Methods of Piloting an Abstraction Tool to Describe Family Engagement in the Hospital Setting: Retrospective Chart Review
Bibliographic record
Abstract
Background: Family engagement in hospitals is crucial for improving outcomes and ensuring holistic, patient-centered care. However, there is limited understanding of how providers document family engagement in electronic medical records (EMR) and how factors such as race and health disparities influence engagement practices. The absence of standardized EMR templates complicates tracking engagement and assessing its impact on patient outcomes. Retrospective chart review (RCR) is an effective method for investigating clinical practice and how family engagement is documented, using both structured and unstructured data from patient records. Despite its potential, gaps remain in the literature regarding distinctions between the prepilot and pilot phases in RCR studies. Objective: This article describes the prepiloting and piloting stages in the development of an abstraction tool for an RCR study, highlighting how these phases refined the tool for extracting family engagement data from the EMRs. Methods: A cohort of 2032 medical records was selected using the Research Patient Database Registry and EMRs. Initially, a draft tool was tested during the prepilot phase to assess its stability. To optimize diversity, the sample was then stratified by race. The modified tool was subsequently piloted on a subset of the sample. Results: The prepilot phase tested the tool on 9 records. In the pilot phase, the tool was applied to 39 records, representing approximately 10% of the sample. After the prepiloting and piloting phases, 293 of the 405 patient records were deemed eligible for inclusion. More than three-quarters of patients had documentation of presence and communication; whereas, only about one-third had documentation of shared decision-making involving families. Conclusions: The prepilot phase helped standardize the abstraction tool, align it with the EMRs, and address potential biases. The pilot phase provided insights into data availability and highlighted areas for refinement before finalizing the tool for the remaining records. Together, these phases ensured the tool's effectiveness for use in large-scale RCR studies.
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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 | 0.179 | 0.270 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".