This paper is in the following e-collection/theme issue:

Clinical or Consumer-Focused Software for Diabetes (18) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (573) Formative Studies and eHealth/mHealth Development (524) Electronic Health Records (1053) Design and Usability of Clinical Software and EHRs (268) Diabetes Self-Management (484) Diabetes-specific EHR Improvements (33) Formative Evaluation of Digital Health Interventions (2412) Design and Usability of Consumer Health Tech and Home Monitoring Devices (218)

Published on in Vol 3, No 3 (2018): Jul-Sep

Design and Development of a Context-Aware Knowledge-Based Module for Identifying Relevant Information and Information Gaps in Patients With Type 1 Diabetes Self-Collected Health Data

Design and Development of a Context-Aware Knowledge-Based Module for Identifying Relevant Information and Information Gaps in Patients With Type 1 Diabetes Self-Collected Health Data

Design and Development of a Context-Aware Knowledge-Based Module for Identifying Relevant Information and Information Gaps in Patients With Type 1 Diabetes Self-Collected Health Data

Authors of this article:

Alain Giordanengo1, 2 Author Orcid Image ;   Pinar Øzturk3 Author Orcid Image ;   Anne Helen Hansen4, 5 Author Orcid Image ;   Eirik Årsand2, 6 Author Orcid Image ;   Astrid Grøttland2 Author Orcid Image ;   Gunnar Hartvigsen1 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

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  2. Bradway M, Giordanengo A, Joakimsen R, Hansen A, Grøttland A, Hartvigsen G, Randine P, Årsand E. Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study. JMIR Research Protocols 2020;9(2):e16657 View
  3. Giordanengo A, Årsand E, Woldaregay A, Bradway M, Grottland A, Hartvigsen G, Granja C, Torsvik T, Hansen A. Design and Prestudy Assessment of a Dashboard for Presenting Self-Collected Health Data of Patients With Diabetes to Clinicians: Iterative Approach and Qualitative Case Study. JMIR Diabetes 2019;4(3):e14002 View
  4. Shen L, Wright A, Lee L, Jajoo K, Nayor J, Landman A. Clinical decision support system, using expert consensus-derived logic and natural language processing, decreased sedation-type order errors for patients undergoing endoscopy. Journal of the American Medical Informatics Association 2021;28(1):95 View
  5. Ozkaynak M, Sircar C, Frye O, Valdez R. A Systematic Review of Design Workshops for Health Information Technologies. Informatics 2021;8(2):34 View