Patient-Caregiver Portal System in Palliative Oncology: Assessment of Usability and Perceived Benefit
Bibliographic record
Abstract
BACKGROUND: The engagement of family caregivers in oncology is not universal or systematic. OBJECTIVE: We implemented a process intervention (ie, patient-caregiver portal system) with an existing patient portal system to (1) allow a patient to specify their caregiver and communication preferences with that caregiver, (2) connect the caregiver to a unique caregiver-specific portal page to indicate their needs, and (3) provide an electronic notification of the dyad's responses to the care team to inform clinicians and connect the caregiver to resources as needed. METHODS: We assessed usability and satisfaction with this patient-caregiver portal system among patients with cancer receiving palliative care, their caregivers, and clinicians. RESULTS: Of 31 consented patient-caregiver dyads, 20 patients and 19 caregivers logged in. Further, 60% (n=12) of patients indicated a preference to communicate equally or together with their caregiver. Caregivers reported high emotional (n=9, 47.3%), financial (n=6, 31.6%), and physical (n=6, 31.6%) caregiving-related strain. The care team received all patient-caregiver responses electronically. Most patients (86.6%, 13/15 who completed the user experience interview) and caregivers (94%, 16/17 who completed the user experience interview) were satisfied with the system, while, of the 6 participating clinicians, 66.7% agreed "quite a bit" (n=1, 16.7%) or "very much" (n=3, 50%) that the system allowed them to provide better care. CONCLUSIONS: Our findings demonstrate system usability, including a systematic way to identify caregiver needs and share with the care team in a way that is acceptable to patients and caregivers and perceived by clinicians to benefit clinical care. Integration of a patient-caregiver portal system may be an effective approach for systematically engaging caregivers. These findings highlight the need for additional research among caregivers of patients with less advanced cancer or with different illnesses.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".