Published on in Vol 21 , No 1 (2019) :January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10793, first published .
Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers

Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers

Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers

Journals

  1. Zhou L, Parmanto B. Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(4):e15075 View
  2. van Mens H, van Eysden M, Nienhuis R, van Delden J, de Keizer N, Cornet R. Evaluation of lexical clarification by patients reading their clinical notes: a quasi-experimental interview study. BMC Medical Informatics and Decision Making 2020;20(S10) View
  3. Lalor J, Hu W, Tran M, Wu H, Mazor K, Yu H. Evaluating the Effectiveness of NoteAid in a Community Hospital Setting: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Patients. Journal of Medical Internet Research 2021;23(5):e26354 View
  4. Valeur H, Lie A, Moen K. Patient Rationales Against the Use of Patient-Accessible Electronic Health Records: Qualitative Study. Journal of Medical Internet Research 2021;23(5):e24090 View
  5. Fisher K, Kennedy K, Bloomstone S, Fukunaga M, Bell S, Mazor K. Can sharing clinic notes improve communication and promote self-management? A qualitative study of patients with COPD. Patient Education and Counseling 2022;105(3):726 View
  6. Lalor J, Wu H, Mazor K, Yu H. Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk. International Journal of Medical Informatics 2023;172:105006 View
  7. Kujala S, Hörhammer I, Väyrynen A, Holmroos M, Nättiaho-Rönnholm M, Hägglund M, Johansen M. Patients' Experiences of Web-Based Access to Electronic Health Records in Finland: Cross-sectional Survey. Journal of Medical Internet Research 2022;24(6):e37438 View
  8. Bompelli A, Wang Y, Wan R, Singh E, Zhou Y, Xu L, Oniani D, Kshatriya B, Balls-Berry J, Zhang R. Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review. Health Data Science 2021;2021 View
  9. van Mens H, Martens S, Paiman E, Mertens A, Nienhuis R, de Keizer N, Cornet R. Diagnosis clarification by generalization to patient-friendly terms and definitions: Validation study. Journal of Biomedical Informatics 2022;129:104071 View
  10. Dong Z, Leveille S, Lewis D, Walker J. People with diabetes who read their clinicians’ visit notes: Behaviors and attitudes. Chronic Illness 2023:174239532311718 View