Dissertations / Theses: 'PCMHE'

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Moore, Rick A. "Measuring the Impact of Recognized Patient-Centered Medical Homes (PCMH)." Thesis, Virginia Commonwealth University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=3746418.

Full text

Abstract:

It has been estimated that by 2020 nearly one-third of all Americans (almost 160 million people) will have at least one chronic disease to manage and the cost of health care will consume over 20 percent of the GDP. The Obama Administration responded to this pending crisis by passing the Patient Protection and Affordable Care Act (PPACA) in 2010. This major legislation aims to instill patient-centered, accountable care into the health care delivery system. Specifically, the United States government is on a mission to reduce the utilization of expensive inpatient care, while increasing access to primary care for all Americans, thereby lowering the total cost of health care.

Primary care practices organized around the principles of the patient-centered medical home (PCMH) can better manage their patients, especially their patients with chronic conditions; and become accountable for their care. In 2008, the National Committee for Quality Assurance (NCQA) released practice-level recognition standards based on the seven Joint Principles of the PCMH, to aid doctors seeking to transform their practices into effective patient-centered delivery systems.

The results of several published studies have touted the successes (e.g., reduced emergency department visits, reduced hospitalizations) of the PCMH model at individual practice sites. These localized successes demonstrated that the principle tenets of the PCMH model—care coordination, team-based care, population management—helped lower utilization of more expensive health care services within the specific practice settings evaluated. However, there has been no study to determine if these core tenets are having a broader impact on the health care delivery system within a community.

One hypothesized outcome of a health care system centered on the PCMH care model is better care coordination and more effective, whole-person care management across the continuum of health care; resulting in a more efficient system that can prevent avoidable hospitalizations.

This dissertation proposal seeks to understand if the increasing numbers (density) of recognized PCMH practices in communities affect avoidable hospitalizations related to ambulatory care sensitive conditions (ACSC), as measured by the AHRQ Composite Prevention Quality Indicators (PQI). The research has two purposes:

1. Establish constructs and hypotheses to measure the effect of the increasing numbers of NCQA-Recognized PCMH practices in communities (counties).

2. Using an outcomes-based measurement approach, investigate the relationship between growing densities of NCQA-Recognized PCMH practice doctors among all primary care doctors (PCD) in a community and the associated impact on the utilization of inpatient care, specifically related to ACSCs, as measured by the AHRQ Composite PQIs.

The research is quasi-experimental in design and is based on a retrospective (2008–2011) analysis of existing data from the NCQA PCMH program, the AHRQ Composite PQI and the Centers for Medicare & Medicaid Services (CMS) National Provider Identification (NPI) databases. Analysis will link NCQA-Recognized PCMH practices (independent variable), AHRQ Risk Adjusted Composite PQIs (dependent variable), and the CMS NPI (total PCDs) on Federal Information Processing Standard (FIPS) identifiers across 114 state and county-level geographical areas in Vermont and North Carolina. The research will inform the following hypotheses:

1. Does the research literature support the measurement construct proposed in this study?

2. Communities with concentrations of recognized PCMH practices among primary care practices will have lower risk-adjusted avoidable hospital admission rates.

3. The use of technology and care coordination will have a greater predictive correlation on risk-adjusted avoidable hospital admission rates than other PCMH capabilities.