Development of policy research-evidence organizer and public health-policy evaluation tool (prophet): a computing paradigm for promoting evidence-informed policymaking in Nigeria
Background: in vast majority of low-and middle-income countries, performance of health systems continues to be abysmally poor with unacceptably low health outcomes. This is not unconnected with implementation of evidence-deficient health policies. Critical research evidence contributes in strengthen...
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| Vydáno v: | Advances in Computing and Engineering Ročník 4; číslo 2; s. 125 - 143 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Academy Publishing Center
08.12.2024
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| ISSN: | 2735-5977, 2735-5985 |
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| Abstract | Background: in vast majority of low-and middle-income countries, performance of health systems continues to be abysmally poor with unacceptably low health outcomes. This is not unconnected with implementation of evidence-deficient health policies. Critical research evidence contributes in strengthening health policies to ensure clear cut targets and context specifics that adequately addresses identified health challenges and inequities. This study modeled a computing paradigm for brokering knowledge translation process and assisting health policymakers in promoting evidenced-informed policymaking. It strategically evaluates and assess level of evidence content, and predict implementation prospects of health policy documents.Methods: its development process adopted object-oriented methodology for structural analysis and design specifications. Visual Basic.net and standard query language server were deployed at the front-end and back-end implementation processes respectively. The study designed an algorithm based on discrete choice experiment technique in an iterative four-scaled user-defined parametric options for rating policy features and assessment of overall policy prospect. Salient policy features/attributes were assembled as assessable variable entities. It adapted machine learning linear model to classify attributes into 6-domains to reflect the WHO promoted 6-policy cycle of a health system. Aggregated scores of policy features across all domains are utilized to compute policy overall grade-point in percentage weight.Results: PROPHET, was used to assess thirty-three (33) national health policies extracted from online repository warehousing health policy documents in Nigeria known as policy information platform. The result shows that only 11 out of the 33 (33.3%) policies passed with at least 50% grade-point fixed in this study as minimum benchmark for implementation considerations.Conclusion: This system rates policy features, assesses overall implementation prospect of policies with seamless real-time data validation and referencing across modules. PROPHET is expected to aid health policymakers in amplifying evidence-informed policymaking for improved health outcomes. Received: 30 October 2024 Accepted: 29 November 2024 Published: 08 December 2024 |
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| AbstractList | Background: in vast majority of low-and middle-income countries, performance of health systems continues to be abysmally poor with unacceptably low health outcomes. This is not unconnected with implementation of evidence-deficient health policies. Critical research evidence contributes in strengthening health policies to ensure clear cut targets and context specifics that adequately addresses identified health challenges and inequities. This study modeled a computing paradigm for brokering knowledge translation process and assisting health policymakers in promoting evidenced-informed policymaking. It strategically evaluates and assess level of evidence content, and predict implementation prospects of health policy documents.Methods: its development process adopted object-oriented methodology for structural analysis and design specifications. Visual Basic.net and standard query language server were deployed at the front-end and back-end implementation processes respectively. The study designed an algorithm based on discrete choice experiment technique in an iterative four-scaled user-defined parametric options for rating policy features and assessment of overall policy prospect. Salient policy features/attributes were assembled as assessable variable entities. It adapted machine learning linear model to classify attributes into 6-domains to reflect the WHO promoted 6-policy cycle of a health system. Aggregated scores of policy features across all domains are utilized to compute policy overall grade-point in percentage weight.Results: PROPHET, was used to assess thirty-three (33) national health policies extracted from online repository warehousing health policy documents in Nigeria known as policy information platform. The result shows that only 11 out of the 33 (33.3%) policies passed with at least 50% grade-point fixed in this study as minimum benchmark for implementation considerations.Conclusion: This system rates policy features, assesses overall implementation prospect of policies with seamless real-time data validation and referencing across modules. PROPHET is expected to aid health policymakers in amplifying evidence-informed policymaking for improved health outcomes. Received: 30 October 2024 Accepted: 29 November 2024 Published: 08 December 2024 |
| Author | Chukwu, Onyedikachi Igboji, Kingsley Otubo Uneke, Chigozie Jesse Onu, Fergus U. |
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| SubjectTerms | vidence-informed, grade-point, knowledge translation, object-oriented, policy feature/attribute, policymaking, user-defined |
| Title | Development of policy research-evidence organizer and public health-policy evaluation tool (prophet): a computing paradigm for promoting evidence-informed policymaking in Nigeria |
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