A Literature Review of Quality in Lower Gastrointestinal Endoscopy from the Patient Perspective
Bibliographic record
Abstract
BACKGROUND: Given the limited state of health care resources, increased demand for colorectal cancer (CRC) screening raises concerns about the quality of endoscopy services. Little is known about quality in colonoscopy and endoscopy from the patient perspective. OBJECTIVE: To systematically review the literature on quality that is relevant to patients who require colonoscopy or endoscopy services. METHODS: A systematic PubMed search was performed on articles that were published between January 2000 and February 2011. Keywords included "colonoscopy" or "sigmoidoscopy" or "endoscopy" AND "quality"; "colonoscopy" or "sigmoidoscopy" or "endoscopy" AND "patient satisfaction" or "willingness to return". The included articles were qualitative and quantitative English language studies regarding aspects of colonoscopy and⁄or endoscopy services that were evaluated by patients in which data were collected within one year of the colonoscopy⁄endoscopy procedure. RESULTS: In total, 28 quantitative studies were identified, of which eight (28.6%) met the inclusion criteria (four cross-sectional, three prospective cohort and one single-blinded controlled study). Aspects of quality included comfort, management of pain and anxiety, endoscopy unit staff manner, skills and specialty, procedure and results discussion with the doctor, physical environment, wait times for the appointment and procedure, and discharge. Qualitative studies eliciting the patient perspective on what constituted quality in colonoscopy⁄endoscopy were not found. CONCLUSIONS: Factors related to comfort, staff, communication and the service environment were evaluated from the patient perspective using closed-ended questions that were designed by clinicians and researchers. Future research using qualitative methodology to elicit the patient perspective on quality in colonoscopy and⁄or endoscopy services is needed.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Systematic review used to answer a health-services question about endoscopy quality from the patient perspective; uses a synthesis method rather than studying one.
This review concerns patient-perceived quality of endoscopy services, not research practice.
Literature review of patient-perceived quality of clinical endoscopy services.
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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.025 | 0.031 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".