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The Effect of Improving Primary Care Depression Management on Employee Absenteeism and Productivity: A Randomized Trial
Open accessAbstract
OBJECTIVE: To test whether an intervention to improve primary care depression management significantly improves productivity at work and absenteeism over 2 years. SETTING AND SUBJECTS: Twelve community primary care practices recruiting depressed primary care patients identified in a previsit screening. RESEARCH DESIGN: Practices were stratified by depression treatment patterns before randomization to enhanced or usual care. After delivering brief training, enhanced care clinicians provided improved depression management over 24 months. The research team evaluated productivity and absenteeism at baseline, 6, 12, 18, and 24 months in 326 patients who reported full-or part-time work at one or more completed waves. RESULTS: Employed patients in the enhanced care condition reported 6.1% greater productivity and 22.8% less absenteeism over 2 years. Consistent with its impact on depression severity and emotional role functioning, intervention effects were more observable in consistently employed subjects where the intervention improved productivity by 8.2% over 2 years at an estimated annual value of US 1982 dollars per depressed full-time equivalent and reduced absenteeism by 28.4% or 12.3 days over 2 years at an estimated annual value of US 619 dollars per depressed full-time equivalent. CONCLUSIONS: This trial, which is the first to our knowledge to demonstrate that improving the quality of care for any chronic disease has positive consequences for productivity and absenteeism, encourages formal cost-benefit research to assess the potential return-on-investment employers of stable workforces can realize from using their purchasing power to encourage better depression treatment for their employees.
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“Thirdly, studies have demonstrated that early recognition and treatment of depression can improve social function, increase productivity and decrease absenteeism in the workplace [25].”
From A pilot randomized controlled trial of a tailored cognitive behavioural therapy based intervention for depressive symptoms in those newly diagnosed with multiple sclerosis (2016) · cites this paper as [25]
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Metadata
- Authors
- Rost, K., Smith, J. L., & Dickinson, M.
- Affiliations
- University of Colorado Health (US)
- Central Arkansas Veterans Healthcare System (US)
- Corresponding author
- Rost, Kathryn
- Dickinson, Miriam
- ORCID
- Smith, Jeffrey L.
- Venue
- Medical Care
- Published
- 2004-12
- Volume
- 42
- Issue
- 12
- Pages
- 1202-1210
- ISSN
- 0025-7079 (ISSN-L)
- PMC
- PMC1350979
- OpenAlex
- W2022997917
- Cited by
- 215
- References
- 45
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 5 · 2023: 2 · 2022: 9 · 2021: 7 · 2020: 4 · 2019: 8 · 2018: 14 · 2017: 11 · 2016: 5 · 2015: 7 · 2014: 9 · 2013: 13 · 2012: 11
- FWCI
- 21.38
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Medical Care (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (MH 63651, R01MH076277, K02MH063651, MH-54444, R01MH054444)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Workplace Health and Well-being
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Keywords
- depression treatment, primary care, absenteeism, labor productivity, quality of care, depression screening, clinician training, chronic care, emotional role functioning
- MeSH terms
- Absenteeism, Adult, Antidepressive Agents, Chronic Disease, Depressive Disorder, Efficiency, Employment, Female, Humans, Male, Middle Aged, Primary Health Care, Quality Assurance, Health Care, Occupational Health, Treatment Outcome, Disease Management, Diagnostic and Statistical Manual of Mental Disorders
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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