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Record W4400972700 · doi:10.2196/58526

Recommendations to Address Barriers to Patient Portal Use Among Persons With Diabetes Seeking Care at Community Health Centers: Interview Study With Patients and Health Care Providers

2024· article· en· W4400972700 on OpenAlexvenueno aff
Samuel Akyirem, Julie Wagner, Helen Fu, Joanna Lipson, Maritza Minchala, Karina Raygoza-Cortez, Robin Whittemore

Bibliographic record

VenueJMIR Diabetes · 2024
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsPatient portalMedicineHealth careFamily medicineDiabetes mellitusNursingGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: Community health centers (CHCs) are safety-net health care facilities in the United States that provide care for a substantial number of low-income, non-English speaking adults with type 2 diabetes (T2D). Whereas patient portals have been shown to be associated with significant improvements in diabetes self-management and outcomes, they remain underused in CHCs. In addition, little is known about the specific barriers to and facilitators of patient portal use in CHCs and strategies to address the barriers. OBJECTIVE: The objectives of this qualitative study were to explore the barriers to and facilitators of the use of patient portals for managing diabetes in 2 CHCs from the perspective of adults with T2D and clinicians (community health workers, nurses, nurse practitioners, and physicians) and to make recommendations on strategies to enhance use. METHODS: A qualitative description design was used. A total of 21 participants (n=13, 62% clinicians and n=8, 38% adults with T2D) were purposively and conveniently selected from 2 CHCs. Adults with T2D were included if they were an established patient of one of the partner CHCs, aged ≥18 years, diagnosed with T2D ≥6 months, and able to read English or Spanish. Clinicians at our partner CHCs who provided care or services for adults with T2D were eligible for this study. Semistructured interviews were conducted in either Spanish or English based on participant preference. Interviews were audio-recorded and transcribed. Spanish interviews were translated into English by a bilingual research assistant. Data were collected between October 5, 2022, and March 16, 2023. Data were analyzed using a rapid content analysis method. Standards of rigor were implemented. RESULTS: Themes generated from interviews included perceived usefulness and challenges of the patient portal, strategies to improve patient portal use, and challenges in diabetes self-management. Participants were enthusiastic about the potential of the portal to improve access to health information and patient-clinician communication. However, challenges of health and technology literacy, maintaining engagement, and clinician burden were identified. Standardized implementation strategies were recommended to raise awareness of patient portal benefits, provide simplified training and technology support, change clinic workflow to triage messages, customize portal notification messages, minimize clinician burden, and enhance the ease with which blood glucose data can be uploaded into the portal. CONCLUSIONS: Adults with T2D and clinicians at CHCs continue to report pervasive challenges to patient portal use in CHCs. Providing training and technical support on patient portal use for patients with low health literacy at CHCs is a critical next step. Implementing standardized patient portal strategies to address the unique needs of patients receiving care at CHCs also has the potential to improve health equity and health outcomes associated with patient portal use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.387
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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