Validation of a Generic Measure of Continuity of Care: When Patients Encounter Several Clinicians
Bibliographic record
Abstract
PURPOSE: Patients who regularly see more than one clinician for health problems risk discontinuity and fragmented care. Our objective was to develop and validate a generic measure of management continuity from the patient perspective. METHODS: Themes from 33 qualitative studies of patient experience with care from various clinicians were matched to existing instruments to identify potential measures and measurement gaps. Adapted and new items were tested cognitively, and the instrument was administered to 376 adult patients consulting in primary care for a variety of health conditions but seeing clinicians in a variety of settings. After initial psychometric analysis, the instrument was modified slightly and readministered after 6 months. The analysis identified reliable subscales and their association with indicators of continuity. RESULTS: Observed factors correspond to 8 intended constructs, with good reliability. Three subscales (12 items) relate to the principal clinician and cover management and relational continuity. Four subscales (13 items) are related to multiple clinicians and address team relational continuity and problems with coordination and gaps in information transfer. Two (11 items) pertain to the patient's partnership in care. Subscales correlate well and in expected directions with indicators of discontinuity (wanting to change clinicians, suffering, and sense of being abandoned, medical errors) and degree of care organization. CONCLUSION: The instrument reliably assesses both positive and negative dimensions of continuity of care across the entire system, and the subscales correlate with continuity effects. It supports patient-centered and relationship-based care and can be used as a whole or in part to assess coordination and continuity in primary 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 | 0.015 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".