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The MES aimed to expand hemodialysis capacity by centralizing procurement, standardizing equipment, and ensuring maintenance across all 47 counties. This study provides the first national evaluation of hemodialysis performance under the MES model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a multi-year retrospective analysis of 54 public hospitals equipped through the MES, six years after implementation, using data from the MES contract, the MES final survey, NHIF reimbursement schedules, and the 2019 Population Census. Hemodialysis system performance was assessed across four domains, including capacity, utilization, reporting accuracy, and cost efficiency, using descriptive statistics, time series trends, and discrepancy analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 54 hemodialysis centers equipped with 305 machines were established across all 47 counties, resulting in national densities of 1.14 centers and 6.41 machines per million people. Machine density varied more than 30-fold across counties. Between June 2015 and April 2021, 392,497 hemodialysis sessions were conducted, with monthly utilization increasing by 376%, from 2,100 sessions in June 2015 to 10,173 in April 2021. Time-series regression showed a significant upward trend (+75.5 sessions per month, R\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.721), with significant effects of year (F\u2009=\u2009258.42,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and calendar month (F\u2009=\u20095.00,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), and two periods of acceleration in June 2016 and January 2020.\n                    <\/jats:p>\n                    <jats:p>Facility throughput ranged from 217 to 79,202 sessions, and 63% of hospitals operated at less than 50% of their machine capacity. Machine-logged session counts exceeded register-based counts by more than 30% in 79% of hospitals, with a mean absolute percentage error of 180.41%. County-level utilization ranged from 89 to 4,363 sessions per million people, a 49-fold difference. The MES program reached breakeven in month 70, with a projected return on investment of 19.76% by month 84.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The MES significantly increased Kenya\u2019s public hemodialysis capacity and supported rapid nationwide growth in service use. However, disparities in geography, facilities, and documentation persisted, with many hospitals operating below capacity and inconsistent reporting. Although the program broke even financially and had a positive return on investment, facility performance varied widely. These results show that expanding infrastructure alone was not enough to achieve equity or efficient hemodialysis service delivery, highlighting the need to improve staffing, data quality, and system coordination to make the most of future renal care investments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12913-026-15127-4","type":"journal-article","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T19:04:09Z","timestamp":1784401449000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Transforming hemodialysis access in Kenya: a national assessment of the Managed Equipment Services model"],"prefix":"10.1186","volume":"26","author":[{"given":"Ephantus","family":"Njagi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sasha","family":"Wawira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonah","family":"Onentiah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenneth","family":"Iloka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laban","family":"Thiga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Muraguri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,18]]},"reference":[{"issue":"7","key":"15127_CR1","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1038\/s41581-024-00820-6","volume":"20","author":"A Francis","year":"2024","unstructured":"Francis A, Harhay MN, Ong ACM, Tummalapalli SL, Ortiz A, Fogo AB, et al. 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Approval for data access was obtained from the Ministry of Health, and ethical clearance was granted by the Kenyatta National Hospital\u2013University of Nairobi Ethics and Research Committee (KNH\u2013UoN ERC) under reference number KNH\u2011UoN ERC P571\/06\/2025. Research involving human data was conducted in accordance with the Declaration of Helsinki. Since the study relied solely on de-identified, aggregated secondary data, informed consent was not required.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No individual\u2011level or identifiable data are presented in this manuscript. Consent for publication was therefore not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"1412"}}