Impact of computerized quality of life screening on physician behaviour and patient satisfaction in lung cancer outpatients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper was to determine if providing patient specific Quality of Life (QL) information to clinic staff before a clinic appointment improved patient care in a lung cancer outpatient clinic. Patients were sequentially assigned to either a usual care control group or the experimental group, which completed a computerized version of the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire in order to provide the clinic staff with QL information prior to the clinic appointment. The control group completed the EORTC QLQ-C30 paper version after the clinic appointment. Outcome measures were patient satisfaction, the degree to which issues identified on the QL questionnaire were addressed in the appointment, and a chart audit, which measured charting of QL issues and actions taken by the clincian relating to QL. In the experimental group, more QL issues identified by the patient on the EORTC QLQ-C30 were addressed during the clinic appointment than in the control group. As well, marginally more categories were charted and a trend towards more actions being taken was seen in the experimental group. Patients reported being equally and highly satisfied with the treatment in both groups. The clinical implication is that the computerized administration of the EORTC QLQ-C30 questionnaire and providing staff with a report highlighting patient-specific QL deficits is a simple, time-effective and acceptable means of improving patient-provider communication in a busy outpatient clinic. Large trials studying its effectiveness in different patient populations and regions would further elucidate the nature of this effect and potentially improve the overall quality of care that patients receive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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