Evidence map›Paper›PMID 36096800›Full record

ArticleBMC medical informatics and decision making2022

Demand sensing and digital tracking for maternal child health (MCH) in Uganda: a pilot study for 'E+TRA health'.

Dawei Wang, Rhoann Kerh, Sungbum Jun, Seokcheon Lee, Roy William Mayega, Julius Ssentongo, Andualem Oumer, Md Haque, Priyanka Brunese, Yuehwern Yih

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Dawei WangSchool of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Rhoann KerhSchool of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Sungbum JunDepartment of Industrial & Systems Engineering, Dongguk University, Seoul, Republic of Korea.
Seokcheon LeeSchool of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Roy William MayegaResilientAfrica Network (RAN), School of Public Health, Makerere University, Kampala, Uganda.
Julius SsentongoResilientAfrica Network (RAN), School of Public Health, Makerere University, Kampala, Uganda.
Andualem OumerManagement Science for Health, Medford, MA, 02155, USA.
Md HaqueR B Annis School of Engineering, University of Indianapolis, Indianapolis, IN, 46227, USA.
Priyanka BruneseSchool of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Yuehwern YihSchool of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA. yih@purdue.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThirteen 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.

methodsWe 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.

resultsThe 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.

conclusionE+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.

Indexed as

Child HealthDelivery of Health CareChildFemaleHealth FacilitiesHumansPilot ProjectsUgandaDemand sensingElectronic medical record (EMR)Healthcare supply chain managementMaternal child health (MCH)

Identifiers

PMID36096800
PMCPMC9469598

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.