Work Description
Title: Data for a Mobile Obstetric Referral Emergency System (MORES) to reduce delays in rural Liberia Open Access Deposited
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(2023). Data for a Mobile Obstetric Referral Emergency System (MORES) to reduce delays in rural Liberia [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/acc1-xr94
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Files (Count: 6; Size: 208 KB)
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MORES_referral_readme.txt | 2023-09-28 | 2023-09-28 | 2.99 KB | Open Access |
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Baseline_Endline_Descriptive_Dat...k.pdf | 2023-09-28 | 2023-09-28 | 81.8 KB | Open Access |
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Baseline_descriptive_data_de-ide...d.csv | 2023-09-28 | 2023-09-28 | 7.22 KB | Open Access |
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Endline_descriptive_data_de-iden...d.csv | 2023-09-28 | 2023-09-28 | 9.62 KB | Open Access |
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Regression_Data_Codebook.pdf | 2023-09-28 | 2023-09-28 | 89.6 KB | Open Access |
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Regression_model_data_de-identified.csv | 2023-09-28 | 2023-09-28 | 17.2 KB | Open Access |
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Date: 28 September 2023
Dataset Title: Data for a Mobile Obstetric Referral Emergency System (MORES) to reduce delays in rural Liberia
Dataset Creators: H. Lee, JR Lori, J. Sieka, CW Reynolds
Dataset Contact: HaEun Lee haeunlee@umich.edu
Key Points:
This is a pre/post descriptive study of chart review data to examine the number of obstetric referrals from RHF to hospitals to identify common reasons for referrals, maternal and newborn outcomes, and time from RHF referral to hospital arrival.
Ethical clearance was obtained from Institutional Review Boards at all engaged sites. This includes ethical review boards from the University of Michigan and the University of Liberia.
DataData were collected from two district hospitals and 20 rural health facilities (RHF) in Bong County, Liberia at two timepoints: baseline (November 1, 2020 to April 30, 2021) and endline (August 1, 2022 to January 31, 2023).
Research Overview:
This study examined the association between a Mobile Obstetric Emergency System (MORES) implementation and referral time for obstetric emergencies as well as maternal/newborn outcomes.
MORES is a two-way communication intervention, using the WhatsApp encrypted platform, between nurses/midwives at twenty (20) rural health facilities (RHF) and providers at 2 district hospitals to assist in prompt referral to the next level of care and providing a feedback loop following the patient’s arrival.
Methodology:
A pre/post descriptive analysis was conducted on data collected from 20 RHFs and two hospitals in Bong County, Liberia. Permission was obtained from administrators at the rural health facilities and district hospitals to conduct chart reviews and collect transfer data.
A retrospective review of the hospital labor and delivery logs for baseline referrals sent from the 20 RHFs to the two district hospitals was conducted prior to implementation of the MORES intervention.
Data collection was repeated at endline, during the final six months of the study. Women with referral data from both RHFs and hospitals were matched and information including transfer time, reasons for referral, and maternal and newborn outcome were extracted.
Descriptive analysis and logistic regression models examined the relationship between the intervention’s implementation and mode of delivery, maternal outcome, newborn outcome, and transfer time from RHF to district hospital.
De-identified data enclosed
Citation:Lee, H., Dahn B., Sieka, J., Nyanplu, A., Reynolds, C., Edson, C., Lockhart, N., & Lori, J. The use of a mobile obstetric emergency system (MORES) to improve obstetric referrals in Bong County, Liberia: A pre/post study. International Journal of Gynecology & Obstetrics. In press. DOI: 10.1002/ijgo.15175
Files included as follows:
MORES referral readme.txt
Baseline_Endline Descriptive Data Codebook.pdf
Baseline descriptive data_de-identified.csv
Endline descriptive data_de-identified.csv
Regression Data Codebook.pdf
Regression model data_de-identified.csv