出版社：Utrecht University, Maastricht University, Groningen University
摘要：Introduction : In Scotland, around 24% of the population have two or more long-term conditions (multimorbidity). At all ages, multimorbidity is associated with complex needs and higher use of resources. Most risk prediction tools for complex patients are trained on historic data to predict mortality, hospital utilisation or resource use. GPs lack a real time primary care sensitive tool to identify people at all ages who have high demand on primary care and may benefit from targeted preventative interventions. Short description : A Complex Case Finder (CCF) tool was developed to help GPs identify patients who could benefit from a personalised Anticipatory Care Plan (ACP) and management of polypharmacy. Aim and theory of change : The aim was to provide GPs with accessible, trusted data on their most complex patients likely to benefit from preventative interventions. The CCF tool uses patient level data from GP electronic records, including eFrailty Index, together with resource utilisation data from the last 12 months: number of ED attendances, emergency admissions, hospital bed days, out of hours contacts, repeat prescription items from formulary. Data from these multiple sources are linked using the patient’s unique identifier – the Community Health Index (CHI) – and an algorithm, heavily weighted by the eFrailty Index, is applied to produce a CCF report. This report is embedded within the Primary Care Information System (PCIS) dashboard. Targeted population and stakeholders : All GPs in Ayrshire and Arran have access to the tools for around 385,000 patients registered with 55 practices. Scores are calculated for patients at any age with eFI > 0 ( a long term condition or frailty deficit). Currently 19,300 patients have a CCF report –approximately 5% of practice list size. Highlights : The tool displays data used to generate the CCF score in real-time and the score is updated monthly. GPs can filter their patient list in the tool, improving how they target specific preventative interventions. The CHI number hyperlinks to a patient specific report listing the relevant interventions and information on resource use. The tool also flags high risk prescribing and links to an enhanced medication summary for GP and pharmacist. Comments on sustainability : Once embedded in the dashboard the CCF tool is self sustained. Comments on transferability : The CCF model has not yet been validated against effect on primary care, hospital care demand or on pharmaceutical care or patient outcomes. However, feedback from local GPs suggests that the tool is ‘finding the right people’ to effectively target preventative interventions. Conclusions and Lessons learned : The CCF tool has been an important innovation to enage GPs in anticipatory care planning and managing polypharmacy. The tool uses routine data from multiple sources to produce information relevant to primary care based prevention. Linkage of this patient level data is feasible and has produced useful real time information to target interventions. The primary care dashboard is accessible, intuitive and well received by GPs. GPs have a high level of trust in tools that are based on their local primary care data. This trust is critical to promote adoption in practice.
关键词：complex ; anticipatory care ; polypharmacy ; tools
