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BACKGROUND/RATIONALE:
VA's reorganization of care presaged the IoM Quality Chasm report by having already launched internal restructuring, including changes in delivery models (eg, networks), adoption of new technologies (eg, CPRS), and implementation of new management strategies (eg, reminders, audit/feedback). In the aggregate, these organizational changes have been found to be associated with substantial gains in VA quality over time and in comparison to Medicare, yet remarkably little is known about the discrete organizational characteristics in VA facilities that specifically contributed to these performance changes. Further, while there is evidence that area characteristics influence how individual facilities are organized, little is known about how environmental context affected the ability of individual facilities to adopt or deploy changes needed to accommodate reorganization directives, policies and/or practice changes.
OBJECTIVE(S):
The purpose of the study is to integrate and analyze a series of highly unique data sources that span VA's reorganization launched in 1996 with Kizer's Vision and Journey for Change policy documents, starting from a pre-directive year (1993), through early (1996) and later reorganization (1999-2000), during which most of the early performance gains had been achieved. To date, these surveys have been used individually in cross-sectional snapshots to evaluate organizational factors associated with VA quality. However, they have never been combined longitudinally to tell the story of VA as a public sector turnaround and to create an empirically-tested substrate for the next wave of VA practice redesign and QI initiatives. Our objective is therefore to evaluate organizational and contextual determinants that contributed to VA's quality transformation.
AIM #1: To evaluate the organizational changes associated with VA performance over VA's reorganization.
AIM #2: To determine the area contextual factors that may have influenced organizational changes over the course of the VA's reorganization and accompanying performance.
AIM #3: To use expert panel methods to integrate and apply findings to produce evidence-based management guidelines in support of ongoing VA quality improvement and translation of lessons to other health care settings.
METHODS:
We have started to combine VA organizational surveys ('93, '96, '99), with selected VA performance measures representing chronic disease (eg, diabetic eye exams) and prevention (eg, flu shots) quality, as well as area and patient characteristics. Additionally, we will be requesting additional EPRP measures at the patient level for selected years. We will use multi-level models to examine contributions of organizational and area characteristics on organizational change and performance, and linear growth curve models to examine influence of organizational change (slope) on performance. We will then use expert panel methods to develop evidence-based management guidelines.
FINDINGS/RESULTS:
First part of the project has been documenting the different data sources that are being merged (.e.g, ARF, organizational surveys) ..
IMPACT:
Understanding how individual VA facilities have organized themselves to respond to VHA's strategic plans for reorganization will help us develop a framework for ongoing evidence-based management, identifying the fixed and mutable characteristics that may serve as levers in ongoing efforts to improve the quality of care our veterans receive. The proposed research will represent the first detailed quantitative portrait of organizational changes underlying VA's transformation over the past decade and the first dynamic modeling of organizational changes in relation to performance changes yet conducted in VA. This work is designed to serve as a substrate for informing evidence-based management, practice and policy for VA's ongoing QI efforts.
PUBLICATIONS:
None at this time.
DRA:
Health Services and Systems
DRE:
Quality of Care, Resource Use and Cost, Technology Development and Assessment
Keywords:
Management, Implementation
MeSH Terms:
none
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