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Background <p>Primary Health Centre (PHC) coverage in Himalayan India is constrained by terrain, dispersed settlement and a population-based norm (one PHC per 20,000 in hilly areas) that treats elevation as exogenous. Existing accessibility analyses describe these gaps but rarely evaluate the resource-allocation trade-offs of closing them.</p> Methods <p>Using village-level Census 2011 data and PHC locations from the Department of Medical Health and Family Welfare, Uttarakhand, we mapped catchment areas in Chamoli and Rudraprayag using Voronoi polygons and 5/10/15-km buffers, and recomputed coverage with attention to the limitations of Euclidean distance in mountainous terrain. We then built a resource-allocation model comparing four scenarios: status quo (S0); strict NHM compliance at one PHC per 20,000 population (S1); a coverage-optimised scenario that adds the minimum number of PHCs needed to bring the share of population beyond 15&#xa0;km below 5% (S2); and an altitude-adjusted dynamic threshold (S3). Costs used Indian Public Health Standards-aligned parameters (capital ₹1.85 crore per new PHC; recurring ₹86 lakh per PHC per year, 2024 prices) discounted at 5% over a 10-year horizon, with one-way sensitivity analysis.</p> Results <p>At baseline, 23% of Chamoli’s population and 2% of Rudraprayag’s lay beyond 15&#xa0;km of any PHC (combined 83.7% coverage; ~94,000 people uncovered). Achieving strict NHM compliance (S1) required 18 additional PHCs at a 10-year present-value (PV) cost of ₹275 crore (incremental cost-effectiveness ratio ICER ₹19,671 per additional person covered). The coverage-optimised scenario S2 required only 6 additional PHCs, reached 96.0% coverage at ₹158 crore PV cost, and dominated all alternatives with an ICER of ₹8,373 per additional person covered. The altitude-adjusted scenario (S3) achieved near-complete coverage but at the highest cost (ICER ₹29,274). Results were most sensitive to the time horizon and recurring cost; capital cost had a small effect (±₹3 crore for ± 25% variation).</p> Conclusions <p>A small, geographically targeted expansion of the PHC network in upper Chamoli yields the largest cost-effectiveness gains and accounts for most of the avoidable access gap. Population thresholds alone are an unreliable allocation rule in mountainous districts; explicit coverage-cost optimisation should inform Health and Wellness Centre placement under Ayushman Bharat in hill regions.</p>

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Cost-effective primary health-centre allocation in Himalayan terrain: a spatial and resource-allocation analysis of Chamoli and Rudraprayag districts, India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Neelkamal Alomayan Kalita,
  • Guru Vasishtha

摘要

Background

Primary Health Centre (PHC) coverage in Himalayan India is constrained by terrain, dispersed settlement and a population-based norm (one PHC per 20,000 in hilly areas) that treats elevation as exogenous. Existing accessibility analyses describe these gaps but rarely evaluate the resource-allocation trade-offs of closing them.

Methods

Using village-level Census 2011 data and PHC locations from the Department of Medical Health and Family Welfare, Uttarakhand, we mapped catchment areas in Chamoli and Rudraprayag using Voronoi polygons and 5/10/15-km buffers, and recomputed coverage with attention to the limitations of Euclidean distance in mountainous terrain. We then built a resource-allocation model comparing four scenarios: status quo (S0); strict NHM compliance at one PHC per 20,000 population (S1); a coverage-optimised scenario that adds the minimum number of PHCs needed to bring the share of population beyond 15 km below 5% (S2); and an altitude-adjusted dynamic threshold (S3). Costs used Indian Public Health Standards-aligned parameters (capital ₹1.85 crore per new PHC; recurring ₹86 lakh per PHC per year, 2024 prices) discounted at 5% over a 10-year horizon, with one-way sensitivity analysis.

Results

At baseline, 23% of Chamoli’s population and 2% of Rudraprayag’s lay beyond 15 km of any PHC (combined 83.7% coverage; ~94,000 people uncovered). Achieving strict NHM compliance (S1) required 18 additional PHCs at a 10-year present-value (PV) cost of ₹275 crore (incremental cost-effectiveness ratio ICER ₹19,671 per additional person covered). The coverage-optimised scenario S2 required only 6 additional PHCs, reached 96.0% coverage at ₹158 crore PV cost, and dominated all alternatives with an ICER of ₹8,373 per additional person covered. The altitude-adjusted scenario (S3) achieved near-complete coverage but at the highest cost (ICER ₹29,274). Results were most sensitive to the time horizon and recurring cost; capital cost had a small effect (±₹3 crore for ± 25% variation).

Conclusions

A small, geographically targeted expansion of the PHC network in upper Chamoli yields the largest cost-effectiveness gains and accounts for most of the avoidable access gap. Population thresholds alone are an unreliable allocation rule in mountainous districts; explicit coverage-cost optimisation should inform Health and Wellness Centre placement under Ayushman Bharat in hill regions.