Cited 3 time in
Demand sensing and digital tracking for maternal child health (MCH) in Uganda: a pilot study for 'E+TRA health'
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Wang, Dawei | - |
| dc.contributor.author | Kerh, Rhoann | - |
| dc.contributor.author | Jun, Sungbum | - |
| dc.contributor.author | Lee, Seokcheon | - |
| dc.contributor.author | Mayega, Roy William | - |
| dc.contributor.author | Ssentongo, Julius | - |
| dc.contributor.author | Oumer, Andualem | - |
| dc.contributor.author | Haque, Md | - |
| dc.contributor.author | Brunese, Priyanka | - |
| dc.contributor.author | Yih, Yuehwern | - |
| dc.date.accessioned | 2023-04-27T09:40:40Z | - |
| dc.date.available | 2023-04-27T09:40:40Z | - |
| dc.date.issued | 2022-09 | - |
| dc.identifier.issn | 1472-6947 | - |
| dc.identifier.issn | 1472-6947 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/2531 | - |
| dc.description.abstract | Background Thirteen essential maternal child health (MCH) commodities, identified by the UN Commission on Life-Saving Commodities for Women and Children, could save the lives of more than 6 million women and children in Low-and-Middle-Income Countries (LMICs) if made available at the point of care. To reduce stockout of those commodities and improve the health supply chains in LMICs, the Electronic TRAcking system for healthcare commodities (E+TRA Health), an all-in-one out-of-box solution, was developed to track and manage medical commodities at lower-level health facilities in rural areas. It aims to support real-time monitoring and decision-making to (1) reduce the time needed to prepare orders, (2) reduce stockout and overstock cases of targeted medical supplies, (3) help improve patient outcomes. In this study, we adopted an integrated approach to analyze the process of information flow, identify and address critical paths of essential supplies associated with maternal health in the Ugandan health system. Methods We apply system engineering principles and work with community partners in hospitals to develop care process workflow charts (based on essential services) for the lifecycle of maternal health continuum of care. Based on this chart, we develop a cloud-based offline-compatible smart sync platform named "E+TRA Health" to triangulate (1) patient admission, diagnoses, delivery information, testing reports from laboratories, (2) inventory information from main store, stores in MCH unit, and (3) lab, to identify the critical list of medical and laboratory supplies, their lead times for procurement and then generate reports and suggested procurement plans for real time decision-making. Results The E+TRA Health platform was piloted in two Healthcare Center IV facilities in Uganda over a period of 6 months. The system collected more than 5000 patient records and managed more than 500 types of medicines. The pilot study demonstrated the functionalities of E+TRA Health and its feasibility to sense demand from point of care. Conclusion E+TRA Health is the first to triangulate supply and demand data from three different departments (main store, lab, and MCH) to forecast and generate orders automatically to meet patient demands. It is capable of generating reports required by Ministry of Health in real time compared to one-week lead-time using paper-based systems. This prompts frontline stakeholders to generate efficient, reliable and sustainable strategic healthcare plans with real time data. This system improves patient outcomes through better commodity availability by sensing true patient demands. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | BioMed Central | - |
| dc.title | Demand sensing and digital tracking for maternal child health (MCH) in Uganda: a pilot study for 'E+TRA health' | - |
| dc.type | Article | - |
| dc.publisher.location | 영국 | - |
| dc.identifier.doi | 10.1186/s12911-022-01982-8 | - |
| dc.identifier.scopusid | 2-s2.0-85137669934 | - |
| dc.identifier.wosid | 000853028900001 | - |
| dc.identifier.bibliographicCitation | BMC Medical Informatics and Decision Making, v.22, no.1 | - |
| dc.citation.title | BMC Medical Informatics and Decision Making | - |
| dc.citation.volume | 22 | - |
| dc.citation.number | 1 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Medical Informatics | - |
| dc.relation.journalWebOfScienceCategory | Medical Informatics | - |
| dc.subject.keywordPlus | DEVELOPING-COUNTRIES | - |
| dc.subject.keywordPlus | INFORMATION-SYSTEM | - |
| dc.subject.keywordPlus | MEDICAL-RECORD | - |
| dc.subject.keywordPlus | INTERVENTIONS | - |
| dc.subject.keywordAuthor | Demand sensing | - |
| dc.subject.keywordAuthor | Healthcare supply chain management | - |
| dc.subject.keywordAuthor | Maternal child health (MCH) | - |
| dc.subject.keywordAuthor | Electronic medical record (EMR) | - |
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