Polibienestar is a Public Research Institute specialized in research, innovation and social technology, technical advice and training in public policies. Its final mission is the improvement of the Welfare and Quality of Life of society. It is composed by an interdisciplinary team with 34 senior and 24 junior researchers with national and European experience from different departments of eight Spanish Universities. This interdisciplinary perspective allows Polibienestar to develop, from innovative and classic research, effective analysis and solutions for new social challenges. Polibienestar has developed in the context of the Valencia Region a first version of a new stratification tool aimed to early detect elderly patients with chronic conditions at risk of suffering future hospital admissions. This tool has been developed and piloted in a primary care centre with the involvement of multidisciplinary teams (GPs, nurses, social workers and researchers). The final goal of the tool is to improve the management of chronic care through a more proactive and patient-oriented approach which would facilitate a more efficient and sustainable allocation of resources (both human and services) and, finally, a better quality of life in patients and increased support in the work carried out by health and social care professionals at primary care centres.
Lead organisation name:
Polibienestar Research Institute – University of Valencia
Ascensión Doñate; Jorge Garcés: Francisco Ródenas
Contact person email:
firstname.lastname@example.org ; email@example.com ; firstname.lastname@example.org
Last update: 17/06/2016
It is available a first version of the tool which has been developed through a wide study in the Valencia Region with the close involvement of multidisciplinary health care professionals from primary care level. Through focus group it was selected a first list of potential variables to be included in the stratification tool as predictor variables. This list was tested in a sample of 100 elderly patients and later depurated according to the results obtained by logistic regression analysis. The new list of variables was piloted in a larger sample which final analysis resulted in a predictive algorithm identifying patients at risk of suffering future hospital admissions.
|Title||Planned Deadline||Current Status||Category||Attachments|
|Focus group with six primary care professionals to create the first list of potential predictor variables||30/06/2014||Achieved||Research: Data (assessments/screenings/reviews/ data collections)|
|Retrospective study to test the first list of predictor variables||30/11/2014||Achieved||Research: Reports (reports, articles, findings)|
|Retrospective study to test the results obtained in the previous study||30/04/2015||Achieved||Research: Data (assessments/screenings/reviews/ data collections)|
|Algorithm to detect elderly patients at risk of future hospital admissions||31/01/2016||Achieved||Research: Tools (methodologies, models, questionnaires, analysis, surveys)|
|Two papers have been published in the journals: 'European Journal of Interdisciplinary Studies' and 'International Journal of Integrated Care', including aspects related to the methodology employed and main results obtained.||07/05/2017||Achieved||Research: Reports (reports, articles, findings)|
|Indicator||Target indicator||Current status|
|Risk of suffering future hospital admissions as a probability calculated by an algorithm||No established yet||1000 patients|