Patient journey modelling – from data to insights into patient pathways

Start Date

23 November 2020

End Date

30 September 2024

Project Participants

Ministry of Health NSW, University of Technology Sydney, WentWest (Western Sydney PHN)

Status: Completed

Tags: acute care, aged care, care pathways, data analytics, data linkage, data visualisation, decision support, health planners, health system, healthcare commissioning, population health, primary care, value-based care

Opportunity 

Health systems generate extensive information about how people move between primary, ambulatory, emergency and hospital care, but converting those records into clear, actionable insights can be difficult.  

The Patient Journey Modelling project set out to explore how linked health data improve understanding of how people access health services in NSW to provide a more complete view of care pathways for patients. 

Objectives 

This project aimed to deliver evidence-based information regarding ‘what happens next’ for patients in the NSW Health system. The research team developed a framework to analyse what happens to patients following a GP or hospital emergency room visit, capturing possible pathways a patient can take through the health system. 

The project made use of the NSW government’s Lumos program – a data linkage initiative which combines consumer data from participating general practices with data from hospitals and other health settings – to build algorithms that mapped patient journeys, and to build predictive tools. 

This work allowed researchers to look at patient treatment journeys across particular patient cohorts. The project team developed a web-based platform that animated these patient journeys across daily, weekly and monthly timeframes. To do this the team developed more efficient ways to retrieve and prepare Lumos data, as well as algorithms to infer missing information from multiple available indicators such as MBS billing records, GP visits, hospital discharge information and emergency department referrals. The team were able to show and compare patient journeys for a residential aged care facility (RACF) cohort against a non-RACF cohort; before and after RACF entry; and for different age groups and co-morbidities.

The project also supported the successful completion of a PhD program.

The project demonstrated how linked health data can be transformed into accessible views of complex patient pathways. The resulting framework provided an approach for exploring care before and after entry to residential aged care, comparing cohorts and identifying patterns that may inform health-service planning. For policy and health system stakeholders, the work illustrates the value of combining primary, ambulatory and acute care data to support value-based healthcare. The project also strengthened Australian capability in health data science, software development and interactive visualisation for decision support. 

While the platform was a proof of concept, the findings suggest that real-time data integration, broader cohort analysis, external data integration and scalable infrastructure would help build toward a production-ready clinical decision support system.  

Integrity, Excellence,
Teamwork and Authenticity

Hand holding a smartphone against a colourful, defocused background