Primary Care Providers’ Preferences and Concerns Regarding Specific Visual Displays for Returning Hemoglobin A1c Test Results to Patients
Bibliographic record
Abstract
Purpose. Patient portals of electronic health record systems currently present patients with tables of laboratory test results, but visual displays can increase patient understanding and sensitivity to result variations. We sought to assess physician preferences and concerns about visual display designs as potential motivators or barriers to their implementation. Methods. In an online survey, 327 primary care physicians (>50% patient care time) recruited through the online e-community/survey research firm SERMO compared hemoglobin A1c (HbA1c) test results presented in table format to various visual displays (number line formats) previously tested in public samples. Half of participants also compared additional visual formats displaying target goal ranges. Outcome measures included preferred display format and whether any displays were unacceptable, would change physician workload, or would induce liability concerns. Results. Most (85%–89%) respondents preferred visual displays over tables for result communications both to patients tested for diagnosis purposes and to diagnosed patients, with a design with color-coded categories most preferred. However, for each format (including tables), 11% to 23% rated them as unacceptable. Most respondents also preferred adding goal range information (in addition to standard ranges) for diagnosed patients. While most physicians anticipated no workload changes, 19% to 32% anticipated increased physician workload while 9% to 28% anticipated decreased workload. Between 32% and 40% had at least some liability concerns. Conclusions. Most primary care physicians prefer visual displays of HbA1c test results over table formats when communicating results to patients. However, workload and liability concerns from a minority of physicians represent a barrier for adoption of such designs in clinical settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".