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Health Services Research & Development

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2009 HSR&D National Meeting Abstract

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National Meeting 2009

1021 — Development of a Nurse Staffing Model: Linking Integrative Review and Expert Panel

Fasoli DR (CHQOER), Haddock KS (WJB Dorn VAMC)

Objectives:
The VA nurse staffing methodology required revitalizing to meet the changing needs of today’s complex, dynamic healthcare system. Our objective was to develop and test a new model, using an expert panel approach, based on a systematic, evidence-based review of workload management systems (WMS). This process informed the model’s pilot study, currently underway.

Methods:
A focused review of the published literature from 1983 – 2007 resulted in 367 publications. 58 met DeGroot’s evaluation methodology abstraction criteria. Three quality rating methods were used. Summarized findings and themes were presented to a panel of experts, including VA and non-VA health care researchers, leaders, and consultants, with diverse backgrounds in nursing administration, workforce planning, nursing economics, and implementation, dissemination, and organizational research. Open discussion and brainstorming resulted in a final set of variables, which were subsequently screened for availability, measurability, and face validity, for inclusion in a staffing model for pilot study.

Results:
No high quality systematic reviews of WMS were identified. The integrative review revealed: limited reliability and validity testing, lack of WMS precision in categorizing patients, inability to reflect nursing work or predict nurse staffing requirements, and workload measurement difficulties. Individual variables were identified which became the underpinning for expert panel discussion and consensus on a final set of potential multi-level indicators: patient (number of medications, age, obesity, complexity), nurse (hours worked, education, federal service years, job satisfaction), unit (scope, turnover, shift length, skill mix, volume, turbulence, number of providers, unit type, physical environment), and organizational indicators (teaching status, hospital complexity, resident turnover).

Implications:
In lieu of evidence of a seminal WMS on which to build, we leveraged the combined power of an expert panel and integrative review to identify variables for inclusion in a staffing model that uses existing available data and that meets the design criteria of simplicity, parsimony, and minimal additional workload.

Impacts:
An integrative literature review, alone, is insufficient to guide WMS development. However, supplementing with an expert panel to provide real-world experience and expertise to critique and exploit an existing evidence-base enables design of a potentially optimal staffing methodology to meet the projected long-term needs of the VA healthcare delivery system.


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