Development of a Quality Assessment Tool for Outpatient Infusion Clinics: A Literature Review and Pilot Survey
Bibliographic record
Abstract
This study aimed to develop a quality assessment tool for outpatient infusion clinics, as a lack of literature exists on the subject. The authors conducted a literature review targeting studies since 2016 to identify variables that affect patient satisfaction in outpatient infusion clinics. Due to the limited number of relevant studies found, the authors shadowed 2 infusion clinic nurses to capture additional determinants of outpatient infusion clinic quality. A total of 72 variables relevant to an outpatient infusion quality assessment tool were listed. From this list of variables, a pilot survey was conducted at an outpatient rheumatology infusion clinic to assess patient satisfaction with 16 variables of interest. The pilot survey (N = 43) revealed that patients were relatively dissatisfied with walking to clinics, lack of access to public transit, lack of parking and/or free parking, lack of privacy, and flexible scheduling and/or cancellation policies. These findings demonstrate how the assessment tool may highlight specific areas of concern at an infusion clinic to identify targets for future quality improvement initiatives. Therefore, the tool presented has the potential to improve the quality of care provided to patients attending infusion facilities.
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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 | 0.043 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".