Data Intelligence: Dashboard to accelerate the decision-making process in CDMX


Problem: The transition to a more modern healthcare system in Mexico City offers an opportunity to move from paper-based records to electronic systems, significantly increasing the efficiency and quality of healthcare services. With a growing recognition of the importance of data culture and digital literacy, data can now be used not only to track outcomes like hospitalizations and consultations, but also to establish key indicators that drive better decision-making and improve  healthcare delivery.

Solution: To address this need, the Health Information and Institutional Systems Directorate of SEDESA developed a dynamic dashboard, with support from the Movement Health Foundation and its partners Microsoft and the Copenhagen Institute for Futures Studies (CIFS). This tool offers a comprehensive visualization of data from the 35 hospitals managed by the Health Department, enabling more strategic analysis to optimize decision-making and improve the efficiency of healthcare management.

Impact: The implementation of this dynamic dashboard will transform the healthcare system by providing decision-makers and the public with key metrics and indicators on access and coverage, supporting more informed decisions. With real-time data on efficiency and quality, SEDESA will be able to conduct comparative analyses with other healthcare systems worldwide. Additionally, this solution will foster collaboration, promote transparency, and allow for effective monitoring of resource performance, as other organizations follow suit and share data to have an even more comprehensive view.As other regions in the country face challenges similar to those in Mexico City, the systematic use of this dashboard will help develop interoperability frameworks for unified analysis across the healthcare system using up-to-date information. Both governmental organizations and various healthcare providers will benefit from a tool that streamlines processes and facilitates optimal resource allocation based on clear,  well-defined, and comparable needs.