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Moving beyond silos: How do we provide distributed personalized medicine to pregnant women everywhere at scale? Insights from PRE-EMPT.

von Dadelszen, P; Magee, LA; Payne, BA; Dunsmuir, DT; Drebit, S; Dumont, GA; Miller, S; Norman, J; Pyne-Mercier, L; Shennan, AH; et al. von Dadelszen, P; Magee, LA; Payne, BA; Dunsmuir, DT; Drebit, S; Dumont, GA; Miller, S; Norman, J; Pyne-Mercier, L; Shennan, AH; Donnay, F; Bhutta, ZA; Ansermino, JM (2015) Moving beyond silos: How do we provide distributed personalized medicine to pregnant women everywhere at scale? Insights from PRE-EMPT. International Journal of Gynecology Obstetrics, 131 Suppl 1. S10-S15. ISSN 1879-3479 https://doi.org/10.1016/j.ijgo.2015.02.008
SGUL Authors: von Dadelszen, Peter Magee, Laura Ann

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Abstract

While we believe that pre-eclampsia matters-because it remains a leading cause of maternal and perinatal morbidity and mortality worldwide-we are convinced that the time has come to look beyond single clinical entities (e.g. pre-eclampsia, postpartum hemorrhage, obstetric sepsis) and to look for an integrated approach that will provide evidence-based personalized care to women wherever they encounter the health system. Accurate outcome prediction models are a powerful way to identify individuals at incrementally increased (and decreased) risks associated with a given condition. Integrating models with decision algorithms into mobile health (mHealth) applications could support community and first level facility healthcare providers to identify those women, fetuses, and newborns most at need of facility-based care, and to initiate lifesaving interventions in their communities prior to transportation. In our opinion, this offers the greatest opportunity to provide distributed individualized care at scale, and soon.

Item Type: Article
Additional Information: © 2015 Published by Elsevier Ireland Ltd. on behalf of International Federation of Gynecology and Obstetrics. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/)
Keywords: Maternal health, Mobile health, Newborn health, Outcome prediction, PRE-EMPT, Stillbirth, Adult, Algorithms, Decision Support Systems, Clinical, Female, Health Facilities, Humans, Infant, Newborn, Maternal Health Services, Pre-Eclampsia, Precision Medicine, Pregnancy, Pregnancy Complications, Risk Assessment, Telemedicine, Humans, Pregnancy Complications, Pre-Eclampsia, Risk Assessment, Telemedicine, Pregnancy, Algorithms, Decision Support Systems, Clinical, Adult, Infant, Newborn, Health Facilities, Maternal Health Services, Female, Precision Medicine, Maternal health, Mobile health, Newborn health, Outcome prediction, PRE-EMPT, Stillbirth, Obstetrics & Reproductive Medicine, 1114 Paediatrics And Reproductive Medicine
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: International Journal of Gynecology Obstetrics
ISSN: 1879-3479
Language: ENG
Dates:
DateEvent
1 October 2015Published
25 February 2015Published Online
Publisher License: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Projects:
Project IDFunderFunder ID
UNSPECIFIEDCanadian Institutes of Health Researchhttp://dx.doi.org/10.13039/501100000024
PubMed ID: 26433496
Web of Science ID: WOS:000362856600004
Go to PubMed abstract
URI: http://sgultest.da.ulcc.ac.uk/id/eprint/108355
Publisher's version: https://doi.org/10.1016/j.ijgo.2015.02.008

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