Resource allocation for depression management in general practice: A simple data-based filter model

Breanne Hobden; Mariko Carey; Rob Sanson-Fisher; Andrew Searles; Christopher Oldmeadow; Allison Boyes

doi:10.1371/journal.pone.0246728

Resource allocation for depression management in general practice: A simple data-based filter model

PLoS One. 2021 Feb 19;16(2):e0246728. doi: 10.1371/journal.pone.0246728. eCollection 2021.

Authors

Breanne Hobden^{1

2

3}, Mariko Carey^{1

2

3}, Rob Sanson-Fisher^{1

2

3}, Andrew Searles³, Christopher Oldmeadow³, Allison Boyes^{1

2

3}

Affiliations

¹ Health Behaviour Research Collaborative, School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.
² Priority Research Centre for Health Behaviour, University of Newcastle, Callaghan, NSW, Australia.
³ Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.

Abstract

Background: This study aimed to illustrate the potential utility of a simple filter model in understanding the patient outcome and cost-effectiveness implications for depression interventions in primary care.

Methods: Modelling of hypothetical intervention scenarios during different stages of the treatment pathway was conducted.

Results: Three scenarios were developed for depression related to increasing detection, treatment response and treatment uptake. The incremental costs, incremental number of successes (i.e., depression remission) and the incremental costs-effectiveness ratio (ICER) were calculated. In the modelled scenarios, increasing provider treatment response resulted in the greatest number of incremental successes above baseline, however, it was also associated with the greatest ICER. Increasing detection rates was associated with the second greatest increase to incremental successes above baseline and had the lowest ICER.

Conclusions: The authors recommend utility of the filter model to guide the identification of areas where policy stakeholders and/or researchers should invest their efforts in depression management.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cost-Benefit Analysis / methods*
Depression / diagnosis
Depression / therapy*
General Practice / economics*
General Practice / methods*
Humans
Models, Statistical
Primary Health Care / organization & administration*
Quality-Adjusted Life Years
Resource Allocation* / economics
Resource Allocation* / organization & administration

Grants and funding

Dr Bree Hobden is supported by a Colin Dodds Australian Rotary Health Postdoctoral Fellowship (G1801108). A/Prof Mariko Carey is supported by a National Health and Medical Research Council Boosting Dementia Research Leadership Fellowship (1137807). Dr Allison Boyes is supported by a National Health and Medical Research Council Early Career Fellowship (1073317). This work was supported by a Strategic Research Partnership Grant (CSR 11-02) from Cancer Council NSW to the Newcastle Cancer Control Collaborative (New-3C) and infrastructure funding from the Hunter Medical Research Institute (HMRI). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.