Project Background

During the early stages of the COVID-19 pandemic, I was asked to design and develop a data analytics application that would provide a health organisation with real-time analysis regarding COVID-19 within their hospital settings.

This was an extremely challenging project for several reasons, namely:

  • Delivery timescales were extremely tight due to the urgent need for COVID-19 data analysis.
  • Obtaining access to data within patient information systems.
  • Data quality issues.
  • Data interoperability concerns.
  • Data Access Agreements (DAA) and Data Protection Impact Assessments (DPIA) needed to be completed due to the sensitivity of the data being analysed.

Outcomes

As Programme Lead I played a critical role in every aspect of delivering this data analytic application.

The application extracted over 2 million rows of data from 7 different data sources, all of which was consolidated into a back end data model. User-centred design lead to interfaces that provided end-users with a high user experience and easy analysis of data, including:

  • Hospital admissions/ discharges.
  • Age, gender, length of stay.
  • Oxygen, ventilator usage.
  • Mortality.

Within a few weeks, the first iteration of the application was deployed to end-users, providing them with next to real-time data.

The application was extremely well received throughout the organisation. This was the first time data from the organisation's primary patient information systems had ever been consolidated into one single platform where users could perform self-service visualisation and discovery of their data.

As one clinician put it, the analytic application:

Provides a glimmer of the potential of what we can achieve now and in the future by having a user-friendly interface that can integrate vast arrays of complex data. This opens avenues for any Healthcare Organisation to better understand itself and to bring advancements in data science to affecting outcomes.

Technology

  • Qlik Sense
  • Microsoft SQL Server
  • Oracle
  • Microsoft Excel
  • SQL