Open access scheduling: Improving access to rural healthcare
Bibliographic record
Abstract
Background and Purpose: Open access scheduling is a model that allows patients to choose appointments at their convenience in an effort to provide timely access to healthcare. Healthcare providers typically have overbooked schedules that make it difficult to provide access to primary care appointments for patients in need without long wait times. The purpose of this quality improvement project was to implement open access scheduling at a federally-qualified health center to evaluate the number of missed patient appointments and the amount of time it takes to receive an appointment. Methods: Patient appointments (N=1,333) were analyzed via the Allscripts™ electronic computer system. During project implementation, staff utilized a written protocol for open access that had been tested at a satellite office with successful results. Patients were placed in appointment slots daily as they were available. Conclusions: The highest no-show rate prior to implementation was 42%, which improved after open access to 27%. Average TNAA trended downward post-implementation from 8.9 days three-months pre-intervention to 4.3 days three-months post-implementation. This scheduling model was successful in decreasing no-show rates by allowing patients to be seen in a timely manner and can be utilized in primary care to improve access to healthcare.
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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 | 0.003 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".