Lessons learned from implementation of the Workload Indicator of Staffing Need (WISN) methodology: An international Delphi study of expert users.
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
BMC
Abstract
Background
Staffing of health services ought to consider the workload experienced to maximize efficiency. However,
this is rarely the case, due to lack of an appropriate approach. The World Health Organization (WHO)
developed and has promoted the Workload Indicators of Staffing Need (WISN) methodology globally. Due
to its relative simplicity compared to previous methods, the WISN has been used extensively, particularly
after its computerization in 2010. Many lessons have been learnt from the introduction and promotion of
the methodology across the globe but have, hitherto, not been synthesized for technical and policy
consideration. This study gathered, synthesized, and now shares the key adaptations, innovations, and
lessons learned. These could facilitate lesson-learning and motivate the WHO’s WISN Thematic Working
Group to review and further ease its application.
Methods
The study aimed to answer four questions: (1) how easy is it for the users to implement each step of the
WISN methodology? (2) what innovations have been used to overcome implementation challenges? (3)
what lessons have been learned that could inform future WISN implementation? and (4) what
recommendations can be made to improve the WISN methodology? We used a three-round traditional
Delphi method to conduct a case study of user-experiences during the adoption of the WISN
methodology. We sent three email iterations to 23 purposively selected WISN expert users across 21
countries in five continents. Thematic analysis of each round was done simultaneously with data
collection.
Results
Participants rated seven of the eight technical steps of the WISN as either “very easy” or “easy” to
implement. The step considered most difficult was obtaining the Category Allowance Factors (CAF). Key
lessons learned were that: the benefits gained from applying the WISN outweigh the challenges faced in
understanding the technical steps; benchmarking during WISN implementation saves time; data quality is
critical for successful implementation; and starting with small-scale projects sets the ground better for
more effective scale-up than attempting massive national application of the methodology the first time
round.
Conclusions
The study provides a good reference for easing WISN implementation for new users and for WHO to
continue promoting and improving upon it.
Description
Keywords
WISN, Health workforce, staffing levels, Traditional Delphi, planning, health systems research.