Download PDF
Appl Clin Inform 2022; 13(05): 1053-1062
DOI: 10.1055/a-1951-3153
Research Article

Characteristics of Adult Primary Care Patients Who Use the Patient Portal: A Cross-Sectional Analysis

Nicholas J. Casacchia
1   Wake Forest Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Gary E. Rosenthal
2   Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Nathaniel S. O'Connell
3   Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
4   Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Richa Bundy
2   Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Lauren Witek
2   Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Brian J. Wells
1   Wake Forest Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
3   Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
4   Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
,
Deepak Palakshappa
2   Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
4   Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
5   Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
› Author Affiliations Funding The study was funded by U.S. Department of Health and Human Services, National Institutes of Health (TL1TR003136), and National Heart, Lung, and Blood Institute (K23HL146902). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
› Further Information
Also available at
    Permissions and Reprints

Abstract

Background The patient portal allows patients to engage with their health care team beyond the clinical encounter. While portals can improve patient outcomes, there may be disparities in which patients access the portal by sociodemographic factors. Understanding the characteristics of patients who use the portal could help design future interventions to expand portal adoption.

Objectives This study aimed to (1) examine the socioeconomic factors, comorbid conditions, and health care utilization among patients of a large academic primary care network who are users and non-users of the patient portal; and (2) describe the portal functions most frequently utilized.

Methods We included all adult patients at Atrium Health Wake Forest Baptist who had at least two primary care visits between 2018 and 2019. Patients' demographics, comorbidities, health care utilization, and portal function usage were extracted from the electronic health record and merged with census data (income, education, and unemployment) from the American Community Survey. A myWakeHealth portal user was defined as a patient who used a bidirectional portal function at least once during the study period. We used multivariable logistic regression to determine which patient characteristics were independently associated with being a portal user.

Results Of the 178,720 patients who met inclusion criteria, 32% (N = 57,122) were users of myWakeHealth. Compared to non-users, users were more likely to be 18 to 64 years of age, female, non-Hispanic White, married, commercially insured, have higher disease burden, and have lower health care utilization. Patients residing in areas with the highest educational attainment had 51% higher odds of being a portal user than the lowest (p <0.001). Among portal users, the most commonly used function was messaging clinic providers.

Conclusion We found that patient demographics and area socioeconomic factors were associated with patient portal adoption. These findings suggest that efforts to improve portal adoption should be targeted at vulnerable patients.

Keywords

patient portal - academic medical center - ambulatory practice - electronic health record

Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles of Medical Research involving Human Subjects. The Wake Forest School of Medicine Institutional Review Board reviewed and approved the study and waived informed consent because it did not involve patient contact.


Supplementary Material



Publication History

Received: 12 May 2022

Accepted: 23 September 2022

Accepted Manuscript online:
27 September 2022

Article published online:
02 November 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Lai Y, Moseley E, Salgueiro F. et al. Integrating non-clinical data with EHRs. In: MIT Critical Data, ed. Secondary Analysis of Electronic Health Records. Cham (CH): Springer; 2016: 51-60
    Google Scholar
  • 2 Lyles CR, Nelson EC, Frampton S, Dykes PC, Cemballi AG, Sarkar U. Using electronic health record portals to improve patient engagement: research priorities and best practices. Ann Intern Med 2020; 172 (Suppl. 11) S123-S129
    CrossrefPubMedGoogle Scholar
  • 3 Department of Health and Human Services. Centers for medicare and medicaid services. Electronic health record incentive program—stage 2. (42 CFR Parts 412, 413, and 495). Fed Regist 2012; 77 (171) 53968-54162
    PubMedGoogle Scholar
  • 4 Ahern DK, Woods SS, Lightowler MC, Finley SW, Houston TK. Promise of and potential for patient-facing technologies to enable meaningful use. Am J Prev Med 2011; 40 (5, suppl 2): S162-S172
    CrossrefPubMedGoogle Scholar
  • 5 Department of health and human services 21st century cures act: interoperability, information blocking, and the ONC Health IT Certification Program. Fed Regist 2020; 85 (85) 25646
    PubMedGoogle Scholar
  • 6 Office of the National Coordinator for Health Information Technology (ONC), Department of Health and Human Services (HHS). 2015 Edition Health Information Technology (Health IT) Certification Criteria, 2015 Edition Base Electronic Health Record (EHR) Definition, and ONC Health IT Certification Program Modifications. Final rule. Fed Regist 2015; 80 (200) 62601-62759
    PubMedGoogle Scholar
  • 7 Turer RW, DesRoches CM, Salmi L, Helmer T, Rosenbloom ST. Patient perceptions of receiving COVID-19 test results via an online patient portal: an open results survey. Appl Clin Inform 2021; 12 (04) 954-959
    Article in Thieme ConnectPubMedGoogle Scholar
  • 8 Ginting K, Stolfi A, Wright J, Omoloja A. Patient portal, patient-generated images, and medical decision-making in a pediatric ambulatory setting. Appl Clin Inform 2020; 11 (05) 764-768
    Article in Thieme ConnectPubMedGoogle Scholar
  • 9 Huang J, Chen Y, Landis JR, Mahoney KB. Difference between users and nonusers of a patient portal in health behaviors and outcomes: retrospective cohort study. J Med Internet Res 2019; 21 (10) e13146
    CrossrefPubMedGoogle Scholar
  • 10 Nguyen OT, Hong YR, Alishahi Tabriz A, Hanna K, Turner K. Prevalence and factors associated with patient-requested corrections to the medical record through use of a patient portal: findings from a national survey. Appl Clin Inform 2022; 13 (01) 242-251
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Bush RA, Vemulakonda VM, Richardson AC, Deakyne Davies SJ, Chiang GJ. Providing access: differences in pediatric portal activation begin at patient check-in. Appl Clin Inform 2019; 10 (04) 670-678
    Article in Thieme ConnectPubMedGoogle Scholar
  • 12 Sulieman L, Steitz B, Rosenbloom ST. Analysis of employee patient portal use and electronic health record access at an academic medical center. Appl Clin Inform 2020; 11 (03) 433-441
    Article in Thieme ConnectPubMedGoogle Scholar
  • 13 Zhong X, Park J, Liang M. et al. Characteristics of patients using different patient portal functions and the impact on primary care service utilization and appointment adherence: retrospective observational study. J Med Internet Res 2020; 22 (02) e14410
    CrossrefPubMedGoogle Scholar
  • 14 Tsai R, Bell III EJ, Woo H, Baldwin K, Pfeffer MA. How patients use a patient portal: an institutional case study of demographics and usage patterns. Appl Clin Inform 2019; 10 (01) 96-102
    Article in Thieme ConnectPubMedGoogle Scholar
  • 15 Abd-Alrazaq AA, Bewick BM, Farragher T, Gardner P. Factors that affect the use of electronic personal health records among patients: a systematic review. Int J Med Inform 2019; 126: 164-175
    CrossrefPubMedGoogle Scholar
  • 16 Oest SER, Hightower M, Krasowski MD. Activation and utilization of an electronic health record patient portal at an academic medical center-impact of patient demographics and geographic location. Acad Pathol 2018; 5: 2374289518797573
    CrossrefPubMedGoogle Scholar
  • 17 Perzynski AT, Roach MJ, Shick S. et al. Patient portals and broadband internet inequality. J Am Med Inform Assoc 2017; 24 (05) 927-932
    CrossrefPubMedGoogle Scholar
  • 18 Goel MS, Brown TL, Williams A, Hasnain-Wynia R, Thompson JA, Baker DW. Disparities in enrollment and use of an electronic patient portal. J Gen Intern Med 2011; 26 (10) 1112-1116
    CrossrefPubMedGoogle Scholar
  • 19 Trivedi N, Patel V, Johnson C, Chou WS. Barriers to accessing online medical records in the United States. Am J Manag Care 2021; 27 (01) 33-40
    CrossrefPubMedGoogle Scholar
  • 20 Elston Lafata J, Miller CA, Shires DA, Dyer K, Ratliff SM, Schreiber M. Patients' adoption of and feature access within electronic patient portals. Am J Manag Care 2018; 24 (11) e352-e357
    PubMedGoogle Scholar
  • 21 Furniss S, Rinehart-Thompson L, MacEwan S. et al. Characteristics of patients using a patient portal via mobile technology. Perspect Health Inf Manag 2020; (Winter): 1-10
    PubMedGoogle Scholar
  • 22 Mook PJ, Trickey AW, Krakowski KE. et al. Exploration of portal activation by patients in a healthcare system. Comput Inform Nurs 2018; 36 (01) 18-26
    CrossrefPubMedGoogle Scholar
  • 23 Ancker JS, Barrón Y, Rockoff ML. et al. Use of an electronic patient portal among disadvantaged populations. J Gen Intern Med 2011; 26 (10) 1117-1123
    CrossrefPubMedGoogle Scholar
  • 24 Arcury TA, Quandt SA, Sandberg JC. et al. Patient portal utilization among ethnically diverse low income older adults: observational study. JMIR Med Inform 2017; 5 (04) e47
    CrossrefPubMedGoogle Scholar
  • 25 Weingart SN, Rind D, Tofias Z, Sands DZ. Who uses the patient internet portal? The PatientSite experience. J Am Med Inform Assoc 2006; 13 (01) 91-95
    CrossrefPubMedGoogle Scholar
  • 26 Wallace LS, Angier H, Huguet N. et al. Patterns of electronic portal use among vulnerable patients in a nationwide practice-based research network: from the OCHIN practice-based research network (PBRN). J Am Board Fam Med 2016; 29 (05) 592-603
    CrossrefPubMedGoogle Scholar
  • 27 Turner K, Clary A, Hong YR, Alishahi Tabriz A, Shea CM. Patient portal barriers and group differences: cross-sectional national survey study. J Med Internet Res 2020; 22 (09) e18870
    CrossrefPubMedGoogle Scholar
  • 28 Swoboda CM, DePuccio MJ, Fareed N, McAlearney AS, Walker DM. Patient portals: useful for whom and for what? a cross-sectional analysis of national survey data. Appl Clin Inform 2021; 12 (03) 573-581
    Article in Thieme ConnectPubMedGoogle Scholar
  • 29 Griffin A, Skinner A, Thornhill J, Weinberger M. Patient portals: who uses them? What features do they use? And do they reduce hospital readmissions?. Appl Clin Inform 2016; 7 (02) 489-501
    Article in Thieme ConnectPubMedGoogle Scholar
  • 30 von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 2008; 61 (04) 344-349
    Google Scholar
  • 31 Quan H, Li B, Couris CM. et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011; 173 (06) 676-682
    Google Scholar
  • 32 Huang YQ, Gou R, Diao YS. et al. Charlson comorbidity index helps predict the risk of mortality for patients with type 2 diabetic nephropathy. J Zhejiang Univ Sci B 2014; 15 (01) 58-66
    CrossrefPubMedGoogle Scholar
  • 33 American Community Survey 2015–2019 5-Year Data Release. December 10, 2020. Updated October 8, 2021. Accessed November 1, 2021 at: https://www.census.gov/newsroom/press-kits/2020/acs-5-year.html
    PubMedGoogle Scholar
  • 34 Beal LL, Kolman JM, Jones SL, Khleif A, Menser T. Quantifying patient portal use: systematic review of utilization metrics. J Med Internet Res 2021; 23 (02) e23493
    CrossrefPubMedGoogle Scholar
  • 35 Chan B, Lyles C, Kaplan C, Lam R, Karliner L. A comparison of electronic patient-portal use among patients with resident and attending primary care providers. J Gen Intern Med 2018; 33 (12) 2085-2091
    CrossrefPubMedGoogle Scholar
  • 36 Glantz S, Slinker B, Neilands T. Primer of Applied Rregression and Analysis of Variance. 3rd ed.. New York: McGraw-Hill Education/Medical; 2016
    Google Scholar
  • 37 Graetz I, Gordon N, Fung V, Hamity C, Reed ME. The digital divide and patient portals: internet access explained differences in patient portal use for secure messaging by age, race, and income. Med Care 2016; 54 (08) 772-779
    CrossrefPubMedGoogle Scholar
  • 38 Park J, Liang M, Alpert JM, Brown RF, Zhong X. The causal relationship between portal usage and self-efficacious health information-seeking behaviors: secondary analysis of the health information national trends survey data. J Med Internet Res 2021; 23 (01) e17782
    CrossrefPubMedGoogle Scholar
  • 39 Greenberg-Worisek AJ, Kurani S, Finney Rutten LJ, Blake KD, Moser RP, Hesse BW. Tracking healthy people 2020 internet, broadband, and mobile device access goals: an update using data from the health information national trends survey. J Med Internet Res 2019; 21 (06) e13300
    CrossrefPubMedGoogle Scholar
  • 40 Benefit EB. Federal Communications Commission. Updated November 15, 2021. Accessed November 30, 2021 at: https://www.fcc.gov/broadbandbenefit
    PubMedGoogle Scholar
  • 41 Stein JN, Klein JW, Payne TH. et al. Communicating with vulnerable patient populations: a randomized intervention to teach inpatients to use the electronic patient portal. Appl Clin Inform 2018; 9 (04) 875-883
    Article in Thieme ConnectPubMedGoogle Scholar
  • 42 Zhong X, Liang M, Sanchez R. et al. On the effect of electronic patient portal on primary care utilization and appointment adherence. BMC Med Inform Decis Mak 2018; 18 (01) 84
    CrossrefPubMedGoogle Scholar
  • 43 Alaeddini A, Yang K, Reddy C, Yu S. A probabilistic model for predicting the probability of no-show in hospital appointments. Health Care Manage Sci 2011; 14 (02) 146-157
    CrossrefPubMedGoogle Scholar
  • 44 Harvey HB, Liu C, Ai J. et al. Predicting no-shows in radiology using regression modeling of data available in the electronic medical record. J Am Coll Radiol 2017; 14 (10) 1303-1309
    CrossrefPubMedGoogle Scholar
  • 45 Daghistani T, AlGhamdi H, Alshammari R, AlHazme RH. Predictors of outpatients' no-show: big data analytics using Apache spark. Journal of Big Data 2020; 7 (01) 108
    CrossrefPubMedGoogle Scholar
  • 46 Pecina J, Duvall MJ, North F. Frequency of and factors associated with care partner proxy interaction with health care teams using patient portal accounts. Telemed J E Health 2020; 26 (11) 1368-1372
    CrossrefPubMedGoogle Scholar