Older Patients’ Perspectives on Quality of Serious Illness Care in Primary Care
Bibliographic record
Abstract
BACKGROUND: Despite increased focus on measuring and improving quality of serious illness care, there has been little emphasis on the primary care context or incorporation of the patient perspective. OBJECTIVE: To explore older patients' perspectives on the quality of serious illness care in primary care. DESIGN: Qualitative interview study. PARTICIPANTS: Twenty patients aged 60 or older who were at risk for or living with serious illness and who had participated in the clinic's quality improvement initiative. METHODS: We used a semistructured, open-ended guide focusing on how older patients perceived quality of serious illness care, particularly in primary care. We transcribed interviews verbatim and inductively identified codes. We identified emergent themes using a thematic and constant comparative method. RESULTS: We identified 5 key themes: (1) the importance of patient-centered communication, (2) coordination of care, (3) the shared decision-making process, (4) clinician competence, and (5) access to care. Communication was an overarching theme that facilitated coordination of care between patients and their clinicians, empowered patients for shared decision-making, related to clinicians' perceived competence, and enabled access to primary and specialty care. Although access to care is not traditionally considered an aspect of quality, patients considered this integral to the quality of care they received. Patients perceived serious illness care as a key aspect of quality in primary care. CONCLUSIONS: Efforts to improve quality measurement and implementation of quality improvement initiatives in serious illness care should consider these aspects of care that patients deem important, particularly communication as an overarching priority.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".