Predictive staffing simulation model methodology

Pamela Johnson-Carlson, Cindy Costanzo, David Kopetsky

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Many factors contribute to the complexity of planning for and having enough nursing staff; however, antiquated planning strategies are a major issue. The purpose of this study was to develop a predictive staffing simulation model. The model included integrating staffing needs (actual patient census, care delivery model, and budget) and staffing availability (filled positions, flex staffing, and absences) factors that influence effective and efficient staffing plans using the staffing prediction and simulation analysis tool. A predictive staffing simulation model provides the ability for nursing leaders to proactively predict nursing resources in establishing effective and efficient staffing models that support an optimal patient care delivery system.

Original languageEnglish (US)
Pages (from-to)161-169
Number of pages9
JournalNursing Economics
Volume35
Issue number4
StatePublished - Jul 1 2017
Externally publishedYes

Fingerprint

Patient Care
Nursing
Nursing Staff
Budgets
Censuses

All Science Journal Classification (ASJC) codes

  • Leadership and Management

Cite this

Johnson-Carlson, P., Costanzo, C., & Kopetsky, D. (2017). Predictive staffing simulation model methodology. Nursing Economics, 35(4), 161-169.

Predictive staffing simulation model methodology. / Johnson-Carlson, Pamela; Costanzo, Cindy; Kopetsky, David.

In: Nursing Economics, Vol. 35, No. 4, 01.07.2017, p. 161-169.

Research output: Contribution to journalArticle

Johnson-Carlson, P, Costanzo, C & Kopetsky, D 2017, 'Predictive staffing simulation model methodology', Nursing Economics, vol. 35, no. 4, pp. 161-169.
Johnson-Carlson P, Costanzo C, Kopetsky D. Predictive staffing simulation model methodology. Nursing Economics. 2017 Jul 1;35(4):161-169.
Johnson-Carlson, Pamela ; Costanzo, Cindy ; Kopetsky, David. / Predictive staffing simulation model methodology. In: Nursing Economics. 2017 ; Vol. 35, No. 4. pp. 161-169.
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