40 Provider Perspectives of a Pediatric Patient Portal
Bibliographic record
Abstract
Abstract Primary Subject area Technology Background Patient portals (PPs) can enhance patient engagement and have potential to improve quality of care. However, despite positive perceptions of them by patients and their families, adoption remains low. Since provider promotion of PPs has been shown to impact patient activation and use, understanding providers’ perspectives of PPs is a critical component to successful implementation and impact. Yet there is sparse information, beyond anecdotal reports, about provider opinion, particularly in pediatrics. Objectives We sought to evaluate clinician perceptions regarding the implementation of a PP in a pediatric environment. Design/Methods An electronic survey was sent to all clinicians in a pediatric tertiary health centre. Perceived and expected PP usefulness/usability, impact on clinician-patient/family relationships, workload, security, privacy, and medicolegal risk were evaluated, as well as overall attitude toward PP adoption and interest in future PP functionality. Descriptive statistics were calculated and analyzed for all survey items. Results Four hundred and seventy-three participants (87% female; 71% < age 50 years; 26% physicians) completed the survey (24% response rate) representing a broad range of clinical areas and PP experience. Respondents understood (94%), accepted (92%), and agreed (89%) that PP implementation provided better patient access and care. Only 24% of respondents felt their PP training was adequate. Clinician observations of their patients and families using the PP are displayed in Figure 1. While 86% of clinicians reported that the PP had not changed their overall workload and productivity, 41% felt it would increase as more patients become active. There were minimal PP-related privacy/security concerns, but 24% of respondents felt their medico-legal risk concerns would increase with a PP, as more patients become active. Seventy-nine percent of respondents reported that PP use does not change the quality of care they deliver. Forty-six percent would like their patients to be active on the PP, while 48% were indifferent. Future portal functionality favoured scheduling, questionnaires, and e-visits. Conclusion While the justification for PP implementation is acknowledged, compared to existing literature and current patient experiences, clinicians underestimate their potential value, overestimate their impact on workload and patient anxiety, and feel that they need more training to properly use a portal. These results will guide the next steps in PP optimization locally, and should aid other centres in understanding and addressing clinician concerns, with the goal of improving PP activation and use. Although concerns about PPs cited by providers are largely unfounded, they persist and remain a barrier to optimal leveraging of this tool.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".