Junxing Chay, Rebecca J Su, Jemima H Kamano, Benjamin Andama, Gerald S Bloomfield, Allison K Delong, Carol R Horowitz, Diana Menya, Richard Mugo, Vitalis Orango, Sonak D Pastakia, Cleophas Wanyonyi, Rajesh Vedanthan, Eric A Finkelstein
{"title":"肯尼亚管理高血压的团体医疗访问和小额信贷干预与常规护理的成本效益对比:对团体综合护理创收桥梁(BIGPIC)试验数据的二次建模分析。","authors":"Junxing Chay, Rebecca J Su, Jemima H Kamano, Benjamin Andama, Gerald S Bloomfield, Allison K Delong, Carol R Horowitz, Diana Menya, Richard Mugo, Vitalis Orango, Sonak D Pastakia, Cleophas Wanyonyi, Rajesh Vedanthan, Eric A Finkelstein","doi":"10.1016/S2214-109X(24)00188-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Bridging Income Generation with Group Integrated Care (BIGPIC) trial in rural Kenya showed that integrating usual care with group medical visits or microfinance interventions reduced systolic blood pressure and cardiovascular risk in participants. We aimed to estimate the incremental cost-effectiveness of three BIGPIC interventions for a modelled cohort and by sex, as well as the cost of implementing these interventions.</p><p><strong>Methods: </strong>For this analysis, we used data collected during the BIGPIC trial, a four-group, cluster-randomised trial conducted in the western Kenyan catchment area of the Academic Model Providing Access to Healthcare. BIGPIC enrolled participants from 24 rural health facilities in rural western Kenya aged 35 years or older with either increased blood pressure or diabetes. Participants were assigned to receive either usual care, group medical visits, microfinance, or a combination of group medical visits and microfinance (GMV-MF). Our model estimated the incremental cost-effectiveness of the three BIGPIC interventions via seven health states (ie, a hypertensive state, five chronic cardiovascular-disease states, and a death state) by simulating transitions between health states for a hypothetical cohort of individuals with hypertension on the basis of QRISK3 scores. In every cycle, participants accrued costs and disability-adjusted life-years (DALYs) associated with their health state. Incremental cost-effectiveness ratios (ICERs) were calculated for the entire modelled cohort and by sex by dividing the incremental cost by the incremental effectiveness of the next most expensive intervention. The main outcome of this analysis was ICERs for each intervention evaluated. This analysis is registered at ClinicalTrials.gov (NCT02501746).</p><p><strong>Findings: </strong>Between Feb 6, 2017, and Dec 29, 2019, 2890 people were recruited to the BIGPIC trial. 2020 (69·9%) of 2890 participants were female and 870 (30·1%) were male. At baseline, mean QRISK3 score was 11·5 (95% CI 11·1-11·9) for the trial population, 11·9 (11·5-12·2) for male participants, and 11·3 (11·0-11·6) for female participants. For the population of Kenya, group medical visits were estimated to cost US$7 more per individual than usual care and result in 0·005 more DALYs averted (ICER $1455 per DALY averted). Microfinance was estimated to cost $19 more than group medical visits but was only estimated to avert 0·001 more DALYs. Relative to group medical visits, GMV-MF was estimated to cost $29 more and avert 0·009 more DALYs ($3235 per DALY averted). Relative to usual care, GMV-MF was estimated to cost $37 more and avert 0·014 more DALYs ($2601 per DALY averted). In the first year of the intervention, usual care was estimated to be the least expensive intervention to implement ($87 per participant; $10 238 per health-facility catchment area [HFCA]), then group medical visits ($99 per participant; $12 268 per HFCA), then microfinance ($120 per participant; $14 172 per HFCA), with GMV-MF estimated to be the most expensive intervention to implement ($139 per participant; $16 913 per HFCA).</p><p><strong>Interpretation: </strong>Group medical visits and GMV-MF were estimated to be cost-effective strategies to improve blood-pressure control in rural Kenya. However, which intervention to pursue depends on resource availability. Policy makers should consider these factors, in addition to sex differences in programme effectiveness, when selecting optimal implementation strategies.</p><p><strong>Funding: </strong>US National Institutes of Health.</p>","PeriodicalId":48783,"journal":{"name":"Lancet Global Health","volume":null,"pages":null},"PeriodicalIF":19.9000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11303878/pdf/","citationCount":"0","resultStr":"{\"title\":\"Cost-effectiveness of group medical visits and microfinance interventions versus usual care to manage hypertension in Kenya: a secondary modelling analysis of data from the Bridging Income Generation with Group Integrated Care (BIGPIC) trial.\",\"authors\":\"Junxing Chay, Rebecca J Su, Jemima H Kamano, Benjamin Andama, Gerald S Bloomfield, Allison K Delong, Carol R Horowitz, Diana Menya, Richard Mugo, Vitalis Orango, Sonak D Pastakia, Cleophas Wanyonyi, Rajesh Vedanthan, Eric A Finkelstein\",\"doi\":\"10.1016/S2214-109X(24)00188-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The Bridging Income Generation with Group Integrated Care (BIGPIC) trial in rural Kenya showed that integrating usual care with group medical visits or microfinance interventions reduced systolic blood pressure and cardiovascular risk in participants. We aimed to estimate the incremental cost-effectiveness of three BIGPIC interventions for a modelled cohort and by sex, as well as the cost of implementing these interventions.</p><p><strong>Methods: </strong>For this analysis, we used data collected during the BIGPIC trial, a four-group, cluster-randomised trial conducted in the western Kenyan catchment area of the Academic Model Providing Access to Healthcare. BIGPIC enrolled participants from 24 rural health facilities in rural western Kenya aged 35 years or older with either increased blood pressure or diabetes. Participants were assigned to receive either usual care, group medical visits, microfinance, or a combination of group medical visits and microfinance (GMV-MF). Our model estimated the incremental cost-effectiveness of the three BIGPIC interventions via seven health states (ie, a hypertensive state, five chronic cardiovascular-disease states, and a death state) by simulating transitions between health states for a hypothetical cohort of individuals with hypertension on the basis of QRISK3 scores. In every cycle, participants accrued costs and disability-adjusted life-years (DALYs) associated with their health state. Incremental cost-effectiveness ratios (ICERs) were calculated for the entire modelled cohort and by sex by dividing the incremental cost by the incremental effectiveness of the next most expensive intervention. The main outcome of this analysis was ICERs for each intervention evaluated. This analysis is registered at ClinicalTrials.gov (NCT02501746).</p><p><strong>Findings: </strong>Between Feb 6, 2017, and Dec 29, 2019, 2890 people were recruited to the BIGPIC trial. 2020 (69·9%) of 2890 participants were female and 870 (30·1%) were male. At baseline, mean QRISK3 score was 11·5 (95% CI 11·1-11·9) for the trial population, 11·9 (11·5-12·2) for male participants, and 11·3 (11·0-11·6) for female participants. For the population of Kenya, group medical visits were estimated to cost US$7 more per individual than usual care and result in 0·005 more DALYs averted (ICER $1455 per DALY averted). Microfinance was estimated to cost $19 more than group medical visits but was only estimated to avert 0·001 more DALYs. Relative to group medical visits, GMV-MF was estimated to cost $29 more and avert 0·009 more DALYs ($3235 per DALY averted). Relative to usual care, GMV-MF was estimated to cost $37 more and avert 0·014 more DALYs ($2601 per DALY averted). 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Cost-effectiveness of group medical visits and microfinance interventions versus usual care to manage hypertension in Kenya: a secondary modelling analysis of data from the Bridging Income Generation with Group Integrated Care (BIGPIC) trial.
Background: The Bridging Income Generation with Group Integrated Care (BIGPIC) trial in rural Kenya showed that integrating usual care with group medical visits or microfinance interventions reduced systolic blood pressure and cardiovascular risk in participants. We aimed to estimate the incremental cost-effectiveness of three BIGPIC interventions for a modelled cohort and by sex, as well as the cost of implementing these interventions.
Methods: For this analysis, we used data collected during the BIGPIC trial, a four-group, cluster-randomised trial conducted in the western Kenyan catchment area of the Academic Model Providing Access to Healthcare. BIGPIC enrolled participants from 24 rural health facilities in rural western Kenya aged 35 years or older with either increased blood pressure or diabetes. Participants were assigned to receive either usual care, group medical visits, microfinance, or a combination of group medical visits and microfinance (GMV-MF). Our model estimated the incremental cost-effectiveness of the three BIGPIC interventions via seven health states (ie, a hypertensive state, five chronic cardiovascular-disease states, and a death state) by simulating transitions between health states for a hypothetical cohort of individuals with hypertension on the basis of QRISK3 scores. In every cycle, participants accrued costs and disability-adjusted life-years (DALYs) associated with their health state. Incremental cost-effectiveness ratios (ICERs) were calculated for the entire modelled cohort and by sex by dividing the incremental cost by the incremental effectiveness of the next most expensive intervention. The main outcome of this analysis was ICERs for each intervention evaluated. This analysis is registered at ClinicalTrials.gov (NCT02501746).
Findings: Between Feb 6, 2017, and Dec 29, 2019, 2890 people were recruited to the BIGPIC trial. 2020 (69·9%) of 2890 participants were female and 870 (30·1%) were male. At baseline, mean QRISK3 score was 11·5 (95% CI 11·1-11·9) for the trial population, 11·9 (11·5-12·2) for male participants, and 11·3 (11·0-11·6) for female participants. For the population of Kenya, group medical visits were estimated to cost US$7 more per individual than usual care and result in 0·005 more DALYs averted (ICER $1455 per DALY averted). Microfinance was estimated to cost $19 more than group medical visits but was only estimated to avert 0·001 more DALYs. Relative to group medical visits, GMV-MF was estimated to cost $29 more and avert 0·009 more DALYs ($3235 per DALY averted). Relative to usual care, GMV-MF was estimated to cost $37 more and avert 0·014 more DALYs ($2601 per DALY averted). In the first year of the intervention, usual care was estimated to be the least expensive intervention to implement ($87 per participant; $10 238 per health-facility catchment area [HFCA]), then group medical visits ($99 per participant; $12 268 per HFCA), then microfinance ($120 per participant; $14 172 per HFCA), with GMV-MF estimated to be the most expensive intervention to implement ($139 per participant; $16 913 per HFCA).
Interpretation: Group medical visits and GMV-MF were estimated to be cost-effective strategies to improve blood-pressure control in rural Kenya. However, which intervention to pursue depends on resource availability. Policy makers should consider these factors, in addition to sex differences in programme effectiveness, when selecting optimal implementation strategies.
期刊介绍:
The Lancet Global Health is an online publication that releases monthly open access (subscription-free) issues.Each issue includes original research, commentary, and correspondence.In addition to this, the publication also provides regular blog posts.
The main focus of The Lancet Global Health is on disadvantaged populations, which can include both entire economic regions and marginalized groups within prosperous nations.The publication prefers to cover topics related to reproductive, maternal, neonatal, child, and adolescent health; infectious diseases (including neglected tropical diseases); non-communicable diseases; mental health; the global health workforce; health systems; surgery; and health policy.