Characteristic of person-centered care as documented in medical records at a medical department – a mixed methods
Bibliographic record
Abstract
Objective: Few studies describe characteristics of content of person-centrered care (PCC) in hospital care. Therefore, this study aim to describe and compare documentation in medical records regarding content of PCC for two diagnostic groups; Chronic Obstructive Pulmonary Disease (COPD) and Chronic Heart Failure (CHF) at a medical department in a hospital in Sweden.Methods: Documentation within medical records (n = 121) regarding content of PCC (patient resources, responsibility, i.e. partnership) were analysed by a mixed methods.Results: The results describe documented healthcare activities (medical records) among patients (COPD1 = 88; CHF2 = 33) treated at medical wards practicing PCC (n = 69, 391/302) and traditional medical wards (n = 52, 491/32). The study showed limited documentation in all medical records regardless of care; however, patients with CHF have higher documentation regarding content of PCC compare to COPD in 6 (symptoms, home situation, objectives, caring activities, patients resources, continuing care) out of 7 areas (planning processes).Conclusions: To improve healthcare with limited resources, there is need to switch mind-sets from what (diagnosis) to who (resources) using all evidence (expert=scientific to expert=lived experiences) by collecting narratives to facilitate mutual health plans (partnership). This change in healthcare organisation facilitates by transformative and shared leadership to improve teamwork (health professionals, patient, relative) in partnership with all involved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".