The Prevalence of No-Shows and Cancellations Rate in Outpatient Physical Therapy Practice and Its Relationship to Age and Gender
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Bibliographic record
Abstract
Background: No-Show and late canceled appointments significantly impact out-patient Physical therapist productivity, patient clinical outcomes, and the clinic's revenue-generating capacity. No-show and appointment cancelation cost the out-patient Physical Therapy practice in this case study $114,505.58CAD in 2017. This study seeks to understand, identify, and provide solutions unique to our local setting for the problem of no-shows and appointment cancellation.Methods: This study uses the 2017 de-identified patient’s attendance records of an out-patient Physical Therapy clinic in Calgary, Canada. Patient data, including sex, age, scheduled appointment, no-show, and cancellation history, were examined. The data were analyzed using chi-square to determine any significant differences in attendance patterns among these groups.Results: A total of 6,162 scheduled appointments were aggregated from the EHR. The overall no-show and cancelation was 20.6%. Male had a slightly higher rate of no-show/cancelation (20.8%) versus females (20.6%), which was not statistically significant (p = 0.734). In the adult age groups, no-show and cancelation rates were highest for 12-20y/o (31.4%), 21-30y/o (31.3%), and 41-50y/o (22.3%). These groups accounted for 50.6% of total revenue loss. There was a significant overall difference among the age groups (p < 0.0001) in no-show/cancelation. The top four reasons for no-show and cancellation include forgetting the appointment, family and personal emergency, lack of transportation, and a scheduling conflict with another equally important appointment.Conclusion: Evidence indicates that no-show and appointment cancelation rates are high in Canadian health institutions leading to poor productivity, inefficiency, and revenue loss. This study seeks to provide an evidence-based intervention.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it