Bibliographic record
Abstract
Purpose Patient experience is a complex multidimensional phenomenon that has been linked to constructs that are also complex to conceptualize, such as patient-centeredness, patient expectations and patient satisfaction. The purpose of this paper is to shed light on the different dimensions of patient experience, including those that receive inadequate attention from policymakers such as the patient’s lived experience of illness and the impact of healthcare politics. The paper proposes a simple classification for these dimensions, which differentiates between two types of dimensions: the determinants and the manifestations of patient experience. Design/methodology/approach This paper uses a narrative review of the literature to explore select constructs and initiatives developed for theorizing or operationalizing patient experience. Literature topics reviewed include healthcare quality, medical anthropology, health policy, healthcare system and public health. Findings The paper identifies five determinants for patient experience: the experience of illness, patient’s subjective influences, quality of healthcare services, health system responsiveness and the politics of healthcare. The paper identifies two manifestations of patient experience: patient satisfaction and patient engagement. Originality/value The paper proposes a classification scheme of the dimensions of patient experience and a concept map that links together heterogeneous constructs related to patient experience. The proposed classification and the concept map provide a holistic view of patient experience and help healthcare providers, quality managers and policymakers organize and focus their healthcare quality improvement endeavors on specific dimensions of patient experience while taking into consideration the other dimensions.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".