سبد خرید

A Configurational Comparative Method to Identify Multiple Pathways to Improve Patient-Centered Medical Home Models

تومان

موجودی: در انبار

This brief focuses on using fuzzy set Qualitative Comparative Analysis (fsQCA) to evaluate patientcentered medical home (PCMH) models. It is  part of a series commissioned by the Agency for Healthcare Research and Quality (AHRQ) and developed by Mathematica Policy Research under contract, with input from other nationally recognized thought leaders in research methods and PCMH models. The series is designed to expand  the toolbox of methods used to evaluate and refine PCMH models. The PCMH is a primary care approach that aims to improve quality, cost, and  patient and provider experience. PCMH models emphasize patient-centered, comprehensive, coordinated, accessible care, and a systematic  focus on quality and safety

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مقایسه

ABSTRACT

This brief focuses on using fuzzy set Qualitative Comparative Analysis (fsQCA) to evaluate patientcentered medical home (PCMH) models. It is  part of a series commissioned by the Agency for Healthcare Research and Quality (AHRQ) and developed by Mathematica Policy Research under contract, with input from other nationally recognized thought leaders in research methods and PCMH models. The series is designed to expand  the toolbox of methods used to evaluate and refine PCMH models. The PCMH is a primary care approach that aims to improve quality, cost, and  patient and provider experience. PCMH models emphasize patient-centered, comprehensive, coordinated, accessible care, and a systematic  focus on quality and safety.

INTRODUCTION

Qualitative Comparative Analysis (QCA) is a powerful approach for studying PCMHs and other health services interventions (Thygeson, Solberg,  Asche, et al., 2012; Kahwati, Lewis, Kane, et al., 2011). QCA was developed in political science to evaluate case studies with too few cases for  standard statistical analysis and where the available data are often qualitative or a combination of qualitative and quantitative (Ragin, 1987;  Rihoux and Ragin, 2009). QCA can be used to identify characteristics of the intervention, practices, patients, and practice settings that are  associated with successful outcomes. QCA differs from traditional regression analyses in that it is based on set theory and logic, not statistics,  and is designed to evaluate social systems characterized by causal complexity. Consequently, QCA is a radically different approach to studying  health services interventions such as medical homes. This has three important implications for investigators. First, QCA assumes there can be many pathways to the same outcome, a phenomenon known as equifinality. Second, QCA assumes each pathway can contain different  combinations of explanatory characteristics. Therefore, the method looks for the effect of combinations—configurations—of necessary and  sufficient explanatory characteristics,1 rather than for the effect of each individual characteristic holding equal the other characteristics. Although  traditional regression approaches may appear to be able to do this using interaction terms, they are not well suited to separately  identifying necessary or sufficient characteristics (Schneider and Wagemann, 2012).

Year: 2013

Publisher : AHRQ

By : N. Marcus Thygeson, M.D.Deborah Peikes, Ph.D., and Aparajita Zutshi, Ph.D

File Information: English Language/ 14 Page / size: 315 KB

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سال : 2013

ناشر : AHRQ

کاری از : N. Marcus Thygeson, M.D.Deborah Peikes, Ph.D., and Aparajita Zutshi, Ph.D

اطلاعات فایل : زبان انگلیسی / 14 صفحه / حجم : KB 315

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