{"title":"在奥约州的设施和地方政府层面使用国家卫生管理信息系统(NHMS)信息:人工智能(AI)工具案例。","authors":"O G Oluwatosin, O A Popoola, E T Owoaje","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The National Health Management Information System (NHMIS) is vital for healthcare decision-making in Nigeria. However, effectiveness requires optimal information use including at the facility and local government level.</p><p><strong>Objective: </strong>We assessed the use of information derived from the NHMIS and factors associated with information use at selected facilities and Local Government Areas (LGAs) in Oyo State.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted in 54 facilities and nine LGAs among healthcare workers responsible for data management and reporting selected by multistage techniques. The Performance of Routine Information System Management (PRISM) tool which assesses seven domains of information use was utilised. Information used was summarised as a mean score on a 0 - 100-point scale with 95% confidence limits. A linear regression was fitted to identify predictors of information use at α - 0.05.</p><p><strong>Results: </strong>The use of information at the facility and LGA level were 42.2 ± 28.8 (95%CI 34.3 - 50.0) and 58.5 ± 39.8 (95%CI 28.0 -89.1) respectively. The positive predictors of use of information were the promotion of problem-solving skills β=0.776 (95%CI 0.031,1.522), the processes of checking data accuracy β=0.715 (95%CI 0.352,1.077), data collection β=1.080 (95% I 0.565,1.594), data transmission β=0.945 (95%CI 0.045, 1.846), data analysis β= 0.636 (95%CI 0.306, 0.966) and data display β=0.488 (95%CI 0.089,0.887).</p><p><strong>Conclusion: </strong>Information use is modest at the facility and LGA level and depends on problem-solving, data collection, data analysis, and data display capacity which is often limited at these healthcare levels. AI tools that bridge these capacity gaps may improve NHMIS information use at the facility and LGA levels.</p>","PeriodicalId":23680,"journal":{"name":"West African journal of medicine","volume":"41 11 Suppl 1","pages":"S41"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"USE OF NATIONAL HEALTH MANAGEMENT INFORMATION SYSTEM (NHMIS) INFORMATION AT FACILITY AND LOCAL GOVERNMENT LEVEL IN OYO STATE: A CASE FOR ARTIFICIAL INTELLIGENCE (AI) TOOLS.\",\"authors\":\"O G Oluwatosin, O A Popoola, E T Owoaje\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>The National Health Management Information System (NHMIS) is vital for healthcare decision-making in Nigeria. However, effectiveness requires optimal information use including at the facility and local government level.</p><p><strong>Objective: </strong>We assessed the use of information derived from the NHMIS and factors associated with information use at selected facilities and Local Government Areas (LGAs) in Oyo State.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted in 54 facilities and nine LGAs among healthcare workers responsible for data management and reporting selected by multistage techniques. The Performance of Routine Information System Management (PRISM) tool which assesses seven domains of information use was utilised. Information used was summarised as a mean score on a 0 - 100-point scale with 95% confidence limits. A linear regression was fitted to identify predictors of information use at α - 0.05.</p><p><strong>Results: </strong>The use of information at the facility and LGA level were 42.2 ± 28.8 (95%CI 34.3 - 50.0) and 58.5 ± 39.8 (95%CI 28.0 -89.1) respectively. The positive predictors of use of information were the promotion of problem-solving skills β=0.776 (95%CI 0.031,1.522), the processes of checking data accuracy β=0.715 (95%CI 0.352,1.077), data collection β=1.080 (95% I 0.565,1.594), data transmission β=0.945 (95%CI 0.045, 1.846), data analysis β= 0.636 (95%CI 0.306, 0.966) and data display β=0.488 (95%CI 0.089,0.887).</p><p><strong>Conclusion: </strong>Information use is modest at the facility and LGA level and depends on problem-solving, data collection, data analysis, and data display capacity which is often limited at these healthcare levels. AI tools that bridge these capacity gaps may improve NHMIS information use at the facility and LGA levels.</p>\",\"PeriodicalId\":23680,\"journal\":{\"name\":\"West African journal of medicine\",\"volume\":\"41 11 Suppl 1\",\"pages\":\"S41\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"West African journal of medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"West African journal of medicine","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
USE OF NATIONAL HEALTH MANAGEMENT INFORMATION SYSTEM (NHMIS) INFORMATION AT FACILITY AND LOCAL GOVERNMENT LEVEL IN OYO STATE: A CASE FOR ARTIFICIAL INTELLIGENCE (AI) TOOLS.
Introduction: The National Health Management Information System (NHMIS) is vital for healthcare decision-making in Nigeria. However, effectiveness requires optimal information use including at the facility and local government level.
Objective: We assessed the use of information derived from the NHMIS and factors associated with information use at selected facilities and Local Government Areas (LGAs) in Oyo State.
Methods: A cross-sectional survey was conducted in 54 facilities and nine LGAs among healthcare workers responsible for data management and reporting selected by multistage techniques. The Performance of Routine Information System Management (PRISM) tool which assesses seven domains of information use was utilised. Information used was summarised as a mean score on a 0 - 100-point scale with 95% confidence limits. A linear regression was fitted to identify predictors of information use at α - 0.05.
Results: The use of information at the facility and LGA level were 42.2 ± 28.8 (95%CI 34.3 - 50.0) and 58.5 ± 39.8 (95%CI 28.0 -89.1) respectively. The positive predictors of use of information were the promotion of problem-solving skills β=0.776 (95%CI 0.031,1.522), the processes of checking data accuracy β=0.715 (95%CI 0.352,1.077), data collection β=1.080 (95% I 0.565,1.594), data transmission β=0.945 (95%CI 0.045, 1.846), data analysis β= 0.636 (95%CI 0.306, 0.966) and data display β=0.488 (95%CI 0.089,0.887).
Conclusion: Information use is modest at the facility and LGA level and depends on problem-solving, data collection, data analysis, and data display capacity which is often limited at these healthcare levels. AI tools that bridge these capacity gaps may improve NHMIS information use at the facility and LGA levels.