1. 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 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 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