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Record W4382515032 · doi:10.35680/2372-0247.1439

A concept analysis of the patient experience

2023· article· en· W4382515032 on OpenAlexaff
Tanja Avlijas, Janet E. Squires, Michelle Lalonde, Chantal Backman

Bibliographic record

VenuePatient Experience Journal · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsInstitut du Savoir MontfortOttawa HospitalBruyèreUniversity of Ottawa
FundersRoyal Society
KeywordsPatient experiencePatient safetyQuality (philosophy)Health careDimension (graph theory)NursingMedicinePatient carePsychology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0080.006
Science and technology studies0.0020.005
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.103
GPT teacher head0.458
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations14
Published2023
Admission routes1
Has abstractyes

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