出版社：Utrecht University, Maastricht University, Groningen University
摘要：Background : Population risk stratification is relevant for implementation of integrated care. It has been presented as an useful tool to (i) help to identify high-risk patients (ii) facilitate services design and (iii) ensure appropriate coverage of prevention and care interventions. Risk stratification (RS) tools are predictive models applied to foresee undesired events. They are algorithms that relate some parameters (demographic, clinical, health services utilization or living conditions) and some predicted outcomes (A&E visits, readmissions, death or expenditure).They are used to stratify a population according to the selected metric. However, lacklustre results have been presented and few stratification tools have been scaled up in Europe. Problems have been linked with scope, data, ICT, clinicians´ involvement, implementation barriers or impactability. The workshop will analyze recent experiences in Spain and UK. It will build from ASSEHS project (http://assehs.eu/). Catalonia has developed a new tool based on Adjusted Morbidity Groups (GMA). It enables the population to be classified into 6 morbidity groups, and in turn divided into 5 levels of complexity, along with one healthy population group. Differences with other tools will be analyzed and concordance between clinical judgement and tool predictions will be discussed. Basque Population Risk stratification was deployed in 2011 covering the whole Basque population. Identified problems were time delays, clinical acceptance and impactability. We will discuss updates including new variables and data process and analysis. Swansea University will discuss Emergency Admission Risk Stratification (EARS). PRISMATIC examined effectiveness of an EARS tool introduced in 32 general practices in Wales, using data from 235,000 patients. We consider the surprising findings. We also surveyed over 70% of UK health boards and commissioning groups on EARS use. We identified widespread implementation and a host of tools. Many areas had made service changes to support EARS – but why were few evaluating it? Between 2015 and 2018, NHS England made major investments in a New Models of Care programme which supported local areas (vanguards) to prototype new ways of delivering integrated care. RS and multidisciplinary teams was a common feature of integrated care vanguards. The national evaluation team did in-depth studies of how five vanguards were implementing risk stratification. We discuss findings, challenges and lessons. Aims and Objectives : Risk stratification tools update Concordance between clinical judgment and tools predictions. Pitfalls in implementation. Impact on performance and outcomes Future use in European health services Format (90m) Introduction: Population Risk stratification, main challenges. Esteban Manuel.Keenoy10m Catalonian experience: Adjusted Morbidity Group. David Monterde. 10m Developments in the Basque Population Risk Stratification. Eduardo Millán. 10m Learnings from PRISMATIC and EARP projects: Alison Porter, Mark Kingston, 10m Risk stratification - learnings from New Care Models vanguards Charles Tallack 10m Q&A and discussion 40m What are the main issues? Are there any common lessons? Who will be using RS in 5 years time (what? why?) Target Audience : Professionals and managers interested in implementing and/or improving integrated care programs. RS researchers and tools developers. Learnings/take away : Recent findings on risk stratification tools development, implementation and impact in real world settings.
关键词：risk stratification ; predictive algorithms ; integrated care ; evaluation
