Evaluation of Family Caregivers’ Use of Their Adult Care Recipient’s Patient Portal From the 2019 Health Information National Trends Survey: Secondary Analysis
Bibliographic record
Abstract
BACKGROUND: Patient engagement is critical for realizing the value of telehealth modalities such as the patient portal. Family caregiver engagement may also be critical for facilitating the use of the patient portal among adult patients, including older adults. OBJECTIVE: This study aims to analyze the 2019 Health Information National Trends Survey to characterize family caregivers' use of their care recipient's patient portal in terms of sociodemographic, health, and caregiving characteristics and caregivers' use of their own portal. METHODS: We conducted a secondary analysis of cross-sectional data from the National Cancer Institute's Health Information National Trends Survey 5 Cycle 3. This survey was administered to 5438 US adults between January and May 2019. We analyzed data from 320 respondents who were identified as family caregivers. We created measures to reflect family caregivers' use of their care recipient's and their own portal, caregiver demographic and caregiving characteristics, and care recipient health characteristics. RESULTS: Over half of the caregivers (179/320, 55.9%) reported using their own portal at least once, whereas only one-third (105/320, 32.8%) reported using their care recipient's record in the previous 12 months. Caregivers using their own portal were significantly more likely to use their care recipient's portal (odds ratio 11.18; P<.001). CONCLUSIONS: Policies should enable patients to designate family caregivers who can access their patient portal. Providers could screen caregivers for challenges in their caregiving responsibilities that may be addressed through the portal so they can better support their adult relatives. Interventions to support family caregivers, especially older caregivers, in using their own portal may facilitate their use of their care recipient's portal.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".