Using the UKROC dataset to make the case for resources to improve cost-efficiency in neurological rehabilitation

PURPOSE: A key challenge for providers and commissioners of rehabilitation services is to find optimal balance between service costs and outcomes. This article presents a “real-lifeâ application of the UK Rehabilitation Outcomes Collaborative (UKROC) dataset. We undertook a comparative cohort analysis of case-episode data (n = 173) from two specialist neurological rehabilitation units (A and B), to compare the cost-efficiency of two service models. KEY MESSAGES: (i) Demographics, casemix and levels of functional dependency on admission and discharge were broadly similar for the two units. (ii) The mean length of stay for Unit A was 1.5 times longer than Unit B, which had 85% higher levels of therapy staffing in relation to occupied bed days so despite higher bed-day costs, Unit B was 20% more cost-efficient overall, for similar gain. (iii) Following analysis, engagement with service commissioners led to successful negotiation of a business plan for service reconfiguration with increased staffing levels for Unit A and further development of local community rehabilitation services. CONCLUSION: (i) Lower front-end service costs do not always signify optimal cost-efficiency. (ii) Analysis of routinely collected clinical data can be used to engage commissioners and to make the case for resources to maximise efficiency and improve patient care.