PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 28, 2026BMC Health Services Research0 citationsOpen Access

Factors influencing selection of models of primary health care delivery in conflict-affected settings: analysis of surveys from humanitarian organizations in Cameroon and Nigeria

LOLundi-Anne OmamKOKelli O’LaughlinIMIko Musa

Key Points

  • The study aims to explore factors influencing humanitarian organizations' selection of primary health care delivery models in conflict-affected settings.
  • Conducted an organizational cross-sectional survey in Cameroon and Nigeria from April to June 2022.
  • Recruited senior staff from humanitarian organizations using purposeful sampling and snowballing.
  • Used an online questionnaire for data collection and performed descriptive and multivariable logistic analysis.
  • A total of 160 organizations participated, primarily national NGOs.
  • Six models of care were reported, with community-based interventions and outreaches being the most utilized.
  • Mobile clinics were more frequently used in peri-urban settings, while home visits were common in urban areas.
  • Ministry of Health priorities and cost significantly influenced the choice of community-based interventions.

Abstract

In conflict-affected settings, primary health care (PHC) is delivered using various models of care due to disruption of usual health systems and infrastructure, with multiple humanitarian focused actors working in health care delivery. While studies have described individual models of care for delivering PHC services in conflict-affected settings, there has not been studies to exploring the complexity of use of different models of care in conflict-affected settings, and what factors associated with the choice of different models by humanitarian organisations. An organisational cross-sectional survey was conducted from April to June 2022 in the Northwest and Southwest Regions of Cameroon, and Northeast Nigeria where there has been protracted armed conflict. We recruited senior level humanitarian organisations staff via purposeful sampling and snowballing. The survey was conducted using an online questionnaire. Descriptive and multivariable logistic stepwise analysis was conducted to describe the models used and explore the association models of care with factors influencing their decision. A total of 160 organisations participated in the survey, with the majority being national NGOs. Six different models of care were reported to be used by humanitarian organisations with community-based interventions (CBI) (n = 82/119), outreaches (n = 82/119) and health facility (n = 71/119) modalities being the most used. Alternatives were mobile clinics (n = 37/119), home visits (n = 54/199) and telemedicine (n = 22/119). The use of mobile clinics was associated with use in peri-urban setting (OR = 3.06, CI = 1.31–7.42, P = 0.011), home visits more likely to be use in urban settings (OR 3.27, CI = 2.41–47.35, p = 0.003). Ministry of Health priorities was associated with CBI being used (OR 9.35, CI = 3.27–6187.03, p = 0.0144); with cost being associated with the use of CBI (OR = 6.33, CI = 3.94–2203.5, p = 0.007). Understanding how different actors in humanitarian settings chose their model of care of service delivery is important for co-ordinating planning of services in a conflict setting. This study highlights the complexity in choice of model of care delivery in conflict settings, with often arbitrary decisions due to the lack of a guidance to assist choice of the most appropriate model for the context. The next steps are to develop a framework to support choice of model of care, with associated tools to measure and support quality of care in delivery of services to those in conflict settings. Registry: ClinicalTrials.gov, NCT05279105, Registration date: 17 February 2022.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Omam et al. (2026) studied this question.

synapsesocial.com/papers/69a286da0a974eb0d3c0210bhttps://doi.org/10.1186/s12913-026-14237-3
Ask AI
Helpful
Bookmark
Share
View Full Paper