Reduce maternel mortality A mobile health application to support health care providers to conduct and to report antenatal care in Burkina Faso Santarelli T., Capello C., Perkins J., Benski A-C., Viviano M., Petignat P., Ouedraogo A., Bargo A. , medical data Burkina Faso in 2015: health education with a focus on birth preparedness and complication Automatic and immediate flagging of pathological data entry to identify medical problems. Maternal Mortality Ratio: 371 per 100,000 live births (1) 70 % of Maternal deaths are due to complications during pregnancy and childbirth like: hemorrhage, hypertensive disorders, sepsis and abortion (2) A Medical Unit where an Individual electronic patient record is automatically generated for every participant. All the records are reread and analyzed by a physician. Maternal death represents 19% of all deaths among 15-49 year-old women (3) Study Objective: Poor-quality of the healthcare contributes to the high rate of maternal and child deaths in Burkina Faso. To preliminary assess the contribution of the PANDA system to support healthcare workers in collecting digital information and in providing complete Antenatal Care (ANC) visits according to international and national recommendations. PANDA (Pregnancy and Newborn Diagnostic Assessment) Methodology: A mobile-health (mHealth) system developed to support healthcare professionals in providing complete, standardized, quality ANC. The objective is To reduce maternal mortality, it is crucial to improve the quality of ANC. Compare two groups of women attending their first antenatal care (ANC1) visits, in the urban health center of Koupéla district. A checklist to determine if all The application was developed according to World Health Organization guidelines for ANC visits and adapted to the guidelines of the local Ministry of Health. recommended components of ANC were completed was used by an observer during The PANDA system is a low-cost and prompt solution applying mobile health technology (5,6,7). the ANC visits of the standard group and for the review of the ANC registers. Results: PANDA offers: Standardized and personalized medical care based on the woman’s characteristics. Complete medical records Continuous care Automatic and immediate emission of alarms upon pathological data entry and the indication of the procedure to follow. Consists of: Study results An m-Health application which guides healthcare workers throughout the ANC visits following pre-established and obligatory components : The rate of complete data retrieved during ANC visits : - Standard group 56.7% PANDA group 98.9% personal data medical history Reduce maternel mortality 8 ANC Standardised Reforce skills continous care effective Quality of ANC Table 2: Sociodemogaphic and clinical characteristics of the study population Variable Standard PANDA p value Age Age, mean ± SD 27.0±7.6 24.9±7.4 0.162 Age, category <20 13(24.1) 16(29.6) 0.293 20-25 12(22.2) 17(31.5) >25 29(53.7) 21(38.9) Gestity Gestity, mean ± SD 3.4±2.2 3.15±2.0 0.780 Gestity, category <2 23(42.6) 0.695 ≥2 31(57.4) 33(61.1) Parity Parity, mean ± SD 2.3±2.2 2.2± 2.0 0.516 Parity, category 36(66.7) 0.321 18(33.3) Number of children Number of children, mean ± SD 2.0±2.0 1.7±1.8 0.394 Number of children, category 35(66.0) 27(50.0) 0.489 18(34.0) Marital Status Single 1 0.118 With a partner 52 54 Missing data   Abbreviations: SD= standard deviation; Figure 3: Overall percentages of provided items according to different chapters of the ANC visit. Conclusion This initial assessment of the PANDA reported on here suggests that the use of this innovative system is able to strengthen the capacity of health care providers in providing complete ANC and in facilitating the collection of a large amount of patient information in digital format, in low-income settings. References: (4) World Health Organization, WHO recommendations on antenatal care for a positive pregnancy experience; WHO, 2016 (1) WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Trends in maternal mortality: 1990 to 2015 Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division, November 2015 (6) Prinja S, Nimesh R, Gupta A, Bahuguna P, Thakur JS, Gupta M, Singh T. Impact assessment and cost-effectiveness of m-health application used by community health workers for maternal, newborn and child health care services in rural Uttar Pradesh, India: a study protocol. Glob Health Action, May 2016 (2) Say L, Chou D, Gemmill A, Tuncalp O, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. Lancet Global Health, 2014 (7) Aranda-Jan CB, Mohutsiwa-Dibe N, Loukanova S., Systematic review on what works, what does not work and why of implementation of mobile health (mHealth) projects in Africa. BMC Public Health, 2014 ;14(1):188. (3) Institut National de la Statistique et de la Démographie, Ministère de l’Économie et des Finances, Enquête démographiques et de santé et à indicateurs multiples IV Burkina Faso 2010. Institut National de la Statistique et de la Démographie, Ministère de l’Économie et des Finances, Ouagadougou, Burkina Faso, Avril 2012 (8) World Health Organization. Bulletin of the World Health Organization, The bigger picture for e-health, WHO, May 2012