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Asuquo DE, Attai KF, Johnson EA, Obot OU, Adeoye OS, Akwaowo CD, Ekpenyong N, Isiguzo C, Ekanem U, Motilewa O, Dan E, Umoh E, Ekpin V, Uzoka FME. Multi-criteria decision analysis method for differential diagnosis of tropical febrile diseases. Health Informatics J 2024; 30:14604582241260659. [PMID: 38860564 DOI: 10.1177/14604582241260659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
This paper employs the Analytical Hierarchy Process (AHP) to enhance the accuracy of differential diagnosis for febrile diseases, particularly prevalent in tropical regions where misdiagnosis may have severe consequences. The migration of health workers from developing countries has resulted in frontline health workers (FHWs) using inadequate protocols for the diagnosis of complex health conditions. The study introduces an innovative AHP-based Medical Decision Support System (MDSS) incorporating disease risk factors derived from physicians' experiential knowledge to address this challenge. The system's aggregate diagnostic factor index determines the likelihood of febrile illnesses. Compared to existing literature, AHP models with risk factors demonstrate superior prediction accuracy, closely aligning with physicians' suspected diagnoses. The model's accuracy ranges from 85.4% to 96.9% for various diseases, surpassing physicians' predictions for Lassa, Dengue, and Yellow Fevers. The MDSS is recommended for use by FHWs in communities lacking medical experts, facilitating timely and precise diagnoses, efficient application of diagnostic test kits, and reducing overhead expenses for administrators.
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Affiliation(s)
- Daniel E Asuquo
- Department of Information Systems, Faculty of Computing, University of Uyo, Uyo, Nigeria
| | - Kingsley F Attai
- Department of Mathematics & Computer Science, Ritman University, Ikot Ekpene, Nigeria
| | - Ekemini A Johnson
- Department of Mathematics & Computer Science, Ritman University, Ikot Ekpene, Nigeria
| | - Okure U Obot
- Department of Software Engineering, Faculty of Computing, University of Uyo, Uyo, Nigeria
| | - Olufemi S Adeoye
- Department of Data Science, Faculty of Computing, University of Uyo, Uyo, Nigeria
| | - Christie Divine Akwaowo
- Community Medicine Department, University of Uyo, Uyo, Nigeria
- Health Systems Research Hub, University of Uyo Teaching Hospital, Uyo, Nigeria
| | - Nnette Ekpenyong
- Community Health Department, University of Calabar, Calabar, Nigeria
| | | | - Uwemedimbuk Ekanem
- Community Medicine Department, University of Uyo, Uyo, Nigeria
- Institute of Health Research and Development, University of Uyo Teaching Hospital, Uyo, Nigeria
| | - Olugbemi Motilewa
- Community Medicine Department, University of Uyo, Uyo, Nigeria
- Health Systems Research Hub, University of Uyo Teaching Hospital, Uyo, Nigeria
- Institute of Health Research and Development, University of Uyo Teaching Hospital, Uyo, Nigeria
| | - Emem Dan
- Health Systems Research Hub, University of Uyo Teaching Hospital, Uyo, Nigeria
| | - Edidiong Umoh
- Health Systems Research Hub, University of Uyo Teaching Hospital, Uyo, Nigeria
| | - Victory Ekpin
- Health Systems Research Hub, University of Uyo Teaching Hospital, Uyo, Nigeria
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Kujawski E. Comment on "Feasibility of Measuring Preferences for Chemotherapy Among Early-Stage Breast Cancer Survivors Using a Direct Rank Ordering Multicriteria Decision Analysis Versus a Time Trade-Off". THE PATIENT 2021; 14:145-146. [PMID: 33169314 DOI: 10.1007/s40271-020-00478-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/29/2020] [Indexed: 06/11/2023]
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