Initial Usability Evaluation of a Knowledge-Based Population Health Information System: The Population Health Record (PopHR).
Bibliographic record
Abstract
We report the baseline usability of a novel web-based application, the Population Health Record (PopHR), designed to facilitate the effective use of population health information by public health professionals and to support evidence-based decision-making. The usability test was conducted with ten potential users who each completed eight tasks using the PopHR system. Participant responses were recorded, including timestamps for each data entry. Overall, the task completion rate was 96% while the success rate was 88%. The average time-on-task was 3.11 minutes, with more time spent on tasks requiring a user to stratify data along multiple dimensions, such as age, sex, or geographical region. Usability scores indicated that the current version of PopHR has good usability. Potential improvements identified included adding supporting information, offering different visualizations, and enhancing system stability. These findings are examples of addressable usability problems encountered in developing a population health record system.
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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 | 0.027 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".