Rights (OCR) O for C. HITECH Act Enforcement Interim Final Rule 2009. https://www.hhs.gov/hipaa/for-professionals/special-topics/hitech-act-enforcement-interim-final-rule/index.html (accessed 5 November 2024).
The Federal Government Has Put Billions into Promoting Electronic Health Record Use: How Is It Going? n.d. https://www.commonwealthfund.org/publications/newsletter-article/federal-government-has-put-billions-promoting-electronic-health (accessed 5 November 2024).
What Are Electronic Health Records (EHRs)? | HealthIT.gov n.d. https://www.healthit.gov/topic/health-it-and-health-information-exchange-basics/what-are-electronic-health-records-ehrs (accessed 5 November 2024).
Blumenthal, D. & Tavenner, M. The “meaningful use” regulation for electronic health records. N. Engl. J. Med. 363, 501–504, https://doi.org/10.1056/NEJMp1006114 (2010).
Konttila, J. et al. Healthcare professionals’ competence in digitalisation: a systematic review. J. Clin. Nurs. 28, 745–761, https://doi.org/10.1111/jocn.14710 (2019).
Yeung, A. W. K. et al. The promise of digital healthcare technologies. Front. Public Health 11. https://doi.org/10.3389/fpubh.2023.1196596. (2023).
Tuckson, R. V., Edmunds, M. & Hodgkins, M. L. Telehealth. N. Engl. J. Med. 377, 1585–1592, https://doi.org/10.1056/NEJMsr1503323 (2017).
Eligible Professional’s Guide to STAGE 2 of the EHR Incentive Programs n.d.
Say Goodbye to Paper and Pagers: Modernizing Clinical Communication | Epic n.d. https://www.epic.com/epic/post/say-goodbye-to-paper-and-pagers-modernizing-clinical-communication-with-secure-chat/ (accessed 5 November 2024).
Secure Messaging Component n.d. https://cernprphelp.cernerworks.com/Help/default.aspx?pg=11 (accessed 5 November 2024).
MEDICARE TELEMEDICINE HEALTH CARE PROVIDER FACT SHEET | CMS n.d. https://www.cms.gov/newsroom/fact-sheets/medicare-telemedicine-health-care-provider-fact-sheet (accessed 5 November 2024).
Ozkaynak, M. et al. Examining the multi-level fit between work and technology in a secure messaging implementation. AMIA Annu. Symp. Proc. 2014, 954–962 (2014).
Haun, J. N. et al. Using electronic data collection platforms to assess complementary and integrative health patient-reported outcomes: feasibility project. JMIR Med. Inf. 8, e15609, https://doi.org/10.2196/15609 (2020).
Sisk, B. A. et al. Oncology clinicians’ perspectives on online patient portal use in pediatric and adolescent cancer. JCO Clin. Cancer Inf. 7, e2300124, https://doi.org/10.1200/CCI.23.00124 (2023).
Liu, T. et al. National trends in billing patient portal messages as e-visit services in traditional Medicare. Health Aff. Sch. 2, qxae040, https://doi.org/10.1093/haschl/qxae040 (2024).
Soekijad, M. Efficiency paradox: introducing secure messaging in outpatient care. Soc. Sci. Med. 365. https://doi.org/10.1016/j.socscimed.2024.117578. (2025).
Fogg, J.F. & Sinsky, C.A. In-basket reduction: a multiyear pragmatic approach to lessen the work burden of primary care physicians. NEJM Catal. 4. https://doi.org/10.1056/CAT.22.0438. (2023)
Kurek, A. et al. The “Inboxologist” — A novel approach to in-basket management in primary care. NEJM Catal. 5. https://doi.org/10.1056/CAT.24.0133. .(2024)
Holmgren, A.J. et al. Changes in secure messaging after implementation of billing E-visits by demographic group. JAMA Netw Open 7, e2427053. https://doi.org/10.1001/jamanetworkopen.2024.27053. (2024).
Cronin, R. M. et al. Automated classification of consumer health information needs in patient portal messages. AMIA Annu. Symp. Proc. 2015, 1861–1870 (2015).
Cronin, R. M. et al. A comparison of rule-based and machine learning approaches for classifying patient portal messages. Int. J. Med. Inf. 105, 110–120, https://doi.org/10.1016/j.ijmedinf.2017.06.004 (2017).
Chen, J. et al. Detecting hypoglycemia incidents reported in patients’ secure messages: using cost-sensitive learning and oversampling to reduce data imbalance. J. Med. Internet Res. 21, e11990, https://doi.org/10.2196/11990 (2019).
Tai-Seale, M. et al. AI-Generated draft replies integrated into health records and physicians’ electronic communication. JAMA Netw. Open 7, e246565, https://doi.org/10.1001/jamanetworkopen.2024.6565 (2024).
Afshar, M. et al. Prompt engineering with a large language model to assist providers in responding to patient inquiries: a real-time implementation in the electronic health record. JAMIA Open 7, ooae080, https://doi.org/10.1093/jamiaopen/ooae080 (2024).
Baxter, S. L. et al. Generative artificial intelligence responses to patient messages in the electronic health record: early lessons learned. JAMIA Open 7, ooae028, https://doi.org/10.1093/jamiaopen/ooae028 (2024).
Sulieman, L., Robinson, J. R. & Jackson, G. P. Automating the classification of complexity of medical decision-making in patient-provider messaging in a patient portal. J. Surg. Res. 255, 224–232, https://doi.org/10.1016/j.jss.2020.05.039 (2020).
Mermin-Bunnell, K. et al. Use of natural language processing of patient-initiated electronic health record messages to identify patients with COVID-19 infection. JAMA Netw. Open 6, e2322299, https://doi.org/10.1001/jamanetworkopen.2023.22299 (2023).
Mastorakos, G. et al. Probing patient messages enhanced by natural language processing: a top-down message corpus analysis. Health Data Sci. 2021. https://doi.org/10.34133/2021/1504854. (2021)
Ko, D.G. et al. Beyond time-based billing: an ai-enabled complexity model for secure message reimbursement. Telemed J E Health. https://doi.org/10.1177/15305627251377376. (2025).
McGeady, D., Kujala, J. & Ilvonen, K. The impact of patient–physician web messaging on healthcare service provision. Int. J. Med. Inf. 77, 17–23, https://doi.org/10.1016/j.ijmedinf.2006.11.004 (2008).
Wallwiener, M. et al. Impact of electronic messaging on the patient-physician interaction. J. Telemed. Telecare 15, 243–250, https://doi.org/10.1258/jtt.2009.090111 (2009).
Goldzweig, C.L. et al. Systematic review: secure messaging between providers and patients, and patients’ access to their own medical record: evidence on health outcomes, satisfaction, efficiency and attitudes. Washington (DC): Department of Veterans Affairs (US); (2012).
Liu, X. et al. Evaluation of secure messaging applications for a health care system: a case study. Appl. Clin. Inf. 10, 140–150, https://doi.org/10.1055/s-0039-1678607 (2019).
Kuo, A. & Dang, S. Secure messaging in electronic health records and its impact on diabetes clinical outcomes: a systematic review. Telemed. E-Health 22, 769–777, https://doi.org/10.1089/tmj.2015.0207 (2016).
Wec, A. et al. Measurement, drivers, and outcomes of patient-initiated secure messaging use and intensity: a scoping review. JAMIA Open 8, ooaf087, https://doi.org/10.1093/jamiaopen/ooaf087 (2025).
Conroy, M. et al. Electronic medical record–based electronic messaging among patients with breast cancer: a systematic review. Appl. Clin. Inf. 14, 134–143, https://doi.org/10.1055/a-2004-6669 (2023).
Hu, D. et al. A systematic review of early evidence on generative AI for drafting responses to patient messages. Npj Health Syst. 2, 27, https://doi.org/10.1038/s44401-025-00032-5 (2025).
Guo, Y. et al. Computational use of patient–provider secure messaging data to achieve better clinical efficiency and quality of communication: a systematic review https://doi.org/10.1101/2025.05.19.25327936. (2025).
Robinson, S. A. et al. Secure messaging, diabetes self-management, and the importance of patient autonomy: a mixed methods study. J. Gen. Intern. Med. 35, 2955–2962, https://doi.org/10.1007/s11606-020-05834-x (2020).
Harris, L. T. et al. Glycemic control associated with secure patient-provider messaging within a shared electronic medical record: a longitudinal analysis. Diab. Care 36, 2726–2733, https://doi.org/10.2337/dc12-2003 (2013).
Russell, N.M. et al. Text-messaging to support diabetes self-management in a rural health clinic: a quality improvement project. Online J. Nurs. Inform. 21, https://www.caremessage.org/text-messaging-to-support-diabetes-self-management/ (2017).
Heisey-Grove, D. M. et al. Associations between patient health outcomes and secure message content exchanged between patients and clinicians: retrospective cohort study. J. Med. Internet Res. 22, e19477, https://doi.org/10.2196/19477 (2020).
Price-Haywood, E. G., Luo, Q. & Monlezun, D. Dose effect of patient-care team communication via secure portal messaging on glucose and blood pressure control. J. Am. Med. Inf. Assoc. 25, 702–708, https://doi.org/10.1093/jamia/ocx161 (2018).
Shimada, S. L. et al. Sustained use of patient portal features and improvements in diabetes physiological measures. J. Med. Internet Res. 18, e179, https://doi.org/10.2196/jmir.5663 (2016).
Robinson, S. A. et al. Differences in secure messaging, self-management, and glycemic control between rural and urban patients: secondary data analysis. JMIR Diab. 6, e32320, https://doi.org/10.2196/32320 (2021).
Lyles, C. R. et al. Communication about diabetes risk factors during between-visit encounters. Am. J. Manag Care 18, 807–815 (2012).
Quinn, C. C. et al. Mobile diabetes intervention study of patient engagement and impact on blood glucose: mixed methods analysis. JMIR MHealth UHealth 6, e31, https://doi.org/10.2196/mhealth.9265 (2018).
Bredfeldt, C. E., Compton-Phillips, A. L. & Snyder, M. H. Effects of between visit physician-patient communication on Diabetes Recognition Program scores. Int. J. Qual. Health Care 23, 664–673, https://doi.org/10.1093/intqhc/mzr061 (2011).
Alexander, J. & Beatty, A. Association of patient portal messaging with survival among radiation oncology patients. Int. J. Radiat. Oncol. Biol. Phys. 120, 627–638, https://doi.org/10.1016/j.ijrobp.2024.05.003 (2024).
Wagner, L. I. et al. Bringing PROMIS to practice: brief and precise symptom screening in ambulatory cancer care. Cancer 121, 927–934, https://doi.org/10.1002/cncr.29104 (2015).
Ralston, J. D. et al. Home blood pressure monitoring, secure electronic messaging and medication intensification for improving hypertension control: a mediation analysis. Appl. Clin. Inf. 5, 232–248, https://doi.org/10.4338/ACI-2013-10-RA-0079 (2014).
Iturralde, E. et al. Changing results-engage and activate to enhance wellness: a randomized clinical trial to improve cardiovascular risk management. J. Am. Heart Assoc. 8, e014021, https://doi.org/10.1161/JAHA.119.014021 (2019).
North, F. et al. Telemonitoring blood pressure by secure message on a patient portal: use, content, and outcomes. Telemed. J. E Health 21, 630–636, https://doi.org/10.1089/tmj.2014.0179 (2015).
Cutrona, S. L. et al. Improving rates of outpatient influenza vaccination through EHR portal messages and interactive automated calls: a randomized controlled trial. J. Gen. Intern. Med. 33, 659–667, https://doi.org/10.1007/s11606-017-4266-9 (2018).
Wijesundara, J. G. et al. Electronic health record portal messages and interactive voice response calls to improve rates of early season influenza vaccination: randomized controlled trial. J. Med. Internet Res. 22, e16373, https://doi.org/10.2196/16373 (2020).
Khan, A. A. et al. A learning health system approach to increasing human papillomavirus immunizations among young adults. Perm. J. 27, 31–36, https://doi.org/10.7812/TPP/22.094 (2023).
Ueberroth, B. E., Labonte, H. R. & Wallace, M. R. Impact of patient portal messaging reminders with self-scheduling option on influenza vaccination rates: a prospective, randomized trial. J. Gen. Intern. Med. 37, 1394–1399, https://doi.org/10.1007/s11606-021-06941-z (2022).
Berset, A. E. et al. Effect of electronic outreach using patient portal messages on well child care visit completion: a randomized clinical trial. JAMA Netw. Open 5, e2242853, https://doi.org/10.1001/jamanetworkopen.2022.42853 (2022).
Rauhut, M. A. Digital engagement and the efficacy of patient portal-based preventive care interventions. Digit Health 11, 20552076251356013, https://doi.org/10.1177/20552076251356013 (2025).
Goshgarian, G. et al. Effect of patient portal messaging before mailing fecal immunochemical test Kit on colorectal cancer screening rates: a randomized clinical trial. JAMA Netw. Open 5, e2146863, https://doi.org/10.1001/jamanetworkopen.2021.46863 (2022).
Halket, D. et al. Targeted electronic patient portal messaging increases Hepatitis C virus screening in primary care: a randomized study. J. Gen. Intern. Med. 37, 3318–3324, https://doi.org/10.1007/s11606-022-07460-1 (2022).
Hojat, L. et al. Doubling Hepatitis C virus screening in primary care using advanced electronic health record tools—a non-randomized controlled trial. J. Gen. Intern. Med. 35, 498–504, https://doi.org/10.1007/s11606-019-05536-z (2020).
Yedulla, N. R. et al. Pre-visit digital messaging improves patient-reported outcome measure participation prior to the orthopaedic ambulatory visit: results from a double-blinded, prospective, randomized controlled trial. J. Bone Jt Surg. Am. 105, 20–26, https://doi.org/10.2106/JBJS.21.00506 (2023).
Yip, J.Y. et al. Impact of a patient portal-based telehealth outreach program on recall of patients with diabetic retinopathy. Telemed E-Health. https://doi.org/10.1089/tmj.2024.0454. (2024).
Lam, S. W. et al. A novel detection method to identify individuals with Alpha-1 Antitrypsin deficiency: linking prescription of COPD medications with the patient-facing electronic medical record. Chronic Obstr. Pulm. Dis. 9, 26–33, https://doi.org/10.15326/jcopdf.2021.0260 (2022).
Sawicki, C. et al. Two-way clinical messaging in a CML specialty pharmacy service model. J. Manag. Care Spec. Pharm. 25, 1290–1296, https://doi.org/10.18553/jmcp.2019.25.11.1290 (2019).
Dicianno, B. E. et al. Feasibility of using mobile health to promote self-management in Spina Bifida. Am. J. Phys. Med Rehabil. 95, 425–437, https://doi.org/10.1097/PHM.0000000000000400 (2016).
Turvey, C. et al. Secure messaging intervention in patients starting new antidepressant to promote adherence: pilot randomized controlled trial. JMIR Form. Res. 7, e51277, https://doi.org/10.2196/51277 (2023).
Manka, M. G. et al. Assessing the impact of hospital dismissal summary readability on patient outcomes following prostatectomy. Urology 157, 201–205, https://doi.org/10.1016/j.urology.2021.06.040 (2021).
Tieu, C. et al. Utilization of patient electronic messaging to promote advance care planning in the primary care setting. Am. J. Hosp. Palliat. Care 34, 665–670, https://doi.org/10.1177/1049909116650237 (2017).
Ginting, K. et al. Patient portal, patient-generated images, and medical decision-making in a pediatric ambulatory setting. Appl. Clin. Inf. 11, 764–768, https://doi.org/10.1055/s-0040-1718754 (2020).
Dang, S. et al. Evaluating an electronic health record intervention for management of heart failure among veterans. Telemed. J. E Health 24, 1006–1013, https://doi.org/10.1089/tmj.2017.0307 (2018).
Lamba, A. H. et al. Characteristics of women enrolled in a patient portal intervention for menopause. Women’s. Health Rep. N. Rochelle 1, 500–510, https://doi.org/10.1089/whr.2020.0091 (2020).
Sadasivam, R. S. et al. Secure asynchronous communication between smokers and tobacco treatment specialists: secondary analysis of a web-assisted tobacco intervention in the QUIT-PRIMO and National dental PBRN networks. J. Med. Internet Res. 22, e13289, https://doi.org/10.2196/13289 (2020).
“Can you hear me now?”: postoperative patient-initiated communication with providers. Am. J. Manag. Care 26, e333–e341. https://doi.org/10.37765/ajmc.2020.88507. (2020).
Zurlo, J. et al. OPT-in for life: a mobile technology–based intervention to improve HIV care continuum for young adults living with HIV. Health Promot Pract. 21, 727–737, https://doi.org/10.1177/1524839920936247 (2020).
Diyaolu, M. et al. Outcome assessment of office Plastibell circumcision in infants utilizing interactive electronic health record. J. Pediatr. Surg. 58, 1008–1013, https://doi.org/10.1016/j.jpedsurg.2023.01.043 (2023).
Smith, J. R. et al. High-frequency utilization of the outpatient messaging system in a specialized outpatient catatonia clinic for individuals with Autism spectrum disorder. J. Child Adolesc. Psychopharmacol. 35, 424–430, https://doi.org/10.1089/cap.2025.0034 (2025).
Carlson, K. J. et al. The effect of geographic rounding on hospitalist work experience: a mixed-methods study. Hosp. Pract. 50, 124–131, https://doi.org/10.1080/21548331.2022.2050649 (2022).
Bala, T. R. An improvement project in reducing after-visit phone calls in a community pediatric neurology clinic: too much communication?. Neurol. Clin. Pract. 14, e200269, https://doi.org/10.1212/CPJ.0000000000200269 (2024).
Edwards, A. L. et al. Association between gastrointestinal symptoms and specialty care utilization among colon cancer survivors: a cohort study. Int. J. Colorectal Dis. 39, 130, https://doi.org/10.1007/s00384-024-04685-w (2024).
Powell, D. S. et al. The annual wellness visit health risk assessment: potential of patient portal-based completion and patient-oriented education and support. Innov. Aging 8, igae023, https://doi.org/10.1093/geroni/igae023 (2024).
Powell, K. R. & Deroche, C. Predictors and patterns of portal use in patients with multiple chronic conditions. Chronic Illn. 16, 275–283, https://doi.org/10.1177/1742395318803663 (2020).
Zhong, X. et al. The impact of e-visits on patient access to primary care. Health Care Manag. Sci. 21, 475–491, https://doi.org/10.1007/s10729-017-9404-8 (2018).
Liss, D. T. et al. Changes in office visit use associated with electronic messaging and telephone encounters among patients with diabetes in the PCMH. Ann. Fam. Med. 12, 338–343, https://doi.org/10.1370/afm.1642 (2014).
North, F. et al. Patient-generated secure messages and eVisits on a patient portal: are patients at risk?. J. Am. Med. Inf. Assoc. 20, 1143–1149, https://doi.org/10.1136/amiajnl-2012-001208 (2013).
Heisey-Grove, D. et al. Associations between patient-provider secure message content and patients’ health care visits. Telemed. J. E Health 28, 690–698, https://doi.org/10.1089/tmj.2021.0164 (2022).
Plate, J. F. et al. Utilization of an electronic patient portal following total joint arthroplasty does not decrease readmissions. J. Arthroplast. 34, 211–214, https://doi.org/10.1016/j.arth.2018.11.002 (2019).
Hong, Y. R. et al. Trends in e-visit adoption among U.S. office-based physicians: evidence from the 2011-2015 NAMCS. Int. J. Med. Inf. 129, 260–266, https://doi.org/10.1016/j.ijmedinf.2019.06.025 (2019).
Neeman, E. et al. Attitudes and perceptions of multidisciplinary cancer care clinicians toward telehealth and secure messages. JAMA Netw. Open 4, e2133877, https://doi.org/10.1001/jamanetworkopen.2021.33877 (2021).
Bavafa, H., Hitt, L. M. & Terwiesch, C. The impact of E-visits on visit frequencies and patient health: evidence from primary care. Manag. Sci. 64, 5461–5480, https://doi.org/10.1287/mnsc.2017.2900 (2018).
Warren, C. J. et al. A Tale of 102,726 messages: characterizing the modern urologist’s portal message burden after common urologic surgeries. Urol Pract. 12. https://doi.org/10.1097/UPJ.0000000000000718. (2025).
Ozdag, Y., Makar, G. S. & Kolessar, D. J. Postoperative communication volume following total joint arthroplasty can be a precursor for emergency department visits. Arthroplast Today 27, 101352, https://doi.org/10.1016/j.artd.2024.101352 (2024).
Chua, T.L. et al. Post-operative patient portal messaging is associated with return to the emergency department after lumbar spine surgery. Spine. https://doi.org/10.1097/BRS.0000000000005006. (2024).
Hoonakker, P. L. T., Carayon, P. & Cartmill, R. S. The impact of secure messaging on workflow in primary care: results of a multiple-case, multiple-method study. Int. J. Med. Inf. 100, 63–76, https://doi.org/10.1016/j.ijmedinf.2017.01.004 (2017).
Shimada, S. L. et al. Patient-provider secure messaging in VA: variations in adoption and association with urgent care utilization. Med. Care 51, S21–S28, https://doi.org/10.1097/MLR.0b013e3182780917 (2013).
Reed, M. et al. Patient-initiated e-mails to providers: associations with out-of-pocket visit costs, and impact on care-seeking and health. Am. J. Manag Care 21, e632–e639 (2015).
O’Shea, A. M. J. et al. Association of secure messaging with primary care in-person and telephone visits among veterans: a matched difference-in-difference analysis. J. Gen. Intern Med 36, 946–951, https://doi.org/10.1007/s11606-020-06541-3 (2021).
Kachroo, N. et al. Does “MyChart” Benefit “My” Surgery? A Look at the impact of electronic patient portals on patient experience. J. Urol. 204, 760–768, https://doi.org/10.1097/JU.0000000000001090 (2020).
Apaydin, E. A. et al. Secure messages, video visits, and burnout among primary care providers in the Veterans Health Administration: national survey study. J. Med. Internet Res. 27, e68858, https://doi.org/10.2196/68858 (2025).
Baxter, S. L. et al. Association of electronic health record in-basket message characteristics with physician burnout. JAMA Netw. Open 5, e2244363, https://doi.org/10.1001/jamanetworkopen.2022.44363 (2022).
Pfaff, E. et al. Recruiting for a pragmatic trial using the electronic health record and patient portal: successes and lessons learned. J. Am. Med. Inf. Assoc. 26, 44–49, https://doi.org/10.1093/jamia/ocy138 (2019).
Miller, H. N. et al. Electronic medical record-based cohort selection and direct-to-patient, targeted recruitment: early efficacy and lessons learned. J. Am. Med. Inf. Assoc. 26, 1209–1217, https://doi.org/10.1093/jamia/ocz168 (2019).
Plante, T. B. et al. Recruitment of trial participants through electronic medical record patient portal messaging: a pilot study. Clin.Trials 17, 30–38, https://doi.org/10.1177/1740774519873657 (2020).
Beaton, M. et al. Using patient portals for large-scale recruitment of individuals underrepresented in biomedical research: an evaluation of engagement patterns throughout the patient portal recruitment process at a single site within the All of Us Research Program. J. Am. Med. Inf. Assoc. 31, 2328–2336, https://doi.org/10.1093/jamia/ocae135 (2024).
Miller, H. N. et al. Use of electronic recruitment methods in a clinical trial of adults with gout. Clin. Trials 18, 92–103, https://doi.org/10.1177/1740774520956969 (2021).
Pogue, J. R. et al. Strategies and lessons learned from a longitudinal study to maximize recruitment in the midst of a global pandemic. Proc. Bayl. Univ. Med. Cent. 35, 309–314, https://doi.org/10.1080/08998280.2022.2034494 (2022).
Nassif, M. et al. Recruitment strategies of a decentralized randomized placebo controlled clinical trial: the canagliflozin impact on health status, quality of life and functional status in heart failure (CHIEF-HF) Trial. J. Card. Fail 29, 863–869, https://doi.org/10.1016/j.cardfail.2023.04.001 (2023).
Baucom, R. B. et al. Case report: patient portal versus telephone recruitment for a surgical research study. Appl. Clin. Inf. 5, 1005–1014, https://doi.org/10.4338/ACI-2014-07-CR-0059 (2014).
Dykes, C. et al. Implementation of MyChart for recruitment at an academic medical center. J. Clin. Transl. Sci. 8, e160, https://doi.org/10.1017/cts.2024.605 (2024).
Ziegenfuss, J.Y. et al. A randomized study comparing patient portal and email communications for trial recruitment. Clin. Trials 17407745251358259. https://doi.org/10.1177/17407745251358259. (2025).
Peeler, A. et al. Centralized registry for COVID-19 research recruitment: design, development, implementation, and preliminary results. J. Clin. Transl. Sci. 5, e152, https://doi.org/10.1017/cts.2021.819 (2021).
Loftus, J. R. et al. Impact of early direct patient notification on follow-up completion for nonurgent actionable incidental radiologic findings. J. Am. Coll. Radio. 21, 558–566, https://doi.org/10.1016/j.jacr.2023.07.026 (2024).
Sun, S. et al. Messaging to your doctors: understanding patient-provider communications via a portal system, Paris, France: Association for Computing Machinery. 1739–1748. https://doi.org/10.1145/2470654.2466230. (2013).
Mehta, S. J. et al. Behavioral interventions to improve population health outreach for hepatitis C screening: randomized clinical trial. BMJ 373, n1022, https://doi.org/10.1136/bmj.n1022 (2021).
Lieu, T. A. et al. Effect of electronic and mail outreach from primary care physicians for COVID-19 vaccination of black and latino older adults: a randomized clinical trial. JAMA Netw. Open 5, e2217004, https://doi.org/10.1001/jamanetworkopen.2022.17004 (2022).
Chen, Y. et al. “I don’t bother with the phone!”. Feeling Closer Phys. using Secur. Messaging 2017, 3813–3822 (2017).
Greenwood, D. A. et al. A comparison of in-person, telephone, and secure messaging for Type 2 diabetes self-management support. Diab. Educ. 40, 516–525, https://doi.org/10.1177/0145721714531337 (2014).
Bundogji, N., Toma, G. & Khan, A. Identification of preferred reminder systems and patient factors to promote adherence in the management of urinary incontinence. PEC Innov. 1, 100067, https://doi.org/10.1016/j.pecinn.2022.100067 (2022).
Paige, S. R. et al. Patient message preferences to promote clinical conversations about chronic obstructive pulmonary disease (COPD): a discrete choice experiment. PEC Innov. 2, 100168, https://doi.org/10.1016/j.pecinn.2023.100168 (2023).
Raghu, T. S. et al. Using secure messaging to update medications list in ambulatory care setting. Int. J. Med. Inf. 84, 754–762, https://doi.org/10.1016/j.ijmedinf.2015.06.003 (2015).
Whiteside, U. et al. Online cognitive behavioral therapy for depressed primary care patients: a pilot feasibility project. Perm. J. 18, 21–27, https://doi.org/10.7812/TPP/13-155 (2014).
Sequist, T. D. et al. Electronic patient messages to promote colorectal cancer screening: a randomized controlled trial. Arch. Intern. Med. 171, 636–641, https://doi.org/10.1001/archinternmed.2010.467 (2011).
Lee, J. K. et al. Randomized trial of patient outreach approaches to de-implement outdated colonoscopy surveillance intervals. Clin. Gastroenterol. Hepatol. 22, 1315–1322.e7, https://doi.org/10.1016/j.cgh.2023.12.027 (2024).
Bennett, W. L. et al. Patient recruitment into a multicenter clinical cohort linking electronic health records from 5 health systems: cross-sectional analysis. J. Med. Internet Res. 23, e24003, https://doi.org/10.2196/24003 (2021).
Fisher, L. et al. A novel household-based patient outreach pilot program to boost late-season influenza vaccination rates during the COVID-19 pandemic. Influenza Other Respir. Viruses 16, 1141–1150, https://doi.org/10.1111/irv.13041 (2022).
Rand, M. L. Nursing interventions increase influenza vaccination quality measures for home telehealth patients. J. Nurs. Care Qual. 37, 47–53, https://doi.org/10.1097/NCQ.0000000000000577 (2022).
Szilagyi, P. G. et al. Text vs patient portal messaging to improve influenza vaccination coverage: a health system-wide randomized clinical trial. JAMA Intern. Med. 184, 519–527, https://doi.org/10.1001/jamainternmed.2024.0001 (2024).
Haff, N. et al. “How” Versus “Why” messaging to increase uptake of booster vaccination against COVID-19: results of a pragmatic randomized trial. J. Gen. Intern. Med. 39, 611–618, https://doi.org/10.1007/s11606-023-08492-x (2024).
Szilagyi, P. G. et al. Video and infographic messages from primary care physicians and influenza vaccination rates: a randomized clinical trial. JAMA Netw. Open 8, e2526514–e2526514, https://doi.org/10.1001/jamanetworkopen.2025.26514 (2025).
Houston, T. K. et al. Evaluating the QUIT-PRIMO clinical practice ePortal to increase smoker engagement with online cessation interventions: a national hybrid type 2 implementation study. Implement Sci. 10, 154, https://doi.org/10.1186/s13012-015-0336-8 (2015).
Erdmann, M., Edwards, B. & Adewumi, M. T. Effect of electronic portal messaging with embedded asynchronous care on physician-assisted smoking cessation attempts: a randomized clinical trial. JAMA Netw. Open 5, e220348, https://doi.org/10.1001/jamanetworkopen.2022.0348 (2022).
Midboe, A. M. et al. Relationship between patient portal tool use and medication adherence and viral load among patients living with HIV. J. Gen. Intern. Med. 39, 127–135, https://doi.org/10.1007/s11606-023-08474-z (2024).
McInnes, D. K. et al. Patient use of electronic prescription refill and secure messaging and its association with undetectable HIV viral load: a retrospective cohort study. J. Med. Internet Res. 19, e34, https://doi.org/10.2196/jmir.6932 (2017).
Nagler, A.R. et al. Patient portal messaging to address delayed follow-up for uncontrolled diabetes: a pragmatic, randomised clinical trial. BMJ Qual Saf.. https://doi.org/10.1136/bmjqs-2024-018249. (2025).
Ralston, J. D. et al. Use of web-based shared medical records among patients with HIV. Am. J. Manag Care 19, e114–e124 (2013).
Steitz, B. et al. Long-term patterns of patient portal use for pediatric patients at an academic medical center. Appl. Clin. Inf. 8, 779–793, https://doi.org/10.4338/ACI-2017-01-RA-0005 (2017).
Waselewski, M. E. et al. A mobile health app to support patients receiving medication-assisted treatment for opioid use disorder: development and feasibility study. JMIR Form. Res. 5, e24561, https://doi.org/10.2196/24561 (2021).
Yamin, C. K. et al. The digital divide in adoption and use of a personal health record. Arch. Intern. Med. 171, 568–574, https://doi.org/10.1001/archinternmed.2011.34 (2011).
Hefner, J. L. et al. Patient portal messaging for care coordination: a qualitative study of perspectives of experienced users with chronic conditions. BMC Fam. Pract. 20, 57, https://doi.org/10.1186/s12875-019-0948-1 (2019).
Furukawa, M. F. et al. WEB FIRST. Despite substantial progress in ehr adoption, health information exchange and patient engagement remain low in office settings. Health Aff. 33, 1672–1679, https://doi.org/10.1377/hlthaff.2014.0445 (2014).
Cronin, R. M. et al. Growth of secure messaging through a patient portal as a form of outpatient interaction across clinical specialties. Appl. Clin. Inf. 6, 288–304, https://doi.org/10.4338/ACI-2014-12-RA-0117 (2015).
Senft, N., Butler, E. & Everson, J. Growing disparities in patient-provider messaging: trend analysis before and after supportive policy. J. Med. Internet Res. 21, e14976, https://doi.org/10.2196/14976 (2019).
Heisey-Grove, D. M. & Carretta, H. J. Disparities in secure messaging uptake between patients and physicians: longitudinal analysis of two national cross-sectional surveys. J. Med. Internet Res. 22, e12611, https://doi.org/10.2196/12611 (2020).
Yousef, C. C. et al. Predicting health care providers’ acceptance of a personal health record secure messaging feature. Appl. Clin. Inf. 13, 148–160, https://doi.org/10.1055/s-0041-1742217 (2022).
Masterman, M. et al. Adoption of secure messaging in a patient portal across pediatric specialties. AMIA Annu. Symp. Proc. 2016, 1930–1939 (2016).
Shenson, J. A. et al. Rapid growth in surgeons’ use of secure messaging in a patient portal. Surg. Endosc. 30, 1432–1440, https://doi.org/10.1007/s00464-015-4347-y (2016).
North, F. et al. A retrospective analysis of provider-to-patient secure messages: how much are they increasing, who is doing the work, and is the work happening after hours? JMIR. Med. Inf. 8, e16521, https://doi.org/10.2196/16521 (2020).
Haun, J. N. et al. Primary care virtual resource use prior and post COVID-19 pandemic onset. BMC Health Serv. Res. 22, 1370. https://doi.org/10.1186/s12913-022-08790-w (2022).
Martinez, K. A. et al. Patient portal message volume and time spent on the EHR: an observational study of primary care clinicians. J. Gen. Intern. Med. 39, 566–572, https://doi.org/10.1007/s11606-023-08577-7 (2024).
Crotty, B. H. et al. Patient-to-physician messaging: volume nearly tripled as more patients joined system, but per capita rate plateaued. Health Aff. Millwood 33, 1817–1822, https://doi.org/10.1377/hlthaff.2013.1145 (2014).
Ryan, S.P. et al. The contemporary “in-basket”: an explosion of unchecked administrative expectations. J. Arthroplasty https://doi.org/10.1016/j.arth.2025.06.069. (2025).
Arndt, B. G. et al. More tethered to the EHR: EHR workload trends among academic primary care physicians, 2019-2023. Ann. Fam. Med. 22, 12–18, https://doi.org/10.1370/afm.3047 (2024).
Huang, M. et al. Patient portal messaging for asynchronous virtual care during the COVID-19 pandemic: retrospective analysis. JMIR Hum. Factors 9, e35187, https://doi.org/10.2196/35187 (2022).
Campbell, B. R. et al. PositiveLinks and the COVID-19 response: importance of low-barrier messaging for PLWH in non-urban virginia in a crisis. AIDS Behav. 25, 3519–3527, https://doi.org/10.1007/s10461-021-03294-w (2021).
Brickson, C. et al. Characterizing electronic messaging use among hospitalists and its association with patient volumes. J. Hosp. Med.. https://doi.org/10.1002/jhm.13462. (2024).
Ko, S. A. et al. Secure messaging use among patients with depression: an analysis using real-world data. Telemed. J. E Health 30, 2157–2164, https://doi.org/10.1089/tmj.2024.0171 (2024).
Hansen, M. A. et al. Impact of COVID-19 lockdown on patient-provider electronic communications. J. Telemed. Telecare 30, 1285–1292, https://doi.org/10.1177/1357633X221146810 (2024).
Holmgren, A. J. et al. National trends in oncology specialists’ EHR inbox work, 2019-2022. J. Natl. Cancer Inst. 117, 1253–1259, https://doi.org/10.1093/jnci/djaf052 (2025).
Holmgren, A. J. et al. Assessing the impact of the COVID-19 pandemic on clinician ambulatory electronic health record use. J. Am. Med. Inf. Assoc. 29, 453–460, https://doi.org/10.1093/jamia/ocab268 (2022).
Holmgren, A. J. et al. Changes in physician electronic health record use with the expansion of telemedicine. JAMA Intern. Med. 183, 1357–1365, https://doi.org/10.1001/jamainternmed.2023.5738 (2023).
Smith, D. C. et al. Sudden shift to Telehealth in COVID-19: a retrospective cohort study of disparities in use of telehealth for prenatal care in a large midwifery service. J. Midwifery Women’s. Health 69, 522–530, https://doi.org/10.1111/jmwh.13601 (2024).
Shimada, S. L. et al. Personal health record reach in the Veterans Health Administration: a cross-sectional analysis. J. Med. Internet Res. 16, e272, https://doi.org/10.2196/jmir.3751 (2014).
Lyles, C. R. et al. Patient race/ethnicity and shared medical record use among diabetes patients. Med. Care 50, 434–440, https://doi.org/10.1097/MLR.0b013e318249d81b (2012).
Riera, K. M. et al. Care delivered by pediatric surgical specialties through patient portal messaging. J. Surg. Res. 234, 231–239, https://doi.org/10.1016/j.jss.2018.09.013 (2019).
Weppner, W. G. et al. Use of a shared medical record with secure messaging by older patients with diabetes. Diab. Care 33, 2314–2319, https://doi.org/10.2337/dc10-1124 (2010).
Neeman, E. et al. Future of teleoncology: trends and disparities in telehealth and secure message utilization in the COVID-19 Era. JCO Clin. Cancer Inf. 6, e2100160, https://doi.org/10.1200/CCI.21.00160 (2022).
Chivela, F. L., Burch, A. E. & Asagbra, O. An assessment of patient portal messaging use by patients with multiple chronic conditions living in rural communities: retrospective analysis. J. Med. Internet Res. 25, e44399, https://doi.org/10.2196/44399 (2023).
Huang, M. et al. Characterizing patient-clinician communication in secure medical messages: retrospective study. J. Med. Internet Res. 24, e17273, https://doi.org/10.2196/17273 (2022).
Ralston, J. D. et al. Patient use of secure electronic messaging within a shared medical record: a cross-sectional study. J. Gen. Intern. Med. 24, 349–355, https://doi.org/10.1007/s11606-008-0899-z (2009).
Khalil, N. et al. Multiple sclerosis and MyChart messaging: a retrospective chart review evaluating its use. Int. J. MS Care 24, 271–274, https://doi.org/10.7224/1537-2073.2020-101 (2022).
Mueller, B. et al. A retrospective cohort study of clinical factors, visit patterns, and demographic factors associated with use of remote communications in patients with headache. Headache 61, 1521–1528, https://doi.org/10.1111/head.14226 (2021).
Couture, A. & Birstler, J. The gender of the sender: assessing gender biases of greetings in patient portal messages. J. Women’s. Health Larchmt. 32, 171–177, https://doi.org/10.1089/jwh.2022.0333 (2023).
Bryan, M. et al. Resource utilization among portal users who send messages: a retrospective cohort study. WMJ 119, 26–32 (2020).
Yakushi, J. et al. Utilization of secure messaging to primary care departments. Perm J. 24. https://doi.org/10.7812/TPP/19.177. (2020).
Huang, M. et al. Characterizing the users of patient portal messaging: a single institutional cohort study. 381–387. https://doi.org/10.1109/ICHI57859.2023.00057. (2023).
Fleming, N. L., Cullen, D. & Luna, G. An evaluation of patient web portal engagement: an exploratory study of patients with hypertension and diabetes. Online J. Nurs. Inform. 19, 1–8 (2015).
Monestime, J. P. et al. Characteristics of office-based providers associated with secure electronic messaging use: achieving meaningful use. Int. J. Med. Inf. 129, 43–48, https://doi.org/10.1016/j.ijmedinf.2019.04.002 (2019).
Hansen, M. A. et al. Demographics and clinical features associated with rates of electronic message utilization in the primary care setting. Int. J. Med. Inf. 183, 105339, https://doi.org/10.1016/j.ijmedinf.2024.105339 (2024).
Siddiqui, S. et al. Use of the Veterans Health Administration online patient portal among Veterans with spinal cord injuries and disorders. J. Spinal Cord. Med. 46, 917–928, https://doi.org/10.1080/10790268.2022.2084967 (2023).
Ukoha, E. P., Feinglass, J. & Yee, L. M. Disparities in electronic patient portal use in prenatal care: retrospective cohort study. J. Med. Internet Res. 21, e14445, https://doi.org/10.2196/14445 (2019).
Levine, D. M., Linder, J. A. & Landon, B. E. Characteristics and disparities among primary care practices in the United States. J. Gen. Intern. Med. 33, 481–486, https://doi.org/10.1007/s11606-017-4239-z (2018).
Huang, M. et al. Midwest rural-urban disparities in use of patient online services for COVID-19. J. Rural Health 38, 908–915, https://doi.org/10.1111/jrh.12657 (2022).
Graetz, I. et al. The digital divide and patient portals: internet access explained differences in patient portal use for secure messaging by age, race, and income. Med. Care 54, 772–779, https://doi.org/10.1097/MLR.0000000000000560 (2016).
Corriveau, B. et al. Sociodemographic variation in use of and preferences for digital technologies among patients in primary care: results from the OurCare national survey. Can. Fam. Phys. 71, 324–336, https://doi.org/10.46747/cfp.7105324 (2025).
Avoundjian, T. et al. Correlates of personal health record registration and utilization among veterans with HIV. JAMIA Open 4, ooab029, https://doi.org/10.1093/jamiaopen/ooab029 (2021).
Staloff, J. et al. High users of primary care secure messaging in the veterans health administration. Ann. Fam. Med. 23, 285–293, https://doi.org/10.1370/afm.240360 (2025).
Semere, W. et al. Secure messaging with physicians by proxies for patients with diabetes: findings from the ECLIPPSE Study. J. Gen. Intern Med 34, 2490–2496, https://doi.org/10.1007/s11606-019-05259-1 (2019).
Alexander, J. & Beatty, A. L. Disparities in patient portal messaging among oncology patients enrolled in the patient portal. JCO Clin. Cancer Inf. 9, e2400234, https://doi.org/10.1200/CCI-24-00234 (2025).
Smith, S. G. et al. Disparities in registration and use of an online patient portal among older adults: findings from the LitCog cohort. J. Am. Med. Inf. Assoc. 22, 888–895, https://doi.org/10.1093/jamia/ocv025 (2015).
Blok, A. C. et al. Impact of patient access to online VA notes on healthcare utilization and clinician documentation: a retrospective Cohort study. J. Gen. Intern. Med. 36, 592–599, https://doi.org/10.1007/s11606-020-06304-0 (2021).
Harris, L. T. et al. Diabetes quality of care and outpatient utilization associated with electronic patient-provider messaging: A cross-sectional analysis. Diab. Care 32, 1182–1187, https://doi.org/10.2337/dc08-1771 (2009).
Zhong, L. et al. Importance of prior patient interactions with the healthcare system to engaging with pretest cancer genetic services via digital health tools among unaffected primary care patients: findings from the BRIDGE Trial. Health Serv. Res. e14652. https://doi.org/10.1111/1475-6773.14652. (2025).
Steitz, B. D. et al. Repeated access to patient portal while awaiting test results and patient-initiated messaging. JAMA Netw. Open 8, e254019–e254019, https://doi.org/10.1001/jamanetworkopen.2025.4019 (2025).
Hoopes, A.J. et al. Characteristics of adolescents who use secure messaging on a health system’s patient portal. Pediatrics 152. https://doi.org/10.1542/peds.2022-060271. (2023).
Ko, D-G. The impact of secure messaging telehealth service on the quality of healthcare. Telehealth Med. Today 8. https://doi.org/10.30953/thmt.v8.435. (2023).
Crotty, B. H. et al. Prevalence and risk profile of unread messages to patients in a patient web portal. Appl. Clin. Inf. 06, 375–382, https://doi.org/10.4338/ACI-2015-01-CR-0006 (2015).
Tang, M. et al. Differences in care team response to patient portal messages by patient race and ethnicity. JAMA Netw. Open 7, e242618, https://doi.org/10.1001/jamanetworkopen.2024.2618 (2024).
Jones, A. L. et al. Low uptake of secure messaging among veterans with experiences of homelessness and substance use disorders. J. Addict. Med. 15, 508–511, https://doi.org/10.1097/ADM.0000000000000785 (2021).
Leung, L. B. et al. Characteristics of veterans experiencing homelessness using telehealth for primary care before and after COVID-19 pandemic onset. J. Gen. Intern. Med. 39, 53–59, https://doi.org/10.1007/s11606-023-08462-3 (2024).
Holder, K. et al. Use of electronic patient messaging by pregnant patients receiving prenatal care at an academic health system: retrospective cohort study. JMIR Mhealth Uhealth 12, e51637, https://doi.org/10.2196/51637 (2024).
Gordon, N. P. et al. Lower use of and potential barriers to using patient portals among limited english proficient latino and Chinese American adults: a health Techquity Concern. Perm. J. 29, 1–22, https://doi.org/10.7812/TPP/24.119 (2025).
Mora, J. et al. Language disparities in patient portal access and use among radiation oncology patients across an integrated health enterprise. Int. J. Radiat. Oncol. Biol. Phys. 120, E48–E49 (2024).
Roy, M. et al. Limited english proficiency and disparities in health care engagement among patients with breast cancer. JCO Oncol. Pract. 17, e1837–e1845, https://doi.org/10.1200/OP.20.01093 (2021).
Judson, T. J. et al. Patient Perceptions of e-visits: qualitative study of older adults to inform health system implementation. JMIR Aging 6, e45641, https://doi.org/10.2196/45641 (2023).
Javier, S. J. et al. Racial and ethnic disparities in use of a personal health record by veterans living with HIV. J. Am. Med. Inf. Assoc. 26, 696–702, https://doi.org/10.1093/jamia/ocz024 (2019).
Arizmendi, B. J. et al. Engagement in GI behavioral health is associated with reduced portal messages, phone calls, and ED visits. Dig. Dis. Sci. 69, 1939–1947, https://doi.org/10.1007/s10620-024-08428-3 (2024).
Wolcott, V., Agarwal, R. & Nelson, D. A. Is Provider secure messaging associated with patient messaging behavior? Evidence from the US Army. J. Med. Internet Res. 19, e103, https://doi.org/10.2196/jmir.6804 (2017).
Heisey-Grove, D. et al. Patient and clinician characteristics associated with secure message content: retrospective Cohort study. J. Med. Internet Res. 23, e26650, https://doi.org/10.2196/26650 (2021).
Branford, G. L. et al. The Gender Gap in EHR Workload: A Comparative Analysis of Primary Care Physician In Basket Usage. J. Gen. Intern Med 40, 2255–2264, https://doi.org/10.1007/s11606-025-09629-w (2025).
Ngo, M. et al. Gender based differences in electronic medical record utilization in an academic ophthalmology practice. AJO Int. 1. https://doi.org/10.1016/j.ajoint.2024.100082. (2024).
Rittenberg, E., Liebman, J. B. & Rexrode, K. M. Primary care physician gender and electronic health record workload. J. Gen. Intern. Med. 37, 3295–3301, https://doi.org/10.1007/s11606-021-07298-z (2022).
Scholes, J. et al. Special topic burnout: the digital workload divide: investigating gender differences in EHR messaging among primary care clinicians. Appl. Clin. Inf. https://doi.org/10.1055/a-2618-4580. (2025).
Ha, D. et al. Gender differences in electronic health record inbox message volumes among pediatric surgeon specialists. J. Pediatr. Surg. 60, 162191, https://doi.org/10.1016/j.jpedsurg.2025.162191 (2025).
Haun, J. N. et al. Evaluating user experiences of the secure messaging tool on the Veterans Affairs’ patient portal system. J. Med. Internet Res. 16, e75, https://doi.org/10.2196/jmir.2976 (2014).
Lam, R. et al. Older adult consumers’ attitudes and preferences on electronic patient-physician messaging. Am. J. Manag. Care 19, eSP7–eSP11 (2013).
Paige, S. R. et al. Cancer patients’ satisfaction with telehealth during the COVID-19 pandemic. PLoS ONE 17, e0268913, https://doi.org/10.1371/journal.pone.0268913 (2022).
Kudel, I. & Perry, T. Communicating treatment-related symptoms using passively collected data and satisfaction/loyalty ratings: exploratory study. JMIR Cancer 8, e29292, https://doi.org/10.2196/29292 (2022).
Short-Russell, M., Thompson, J. & Waldrop, J. Secure messaging: demonstration and enrollment patient portal program: patient portal use in vulnerable populations. Comput. Inf. Nurs. 42, 104–108, https://doi.org/10.1097/CIN.0000000000001098 (2024).
Heyworth, L. et al. Aligning medication reconciliation and secure messaging: qualitative study of primary care providers’ perspectives. J. Med. Internet Res. 15, e264, https://doi.org/10.2196/jmir.2793 (2013).
Turvey, C. L. et al. Patient and provider experience of electronic patient portals and secure messaging in mental health treatment. Telemed. J. E Health 28, 189–198, https://doi.org/10.1089/tmj.2020.0395 (2022).
Haun, J. N. et al. Large-scale survey findings inform patients’ experiences in using secure messaging to engage in patient-provider communication and self-care management: a quantitative assessment. J. Med. Internet Res. 17, e282, https://doi.org/10.2196/jmir.5152 (2015).
Rief, J. J. et al. Using health information technology to foster engagement: patients’ experiences with an active patient health record. Health Commun. 32, 310–319, https://doi.org/10.1080/10410236.2016.1138378 (2017).
Brady, J. E. et al. The perceived effectiveness of secure messaging for medication reconciliation during transitions of care: semistructured interviews with patients. JMIR Hum. Factors 9, e36652, https://doi.org/10.2196/36652 (2022).
Lieu, T. A. et al. Primary care physicians’ experiences with and strategies for managing electronic messages. JAMA Netw. Open 2, e1918287, https://doi.org/10.1001/jamanetworkopen.2019.18287 (2019).
Harary, M. et al. Audit of postoperative readmissions and patient messages following endoscopic transnasal transsphenoidal surgery. J. Neurol. Surg. B Skull Base 83, 611–617, https://doi.org/10.1055/a-1840-9874 (2022).
Makhnoon, S. et al. Electronic patient portals as a modality for returning reclassified genetic test results. Mol. Genet Genom. Med. 13, e70123, https://doi.org/10.1002/mgg3.70123 (2025).
Mervak, B. M. et al. What the patient wants: an analysis of radiology-related inquiries from a web-based patient portal. J. Am. Coll. Radio. 13, 1311–1318, https://doi.org/10.1016/j.jacr.2016.05.022 (2016).
Heukelom, J. V. et al. Patient satisfaction with return of pharmacogenomic results utilizing a patient portal message. Pharmacogenomics 24, 315–323, https://doi.org/10.2217/pgs-2023-0032 (2023).
Wade-Vuturo, A. E., Mayberry, L. S. & Osborn, C. Y. Secure messaging and diabetes management: experiences and perspectives of patient portal users. J. Am. Med. Inf. Assoc. 20, 519–525, https://doi.org/10.1136/amiajnl-2012-001253 (2013).
Hoopes, A. J. et al. Teen secure messaging is associated with use of sexual and reproductive health services in one health system. J. Adolesc. Health 76, 455–462, https://doi.org/10.1016/j.jadohealth.2024.10.016 (2025).
Haun, J. N. et al. Clinical practice informs secure messaging benefits and best practices. Appl. Clin. Inf. 8, 1003–1011, https://doi.org/10.4338/ACI-2017-05-RA-0088 (2017).
Alpert, J. M. et al. Improving secure messaging: a framework for support, partnership & information-giving communicating electronically (SPICE). Patient Educ. Couns. 104, 1380–1386, https://doi.org/10.1016/j.pec.2020.11.021 (2021).
Hernandez, B. F. et al. Communication preferences and satisfaction of secure messaging among patients and providers in the military healthcare system. Mil. Med. 183, e383–e390, https://doi.org/10.1093/milmed/usy094 (2018).
Nazi, K. M. The personal health record paradox: health care professionals’ perspectives and the information ecology of personal health record systems in organizational and clinical settings. J. Med. Internet Res. 15, e70, https://doi.org/10.2196/jmir.2443 (2013).
Brown, W. 3rd et al. Challenges and solutions to employing natural language processing and machine learning to measure patients’ health literacy and physician writing complexity: the ECLIPPSE study. J. Biomed. Inf. 113, 103658, https://doi.org/10.1016/j.jbi.2020.103658 (2021).
Eschler, J. et al. Designing asynchronous communication tools for optimization of patient-clinician coordination. AMIA Annu. Symp. Proc. 2015, 543–552 (2015).
Stewart, M. T. et al. The promise of patient portals for individuals living with chronic illness: qualitative study identifying pathways of patient engagement. J. Med. Internet Res. 22, e17744, https://doi.org/10.2196/17744 (2020).
Sieck, C. J. et al. The rules of engagement: perspectives on secure messaging from experienced ambulatory patient portal users. MMIR Red Inf 5, e13, https://doi.org/10.2196/medinform.7516 (2017).
Bosold, A. L. et al. Older adults’ personal health information management: the role and perspective of various healthcare providers. AMIA Annu. Symp. Proc. 2021, 255–264 (2021).
Alpert, J. M. et al. Clinicians’ attitudes and behaviors towards communicating electronically with patients: a grounded practical theory approach. J. Health Commun. 27, 103–114, https://doi.org/10.1080/10810730.2022.2059723 (2022).
Strand, M. et al. Exploring working relationships in mental health care via an E-recovery portal: qualitative study on the experiences of service users and health providers. JMIR Ment. Health 4, e54, https://doi.org/10.2196/mental.8491 (2017).
Haun, J. N. et al. Evaluating secure messaging from the veteran perspective: informing the adoption and sustained use of a patient-driven communication platform. Ann. Anthropol. Pract. 37, 57–74, https://doi.org/10.1111/napa.12029 (2013).
Knees, M. et al. Academic hospitalist perspectives on the benefits and challenges of secure messaging: a mixed methods analysis. J. Hosp. Med. 20, 248–257, https://doi.org/10.1002/jhm.13522 (2025).
King, G. et al. Connecting families to their health record and care team: the use, utility, and impact of a client/family health portal at a children’s rehabilitation hospital. J. Med. Internet Res. 19, e97, https://doi.org/10.2196/jmir.6811 (2017).
Crotty, B. H., Mostaghimi, A. & Landon, B. E. Preparing residents for future practice: report of a curriculum for electronic patient-doctor communication. Postgrad. Med. J. 89, 554–559, https://doi.org/10.1136/postgradmedj-2012-131688 (2013).
Lew, D. et al. Association of EHR-integrated secure messaging use with clinician workload and attention switching. J. Gen. Intern. Med. https://doi.org/10.1007/s11606-025-09466-x. (2025).
Akbar, F. et al. Physicians’ electronic inbox work patterns and factors associated with high inbox work duration. J. Am. Med. Inf. Assoc. 28, 923–930, https://doi.org/10.1093/jamia/ocaa229 (2021).
Laccetti, A. L. et al. Increase in cancer center staff effort related to electronic patient portal use. J. Oncol. Pract. 12, e981–e990, https://doi.org/10.1200/JOP.2016.011817 (2016).
Apathy, N. C. et al. Inbox message prioritization and management approaches in primary care. JAMIA Open 7, ooae135, https://doi.org/10.1093/jamiaopen/ooae135 (2024).
Hadeed, N. et al. Taming the in-basket-how two simple tools reduced portal message volume in an academic internal medicine clinic. J .Gen. Intern. Med. https://doi.org/10.1007/s11606-025-09478-7. (2025).
Lee, J. L. et al. Insecure messaging: how clinicians approach potentially problematic messages from patients. JAMIA Open 3, 576–582, https://doi.org/10.1093/jamiaopen/ooaa051 (2020).
Lieu, T. A. et al. Evaluation of attention switching and duration of electronic inbox work among primary care physicians. JAMA Netw. Open 4, e2031856, https://doi.org/10.1001/jamanetworkopen.2020.31856 (2021).
Akbar, F. et al. Physician stress during electronic health record inbox work: in situ measurement with wearable sensors. JMIR Med. Inf. 9, e24014, https://doi.org/10.2196/24014 (2021).
Murphy, D. R. et al. An exploration of barriers, facilitators, and suggestions for improving electronic health record inbox-related usability: a qualitative analysis. JAMA Netw. Open 2, e1912638, https://doi.org/10.1001/jamanetworkopen.2019.12638 (2019).
Hoerter, J.E., Debbaneh, P.M. & Jiang, N. Differences in patient secure message volume among otolaryngologists: a retrospective cohort study. Ann. Otol. Rhinol. Laryngol. 34894241264114. https://doi.org/10.1177/00034894241264114. (2024).
Mandal, S. et al. Quantifying the impact of telemedicine and patient medical advice request messages on physicians’ work-outside-work. Npj Digit. Med. 7. https://doi.org/10.1038/s41746-024-01001-2. (2024).
McAlearney, A. S. et al. Empowering patients during hospitalization: perspectives on inpatient portal use. Appl. Clin. Inf. 10, 103–112, https://doi.org/10.1055/s-0039-1677722 (2019).
Halterman, A.W. et al. Pediatric resident use, perceptions, and desires for improvement of a clinical secure messaging application. Comput. Methods Programs Biomed. Update. 6. https://doi.org/10.1016/j.cmpbup.2024.100162. (2024).
Lanham, H. J., Leykum, L. K. & Pugh, J. A. Examining the complexity of patient-outpatient care team secure message communication: qualitative analysis. J. Med. Internet Res. 20, e218, https://doi.org/10.2196/jmir.9269 (2018).
Wooldridge, A.R. et al. Technology-mediated communication between patients and primary care clinicians and staff: ambiguity in secure messaging. 556–560. https://doi.org/10.1177/1541931213601128. (2016).
Shimada, S. L. et al. Impact of patient-clinical team secure messaging on communication patterns and patient experience: randomized encouragement design trial. J. Med. Internet Res. 22, e22307, https://doi.org/10.2196/22307 (2020).
Lee, J. L. et al. Too many don’ts and not enough do’s? A Survey of hospitals about their portal instructions for patients. J. Gen. Intern. Med. 35, 1029–1034, https://doi.org/10.1007/s11606-019-05528-z (2020).
Rule, A. et al. Primary care staff members’ experiences with managing electronic health record inbox messages. J. Am. Med. Inf. Assoc. 32, 1040–1049, https://doi.org/10.1093/jamia/ocaf067 (2025).
Zallman, L. et al. Do medical scribes help primary care providers respond more quickly to out-of-visit tasks?. J. Am. Board Fam. Med. 34, 70–77, https://doi.org/10.3122/jabfm.2021.01.200330 (2021).
Miller, H. N. et al. Describing current use, barriers, and facilitators of patient portal messaging for research recruitment: Perspectives from study teams and patients at one institution. J. Clin. Transl. Sci. 7, e96, https://doi.org/10.1017/cts.2023.522 (2023).
Hefner, J. L., Sieck, C. J. & Walker, D. M. Patient and physician perspectives on training to improve communication through secure messaging: clarifying the rules of engagement. Health Care Manag. Rev. 47, 3–11, https://doi.org/10.1097/HMR.0000000000000279 (2022).
Hefner, J., Sieck, C. & McAlearney, A. Training to optimize collaborative use of an inpatient portal. Appl. Clin. Inf. 09, 558–564, https://doi.org/10.1055/s-0038-1666993 (2018).
Hyslop, A., Swazo, R. & Smith, J. P. “A friendly reminder” – Improving workflow and efficiency in a pulmonary fellows’ outpatient continuity clinic. Heart Lung 63, 167–174, https://doi.org/10.1016/j.hrtlng.2023.10.007 (2024).
Smith, R. C. et al. Ways to improve workflow and morale in an ophthalmology clinic: survey advice from clinic staff. J. Biotechnol. Biomed. 6, 460–467, https://doi.org/10.26502/jbb.2642-91280108 (2023).
Morrow, D. et al. Contextualizing numeric clinical test results for gist comprehension: implications for EHR patient portals. J. Exp. Psychol. Appl. 25, 41–61, https://doi.org/10.1037/xap0000203 (2019).
Kapoor, A. et al. Comparing the efficacy of targeted and blast portal messaging in message opening rate and anticoagulation initiation in patients with atrial fibrillation in the preventing preventable strokes study II: prospective cohort study. JMIR Cardio. 8, e49590, https://doi.org/10.2196/49590 (2024).
Taylor Pearson, K. E. Pediatric clinical staff perspectives on secure messaging. J. Nurs. Care Qual. 39, 317–323, https://doi.org/10.1097/NCQ.0000000000000775 (2024).
Alpert, J. M. et al. Integrating patient-centeredness into online patient-clinician communication: a qualitative analysis of clinicians’ secure messaging usage. Support Care Cancer 30, 9851–9857, https://doi.org/10.1007/s00520-022-07408-5 (2022).
Roscoe, R.D. et al. Automated strategy feedback can improve the readability of physicians’ electronic communications to simulated patients. Int. J. Hum. Comput. Stud. 176. https://doi.org/10.1016/j.ijhcs.2023.103059. (2023).
Padman, R. et al. eVisit: a pilot study of a new kind of healthcare delivery. Stud. Health Technol. Inf. 160, 262–266 (2010).
Parpia, C. et al. Evaluation of a secure messaging system in the care of children with medical complexity: mixed methods study. JMIR Form. Res. 7, e42881, https://doi.org/10.2196/42881 (2023).
Rohrer, J. E. et al. Timely response to secure messages from primary care patients. Qual. Manag Health Care 22, 161–166, https://doi.org/10.1097/QMH.0b013e31828be314 (2013).
Dyrbye, L. N. et al. Relationships between EHR-based audit log data and physician burnout and clinical practice process measures. Mayo Clin. Proc. 98, 398–409, https://doi.org/10.1016/j.mayocp.2022.10.027 (2023).
Jahn, M. A. et al. Usability assessment of secure messaging for clinical document sharing between health care providers and patients. Appl. Clin. Inf. 9, 467–477, https://doi.org/10.1055/s-0038-1660521 (2018).
Chen, M.L. et al. Analysing common topics of secure patient messages in hidradenitis suppurativa: a text-embedding and natural language-processing approach. Br J Dermatol 2024. https://doi.org/10.1093/bjd/ljae222.
Morrow, D. et al. A multidisciplinary approach to designing and evaluating Electronic Medical Record portal messages that support patient self-care. J. Biomed. Inf. 69, 63–74, https://doi.org/10.1016/j.jbi.2017.03.015 (2017).
Garvin, L. A. & Simon, S. R. Prioritizing measures of digital patient engagement: a delphi expert panel study. J. Med. Internet Res. 19, e182, https://doi.org/10.2196/jmir.4778 (2017).
Alpert, J. M. et al. Evaluating the SEND eHealth application to improve patients’ secure message writing. J. Cancer Educ. https://doi.org/10.1007/s13187-024-02491-0 (2024).
Mirsky, J. B. et al. Readability assessment of patient-provider electronic messages in a primary care setting. J. Am. Med. Inf. Assoc. 23, 202–206, https://doi.org/10.1093/jamia/ocv087 (2016).
Crossley, S. A. et al. Predicting the readability of physicians’ secure messages to improve health communication using novel linguistic features: findings from the ECLIPPSE study. J. Commun. Heal 13, 1–13, https://doi.org/10.1080/17538068.2020.1822726 (2020).
Crossley, S. A. et al. Developing and testing automatic models of patient communicative health literacy using linguistic features: findings from the ECLIPPSE study. Health Commun. 36, 1018–1028, https://doi.org/10.1080/10410236.2020.1731781 (2021).
Schillinger, D. et al. Employing computational linguistics techniques to identify limited patient health literacy: findings from the ECLIPPSE study. Health Serv. Res. 56, 132–144, https://doi.org/10.1111/1475-6773.13560 (2021).
Schillinger, D. et al. Validity of a computational linguistics-derived automated health literacy measure across race/ethnicity: findings from the ECLIPPSE project. J. Health Care Poor Underserved 32, 347–365, https://doi.org/10.1353/hpu.2021.0067 (2021).
Gao, M. et al. Development of a flexible chain of thought framework for automated routing of patient portal messages. AMIA Annu Symp. Proc. 2024, 443–452 (2024).
Mao, C. M. & Hovick, S. R. Adding affordances and communication efficacy to the technology acceptance model to study the messaging features of online patient portals among young adults. Health Commun. 37, 307–315, https://doi.org/10.1080/10410236.2020.1838106 (2022).
Martin, D. et al. Systematic identification of caregivers of patients living with dementia in the electronic health record: known contacts and natural language processing cohort study. J. Med. Internet Res. 27, e63654, https://doi.org/10.2196/63654 (2025).
Anderson, B.J. et al. Development and evaluation of a model to manage patient portal messages. NEJM AI 2. https://doi.org/10.1056/AIoa2400354. (2025).
Huang, M. et al. Identification of transportation barriers in patient portal messages via deep semantic embeddings and clustering. Stud. Health Technol. Inf. 290, 794–798, https://doi.org/10.3233/SHTI220188 (2022).
Duvall, M. J. et al. Portal message language use prior to suicide, suicide attempts, and hospitalization for depression. Telemed. J. E Health 28, 1143–1150, https://doi.org/10.1089/tmj.2021.0318 (2022).
Duvall, M. et al. Patient portal message characteristics and reported thoughts of self-harm and suicide: a retrospective cohort study. J. Telemed. Telecare 27, 501–508, https://doi.org/10.1177/1357633X19887262 (2021).
Tafti, A.P. et al. Artificial intelligence to organize patient portal messages: a journey from an ensemble deep learning text classification to rule-based named entity recognition. 1380–1387. https://doi.org/10.1109/BIBM47256.2019.8982942. (2019).
Si, S. et al. Students need more attention: BERT-based attention model for small data with application to automatic patient message triage. Proc. Mach. Learn. Res. 126, 436–456 (2020).
Yang, J. et al. Development and evaluation of an artificial intelligence-based workflow for the prioritization of patient portal messages. JAMIA Open 7, ooae078, https://doi.org/10.1093/jamiaopen/ooae078 (2024).
Moon, S. et al. Automated identification of patients’ unmet social needs in clinical text using natural language processing. Mayo Clin. Proc. Digit. Health 2, 411–420, https://doi.org/10.1016/j.mcpdig.2024.06.008 (2024).
Ren, Y. et al. Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models. J. Am. Med. Inf. Assoc. 31, 1714–1724, https://doi.org/10.1093/jamia/ocae144 (2024).
Baek, J. et al. Assessing patient needs during natural disasters: mixed methods analysis of portal messages sent during Hurricane Harvey. J. Med. Internet Res. 23, e31264, https://doi.org/10.2196/31264 (2021).
Alpert, J. M. et al. Secure messaging and COVID-19: a content analysis of patient-clinician communication during the pandemic. Telemed. J. E Health 28, 1028–1034, https://doi.org/10.1089/tmj.2021.0316 (2022).
Bhandarkar, A. R. et al. Building a natural language processing artificial intelligence to predict suicide-related events based on patient portal message data. Mayo Clin. Proc. Digit. Health 1, 510–518, https://doi.org/10.1016/j.mcpdig.2023.09.001 (2023).
Sulieman, L. et al. Classifying patient portal messages using convolutional neural networks. J. Biomed. Inf. 74, 59–70, https://doi.org/10.1016/j.jbi.2017.08.014 (2017).
De, A. et al. Analyzing patient secure messages using a fast health care interoperability resources (FIHR)-based data model: development and topic modeling study. J. Med. Internet Res. 23, e26770, https://doi.org/10.2196/26770 (2021).
Kiani, H. et al. Improving emergency department visit risk prediction: exploring the operational utility of applied patient portal messages. AMIA Annu. Symp. Proc. 2024, 610–619 (2024).
Sulieman, L., Yin, Z. & Malin, B. A. Why patient portal messages indicate risk of readmission for patients with ischemic heart disease. AMIA Annu. Symp. Proc. 2019, 828–837 (2019).
Song, Q. et al. Optimizing word embeddings for small dataset: a case study on patient portal messages from breast cancer patients. Sci. Rep. 14, 16117. https://doi.org/10.1038/s41598-024-66319-z (2024).
Wang, N. et al. Taxonomy-based prompt engineering to generate synthetic drug-related patient portal messages. J. Biomed. Inform. 160. https://doi.org/10.1016/j.jbi.2024.104752. (2024).
Liu, S. et al. Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation. J. Am. Med. Inf. Assoc. 32, 1032–1039, https://doi.org/10.1093/jamia/ocaf059 (2025).
Kim, J. et al. Artificial intelligence tools in supporting healthcare professionals for tailored patient care. NPJ Digit. Med. 8, 210, https://doi.org/10.1038/s41746-025-01604-3 (2025).
Chekuri, A. et al. Towards optimizing LLM use in healthcare: identifying patient questions in MyChart messages. AMIA Annu. Symp. Proc. 2024, 232–241 (2024).
Alsumait, A. et al. Triage of patient messages sent to the eye clinic via the electronic medical record: a comparative study on AI and human triage performance. J. Clin. Med. 14. https://doi.org/10.3390/jcm14072395. (2025).
Pham, J. H. et al. Large language model triaging of simulated nephrology patient inbox messages. Front. Artif. Intell. 7, 1452469, https://doi.org/10.3389/frai.2024.1452469 (2024).
Garcia, P. et al. Artificial intelligence-generated draft replies to patient inbox messages. JAMA Netw. Open 7, e243201, https://doi.org/10.1001/jamanetworkopen.2024.3201 (2024).
Small, W. R. et al. Large language model–based responses to patients’ in-basket messages. JAMA Netw. Open 7, e2422399, https://doi.org/10.1001/jamanetworkopen.2024.22399 (2024).
Tailor, P. D. et al. A comparative study of responses to retina questions from either experts, expert-edited large language models, or expert-edited large language models alone. Ophthalmol. Sci. 4, 100485, https://doi.org/10.1016/j.xops.2024.100485 (2024).
Tailor, P. D. et al. Appropriateness of ophthalmology recommendations from an online chat-based artificial intelligence model. Mayo Clin. Proc. Digit Health 2, 119–128, https://doi.org/10.1016/j.mcpdig.2024.01.003 (2024).
Proctor, S., Lawton, G. & Sinha, S. An AI-powered strategy for managing patient messaging load and reducing burnout. Appl. Clin. Inf. 16, 747–752, https://doi.org/10.1055/a-2576-0579 (2025).
Chen, S. et al. The effect of using a large language model to respond to patient messages. Lancet Digit Health 6, e379–e381, https://doi.org/10.1016/S2589-7500(24)00060-8 (2024).
Liu, S. et al. Leveraging large language models for generating responses to patient messages—a subjective analysis. J. Am. Med. Inf. Assoc. 31, 1367–1379, https://doi.org/10.1093/jamia/ocae052 (2024).
Cavalier, J. S. et al. Ethics in patient preferences for artificial intelligence–drafted responses to electronic messages. JAMA Netw. Open 8, e250449, https://doi.org/10.1001/jamanetworkopen.2025.0449 (2025).
Athavale, A. et al. The potential of chatbots in chronic venous disease patient management. JVS Vasc. Insights 1. https://doi.org/10.1016/j.jvsvi.2023.100019. (2023).
Nov, O., Singh, N. & Mann, D. Putting ChatGPT’s medical advice to the (turing) test: survey study. JMIR Med. Educ. 9, e46939, https://doi.org/10.2196/46939 (2023).
English, E. et al. Utility of artificial intelligence-generative draft replies to patient messages. JAMA Netw. Open 7, e2438573, https://doi.org/10.1001/jamanetworkopen.2024.38573 (2024).
Kim, J. et al. Patient perspectives on large language model responses to patient messages. https://doi.org/10.2139/ssrn.4867523. .(2024)
Robinson, E. J. et al. Physician vs. AI-generated messages in urology: evaluation of accuracy, completeness, and preference by patients and physicians. World J. Urol. 43, 48, https://doi.org/10.1007/s00345-024-05399-y (2024).
Scott, M. et al. Assessing artificial intelligence–generated responses to urology patient in-basket messages. Urol. Pract. 11, 793–798, https://doi.org/10.1097/UPJ.0000000000000637 (2024).
Soroudi, D. et al. Comparing provider and ChatGPT responses to breast reconstruction patient questions in the electronic health record. Ann. Plast. Surg. 93, 541–545, https://doi.org/10.1097/SAP.0000000000004090 (2024).
Hao, Y. et al. Retrospective comparative analysis of prostate cancer in-basket messages: responses from closed-domain large language models versus clinical teams. Mayo Clin. Proc. Digit. Health 3. https://doi.org/10.1016/j.mcpdig.2025.100198. (2025).
Hong, C. et al. Application of unified health large language model evaluation framework to in-basket message replies: bridging qualitative and quantitative assessments. J. Am. Med. Inf. Assoc. https://doi.org/10.1093/jamia/ocaf023. (2025).
Kaur, A. et al. Primary care providers acceptance of generative ai responses to patient portal messages. Appl. Clin. Inform. https://doi.org/10.1055/a-2565-9155. (2025).
Tse, G. et al. Large language model responses to adolescent patient and proxy messages. JAMA Pediatr. 179, 93–94, https://doi.org/10.1001/jamapediatrics.2024.4438 (2025).
Bootsma-Robroeks CMHHT, Workum, J. D. et al. AI-generated draft replies to patient messages: exploring effects of implementation. Front. Digit. Health 7, 1588143, https://doi.org/10.3389/fdgth.2025.1588143 (2025).
Andreadis, K. et al. Bridging gaps with generative AI: enhancing hypertension monitoring through patient and provider insights. Stud. Health Technol. Inf. 316, 939–943, https://doi.org/10.3233/SHTI240565 (2024).
Reynolds, K. et al. Comparing the quality of ChatGPT- and physician-generated responses to patients’ dermatology questions in the electronic medical record. Clin. Exp. Dermatol. 49, 715–718, https://doi.org/10.1093/ced/llad456 (2024).
Kim, J. et al. Perspectives on artificial intelligence-generated responses to patient messages. JAMA Netw. Open 7, e2438535, https://doi.org/10.1001/jamanetworkopen.2024.38535 (2024).
Luo, M. et al. Assessing empathy in large language models with real-world physician-patient interactions. 6510–6519. https://doi.org/10.1109/BigData62323.2024.10825307. (2024).
Liu, S. et al. Using large language model to guide patients to create efficient and comprehensive clinical care message. J. Am. Med. Inf. Assoc. 31, 1665–1670, https://doi.org/10.1093/jamia/ocae142 (2024).
Yan, S. et al. Prompt engineering on leveraging large language models in generating response to InBasket messages. J. Am. Med. Inf. Assoc. 31, 2263–2270, https://doi.org/10.1093/jamia/ocae172 (2024).
Kaur, A. et al. Automating responses to patient portal messages using generative AI. https://doi.org/10.1101/2024.04.25.24306183.
Lee, N. S. et al. Use of a medical communication framework to assess the quality of generative artificial intelligence replies to primary care patient portal messages: content analysis. JMIR Form. Res. 9, e71966, https://doi.org/10.2196/71966 (2025).
Biro, J. M. et al. Opportunities and risks of artificial intelligence in patient portal messaging in primary care. NPJ Digit. Med. 8, 222, https://doi.org/10.1038/s41746-025-01586-2 (2025).
Foresman, G. et al. Patient perspectives on artificial intelligence in health care: focus group study for diagnostic communication and tool implementation. J. Particip. Med. 17, e69564, https://doi.org/10.2196/69564 (2025).
Green, A. R. et al. Characterizing patient portal use of people with cognitive impairment and potentially inappropriate medications. J. Am. Geriatr. Soc. 73, 750–758, https://doi.org/10.1111/jgs.19284 (2025).
Lieu, T. A. et al. Pharmacist vs physician management of e-visit requests for COVID-19 medication: a randomized clinical trial. J. Manag Care Spec. Pharm. 31, 189–197, https://doi.org/10.18553/jmcp.2025.31.2.189 (2025).
Shimada, S. L. et al. An analysis of patient-provider secure messaging at two Veterans Health Administration medical centers: message content and resolution through secure messaging. J. Am. Med. Inf. Assoc. 24, 942–949, https://doi.org/10.1093/jamia/ocx021 (2017).
Heisey-Grove, D. et al. Classification of patient- and clinician-generated secure messages using a theory-based taxonomy. Health Sci. Rep. 4, e295, https://doi.org/10.1002/hsr2.295 (2021).
Flickinger, T. E. et al. Communication between patients, peers, and care providers through a mobile health intervention supporting medication-assisted treatment for opioid use disorder. Patient Educ. Couns. 105, 2110–2115, https://doi.org/10.1016/j.pec.2022.02.014 (2022).
Davoudi, A. et al. Identifying medication-related intents from a bidirectional text messaging platform for hypertension management using an unsupervised learning approach: retrospective observational pilot study. J. Med. Internet Res. 24, e36151, https://doi.org/10.2196/36151 (2022).
Robinson, S. A. et al. Secure messaging for diabetes management: content analysis. JMIR Diabetes 8, e40272, https://doi.org/10.2196/40272 (2023).
Green, A. R. et al. Use of the patient portal to discuss medications among people with dementia and their care partners: patient portal correspondence about medications. J. Gen. Intern. Med. 39, 3164–3171, https://doi.org/10.1007/s11606-024-09064-3 (2024).
Anderson, B. et al. Empowering care teams: redefining message management to enhance care delivery and alleviate oncologist burnout. JNCCN J. Natl. Compr. Cancer Netw. 22, 664–669, https://doi.org/10.6004/jnccn.2024.7055 (2024).
Ramirez-Zohfeld, V. et al. Use of electronic health records by older adults, 85 Years and older, and their caregivers. J. Am. Geriatr. Soc. 68, 1078–1082, https://doi.org/10.1111/jgs.16393 (2020).
Sieck, C. J. et al. Understanding secure messaging in the inpatient environment: a new avenue for communication and patient engagement. Appl. Clin. Inf. 9, 860–868, https://doi.org/10.1055/s-0038-1675814 (2018).
Yin, Z. et al. The therapy is making me sick: how online portal communications between breast cancer patients and physicians indicate medication discontinuation. J. Am. Med. Inf. Assoc. 25, 1444–1451, https://doi.org/10.1093/jamia/ocy118 (2018).
Carter, R. R. et al. Assessing mental models from communications: patient, family, and care team messaging within the Hospital. Proc. Hum. Factors Erg. Soc. Annu. Meet. 63, 653–657, https://doi.org/10.1177/1071181319631440 (2019).
Meier-Diedrich, E. et al. Patient-health care professional communication via a secure web-based portal in severe mental health conditions: qualitative analysis of secure messages. JMIR Form. Res. 9, e63713, https://doi.org/10.2196/63713 (2025).
Yin, Z. et al. Patient messaging content associated with initiating hormonal therapy after a breast cancer diagnosis. AMIA Annu. Symp. Proc. 2019, 962–971 (2019).
Heisey-Grove, D. M. & DeShazo, J. P. Look who’s talking: application of a theory-based taxonomy to patient-clinician E-mail messages. Telemed. J. E Health 26, 1345–1352, https://doi.org/10.1089/tmj.2019.0192 (2020).
Shetty, V.A. et al. Discussions of cannabis over patient portal secure messaging: content analysis. J. Med. Internet Res. 26. https://doi.org/10.2196/63311. (2024).
Palmer, S.K. et al. Deep inferior epigastric perforator in-basket? evaluation of patient electronic communication following autologous breast reconstruction. Aesthet. Surg. J. https://doi.org/10.1093/asj/sjaf177. (2025).
Hogan, T. P. et al. Patient centeredness in electronic communication: evaluation of patient-to-health care team secure messaging. J. Med. Internet Res. 20, e82, https://doi.org/10.2196/jmir.8801 (2018).
Spencer, C., Loehr, K. & Byrd, A. Patient and family perpetrated cyber-incivility and cyber-aggression within healthcare: a cross-sectional descriptive study. SAGE Open Nurs. 9, 23779608231158970, https://doi.org/10.1177/23779608231158970 (2023).
Alpert, J. M., Dyer, K. E. & Lafata, J. E. Patient-centered communication in digital medical encounters. Patient Educ. Couns. 100, 1852–1858, https://doi.org/10.1016/j.pec.2017.04.019 (2017).
Robinson, J. R. et al. Complexity of medical decision-making in care provided by surgeons through patient portals. J. Surg. Res. 214, 93–101, https://doi.org/10.1016/j.jss.2017.02.077 (2017).
Kim, J. et al. Patient-centered research through artificial intelligence to identify priorities in cancer care. JAMA Oncol. 11, 630–635, https://doi.org/10.1001/jamaoncol.2025.0694 (2025).
ONC’s Cures Act Final Rule | HealthIT.gov n.d. https://www.healthit.gov/topic/oncs-cures-act-final-rule (accessed November 6, 2024).
Xie, J. et al. Ensuring adolescent patient portal confidentiality in the age of the cures act final rule. J. Adolesc. Health 69, 933–939, https://doi.org/10.1016/j.jadohealth.2021.09.009 (2021).
Ip, W. et al. Assessment of prevalence of adolescent patient portal account access by guardians. JAMA Netw. Open 4, e2124733, https://doi.org/10.1001/jamanetworkopen.2021.24733 (2021).
Sisk, B. A. et al. Acceptability of adolescent portal access policies to parents and adolescents: a delphi study. J. Adolesc. Health 76, 448–454, https://doi.org/10.1016/j.jadohealth.2024.10.021 (2025).
Gleason, K. T. et al. Use of the patient portal among older adults with diagnosed dementia and their care partners. Alzheimers Dement https://doi.org/10.1002/alz.13354 (2023).
Semere, W. et al. Care partner engagement in secure messaging between patients with diabetes and their clinicians: cohort study. JMIR Diab. 9, e49491, https://doi.org/10.2196/49491 (2024).
Pecina, J, Duvall, M.J. & North, F. Frequency of and factors associated with care partner proxy interaction with health care teams using patient portal accounts. Telemed. E Health 26, 1368–1372. https://doi.org/10.1089/tmj.2019.0208. (2020).
Benda, N. C. et al. Identifying nonpatient authors of patient portal secure messages in oncology: a proof-of-concept demonstration of natural language processing methods. JCO Clin. Cancer Inf. 6, e2200071, https://doi.org/10.1200/CCI.22.00071 (2022).
Balyan, R. et al. Using natural language processing and machine learning to classify health literacy from secure messages: the ECLIPPSE study. PLoS ONE 14, e0212488, https://doi.org/10.1371/journal.pone.0212488 (2019).
Holmgren, A. J. et al. Association between billing patient portal messages as e-visits and patient messaging volume. JAMA 329, 339, https://doi.org/10.1001/jama.2022.24710 (2023).
Alpert, J. M. et al. Qualitative analysis of patients’ and physicians’ attitudes and behaviors toward billing patient portal messages. Ann. Intern. Med. 177, 1734–1736, https://doi.org/10.7326/ANNALS-24-00560 (2024).
Dunlay, S. M. et al. Implementation of billing for patient portal messages as E-visits in a large integrated health system. Ann. Intern Med. 178, 11–19, https://doi.org/10.7326/ANNALS-24-01711 (2025).
Ko, DG, Tachinardi, U & Warm, EJ. Secure messaging telehealth billing in the digital age: moving beyond time-based metrics. J. Am. Med. Inf. Assoc. https://doi.org/10.1093/jamia/ocae250. (2024).
Oke, I. et al. Trends in billing secure messages at ophthalmology practices across the United States. Ophthalmol. Sci. 5. https://doi.org/10.1016/j.xops.2024.100683. (2025).
Reynolds, TL, Ali, N & Zheng, K. What do patients and caregivers want? A systematic review of user suggestions to improve patient portals n.d.
Raisa, A. et al. Identifying the mechanisms of patient-centred communication in secure messages between clinicians and cancer patients. PEC Innov. 2, 100161, https://doi.org/10.1016/j.pecinn.2023.100161 (2023).
Mccormack, J. et al. Direct secure messaging in practice: addressing workflow challenges…19th World Congress on medical and health informatics, July 8-12, 2023, New South Wales, Australia. Stud. Health Technol. Inf. 310, 189–193, https://doi.org/10.3233/SHTI230953 (2023).
Rodriguez DV, et al. Development of a GenAI-powered hypertension management assistant: early development phases and architectural design. 350–359. https://doi.org/10.1109/ICHI61247.2024.00052. (2024).
Ball, S. L. et al. Clinician and staff experiences with frustrated patients during an electronic health record transition: a qualitative case study. BMC Health Serv. Res. 24, 535. https://doi.org/10.1186/s12913-024-10974-5 (2024).
Alpert, J. M. et al. Twenty-first Century bedside manner: exploring patient-centered communication in secure messaging with cancer patients. J. Cancer Educ. 36, 16–24, https://doi.org/10.1007/s13187-019-01592-5 (2021).
Gold, K. J. et al. Patient-reported reasons for sending portal messages: a survey of use in a family medicine department. J. Gen. Intern Med. 39, 2608–2611, https://doi.org/10.1007/s11606-024-08815-6 (2024).
Hu D, et al. When AI writes back: ethical considerations by physicians on AI-drafted patient message replies. https://doi.org/10.48550/ARXIV.2508.13217. (2025).
Reddy, S. Generative AI in healthcare: an implementation science informed translational path on application, integration and governance. Implement Sci. 19, 27, https://doi.org/10.1186/s13012-024-01357-9 (2024).
Ren, Y. et al. Classification of patient portal messages with BERT-based Language Models. 176–182. https://doi.org/10.1109/ICHI57859.2023.00033. (2023).
Van Buchem, M. M. et al. Applying natural language processing to patient messages to identify depression concerns in cancer patients. J. Am. Med. Inf. Assoc. 31, 2255–2262, https://doi.org/10.1093/jamia/ocae188 (2024).
Clusmann, J. et al. The future landscape of large language models in medicine. Commun. Med. 3, 141, https://doi.org/10.1038/s43856-023-00370-1 (2023).
Haider, S. A. et al. The development and evaluation of a retrieval-augmented generation large language model virtual assistant for postoperative instructions. Bioengineering 12, 1219, https://doi.org/10.3390/bioengineering12111219 (2025).
Yim, D. et al. Preliminary evidence of the use of generative AI in health care clinical services: systematic narrative review. JMIR Med. Inf. 12, e52073, https://doi.org/10.2196/52073 (2024).
