Is research on patient portals attuned to health equity? A scoping review
Bibliographic record
Abstract
OBJECTIVE: Our scoping review examined how research on patient portals addresses health equity. Questions guiding our review were: 1) What health equity concepts are addressed in patient portal research-both explicitly and implicitly? 2) What are the gaps? 3) Is the potential for ehealth-related health inequities explicitly acknowledged in studies on patient portals? 4) What novel approaches and interventions to reduce health inequities are tested in patient portal research? MATERIALS AND METHODS: We searched 4 databases. Search terms included "patient portal" in combination with a comprehensive list of health equity terms relevant in ehealth context. Authors independently reviewed the papers during initial screening and full-text review. We applied the eHealth Equity Framework to develop search terms and analyze the included studies. RESULTS: Based on eHealth Equity Framework categories, the main findings generated from 65 reviewed papers were governance structures, ehealth policies, and cultural and societal values may further inequities; social position of providers and patients introduces differential preferences in portal use; equitable portal implementation can be supported through diverse user-centered design; and intermediary strategies are typically recommended to encourage portal use across populations. DISCUSSION: The predominant focus on barriers in portal use may be inadvertently placing individual responsibility in addressing these barriers on patients already experiencing the greatest health disparities. This approach may mask the impact of the socio-technical-economic-political context on outcomes for different populations. CONCLUSION: To support equitable health outcomes related to patient portals we need to look beyond intermediary initiatives and develop equitable strategies across policy, practice, research, and implementation.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.073 | 0.311 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.027 | 0.027 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".