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 2024;20(1):173 View
11. van Mens H, Hannen G, Nienhuis R, Bolt R, de Keizer N, Cornet R. Evaluation of Patient-Friendly Diagnosis Clarifications in a Hospital Patient Portal. Applied Clinical Informatics 2023;14(03):455 View
12. Chu S, Sisk B, Kolmar A, Malone J. Open Notes Experiences of Parents in the Pediatric ICU. Pediatrics 2024;153(5) View
13. Swanson K, He S, Calvano J, Chen D, Telvizian T, Jiang L, Chong P, Schwell J, Mak G, Lee J, Tariq A. Biomedical text readability after hypernym substitution with fine-tuned large language models. PLOS Digital Health 2024;3(4):e0000489 View
14. Taylor Pearson K. Pediatric Clinical Staff Perspectives on Secure Messaging. Journal of Nursing Care Quality 2024;39(4):317 View
15. Lalor J, Levy D, Jordan H, Hu W, Smirnova J, Yu H. Evaluating Expert-Layperson Agreement in Identifying Jargon Terms in Electronic Health Record Notes: Observational Study. Journal of Medical Internet Research 2024;26:e49704 View
16. Levy D, Jordan H, Lalor J, Smirnova J, Hu W, Liu W, Yu H. Individual Factors That Affect Laypeople's Understanding of Definitions of Medical Jargon. Health Policy and Technology 2024:100932 View