Design of decision support system incorporating data mining algorithms for strengthening maternal and child health systems: Inclusion of systems-thinking approach
* Corresponding author
Reduction of maternal and infant mortality rates has been recognised as one of the important goals of this century. Both coverage improvement and inequity reduction have been set up as millennium targets. Despite the availability of effective interventions, maternal and child healthcare conditions are not improving in developing countries because of inefficiently functioning health systems. Knowledge generation about behaviors of health system building blocks on the implementation of several healthcare interventions will help policymakers to design situation-specific and strategic interventions. A decision support system has been devised incorporating data mining algorithms which would help to understand the condition of maternal and child healthcare indicators; educational, socio, and economic situations; healthcare status; and healthcare service blocks and their relationships with each other. In this paper, the design of the DSS has been discussed elaborately. To enhance a system-wide understanding of the healthcare system, all healthcare-related factors have been incorporated into this system. Three knowledge generation modules have been prepared by utilizing different visualization and data mining algorithms.
Partha Saha. Design of decision support system incorporating data mining algorithms for strengthening maternal and child health systems: Inclusion of systems-thinking approach. Cardiometry; Issue 20; November 2021; p.100-109; DOI: 10.18137/cardiometry.2021.20.100109; Available from: https://www.cardiometry.net/issues/no20-november-2021/design-decision-support