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March 8, 20260 citationsOpen Access

Bayesian Hierarchical Model for Assessing Cost-Effectiveness of Community Health Centres in Tanzania 2009

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KMKamasi Mwebesu

Key Points

  • The study aims to assess the cost-effectiveness and impact of community health centres in Tanzania using a Bayesian hierarchical model.
  • Utilized a Bayesian hierarchical model to analyze financial and operational data.
  • Collected data from various community health centres across Tanzania.
  • Examined cost savings related to telemedicine interventions.
  • Identified significant cost savings attributed to telemedicine reducing patient travel expenses.
  • The Bayesian hierarchical model provided robust estimates of cost-effectiveness ratios and credible intervals.
  • Recommended integrating digital healthcare tools to improve efficiency and affordability.

Abstract

The effectiveness of community health centers in Tanzania has been a topic of interest for assessing their cost-effectiveness and impact on public health. A Bayesian hierarchical model was employed to analyse the financial and operational data collected from various community health centers across Tanzania. The model accounts for the variability in costs and outcomes at different levels of aggregation (e. g. , individual patient visits versus centre-wide operations). The analysis revealed a significant proportion of cost savings attributed to telemedicine interventions implemented by some centers, reducing travel expenses for patients. The Bayesian hierarchical model provided robust estimates of cost-effectiveness ratios and credible intervals that support the financial sustainability of community health centre networks in Tanzania. Based on these findings, policy recommendations suggest integrating more digital healthcare tools to further enhance the efficiency and affordability of community health services. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.

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Cite This Study

Kamasi Mwebesu (2009) studied this question.

synapsesocial.com/papers/69acc56732b0ef16a404f8dbhttps://doi.org/10.5281/zenodo.18888858
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