healthcare system: one study found that nearly all of the cost growth from 1987 to 2002 occurred among patients being treated for 5 or more conditions.9 Another noted that among Medicare beneficiaries, 10% of patients—typically those with multiple chronic illnesses that require numerous prescription medications, and who experience frequent hospitalization—account for 70% of healthcare costs.5 The presence of chronic illness makes accurate, readily accessible medical records essential to providing quality care, and effective management may require ongoing patient contact, even outside of the doctor’s office.

The patient-centered medical home (PCMH) model offers a promising alternative to the current paradigm in primary care. The concept of the “medical home” originated in 1967 with the American Academy of Pediatrics (AAP), was initially presented as a model for addressing special healthcare needs among children. The medical home focuses on a team-based approach to primary care whereby a physician-leader coordinates care received from other providers across multiple sites and specialties. This methodology encourages increased access in terms of expanded practice hours and enabling new ways to engage with patients.10 Information technology, such as electronic health records, is part of this approach, which can facilitate better identification of patient needs, more effective care management, and more efficient tracking of health outcomes. Incentivebased payment structures to better reward evaluation and management are also included. This concept gained wider attention following the 2007 statement of Joint Principles by the American Academy of Family Physicians, AAP, ACP, and American Osteopathic Association, which offered a unified vision of the central components of the PCMH model.11,12

Some preliminary research has shown promising, though mixed, early results for practices adopting the PCMH model in terms of patient experience13,14 and in reducing utilization of high-cost medical interventions, such as emergency department (ED) visits and hospitalizations. 14-17 This was corroborated by a recent review of studies of the PCMH model which showed that while individual programs have yielded successes, the overall evidence is more mixed. Adoption of the PCMH model appears to have positive effects on patient experience and provision of preventive services to patients, but its effect on ED utilization, an important driver of healthcare costs, was limited to older patients. Moreover, this review found no consistent reduction in hospital admissions or overall expenditures for patients in practices that adopted the PCMH model.18 Given inconsistent definitions of the “medical home,"18,19 this review and others point to the difficulty in assessing the impact of the PCMH model. As much of the work to date has been inconclusive, this analysis will focus on the relevant subpopulation of chronically ill patients for whom the PCMH model would be most likely to yield benefits.

This paper aims to contribute to the growing body of literature and evidence on the PCMH model. Previous work, such as the 2010 Group Health Cooperative (GHC) study by Reid et al14 and Friedberg et al's,20 study on the Pennsylvania Chronic Care Initiative (PACCI) have evaluated the effects of the medical home on costs and utilization for all patients. This study focuses on the PCMH effect on patients with chronic illness(es). This subpopulation requires complex care and frequent contact with the healthcare system, which makes them more likely to benefit from improved coordination of care and enhanced access and communication.21,22 We hypothesize that implementing PCMH practices will result in lower total, inpatient, and specialist per member per month (PMPM) costs, and will lower relative utilization of hospital admissions and specialist visits over the 3-year study period.


Program Description

This study evaluates early implementation of the PCMH model using data collected from the PACCI. This initiative was convened as a collaborative effort by the state’s largest commercial health plans (led by Independence Blue Cross), all 3 Medicaid managed care plans, and 32 medical practices, and was organized by the Governor’s Office of Health Care Reform to promote the adoption of the PCMH model and improve the quality of primary care for patients with chronic illnesses. Engagement by multiple stakeholders allowed for the appropriate resources, scale, and support to be provided, creating a framework for education, training, and data submission, as well as allowing for consistency in monitoring outcomes across the program.

To facilitate transition to the PCMH model, practices received supplemental financial incentives and were required to participate in a Learning Collaborative based on Wagner’s Chronic Care Model,23 working toward recognition from the National Committee for Quality Assurance (NCQA) as a PCMH by the end of the first year of participation. Each practice enrolled in the initiative was required to a) have at least 1 physician, plus a practice support leader, in attendance at each of 7 full-day sessions and to b) participate in weekly meetings. Furthermore, practices were paired with practice coaches responsible for providing additional support and training.

Data from practices in the PACCI pilot were used to determine the program’s effect on patients with chronic illness(es), a subpopulation requiring complex care. This was a longitudinal observational study conducted to assess the impact of adopting the PCMH as a model for improving primary care, focusing on PMPM healthcare costs and utilization per 1000 patients over 3 years of follow-up data.

Study Population

A cohort of chronically ill members—defined as patients having asthma, coronary artery disease, congestive heart failure, chronic obstructive pulmonary disease, diabetes, and/or hypertension—was created from administrative medical claims in the baseline year, 2008. Chronic illness was identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes from medical claims data. Additionally, all patients must have been continuously enrolled in the same practice from 2008 through 2011. We also limited our analysis to practices located within Philadelphia city limits in order to limit the effect of urban-suburban disparities on our findings24,25 and because the majority of initial PCMH practices were located within the city.

Defining the Patient-Centered Medical Home

To provide an operational definition of a “medical home,” the PACCI relied on the definition provided by the NCQA as of 2008.26 Practices were assigned PCMH status if they received at least Level 1 NCQA recognition in 2009 and maintained recognition through at least 2011. Level 1 recognition required that practices meet 5 of 10 possible “must pass” criteria and accumulate 25 total “points.” The complete list of potential PCMH improvements recognized by the NCQA appears in Table 1. Practices designated “non-PCMH” did not join the PCMH program at any point during years 2008 to 2011 and were used as controls. The resulting study population consisted of 2674 patients enrolled in 11 PCMH practices and 19,546 patients in 393 non-PCMH practices, all of which were located within Philadelphia city limits.

Analytical Framework

This study was conducted as a longitudinal observational study to best assess the impact of adopting the PCMH model as a vehicle for improving primary care of chronically ill members. The outcomes of interest were PMPM healthcare utilization and costs. Costs were reported separately as inpatient, ED, specialist, and outpatient care costs, as well total PMPM costs. Utilization was reported in terms of inpatient admissions, ED visits, specialist visits, and outpatient visits per 1000 patients over 3 years of follow-up. Data on costs and utilization were extracted from medical claims; patient-level covariates of age and gender were recorded from enrollment data. To control for differences between the PCMH and non-PCMH groups at baseline, patient-level covariates (age, gender, and costs at baseline) were included in regression models.

At baseline, a number of differences were observed between case and control practices in terms of patient age and risk profile, socioeconomic characteristics, and comorbid conditions, which translated into significant differences in terms of costs and utilization even before the introduction of PCMH changes in the cases. The Figure presents some of these baseline comparisons. Patients in practices adopting PCMH reforms were generally younger (aged 39.2 years vs 45.4 years; P <.0001), but had lower estimated risk scores (1.61 vs 1.81; P <.05) and significantly different case mix in terms of illness profiles.

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