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| Funder | EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT |
|---|---|
| Recipient Organization | Weill Medical Coll of Cornell Univ |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Sep 02, 2022 |
| Duration | 366 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10477455 |
PROJECT SUMMARY 1 Women in the ethnic minority, Chin state of western Myanmar have one of the highest maternal mortality rates 2 in Asia (357 per 100,000 live births). Currently, less than 10% of births take place in a healthcare facility 3 because most women have to travel two or more days on foot through mountainous regions to reach one. Lack
4 of prenatal care and obstetric ultrasound means that high-risk conditions, including breech position and 5 multiple births, are often not identified prior to the woman presenting in labor. The dual objectives of our 6 proposed “mHealth and Mobile Ultrasound for Mothers in Myanmar” (mMUMM) stepped-wedge cluster
7 randomized trial are to evaluate: (1) the utility of using a mobile health (mHealth) application to collect 8 population surveillance data, and (2) the effectiveness of using a portable ultrasound device to improve the 9 rates of attended births and successful transfers for high-risk pregnancies to a hospital. The mMUMM trial
10 responds directly to the priorities of Health and Hope Myanmar (HHM), the only nonprofit organization 11 providing healthcare in the Chin state. Over the last 10-years, HHM has built comprehensive health, 12 agriculture, and education programs in western Myanmar, including the training of 834 CHWs and 166
13 traditional birth attendants. HHM is currently expanding its focus to mHealth-based population health 14 surveillance data collection following millions of dollars of investment in telecommunications infrastructure 15 across Myanmar, including the Chin state, by the government and international agencies. In the R21 phase we
16 will 1) evaluate the quality of data collected using a mHealth population health surveillance application 17 (Survey123), refine to optimize quality, and 2) assess data quality and the feasibility of collecting and 18 interpreting ultrasound images by local midwives. In the R33 phase we will randomize 55 villages, evaluate the
19 effectiveness of mHealth population surveillance and mHealth population surveillance plus ultrasound on rates 20 of attended or transferred births. Our central hypothesis is that the combination of both mHealth 21 surveillance and ultrasound will increase the composite outcome of prevalence of attended births and
22 successful transfers for high-risk pregnancies to a hospital. Through earlier recognition, midwives can plan to 23 attend low-risk births in the villages and transfer women with high-risk presentations to a hospital (far in 24 advance of the birth) that can conduct surgical procedures, including a cesarean section. The long-term goals
25 of this program of research are to improve the quality and timeliness of population health surveillance, and 26 improve maternal and child outcomes in this remote, low-resource region of Western Myanmar.
Weill Medical Coll of Cornell Univ
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