Article ; Online: Implementing electronic decision-support tools to strengthen healthcare network data-driven decision-making
Archives of Public Health, Vol 78, Iss 1, Pp 1-
2020 Volume 11
Abstract: Abstract Background Ministries of health in low- and middle-income countries often lack timely quality data for data-driven decision making in healthcare networks. We describe the design and implementation of decision-support electronic tools by the ... ...
| Abstract | Abstract Background Ministries of health in low- and middle-income countries often lack timely quality data for data-driven decision making in healthcare networks. We describe the design and implementation of decision-support electronic tools by the Ministry of Health of the State of Chiapas, in Mexico, as part of Salud Mesoamerica Initiative. Methods Three electronic decision-support tools were designed through an iterative process focused on streamlined implementation: 1) to collect and report health facility data at health facilities; 2) to compile and analyze data at health district and central level; and, 3) to support stratified sampling of health facilities. Data was collected for five composite indicators measuring availability of equipment, medicines, and supplies for maternal and child health. Quality Assurance Teams collected data, evaluated results and supported quality improvement. Data was also analyzed at the central level and health districts for decision-making. Results Data from 300 health facilities in four health districts was collected and analyzed (November 2014—June 2015). The first wave revealed gaps on availability of equipment and supplies in more than half of health facilities. Electronic tools provided the ministry of health officers new ways to visualize data, identify patterns and make hypothesis on root-causes. Between the first and second measurement, the number of missing items decreased, and actions performed by quality improvement teams became more proactive. In the final measurement, 89.7—100% of all health facilities achieved all the required items for each indicator. Conclusions Our experience could help guide others seeking to implement electronic decision-support tools in low- and middle-income countries. Electronic decision-support tools supported data-driven decision-making by identifying gaps on heatmaps and graphs at the health facility, subdistrict, district or state level. Through a rapid improvement process, the Ministry of Health met targets of externally verified indicators. Using available information technology resources facilitated prompt implementation and adoption of technology. |
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| Keywords | Decision-support tools ; Maternal health ; Health information systems ; Decision-making ; Data-driven ; Evidence-based ; Public aspects of medicine ; RA1-1270 |
| Subject code | 360 |
| Language | English |
| Publishing date | 2020-06-01T00:00:00Z |
| Publisher | BMC |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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