Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis
Abstract Background Improving health system efficiency is a key strategy to increase health system performance and accelerate progress towards Universal Health Coverage. In 2013, Kenya transitioned into a devolved system of government granting county governments autonomy over budgets and priorities....
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| Format: | Article |
| Language: | English |
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BMC
2021-12-01
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| Series: | Cost Effectiveness and Resource Allocation |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12962-021-00332-1 |
| _version_ | 1818723467797725184 |
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| author | Edwine Barasa Anita Musiega Kara Hanson Lizah Nyawira Andrew Mulwa Sassy Molyneux Isabel Maina Benjamin Tsofa Charles Normand Julie Jemutai |
| author_facet | Edwine Barasa Anita Musiega Kara Hanson Lizah Nyawira Andrew Mulwa Sassy Molyneux Isabel Maina Benjamin Tsofa Charles Normand Julie Jemutai |
| author_sort | Edwine Barasa |
| collection | DOAJ |
| description | Abstract Background Improving health system efficiency is a key strategy to increase health system performance and accelerate progress towards Universal Health Coverage. In 2013, Kenya transitioned into a devolved system of government granting county governments autonomy over budgets and priorities. We assessed the level and determinants of technical efficiency of the 47 county health systems in Kenya. Methods We carried out a two-stage data envelopment analysis (DEA) using Simar and Wilson’s double bootstrap method using data from all the 47 counties in Kenya. In the first stage, we derived the bootstrapped DEA scores using an output orientation. We used three input variables (Public county health expenditure, Private county health expenditure, number of healthcare facilities), and one outcome variable (Disability Adjusted Life Years) using 2018 data. In the second stage, the bias corrected technical inefficiency scores were regressed against 14 exogenous factors using a bootstrapped truncated regression. Results The mean bias-corrected technical efficiency score of the 47 counties was 69.72% (95% CI 66.41–73.01%), indicating that on average, county health systems could increase their outputs by 30.28% at the same level of inputs. County technical efficiency scores ranged from 42.69% (95% CI 38.11–45.26%) to 91.99% (95% CI 83.78–98.95%). Higher HIV prevalence was associated with greater technical inefficiency of county health systems, while higher population density, county absorption of development budgets, and quality of care provided by healthcare facilities were associated with lower county health system inefficiency. Conclusions The findings from this analysis highlight the need for county health departments to consider ways to improve the efficiency of county health systems. Approaches could include prioritizing resources to interventions that will reduce high chronic disease burden, filling structural quality gaps, implementing interventions to improve process quality, identifying the challenges to absorption rates and reforming public finance management systems to enhance their efficiency. |
| first_indexed | 2024-12-17T21:10:59Z |
| format | Article |
| id | doaj.art-83a0dde0138d45e2aa55c2c44e0de0c6 |
| institution | Directory Open Access Journal |
| issn | 1478-7547 |
| language | English |
| last_indexed | 2024-12-17T21:10:59Z |
| publishDate | 2021-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Cost Effectiveness and Resource Allocation |
| spelling | doaj.art-83a0dde0138d45e2aa55c2c44e0de0c62022-12-21T21:32:28ZengBMCCost Effectiveness and Resource Allocation1478-75472021-12-0119111110.1186/s12962-021-00332-1Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysisEdwine Barasa0Anita Musiega1Kara Hanson2Lizah Nyawira3Andrew Mulwa4Sassy Molyneux5Isabel Maina6Benjamin Tsofa7Charles Normand8Julie Jemutai9Health Economics Research Unit, KEMRI-Wellcome Trust Research ProgrammeHealth Economics Research Unit, KEMRI-Wellcome Trust Research ProgrammeFaculty of Public Health and Policy, London School of Hygiene and Tropical MedicineHealth Economics Research Unit, KEMRI-Wellcome Trust Research ProgrammeCounty Department of Health, Makueni County GovernmentHealth Systems and Research Ethics Department, KEMRI-Wellcome Trust Research ProgrammeHealth Financing Department, Ministry of HealthHealth Systems and Research Ethics Department, KEMRI-Wellcome Trust Research ProgrammeCentre for Health Policy and Management, Trinity College, The University of DublinHealth Economics Research Unit, KEMRI-Wellcome Trust Research ProgrammeAbstract Background Improving health system efficiency is a key strategy to increase health system performance and accelerate progress towards Universal Health Coverage. In 2013, Kenya transitioned into a devolved system of government granting county governments autonomy over budgets and priorities. We assessed the level and determinants of technical efficiency of the 47 county health systems in Kenya. Methods We carried out a two-stage data envelopment analysis (DEA) using Simar and Wilson’s double bootstrap method using data from all the 47 counties in Kenya. In the first stage, we derived the bootstrapped DEA scores using an output orientation. We used three input variables (Public county health expenditure, Private county health expenditure, number of healthcare facilities), and one outcome variable (Disability Adjusted Life Years) using 2018 data. In the second stage, the bias corrected technical inefficiency scores were regressed against 14 exogenous factors using a bootstrapped truncated regression. Results The mean bias-corrected technical efficiency score of the 47 counties was 69.72% (95% CI 66.41–73.01%), indicating that on average, county health systems could increase their outputs by 30.28% at the same level of inputs. County technical efficiency scores ranged from 42.69% (95% CI 38.11–45.26%) to 91.99% (95% CI 83.78–98.95%). Higher HIV prevalence was associated with greater technical inefficiency of county health systems, while higher population density, county absorption of development budgets, and quality of care provided by healthcare facilities were associated with lower county health system inefficiency. Conclusions The findings from this analysis highlight the need for county health departments to consider ways to improve the efficiency of county health systems. Approaches could include prioritizing resources to interventions that will reduce high chronic disease burden, filling structural quality gaps, implementing interventions to improve process quality, identifying the challenges to absorption rates and reforming public finance management systems to enhance their efficiency.https://doi.org/10.1186/s12962-021-00332-1EfficiencyDecentralizationDevolutionDEAKenya |
| spellingShingle | Edwine Barasa Anita Musiega Kara Hanson Lizah Nyawira Andrew Mulwa Sassy Molyneux Isabel Maina Benjamin Tsofa Charles Normand Julie Jemutai Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis Cost Effectiveness and Resource Allocation Efficiency Decentralization Devolution DEA Kenya |
| title | Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis |
| title_full | Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis |
| title_fullStr | Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis |
| title_full_unstemmed | Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis |
| title_short | Level and determinants of county health system technical efficiency in Kenya: two stage data envelopment analysis |
| title_sort | level and determinants of county health system technical efficiency in kenya two stage data envelopment analysis |
| topic | Efficiency Decentralization Devolution DEA Kenya |
| url | https://doi.org/10.1186/s12962-021-00332-1 |
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