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Purpose <p>To examine factors associated with sick leave status at referral to clinical psychology and its duration using electronic health records (EHRs).</p> Methods <p>A population-based observational study was conducted with 2,765 patients referred from primary care to mental health units in a regional public healthcare system in Spain in 2021. Sociodemographic and clinical variables were analysed, and a subsample of 400 patients provided additional data on healthcare use and prior sick leave. Logistic regression and generalized linear models were applied.</p> Results <p>At referral, 22.1% of patients were on sick leave (median = 181 d). In analyses based on the full sample, psychopharmacological treatment and being in a relationship were associated with higher odds, whereas female sex was associated with lower odds. In the subsample including prior history variables, prior sick leave emerged as the strongest predictor of both status and duration.</p> Conclusions <p>Routine clinical variables have limited predictive value, whereas prior sick leave episodes are a key and readily available indicator of risk for prolonged sick leave. Incorporating standardized clinical and work-related measures into EHRs may facilitate early identification of individuals at risk of prolonged sick leave and permanent work disability.</p>

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Predictors of Mental Health–Related Sick Leave at Referral to Clinical Psychology: A Population-Based Study Using Electronic Health Records

  • 期刊论文

  • 发表日期：

    2026年5月18日

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  • César González-Blanch,
  • Sandra Martínez-Gómez,
  • Saioa Pérez-García-Abad,
  • Jose Ruiz-Gutiérrez,
  • María del Mar Miras-Aguilar,
  • Carmen Ramos-Barrón,
  • Emilio Pariente-Rodrigo,
  • Lourdes Piñán-Setién,
  • Noelia Otero-Cabanillas,
  • María Isabel Priede

摘要

Purpose

To examine factors associated with sick leave status at referral to clinical psychology and its duration using electronic health records (EHRs).

Methods

A population-based observational study was conducted with 2,765 patients referred from primary care to mental health units in a regional public healthcare system in Spain in 2021. Sociodemographic and clinical variables were analysed, and a subsample of 400 patients provided additional data on healthcare use and prior sick leave. Logistic regression and generalized linear models were applied.

Results

At referral, 22.1% of patients were on sick leave (median = 181 d). In analyses based on the full sample, psychopharmacological treatment and being in a relationship were associated with higher odds, whereas female sex was associated with lower odds. In the subsample including prior history variables, prior sick leave emerged as the strongest predictor of both status and duration.

Conclusions

Routine clinical variables have limited predictive value, whereas prior sick leave episodes are a key and readily available indicator of risk for prolonged sick leave. Incorporating standardized clinical and work-related measures into EHRs may facilitate early identification of individuals at risk of prolonged sick leave and permanent work disability.