​EHR Project

Mining EHR in Kenya for Research Purposes 

Project Brief 

Introduction: 

Data in the 21st century is like oil in the 18th century, and within an LMIC setting can be an immensely valuable at identifying new innovative solutions. Within AKDN (Aga Khan Development Network) and AKU(Aga Khan University) specifically, little to no work has been done to extract data from our hospital systems (EHR) and mine that data to understand trends and identify better care pathways for the communities we serve. This project aims to change that paradigm by extracting data from key hospital systems in Nairobi and Mombasa, organising​ the data in a manner optimised for analytics and machine learning and then making the repository available to AKU faculty for research purposes. The project will also build a similar repository for AKHS (Aga Khan Health Services) in Mombasa for them to use for their operations. 

Goals: ​

  • Build an analytic data repository at AKU with data from Care2000 systems in Nairobi and Mombasa to be used for research purposes 
  • Work with team at AKHS Mombasa to build similar repository for them to use internally with data from Care2000 in Mombasa. 
  • Build a community of users on the AKU repository including Informatics office, Research faculty within AKU, and other AKU teams as needed.
  • Mine the data and produce 2 – 3 data packages that provide key trends, findings and insights that highlight the value of the investment.

Tenets: 

The following tenets are guiding principles which will be used to evaluate the approaches and prioritiz​e activities: 

  • Small cross functional team comprised of clinicians and data architects/ engineers (max team size is 8 persons) 
  • Tangible output and outcomes delivered at the end of every 6-week sprint. 
  • Use of open source/ open data algorithms vs. proprietary/ custom code. 
  • Development code/ scripts should be crafted in a manner to be replicable across the Care2000 systems i.e., the same script applied in Nairobi should run in Mombasa.

Approach: 

  • The project will be executed using agile methodologies using a 6-week sprint cycle. 
  • The project will kick off with an Explore/ Planning sprint that will determine key architectural elements including: 
    1. Detailed understanding of the Care2000 hospital system including data relationships, data quality, and types of data. 
    2. High level understanding of the data model to be used .e.g. OMOP  
    3. Alignment with clinicians on how data will be extracted to align with having a complete working model at the end of each sprint.
  • Detailed understanding of what can be done in compliance with Kenya Data Protection Laws.
  • Post the Explore/ Planning sprint – each sprint will comprise of working data extract starting with Nairobi; the subsequent sprint will be the same data extract within the Mombasa system.