Assessing Performance in Health Care Using International Surveys: Are Patient and Clinician Perspectives Complementary or Substitutive
Bibliographic record
Abstract
Background: Over the last decade, international surveys of patients and clinicians have been used to compare health care across countries. Findings from these surveys have been extensively used to create aggregate scores and rankings. Objective: To assess the concordance of survey responses provided by patients and clinicians. Methods: Analysis of 16 pairs of questions that focused on coordination, organizational factors, and patient-centered competencies from the Commonwealth Fund International Health Policy Survey of older adults (2014) and of primary care physicians (2015). Concordance was assessed by comparing absolute rates and relative rankings. Results: In absolute terms, patients and clinicians gave differing responses for questions about coordination of care (patients were more positive) and provision of after-hours care (patients were less positive). In relative terms, country rankings were positively correlated for 5 of 16 question pairs (Spearman ρ > .6 and P < .05). Conclusion: Patterns of concordance between patient and clinician perspectives provides information to guide the use of survey data in performance assessment. However, this study highlights the need to assess the complementarity and substitutive nature of patients’ and clinicians’ perspectives before combining them to create aggregate assessments of performance.
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.
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 | 0.061 | 0.135 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".