Dissertation/Thesis Abstract

Learning from the Workload Indicator of Staffing Need Methodology Technical Implementation Experiences
by Namaganda, Grace Nyendwoha, D.H.A., Capella University, 2018, 217; 10929505
Abstract (Summary)

This study was motivated by the fact that despite its numerous advantages, the use of the Workload Indicator of Staffing Need (WISN) methodology in Health Human Resource (HHR) planning and management is constrained. This is because some WISN users find the methodology especially, the implementation of its technical steps complex and laborious. Moreover, to date, the knowledge gained through the diverse WISN implementation experiences remains fragmented and untapped for peer learning and improvement of the WISN methodology. To promote peer and organizational learning, this study set out to use the direct experiences of the WISN users to obtain and document the lessons learned, innovations developed, and recommendations for WISN improvement. The traditional Delphi approach was used to collect data from 23 purposively selected WISN experts from 21 countries through a three-round Delphi online discussion. The WISN experts discussed and came to a consensus on the practicability of carrying out each of the WISN technical steps, key strategies and innovations that can be used to mitigate the common challenges encountered during WISN implementation. The experts also made recommendations of how to ease implementation of the WISN technical steps and to improve the WISN methodology as a whole. These included: revising the WISN User’s Manual, training, and Software; using a combined approach for setting activity standards; adapting the workforce optimization model’s approach to account for individual and category allowances; advocating for enabling policies for WISN implementation; establishing systems to facilitate benchmarking and peer learning; and establishing systems to ensure sustainable provision of WISN technical support to countries.

Indexing (document details)
Advisor: Whitright, Audrey
School: Capella University
Department: School of Nursing and Health Sciences
School Location: United States -- Minnesota
Source: DAI-B 80/01(E), Dissertation Abstracts International
Subjects: Health sciences, Organizational behavior, Health care management
Keywords: Health workfoce, Staff mix, Staffing, Staffing levels, Staffing norms, Workload indicator
Publication Number: 10929505
ISBN: 978-0-438-36662-6
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