The Personal Health Network Mobile App for Chemotherapy Care Coordination: Qualitative Evaluation of a Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Cancer care coordination addresses the fragmented and inefficient care of individuals with complex care needs. The complexity of care coordination can be aided by innovative technology. Few examples of information technology-enabled care coordination exist beyond the conventional telephone follow-up. For this study, we implemented a custom-designed app, the Personal Health Network (PHN)-a Health Insurance Portability and Accountability Act-compliant social network built around a patient to enable patient-centered health and health care activities in collaboration with clinicians, care team members, caregivers, and others designated by the patient. The app facilitates a care coordination intervention for patients undergoing chemotherapy. OBJECTIVE: This study aimed to understand patient experiences with PHN technology and assess their perspectives on the usability and usefulness of PHNs with care coordination during chemotherapy. METHODS: A two-arm randomized clinical trial was conducted to compare the PHN and care coordination with care coordination alone over a 6-month period beginning with the initiation of chemotherapy. A semistructured interview guide was constructed based on a theoretical framework of technology acceptance addressing usefulness, usability, and the context of use of the technology within the participant's life and health care setting. All participants in the intervention arm were interviewed on completion of the study. Interviews were recorded and transcribed verbatim. A summative thematic analysis was completed for the transcribed interviews. Features of the app were also evaluated. RESULTS: A total of 27 interviews were completed. The resulting themes included the care coordinator as a partner in care, learning while sick, comparison of other technology to make sense of the PHN, communication, learning, usability, and usefulness. Users expressed that the nurse care coordinators were beneficial to them because they helped them stay connected to the care team and answered their questions. They shared that the mobile app gave them access to the health information they were seeking. Users expressed that the mobile app would be more useful if it was fully integrated with the electronic health record. CONCLUSIONS: The findings highlight the value of care coordination from the perspectives of cancer patients undergoing chemotherapy and the important role of technology, such as the PHN, in enhancing this process by facilitating better communication and access to information regarding their illness.
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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 | 0.139 | 0.166 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".