Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri
{"title":"南非卫生系统中社区主导监督的变革性影响:综合分析","authors":"Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri","doi":"10.3389/ijph.2024.1606591","DOIUrl":null,"url":null,"abstract":"Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.","PeriodicalId":504643,"journal":{"name":"International Journal of Public Health","volume":"45 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Transformative Impact of Community-Led Monitoring in the South African Health System: A Comprehensive Analysis\",\"authors\":\"Ndumiso Tshuma, Daniel Ngbede Elakpa, Clinton Moyo, M. Soboyisi, Sehlule Moyo, Sihlobosenkosi Mpofu, Martha Chadyiwa, Mokgadi Malahlela, Caroline Tiba, David Mnkandla, Tshepo M. Ndhlovu, Tsenolo Moruthoane, David D. Mphuthi, Oliver Mtapuri\",\"doi\":\"10.3389/ijph.2024.1606591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.\",\"PeriodicalId\":504643,\"journal\":{\"name\":\"International Journal of Public Health\",\"volume\":\"45 12\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Public Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/ijph.2024.1606591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Public Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/ijph.2024.1606591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Transformative Impact of Community-Led Monitoring in the South African Health System: A Comprehensive Analysis
Objectives: Community-led monitoring (CLM) is an emerging approach that empowers local communities to actively participate in data collection and decision-making processes within the health system. The research aimed to explore stakeholder perceptions of CLM data and establish a CLM Data Value Chain, covering data collection and its impact.Methods: Qualitative data were collected from stakeholders engaged in health programs in South Africa. Data analysis involved a collaborative workshop that integrated elements of affinity diagramming, thematic analysis, and the systematic coding process outlined in Giorgi’s method. The workshop fostered joint identification, co-creation of knowledge, and collaborative analysis in developing the data value chain.Results: The findings showed that CLM data enabled community-level analysis, fostering program advocacy and local collaboration. It enhanced program redesign, operational efficiency, and rapid response capabilities. Context-specific solutions emerged through the CLM Data Value Chain, promoting sustainable and efficient program implementation.Conclusion: CLM is a powerful tool for improving program implementation, quality, and advocacy in South African healthcare. It strengthens accountability, trust, and transparency by involving local communities in data-driven decision-making. CLM addresses context-specific challenges and tailors interventions to local needs.