The importance of multimorbidity in explaining utilisation and costs across health and social care settings: evidence from South Somersets Symphony Project
Aims - Since the inception of the NHS, an ever-present challenge has been to improve integration of care within the health care system and with social care. Many people have complex and ongoing care needs and require support from multiple agencies and various professionals. But care is often fragmented and uncoordinated, with no one agency taking overall responsibility, so it is often left to individuals and their families to negotiate the system as best they can. South Somersets Symphony is designed to establish greater collaboration between primary, community, acute and social care, particularly for people with complex conditions. Methods - We examine patterns of health and social care utilisation and costs for the local population to identify which groups of people would most benefit from better integrated care. We analyse data to identify groups of people according to the frequency of occurrence of underlying conditions; the cost of care; and utilisation of services across diverse settings. The empirical identification strategy is supplemented by local intelligence gained through workshops with health and social care professionals about the appropriateness of existing patterns of provision. We employ two-part regression models to explain variability in individual health and social costs, in total and in each setting. Data - The Symphony Project has an anonymised individual-level dataset, spanning primary, community, acute, mental health and social care. This includes activity, costs, clinical conditions, age, sex and ward of residence for the entire population of 114,874 people in 2012. Each persons morbidity profile is described using the United Healthâ€™s Episode Treatment Groups (ETG), which build upon ICD and Read codes. Results - We identify the frequency of conditions and co-morbidity profile of the entire population and, for the most frequent conditions, we assess utilization and costs of care across health and social care settings. For example, for those with asthma and diabetes, hospital costs account for the largest proportion of costs; in contrast, costs for those with dementia occur mostly in social care, mental health care and community care settings. For the population as a whole, we find that costs of health and social care are driven more by an individuals morbidity profile than by their age. Data for those with the most frequent conditions were reviewed by local health and social care professionals and managers. It was decided to undertake more detailed analyses for those with diabetes or dementia. 5,676 people are recorded as having diabetes in South Somerset, with hypertension being the most common comorbidity. For those with a sole diagnosis of diabetes, costs are around Â£1,000 on average but as people are recorded as having more diagnoses, average costs increase progressively. Costs are also higher for older people and women. People with dementia account for only 0.92% of the South Somerset population, but the average annual cost for the 1,062 people with dementia is around Â£12,000. A high proportion of these costs are related to the provision of mental health, social and continuing care. Costs are higher the more co-morbidities a person has, and for people from more deprived areas. Age and gender do not explain variation in costs for people with dementia. Conclusions - This work forms a basis for identifying groups that would most benefit from improved integrated care, which might be facilitated by integrated financial arrangements and better pathway management. The more co-morbidities that a person has, the more likely they are to require care across diverse settings, and the higher their costs. Our analysis identifies those groups of the population which are the highest users of services by activity and cost and provides baseline information to allow budgetary arrangements to be developed for these targeted groups.
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- Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-26, April.
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