Key aspects related to implementation of risk stratification in health care systems-the ASSEHS study

Abstract

BackgroundThe lack of proven efficacy of new healthcare interventions represents a problem for health systems globally. It is partly related to suboptimal implementation processes, leading to poor adoption of new interventions. Activation of Stratification Strategies and Results of the interventions on frail patients of Healthcare Services (ASSEHS) EU project (N° 2013 12 04) aims to study current existing health Risk Stratification (RS) strategies and tools on frail elderly patients. This paper aims at identifying variables that make the implementation of population RS tools feasible in different healthcare services.MethodsTwo different methods have been used to identify the key elements in stratification implementation; i) a Scoping Review, in order to search and gather scientific evidence and ii) Semi-structured interviews with six key experts that had been actively involved in the design and/or implementation of RS strategies. It aims to focus the implementation construct on real-life contextual understandings, multi-level perspectives, and cultural influences.ResultsA Feasibility Framework has been drawn. Two dimensions impact the feasibility of RS: (i) Planning, deployment and change management and (ii) Care intervention. The former comprises communication, training and mutual learning, multidisciplinarity of the team, clinicians’ engagement, operational plan and ICT display and functionalities. The latter includes case finding and selection of the target population, pathway definition and quality improvement process.ConclusionsThe Feasibility Framework provides a list of key elements that should be considered for an effective implementation of population risk stratification interventions. It helps to identify, plan and consider relevant elements to ensure a proper RS implementation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2275-3) contains supplementary material, which is available to authorized users.

Using deep-learning to obtain calibrated individual disease and ADL damage transition probabilities between successive ELSA waves

“…We find HRs between 3 and 10 (the largest possible for deciles) – indicating substantial risk stratification is possible with our approach. Our well-calibrated model provides accuracy in risk prediction results which would provide reliability for decision-making [34, 35]. Since we had calibrated probabilities, we also considered the distributions of transition probabilities.…”

Utilization of Primary Healthcare Services in Patients with Multimorbidity According to Their Risk Level by Adjusted Morbidity Groups: A Cross-Sectional Study in Chamartín District (Madrid)

“…The WHO has highlighted the fundamental role of primary care in the management of patients with multimorbidity [3,7]. To guide this management, many countries use morbidity groupers to stratify populations according to complexity [8]. In Spain, the Adjusted Morbidity Groups (AMGs) have been developed within the Spanish healthcare system and are integrated into the electronic medical records of primary care [9].…”

“…The AMG grouper enables the measurement of multimorbidity to determine its impact on clinical-care management, epidemiology and healthcare administration, while also classifying patients into risk categories based on their morbidity and complexity [10]. This tool is useful for primary care professionals and policymakers, as it reveals the characteristics and use of services in patients with multimorbidity, serving as a guide to allocate healthcare resources efficiently and to plan appropriate care models and interventions based on each individual risk level, thereby successfully meeting the healthcare needs of patients with multimorbidity and efficiently managing healthcare services [8][9][10].…”

On the road to universal coverage of postnatal care: considerations for a targeted postnatal care approach for at-risk mother–baby dyads in low-income and middle-income countries informed by a consultation with global experts

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