Abstract
BackgroundTo improve population health it is crucial to understand the different care needs within a population. Traditional population groups are often based on characteristics such as age or morbidities. However, this does not take into account specific care needs across care settings and tends to focus on high-needs patients only. This paper explores the potential of using utilization-based cluster analysis to segment a general patient population into homogenous groups.MethodsAdministrative datasets covering primary and secondary care were used to construct a database of 300,000 patients, which included socio-demographic variables, morbidities, care utilization, and cost. A k-means cluster analysis grouped the patients into segments with distinct care utilization, based on six utilization variables: non-elective inpatient admissions, elective inpatient admissions, outpatient visits, GP practice visits, GP home visits, and prescriptions. These segments were analyzed post-hoc to understand their morbidity and demographic profile.ResultsEight population segments were identified, and utilization of each care setting was significantly different across all segments. Each segment also presented with different morbidity patterns and demographic characteristics, creating eight distinct care user types. Comparing these segments to traditional patient groups shows the heterogeneity of these approaches, especially for lower-needs patients.ConclusionsThis analysis shows that utilization-based cluster analysis segments a patient population into distinct groups with unique care priorities, providing a quantitative evidence base to improve population health. Contrary to traditional methods, this approach also segments lower-needs populations, which can be used to inform preventive interventions. In addition, the identification of different care user types provides insight into needs across the care continuum.Electronic supplementary materialThe online version of this article (doi:10.1186/s12963-016-0115-z) contains supplementary material, which is available to authorized users.
Highlights
The central purpose of this paper is to challenge those involved in integrated care and public health to ‘join up the dots’
Improving population health is not just the responsibility of health and social care services, or of public health professionals. We argue that it requires co-ordinated efforts across population health systems
Our principal purpose is to challenge those involved in integrated care and in public health to ‘join up the dots’
Summary
Integrated care has become a central part of the language of health service reform in England in recent years due to the challenges posed by an ageing population and the changing burden of disease. Policy initiatives introduced by the coalition government have sought to accelerate integration of services both within the NHS and between NHS and social care, and some areas are making progress in coordinating care for older people and those with complex needs While this shift marks progress from the fragmentation that has come to characterise the NHS and social care system, these efforts have not typically extended into a concern for the broader health of local populations and the impact of the wider determinants of health. This means thinking of integrated care as part of a broader shift away from fragmentation and heading towards population health Making this shift will require action and alignment across a number of different levels, from central government and national bodies to local communities and individuals. These examples provide lessons for us in England as the development of integrated care continues
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