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

Mor Peleg, Yuval Shahar, Silvana Quaglini, Adi Fux, Gema García-Sáez, Ayelet Goldstein, M Elena Hernando, Denis Klimov, Iñaki Martínez-Sarriegui, Carlo Napolitano, Enea Parimbelli, Mercedes Rigla, Lucia Sacchi, Erez Shalom, Pnina Soffer

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)159-213
Number of pages55
JournalUser Modeling and User-Adapted Interaction
Volume27
Issue number2
DOIs
Publication statusPublished - Jun 1 2017

Keywords

  • Clinical guidelines
  • Computer-interpretable guidelines
  • Decision-support system
  • Mobile health
  • Patient centrality
  • Personalization

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction
  • Computer Science Applications

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