MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains

Peleg, Mor and Shahar, Yuval and Quaglini, Silvana and Fux, Adi and García Sáez, Gema and Goldstein, Ayelet and Hernando Pérez, María Elena and Klimov, Denis and Martínez Sarriegui, Iñaki and Napolitano, Carlo and Parimbelli, Enea and Rigla Cros, Mercedes and Sacchi, Lucia and Shalom, Erez and Soffer, Pnina (2017). MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains. "User Modeling And User-Adapted Interaction", v. 27 (n. 2); pp. 159-213. ISSN 0924-1868. https://doi.org/10.1007/s11257-017-9190-5.

Description

Title: MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains
Author/s:
  • Peleg, Mor
  • Shahar, Yuval
  • Quaglini, Silvana
  • Fux, Adi
  • García Sáez, Gema
  • Goldstein, Ayelet
  • Hernando Pérez, María Elena
  • Klimov, Denis
  • Martínez Sarriegui, Iñaki
  • Napolitano, Carlo
  • Parimbelli, Enea
  • Rigla Cros, Mercedes
  • Sacchi, Lucia
  • Shalom, Erez
  • Soffer, Pnina
Item Type: Article
Título de Revista/Publicación: User Modeling And User-Adapted Interaction
Date: June 2017
ISSN: 0924-1868
Volume: 27
Subjects:
Freetext Keywords: Computer-interpretable guidelines Decision-support system Clinical guidelines Patient centrality Personalization Mobile health
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica y Bioingeniería
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

MobiGuide is a ubiquitous, distributed and personalized evidence-based decision-support system (DSS) used by patients and their care providers. Its central DSS applies computer-interpretable clinical guidelines (CIGs) to provide real-time patient-specific and personalized recommendations by matching CIG knowledge with a highly-adaptive patient model, the parameters of which are stored in a personal health record (PHR). The PHR integrates data from hospital medical records, mobile biosensors, data entered by patients, and recommendations and abstractions output by the DSS. CIGs are customized to consider the patients’ psycho-social context and their preferences; shared decision making is supported via decision trees instantiated with patient utilities. The central DSS “projects” personalized CIG-knowledge to a mobile DSS operating on the patients’ smart phones that applies that knowledge locally. In this paper we explain the knowledge elicitation and specification methodologies that we have developed for making CIGs patient-centered and enabling their personalization. We then demonstrate feasibility, in two very different clinical domains, and two different geographic sites, as part of a multi-national feasibility study, of the full architecture that we have designed and implemented. We analyze usage patterns and opinions collected via questionnaires of the 10 atrial fibrillation (AF) and 20 gestational diabetes mellitus (GDM) patients and their care providers. The analysis is guided by three hypotheses concerning the effect of the personal patient model on patients and clinicians’ behavior and on patients’ satisfaction. The results demonstrate the sustainable usage of the system by patients and their care providers and patients’ satisfaction, which stems mostly from their increased sense of safety. The system has affected the behavior of clinicians, which have inspected the patients’ models between scheduled visits, resulting in change of diagnosis for two of the ten AF patients and anticipated change in therapy for eleven of the twenty GDM patients.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7287811MobiGuideUnspecifiedGuiding Patients Anytime Everywhere

More information

Item ID: 49769
DC Identifier: http://oa.upm.es/49769/
OAI Identifier: oai:oa.upm.es:49769
DOI: 10.1007/s11257-017-9190-5
Official URL: https://link.springer.com/article/10.1007/s11257-017-9190-5
Deposited by: Memoria Investigacion
Deposited on: 17 Apr 2018 16:32
Last Modified: 19 Mar 2019 15:26
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