Aller au contenu principal
Accès ouvert déclaré 2025 article

Comprehensive primary health care for cost-effective scale-up of depression screening in India: an economic modelling study

0Citations signalées, ce qui n’est pas une note de qualité
3Institutions déclarées
1Pays d’affiliation déclarés

Rattachement africain : in. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Background: The Government of India envisions integrating population-based depression screening within the framework of comprehensive primary health care. This study assesses the economic impact and cost-utility of implementing universal depression screening for different age groups (≥30 years and ≥20 years) compared to the current practice of opportunistic diagnosis and management of symptomatic patients. Methods: A hybrid model comprising of a decision tree and Markov model was developed for economic evaluation. The input parameters were acquired through comprehensive literature search, stakeholder consultations, analysis of the data from National Mental Health Survey, and the National Sample Survey, besides primary data collected from 259 patients for quality of life. The analysis was performed from both abridged societal (consideration of direct costs) and societal perspective (consideration of direct as well as indirect costs). In line with Indian economic evaluation standards, a screening strategy was deemed cost-effective if its incremental cost-utility ratio (ICUR) was below the per capita gross domestic product (GDP) threshold of ₹1,71,498 ($2182). Findings: The gain in QALYs per person from universal screening ranged from 0·0273 (0·0265-0·0281) to 0·0295 (0·0287-0·0303), depending on the target age group. The program is expected to generate net savings of ₹291 billion ($3·7 billion) to ₹482 billion ($6·1 billion), equivalent to 0·19% to 0·32% of GDP. Furthermore, the ICURs were below the threshold, with ≥20 years aged cohort screening (₹43,995, $620) being more cost-effective than the screening in ≥30 years aged population (₹48,746, $560) from the abridged societal perspective. However, the program ceases to yield positive net health benefits if the sensitivity of the PHQ-2 decreases to 26%, or if the combined sensitivity of the sequential PHQ-2 and PHQ-9 approach falls below 35%. The intervention is likely to result in cost savings if at least 60% of patients seeking treatment after screening use public health facilities. Interpretation: Integrating depression screening and management into the government primary healthcare system provides substantial public health and economic benefits, supporting the case for a PHC-oriented health system. Expanding coverage to individuals aged 20 years and above, along with ensuring high diagnostic accuracy through quality training and supportive supervision, will be key to sustaining and maximizing the programme's impact. Funding: The study was supported by funding from the Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Comprehensive primary health care for cost-effective scale-up of depression screening in India: an economic modelling study
Date Crossref
01/12/2025
Éditeur
Elsevier BV
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Mental Health Treatment and AccessHealthcare Systems and ReformsHealth Systems, Economic Evaluations, Quality of Life

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.