Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33470, first published .
Developing a User-Centered Digital Clinical Decision Support App for Evidence-Based Medication Recommendations for Type 2 Diabetes Mellitus: Prototype User Testing and Validation Study

Developing a User-Centered Digital Clinical Decision Support App for Evidence-Based Medication Recommendations for Type 2 Diabetes Mellitus: Prototype User Testing and Validation Study

Developing a User-Centered Digital Clinical Decision Support App for Evidence-Based Medication Recommendations for Type 2 Diabetes Mellitus: Prototype User Testing and Validation Study

Journals

  1. Heald A, Gimeno L, Gilingham E, Hudson L, Price L, Saboo A, Beresford L, Seviour S, White A, Roberts S, Abraham J. Enhancing type 2 diabetes treatment through digital plans of care. First results from the East Cheshire Study of an App to support people in the management of type 2 diabetes. Cardiovascular Endocrinology & Metabolism 2022;11(3) View
  2. Awad S, Amon K, Baillie A, Loveday T, Baysari M. Human factors and safety analysis methods used in the design and redesign of electronic medication management systems: A systematic review. International Journal of Medical Informatics 2023;172:105017 View
  3. Friel K, McCauley C, O’Kane M, McCann M, Delaney G, Coates V. Can Clinical Outcomes Be Improved, and Inpatient Length of Stay Reduced for Adults With Diabetes? A Systematic Review. Frontiers in Clinical Diabetes and Healthcare 2022;3 View
  4. Müller S, Tsirozidis G, Mathiasen M, Nordenhof L, Jakobsen D, Mahler B. Eliciting Information Needs of Child Patients: Adapting the Kano Model to the Design of mHealth Applications. Methods of Information in Medicine 2022;61(03/04):123 View
  5. Chen J, Baxter S, van den Brandt A, Lieu A, Camp A, Do J, Welsbie D, Moghimi S, Christopher M, Weinreb R, Zangwill L. Usability and Clinician Acceptance of a Deep Learning-Based Clinical Decision Support Tool for Predicting Glaucomatous Visual Field Progression. Journal of Glaucoma 2023;32(3):151 View
  6. Heald A, Roberts S, Albeda Gimeno L, Gilingham E, James M, White A, Saboo A, Beresford L, Crofts A, Abraham J. A Randomised Control Trial to Explore the Impact and Efficacy of the Healum Collaborative Care Planning Software and App on Condition Management in the Type 2 Diabetes Mellitus Population in NHS Primary Care. Diabetes Therapy 2023;14(6):977 View
  7. Yao Y, Dunn Lopez K, Bjarnadottir R, Macieira T, Dos Santos F, Madandola O, Cho H, Priola K, Wolf J, Wilkie D, Keenan G. Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses’ Graph Literacy: National, Web-Based Randomized Controlled Trial. Journal of Medical Internet Research 2023;25:e45043 View
  8. Pinto A, Martinho D, Matos J, Greer D, Vieira A, Ramalho A, Marreiros G, Freitas A. Recommendation systems to promote behavior change in patients with diabetes mellitus type 2: A systematic review. Expert Systems with Applications 2023;231:120726 View
  9. Tacke T, Nohl-Deryk P, Lingwal N, Reimer L, Starnecker F, Güthlin C, Gerlach F, Schunkert H, Jonas S, Müller A. The German version of the mHealth App Usability Questionnaire (GER-MAUQ): Translation and validation study in patients with cardiovascular disease. DIGITAL HEALTH 2024;10 View
  10. Kang M, Rossetti S, Lowenthal G, Knaplund C, Zhou L, Schnock K, Cato K, Dykes P. Designing and testing clinical simulations of an early warning system for implementation in acute care settings. JAMIA Open 2024;7(4) View

Books/Policy Documents

  1. Zhang X, Jiang H, Ozanich G. Telehealth and Telemedicine - The Far-Reaching Medicine for Everyone and Everywhere. View