Population Health Management (PHM) is an approach that uses data to identify and anticipate the needs of population groups and individuals so that services act as early as possible to keep people well and target support where it will have the greatest impact.
Our business intelligence specialists supported Dudley Clinical Commissioning Group (CCG) with PHM, using integrated data analytics to help determine how best to commission preventative and interventional care.
Action
We worked with the CCG and Public Health colleagues to produce the intelligence and insight needed for their decision-making. We analysed integrated datasets (taking primary, secondary, community and mental health care data along with population, epidemiology and prescribing data) to create a visualisation report. This segmented the blended data to group similar people together.
Using machine learning tools, we searched the blended data (for example by extracting patterns of need, demand, deterioration, complexity and expense) for opportunities to systematically optimise population level commissioning.
We held a system level workshop to analyse opportunity, assess impact and determine priorities.
Impact
Blending the CCG’s data with other sources produced a holistic picture and enabled data quality management. The insight led to better understanding of populations and unwarranted variation. This in turn meant interventions or service redesign could be targeted and tailored for maximum impact, optimising cost effective care and outcomes.
Our triangulation of data sources at population level gave the commissioners new insight, for example regarding deprived Asian men’s utilisation of planned and unplanned care, older white affluent people’s use of mental health and A&E services, and GP socioeconomic profile against their prescribing costs.