VP29 Designing A Mobile Clinical Decision Support System For Dementia

2019 ◽  
Vol 35 (S1) ◽  
pp. 83-83
Author(s):  
Noemí Robles ◽  
Carme Carrion i Ribas ◽  
Marta Aymerich

IntroductionE-health offers the opportunity of supporting the management of several diseases, but most of these tools are far from being based on scientific evidence and demonstrating their effectiveness and efficacy. The PSICODEM Project aims to develop a mobile personalized clinical decision support system (CDSS) based on evidence for contributing to e-health interventions addressed to the management of dementia that require not only a pharmacological approach but also psychosocial interventions for improving patients’ quality of life and reducing emotional, cognitive and behavioral symptoms. The present communication focuses on the identification of the evidence on which the CDSS algorithm will be developed.MethodsThree systematic reviews were carried out in order to identify the existing scientific evidence published in relation to the effectiveness of behavioral, emotional and cognitive therapies addressing dementia (January 2009 to December 2017). The main databases were consulted (PubMed, Cochrane Library, PsychoInfo) and only randomized control trials (RCT) were considered. Articles were reviewed by two independent reviewers. The quality of the selected publications was assessed according to the SIGN criteria.ResultsForty-seven RCTs were selected for cognitive therapies, thirty-two for emotional ones and fifteen for behavioral interventions. Those therapies with more support of evidence were skills training for cognitive therapies and reminiscence interventions for emotional interventions; however, in behavioral interventions a variety of therapeutically approaches were found. Wide differences were found between studies in terms of types and levels of dementia, forms of intervention (number, length and frequency of sessions) and outcome measures.ConclusionsIn-depth analysis of evidence will allow the identification of those interventions more appropriate for each patient according to their symptoms and level of dementia. According to this evidence, the mobile CDSS algorithm will be developed. Additionally, these findings point out the gaps in psychosocial intervention research.

2020 ◽  
Vol 44 (10) ◽  
Author(s):  
David L. Chin ◽  
Michelle H. Wilson ◽  
Ashley S. Trask ◽  
Victoria T. Johnson ◽  
Brittanie I. Neaves ◽  
...  

2020 ◽  
pp. 50-57
Author(s):  
Ali Кhusein ◽  
Urquhart A

The application of the Clinical Decision Support Systems (CDSS) in the process of facilitating the activity of the evidence-centred treatment project effect enhances the quality of the healthcare services. The main purpose of this article is to define and illustrate the basis of the processes of the evidencecentred decision support tracking at the two thousand AMIA symposium spring. The analysis has been done on the basis of protocol issues when capturing the evidence-centred practices in machine interpretation and repositories for supporting and developing the CDSS for evidence-centred treatment. As a result, the research recommendations are based on five areas: capturing literature-centered and practice-centred evidence in the interpretation of machine knowledge and bases; creating maintainable methodological and technical elements for computer-centred decision support CDSS; assessing the medical costs and effects for clinical decision support system and the manner in which the systems affect the organizational best practices; disseminating and identifying the works based on work-flow sensitivity approach for the system and creating the public policy which will effectively provide the incentives meant to implement CDSS to enhance the quality of healthcare services. The paper is concluded with an assumption of evidence-based medicine aspect being strong. However, future research is still recommended in CDSS to potentially realize more defined benefits of the systems.


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