| Title |
Key aspects related to implementation of risk stratification in health care systems-the ASSEHS study
|
|---|---|
| Published in |
BMC Health Services Research, May 2017
|
| DOI | 10.1186/s12913-017-2275-3 |
| Pubmed ID | |
| Authors |
Joana Mora, Miren David Iturralde, Lucía Prieto, Cristina Domingo, Marie-Pierre Gagnon, Catalina Martínez-Carazo, Anna Giné March, Daniele De Massari, Tino Martí, Marco Nalin, Francesca Avolio, Jean Bousquet, Esteban de Manuel Keenoy, all ASSEHS group |
| Abstract |
The 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. Two 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. A 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. The 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 82 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 12% |
| Other | 9 | 11% |
| Student > Master | 7 | 9% |
| Student > Ph. D. Student | 6 | 7% |
| Student > Bachelor | 5 | 6% |
| Other | 16 | 20% |
| Unknown | 29 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 22% |
| Nursing and Health Professions | 8 | 10% |
| Social Sciences | 7 | 9% |
| Computer Science | 3 | 4% |
| Psychology | 3 | 4% |
| Other | 13 | 16% |
| Unknown | 30 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2021.
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#6,475,974
of 22,971,207 outputs
Outputs from BMC Health Services Research
#3,138
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Outputs of similar age
#103,264
of 310,732 outputs
Outputs of similar age from BMC Health Services Research
#56
of 132 outputs
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