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2008 HSR&D National Meeting Abstract

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National Meeting 2008

2006 — Measuring Nurse Staffing Levels: VA and Non-VA Perspectives

Li YF (COE, Seattle), Phibbs CS (Health Economics Resource Center (HERC)), Sales AE (University of Alberta), Needleman J (UCLA)

Workshop Objectives:
Healthcare administrators and policy makers have long been looking for a systematic approach to make nurse staffing decisions that ensures effective nursing resource management for the delivery of safe and high-quality nursing care. Major challenges for research in this area include the operational definition of nurse staffing levels, the reliability of source data, and the unit of analysis for nurse staffing studies. The objectives of this workshop are to: (1) provide an overview of existing resources for measuring nurse staffing levels, (2) discuss recent advancements in nurse staffing studies using VA and non-VA data, and (3) suggest future VA research and development to provide decision support for nursing management.

Activities:
Dr. Li will give a brief overview of measures used to calculate nurse staffing levels. Dr. Li will then compare the pros and cons of two DSS national data extracts, Account Level Budgeter Cost Center and Account Level Budgeter Hours, that have been included in two VA-funded projects to construct nurse staffing measures. Dr. Phibbs will discuss the lessons learned from measuring nurse human capital from the PAID data in his current Robert Wood Johnson Foundation funded study. Dr. Sales will present research findings on costs to improve nurses’ perception of practice environments based on data from two VA-funded studies. Dr. Needleman will discuss recent methodological developments in measuring nurse staffing and future directions for nurse staffing research. Discussions and questions between the presenters and audience will follow.

Target Audience:
The intended audience includes nurse and organizational researchers and managers interested in staff/resource allocation and budget planning.

Assumed Audience Familiarity with Topic:
No familiarity with the topics presented is assumed.


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