Bridging the Digital Health Divide
Characterizing Patient Portal Users and Nonusers in the U.S
Bibliographic Data
| ID | 9098622 |
|---|---|
| Authors | Naheed Ahmed (0000-0002-5980-8480, NYU Grossman School of Medicine, corresponding author), Jason Brown (0000-0003-2501-3556, MedStar Health Research Institute, Hyattsville, MD), Codrin Parau (MedStar Health Research Institute), Codrin A Parau (MedStar Health), Asli Mccullers (0000-0002-3704-2728, MedStar Center for Health Equity Research), Kavya Sanghavi (MedStar Health Research Institute), Kavya K Sanghavi (0000-0002-6324-7719, MedStar Health), Robin Littlejohn (MedStar Health Research Institute), Deliya B Wesley (0000-0002-4764-3244, Mathematica, Washington, DC) |
| Year | 2023 |
| Volume | 61 |
| Issue | 7 |
| Pages | 448-455 |
| Publication date | 2023-07-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0000000000001869 |
| PMID | 37289563 |
| OpenAlex | W4379877525 |
| Language | EN |
| Citations received | 1 |
| References cited | 25 |
OBJECTIVE: The objectives of this study were to (1) examine demographic differences between patient portal users and nonusers; and (2) examine health literacy, patient self-efficacy, and technology usage and attitudes between patient portal users and nonusers. METHODS: Data were collected from Amazon Mechanical Turk (MTurk) workers from December 2021 to January 2022. MTurk workers completed an online survey, which asked about their health, access to technology, health literacy, patient self-efficacy, media and technology attitudes, and patient portal use for those with an account. A total of 489 MTurk workers completed the survey. Data were analyzed using latent class analysis (LCA) and multivariate logistic regression models. RESULTS: Latent class analysis models revealed some qualitative differences between users and nonusers of patient portals in relation to neighborhood type, education, income, disability status, comorbidity of any type, insurance type, and the presence or absence of primary care providers. These results were partially confirmed by logistic regression models, which showed that participants with insurance, a primary care provider, or a disability or comorbid condition were more likely to have a patient portal account. CONCLUSIONS: Our study findings suggest that access to health care, along with ongoing patient health needs, influence the usage of patient portal platforms. Patients with health insurance have the opportunity to access health care services, including establishing a relationship with a primary care provider. This relationship can be critical to a patient ever creating a patient portal account and actively engaging in their care, including communicating with their care team
eHealth · Family medicine · Health care · Health literacy · Latent class model · Literacy · Logistic regression · Patient portal · Electronic Health Records Systems · Medicine · Mobile Health and mHealth Applications · Nursing · Psychology · Telemedicine and Telehealth Implementation
| Unique citing works | 1 |
|---|---|
| Citations per year | 0.5 |
| Citation span | 2024 - 2024 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |