Changes in Documentation Due to Patient Access to Electronic Health Records: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Internationally, patient-accessible electronic health records (PAEHRs) are increasingly being implemented. Despite reported benefits to patients, the innovation has prompted concerns among health care professionals (HCPs), including the possibility that access incurs a "dumbing down" of clinical records. Currently, no review has investigated empirical evidence of whether and how documentation changes after introducing PAEHRs. OBJECTIVE: This paper presents the protocol for a scoping review examining potential subjective and objective changes in HCPs documentation after using PAEHRs. METHODS: This scoping review will be carried out based on the framework of Arksey and O'Malley. Several databases will be used to conduct a literature search (APA PsycInfo, CINAHL, PubMed, and Web of Science Core Collection). Authors will participate in screening identified papers to explore the research questions: How do PAEHRs affect HCPs' documentation practices? and What subjective and objective changes to the clinical notes arise after patient access? Only studies that relate to actual use experiences, and not merely prior expectations about PAEHRs, will be selected in the review. Data abstraction will include but will not be limited to publication type, publication year, country, sample characteristics, setting, study aim, research question, and conclusions. The Mixed Methods Appraisal Tool will be used to assess the quality of the studies included. RESULTS: The results from this scoping review will be presented as a narrative synthesis structured along the key themes of the corpus of evidence. Additional data will be prepared in charts or tabular format. We anticipate the results to be presented in a scoping review at a later date. They will be disseminated at scientific conferences and through publication in a peer-reviewed journal. CONCLUSIONS: This is the first scoping review that considers potential change in documentation after implementation of PAEHRs. The results can potentially help affirm or refute prior opinions and expectations among various stakeholders about the use of PAEHRs and thereby help to address uncertainties. Results may help to provide guidance to clinicians in writing notes and thus have immediate practical relevance to care. In addition, the review will help to identify any substantive research gaps in this field of research. In the longer term, our findings may contribute to the development of shared documentation guidelines, which in turn are central to improving patient communication and safety. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46722.
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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 | 0.140 | 0.136 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.066 | 0.014 |
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".