{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T12:00:19Z","timestamp":1780056019677,"version":"3.54.0"},"reference-count":84,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:p>We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor\/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.<\/jats:p>","DOI":"10.1177\/00375497211030931","type":"journal-article","created":{"date-parts":[[2021,7,19]],"date-time":"2021-07-19T02:15:32Z","timestamp":1626660932000},"page":"183-208","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":22,"title":["Simulation modeling and analysis of primary health center operations"],"prefix":"10.1177","volume":"98","author":[{"given":"Mohd","family":"Shoaib","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6517-9142","authenticated-orcid":false,"given":"Varun","family":"Ramamohan","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2021,7,18]]},"reference":[{"key":"bibr1-00375497211030931","doi-asserted-by":"publisher","DOI":"10.4103\/2347-9019.129126"},{"key":"bibr2-00375497211030931","unstructured":"The World Bank. 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