Primary Sense: a new population health management tool for general practice

Primary Sense is a new data extraction, analysis and reporting tool that the Gold Coast Primary Health Network (GCPHN) has developed to enable practical and effective population health management in general practice and also on a regional level. Once installed, the tool de-identifies data within the practice before running it through various clinical risk algorithms to create practical information that can easily be actioned within the general practice business model in at least two ways. The first is to generate up-to-date reports of patients who are most likely to benefit from specific interventions or occasions of service. The second is to identify potentially serious medication safety issues, alerting clinicians in real time at point of prescribing. Formal live testing of the system was completed in nine practices where 22 managers and nurses and 42 GPs used the tool over a 5-month period in 2019. The live test monitored the use of reports and alerts, and regular feedback from users enabled small but important improvements to the tool. Practice teams successfully used the reports to target specific groups of patients with outstanding care needs or who were at greatest risk of adverse health outcomes. The results of the live test showed that users found Primary Sense to be easy to use and beneficial to general practice. The next phase of this project is now underway to further trial the scalability and change management requirements for full implementation of Primary Sense. As more and more practices adopt the tool, the aggregated data will increasingly help to support population health planning, commissioning of local services, active health surveillance and other related activities.

Structured yet simple approaches to primary care data quality improvements can indeed strike gold

General practice data provide important opportunities for both population health and within-practice initiatives to improve health. Despite its promise, a lack of accuracy affects the use of such data. The Sentinel Practices Data Sourcing (SPDS) project is a structured chronic disease surveillance and data quality improvement strategy in general practice. A mixed-methods approach was used to evaluate data quality improvement in 99 participating practices over 12 months. Quantitative data were obtained by measuring performance against 10 defined indicators, whereas 48 semi-structured interviews provided qualitative data. Aggregated scores demonstrated improvements in all indicators, ranging from minor to substantially significant improvements. Participants reported positively on levels of support provided, and acquisition of new knowledge and skills relating to data entry and cleansing. This evaluation provides evidence of the effectiveness of a structured approach to improve the quality of primary care data. Investing in this targeted intervention has the potential to create sustained improvements in data quality, which can drive clinical practice improvement.