Validation of a tool to assess patient satisfaction, waiting times, healthcare utilization, and cost
Bibliographic record
Abstract
AIM: Patients' experience of the quality of care received throughout their continuum of care can be used to direct quality improvement efforts in areas where they are most needed. This study aims to establish validity and reliability of the Healthcare Access and Patient Satisfaction Questionnaire (HAPSQ) - a tool that collects patients' experience that quantifies aspect of care used to make judgments about quality from the perspective of the Alberta Quality Matrix for Health (AQMH). BACKGROUND: The AQMH is a framework that can be used to assess and compare the quality of care in different healthcare settings. The AQMH provides a common language, understanding, and approach to assessing quality. The HAPSQ is one tool that is able to assess quality of care according to five of six AQMH's dimensions. METHODS: This was a prospective methodologic study. Between March and October 2015, a convenience sample of patients presenting with chronic full-thickness rotator cuff tears was recruited prospectively from the University of Calgary Sport Medicine Centre in Calgary, Alberta, Canada. Reliability of the HAPSQ was assessed using test-retest reliability [interclass correlation coefficient (ICC)>0.70]. Validity was assessed through content validity (patient interviews, floor and ceiling effects), criterion validity (percent agreement >70%), and construct validity (hypothesis testing). FINDINGS: Reliability testing was completed on 70 patients; validity testing occurred on 96 patients. The mean duration of symptoms was three years (SD: 5.0, range: 0.1-29). Only out-of-pocket utilization possessed an ICC<0.70. Patients reported that items were relevant and appropriate to measuring quality of care. No floor or ceiling effects were present. Criterion validity was reached for all items assessed. A priori hypotheses were confirmed. The HAPSQ represents an inexpensive, reliable, and valid approach toward collecting clinical information across a patient's continuum of care.
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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 | 0.045 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".