A concept analysis of the patient experience
Bibliographic record
Abstract
Patient experience, an essential indicator of quality patient care, is of increasing importance to hospitals that want to improve and maintain strong patient experience metrics to remain competitive in the business of healthcare. The aim of this study was to clarify the concept of the patient experience by identifying its existing definitions, methods of measurement, and underlying themes and attributes, to differentiate it from similar concepts and propose an operational and theoretical definition to guide valid and reliable development of future assessment tools. Walker and Avant’s eight-step methodology served as the framework for this concept analysis. A literature search, using seven databases and one search engine, was conducted of existing literature published any time up until September 2021. The search identified 19,447 references of which 436 articles and organizational websites were included. Twenty attributes (n= 20) were found to define the patient experience: (1) communication; (2) respect for patients; (3) information and education; (4) patient-centered care; (5) comfort and pain; (6) discharge from hospital; (7) hospital environment; (8) professionalism and trust; (9) clinical care and staff competency; (10) access to care; (11) global ratings (12) medication; (13) transitions and continuity; (14) emotional dimension; (15) outcomes; (16) hospital processes; (17) safety and security; (18) interdisciplinary team; (19) social dimension; and, (20) patient dependent features. The proposed definition of the patient experience is: “Patient experience is the combination of external and internal hospital processes, patient-centered attributes, patient-staff and staff-staff interactions during all episodes of care.” Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".