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How we introduced population health management to our hospital trust

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Developing a population health management tool as part of our trust's digital transformation

Source: Mclean/Shutterstock.com

In March 2019, University College London Hospitals (UCLH) NHS Foundation Trust underwent possibly its biggest ever change — a project that took an enormous number of staff hours to complete and will touch every single employee within the trust, across all of our sites.

We implemented Epic — the new electronic health record system (EHRS) — which will connect or replace around 150 different electronic systems that we use across the trust. Countless workflows that were previously managed without an electronic system are now digitised. This data collection will really improve how we care for our patients and how we do research.

But as well as introducing applications for our usual activities, the UCLH board also decided to introduce a tool for population health management — a fresh approach to care aims to improve outcomes, promote wellbeing and reduce health inequalities across an entire population. The trust can use its patients’ data to identify groups with similar characteristics and design new models of proactive care specifically for them.

Along with some speciality consultants, I’m the pharmacist leading the creation and implementation of the tool, and I am interested in seeing the uptake and impact of the six pilot programmes on population health management that we have selected for the tool’s development: paediatric diabetes, epilepsy, rheumatology, COPD, adolescent inflammatory bowel disorder and multiple sclerosis.

The toolset will use hundreds of individually tailored rules to search through the patient record to retrieve specific items of data, which can then be refined or combined before being shown to the user. The range of visualisation methods created for the programmes include dashboards, graphs, metrics, risk scores, reports and columns. A longitudinal view of many outputs for each programme can show quarterly, monthly and weekly data trends.

The six specialist programmes have important measures, with some common threads and obvious diversity between disease areas. Individual metrics allow specialists to maintain regular review of these measures. Risk scores enable factors affecting specific diseases, such as HbA1c or spirometry readings, to be combined with more generalised factors such as hospital admissions, mental health, living conditions and demographics, creating a holistic view of the patient for stratification.

But there are challenges: reportable data must be accessible and documented separately (discrete data). In existing practices within the NHS, comparable data may be held in various formats, may not be optimised for reporting, and may not be easily transferable from one system to another.

Tangible, quantifiable and chronological items — such as laboratory tests, medications, procedures and encounter data — are well suited to this framework; they are frequently documented using a tool optimised for reporting that is, importantly, one that users are familiar with using. Clinicians who rely primarily on this type of data to measure disease state are at an advantage, but it may be challenging for others for whom the measurable outcomes may be more esoteric, or held in a range of forms, including free-text notes.

So we have given significant consideration to creating clinical workflows that allow highly specialised clinicians to collect discrete data, without suddenly and completely altering their practices.

Many clinicians in the trust had never used an EHRS, and they wanted to be comfortable with its general use before taking on more advanced features, so training on the population health management tool was staggered from July 2019 to September 2019, and the clinicians’ progress has been encouraging.

Our shift to digitise UCLH will help us to better document discrete data and make healthcare more measurable. But this work is just a foundation; once clinicians have adjusted to working with an EHRS, we will be able to identify enhancements for the toolset and adjust practices to match.

James Cole, electronic health records system deputy delivery manager for clinical outpatients, University College London Hospitals NHS Foundation Trust

Readers' comments (1)

  • It would have been good to see a sample(s) of the visualisation methods.

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