Cargando…

Work productivity loss from depression: evidence from an employer survey

BACKGROUND: National working groups identify the need for return on investment research conducted from the purchaser perspective; however, the field has not developed standardized methods for measuring the basic components of return on investment, including costing out the value of work productivity...

Descripción completa

Detalles Bibliográficos
Autores principales: Rost, Kathryn M, Meng, Hongdao, Xu, Stanley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307989/
https://www.ncbi.nlm.nih.gov/pubmed/25519705
http://dx.doi.org/10.1186/s12913-014-0597-y
_version_ 1782354528157302784
author Rost, Kathryn M
Meng, Hongdao
Xu, Stanley
author_facet Rost, Kathryn M
Meng, Hongdao
Xu, Stanley
author_sort Rost, Kathryn M
collection PubMed
description BACKGROUND: National working groups identify the need for return on investment research conducted from the purchaser perspective; however, the field has not developed standardized methods for measuring the basic components of return on investment, including costing out the value of work productivity loss due to illness. Recent literature is divided on whether the most commonly used method underestimates or overestimates this loss. The goal of this manuscript is to characterize between and within variation in the cost of work productivity loss from illness estimated by the most commonly used method and its two refinements. METHODS: One senior health benefit specialist from each of 325 companies employing 100+ workers completed a cross-sectional survey describing their company size, industry and policies/practices regarding work loss which allowed the research team to derive the variables needed to estimate work productivity loss from illness using three methods. Compensation estimates were derived by multiplying lost work hours from presenteeism and absenteeism by wage/fringe. Disruption correction adjusted this estimate to account for co-worker disruption, while friction correction accounted for labor substitution. The analysis compared bootstrapped means and medians between and within these three methods. RESULTS: The average company realized an annual $617 (SD = $75) per capita loss from depression by compensation methods and a $649 (SD = $78) loss by disruption correction, compared to a $316 (SD = $58) loss by friction correction (p < .0001). Agreement across estimates was 0.92 (95% CI 0.90, 0.93). CONCLUSION: Although the methods identify similar companies with high costs from lost productivity, friction correction reduces the size of compensation estimates of productivity loss by one half. In analyzing the potential consequences of method selection for the dissemination of interventions to employers, intervention developers are encouraged to include friction methods in their estimate of the economic value of interventions designed to improve absenteeism and presenteeism. Business leaders in industries where labor substitution is common are encouraged to seek friction corrected estimates of return on investment. Health policy analysts are encouraged to target the dissemination of productivity enhancing interventions to employers with high losses rather than all employers. TRIAL REGISTRATION: Clinical trials registration number: NCT01013220.
format Online
Article
Text
id pubmed-4307989
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-43079892015-01-28 Work productivity loss from depression: evidence from an employer survey Rost, Kathryn M Meng, Hongdao Xu, Stanley BMC Health Serv Res Research Article BACKGROUND: National working groups identify the need for return on investment research conducted from the purchaser perspective; however, the field has not developed standardized methods for measuring the basic components of return on investment, including costing out the value of work productivity loss due to illness. Recent literature is divided on whether the most commonly used method underestimates or overestimates this loss. The goal of this manuscript is to characterize between and within variation in the cost of work productivity loss from illness estimated by the most commonly used method and its two refinements. METHODS: One senior health benefit specialist from each of 325 companies employing 100+ workers completed a cross-sectional survey describing their company size, industry and policies/practices regarding work loss which allowed the research team to derive the variables needed to estimate work productivity loss from illness using three methods. Compensation estimates were derived by multiplying lost work hours from presenteeism and absenteeism by wage/fringe. Disruption correction adjusted this estimate to account for co-worker disruption, while friction correction accounted for labor substitution. The analysis compared bootstrapped means and medians between and within these three methods. RESULTS: The average company realized an annual $617 (SD = $75) per capita loss from depression by compensation methods and a $649 (SD = $78) loss by disruption correction, compared to a $316 (SD = $58) loss by friction correction (p < .0001). Agreement across estimates was 0.92 (95% CI 0.90, 0.93). CONCLUSION: Although the methods identify similar companies with high costs from lost productivity, friction correction reduces the size of compensation estimates of productivity loss by one half. In analyzing the potential consequences of method selection for the dissemination of interventions to employers, intervention developers are encouraged to include friction methods in their estimate of the economic value of interventions designed to improve absenteeism and presenteeism. Business leaders in industries where labor substitution is common are encouraged to seek friction corrected estimates of return on investment. Health policy analysts are encouraged to target the dissemination of productivity enhancing interventions to employers with high losses rather than all employers. TRIAL REGISTRATION: Clinical trials registration number: NCT01013220. BioMed Central 2014-12-18 /pmc/articles/PMC4307989/ /pubmed/25519705 http://dx.doi.org/10.1186/s12913-014-0597-y Text en © Rost et al.; licensee BioMed Central. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Rost, Kathryn M
Meng, Hongdao
Xu, Stanley
Work productivity loss from depression: evidence from an employer survey
title Work productivity loss from depression: evidence from an employer survey
title_full Work productivity loss from depression: evidence from an employer survey
title_fullStr Work productivity loss from depression: evidence from an employer survey
title_full_unstemmed Work productivity loss from depression: evidence from an employer survey
title_short Work productivity loss from depression: evidence from an employer survey
title_sort work productivity loss from depression: evidence from an employer survey
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307989/
https://www.ncbi.nlm.nih.gov/pubmed/25519705
http://dx.doi.org/10.1186/s12913-014-0597-y
work_keys_str_mv AT rostkathrynm workproductivitylossfromdepressionevidencefromanemployersurvey
AT menghongdao workproductivitylossfromdepressionevidencefromanemployersurvey
AT xustanley workproductivitylossfromdepressionevidencefromanemployersurvey