{"title":"Standardising workforce cost estimates across Australian jurisdictions: genomic testing as a use case.","authors":"Dylan A Mordaunt","doi":"10.1071/AH24126","DOIUrl":null,"url":null,"abstract":"<p><p>Introduction Labour costs are a key driver of healthcare costs and a key component of economic evaluations in healthcare. We undertook the current study to collect information about workforce costs related to clinical genomic testing in Australia, identifying key components of pay scales and contracts, and incorporating these into a matrix to enable modelling of disaggregated costs. Methods We undertook a microcosting study of health workforce labour costs in Australia, from a health services perspective. We mapped the genomic testing processes, identifying the relevant workforce. Data was collected on the identified workforce from publicly available pay scales. Estimates were used to model the total cost from a public health services employer perspective, undertaking deterministic and probabilistic sensitivity analyses. Results We identified significant variability in the way in which pay scales and related conditions are both structured and the levels between jurisdictions. The total costs (2023-2024 Australian dollars) ranged from 160,794 (113,848-233,350) for administrative staff to 703,206 (548,011-923,661) for pathology staff (full-time equivalent). Deterministic sensitivity analysis identified that the base salary accounts for the greatest source of uncertainty, from 24.8% (20.0-32.9%) for laboratory technicians to 53.6% (52.8-54.4%) for medical scientists. Conclusion Variations in remuneration levels and conditions between Australian jurisdictions account for considerable variation in the estimated cost of labour and may contribute significantly to the uncertainty of economic assessments of genomic testing and other labour-intensive health technologies. We outline an approach to standardise the collection and estimation of uncertainty for Australian health workforce costs and provide current estimates for labour costs.</p>","PeriodicalId":93891,"journal":{"name":"Australian health review : a publication of the Australian Hospital Association","volume":" ","pages":"634-641"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian health review : a publication of the Australian Hospital Association","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1071/AH24126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Introduction Labour costs are a key driver of healthcare costs and a key component of economic evaluations in healthcare. We undertook the current study to collect information about workforce costs related to clinical genomic testing in Australia, identifying key components of pay scales and contracts, and incorporating these into a matrix to enable modelling of disaggregated costs. Methods We undertook a microcosting study of health workforce labour costs in Australia, from a health services perspective. We mapped the genomic testing processes, identifying the relevant workforce. Data was collected on the identified workforce from publicly available pay scales. Estimates were used to model the total cost from a public health services employer perspective, undertaking deterministic and probabilistic sensitivity analyses. Results We identified significant variability in the way in which pay scales and related conditions are both structured and the levels between jurisdictions. The total costs (2023-2024 Australian dollars) ranged from 160,794 (113,848-233,350) for administrative staff to 703,206 (548,011-923,661) for pathology staff (full-time equivalent). Deterministic sensitivity analysis identified that the base salary accounts for the greatest source of uncertainty, from 24.8% (20.0-32.9%) for laboratory technicians to 53.6% (52.8-54.4%) for medical scientists. Conclusion Variations in remuneration levels and conditions between Australian jurisdictions account for considerable variation in the estimated cost of labour and may contribute significantly to the uncertainty of economic assessments of genomic testing and other labour-intensive health technologies. We outline an approach to standardise the collection and estimation of uncertainty for Australian health workforce costs and provide current estimates for labour costs.