New ways of thinking about nurse scheduling

Deisell M. Diaz, Murat Erkoc, Shihab S. Asfour, Edward K. Baker

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


PurposeThe purpose of this paper is to present a new look at solving the national nursing shortage problem by discussing new approaches to minimize the impact of nursing miss‐utilization and or miss‐allocation. Design/methodology/approachAmong the approaches explored is the well‐known financial engineering derivative interest rate swap as well as new scheduling applications including inventory management and queuing models. FindingsThe study found that there is great interest in the field of the nurse scheduling and staffing problem. The problems are, however, studied in isolation from one another, while their respective nature is inter‐related: staffing policies impact nursing problem model constraints. This gap may be one of the contributing factors to a well‐known gap between industry application and academic literature. Industry solutions focus encouraging the growth of nurses in the field, most of which result in a financial paradox due to increasing rate capitation for health service facilities, which began in the mid‐1990s. Research limitations/implicationsPossible limitations include a resistance to application from industry, as it has not been possible to minimize the application gap. Originality/valueThis paper introduces a swap model that satisfies the key problems resulting from the shortage: increasing costs and gap needs. The additional approaches offer a new look from outside industry application that have yielded solutions needed in the nurse scheduling problem.

Original languageEnglish (US)
Pages (from-to)76-93
Number of pages18
JournalJournal of Advances in Management Research
Issue number1
StatePublished - May 25 2010


  • Competitive strategy
  • Health services sector
  • Human resource management
  • Nurses
  • United States of America

ASJC Scopus subject areas

  • Business, Management and Accounting(all)


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