Workload capacity measures for estimating allied health staffing requirements
Article
Article Title | Workload capacity measures for estimating allied health staffing requirements |
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ERA Journal ID | 13431 |
Article Category | Article |
Authors | Schoo, Adrian M. (Author), Boyce, Rosalie A. (Author), Ridoutt, Lee (Author) and Santos, Teresa (Author) |
Journal Title | Australian Health Review |
Journal Citation | 32 (3), pp. 548-558 |
Number of Pages | 11 |
Year | 2008 |
Publisher | CSIRO Publishing |
Place of Publication | Melbourne, Australia |
ISSN | 0156-5788 |
1449-8944 | |
Digital Object Identifier (DOI) | https://doi.org/10.1071/AH080548 |
Web Address (URL) | http://www.publish.csiro.au/?act=view_file&file_id=AH080548.pdf |
Abstract | Workforce planning methodologies for the allied health professions are acknowledged as rudimentary despite the increasing importance of these professions to health care across the spectrum of health services settings. The objectives of this study were to (i) identify workload capacity measures and methods for profiling allied health workforce requirements from a systematic review of the international literature; (ii) explore the use of these methods in planning workforce requirements; (iii) identify barriers to applying such methods; and (iv) recommend further action. Future approaches to workforce planning were explored through a systematic review of the literature, interviews with key stakeholders and focus group discussions with representatives from the different professional bodies and health agencies in Victoria. Results identified a range of methods used to calculate workload requirements or capacity. In order of increasing data demands and costliness to implement, workload capacity methods can be broadly classified into four groups: ratio-based, procedure-based, categories of care-based and diagnostic or casemix-based. Despite inherent limitations, the procedure-based measurement approach appears to be most widely accepted. Barriers to more rigorous workforce planning methods are discussed and future directions explored through an examination of the potential of casemix and mixed-method approaches. |
Keywords | allied health personnel; diagnosis-related groups; focus groups; health services research; needs assessment; personnel staffing; scheduling; task performance |
ANZSRC Field of Research 2020 | 440706. Health policy |
420306. Health care administration | |
350503. Human resources management | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Department of Health, Victoria |
University of Queensland | |
Human Capital Alliance, Australia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0w6z/workload-capacity-measures-for-estimating-allied-health-staffing-requirements
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