IMPLEMENTATING BUSINESS INTELLIGENCE SOLUTIONS IN THE HEALTH SECTOR: LESSONS FROM THE KENYA HMIS PROJECT

Mwenda Gitonga, Ali Karisa, Brian Wakhutu, Mysha Sissine, Joshua Oiro, Donna Medeiros, Bobby Jefferson

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Keywords

Public Health Informatics; Data Demand and InformationUse; Evidence Based Decision Making; Data Mart; DataWarehouse; Business Intelligence;

Abstract

Background Futures Group through a CDC co-operative agreement has been working with the Kenya Ministry of Health (MoH) to develop a patient-level data warehouse and business intelligence (BI) solutions to ensure that electronic patient care data is used in real-time decision making. Challenge While the Kenya MoH has been investing in information communication technology (ICT) implementations to improve service delivery, a number of these implementations are silos leading to multiple un- integrated systems. This has consequently deprived policy makers and the general public of a rich and centralized repository of data for country level business intelligence, analytics and reporting capabilities. Response To address this challenge, the Kenya MoH and Futures Group have started development of a HIV centric data mart to further understanding requirements, design, implementation and data security needs. Lessons Learnt The computerization of patient medical records together with the goodwill of stakeholders in the Kenya MoH has made it possible to consolidate patient data for decision making in a centralized data repository. There continues to be a need for rigorous processes to be undertaken in development of data governance policies around patient data security and administration. Next Steps In order to develop a meaningful and sustainable data warehouse, the Kenya HMIS project aims at increasing technical capacity within the ministry through workshops and other stakeholder engagement forums. A culture of data demand and information use is also being cultivated at health facilities with an aim of not only developing analytics capacity at the health facility but also improve on the quality of data generated by these facilities.

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