An evaluation of a model for the systematic documentation of hospital based health promotion activities: results from a multicentre study
Bibliographic record
Abstract
BACKGROUND: The first step of handling health promotion (HP) in Diagnosis Related Groups (DRGs) is a systematic documentation and registration of the activities in the medical records. So far the possibility and tradition for systematic registration of clinical HP activities in the medical records and in patient administrative systems have been sparse. Therefore, the activities are mostly invisible in the registers of hospital services as well as in budgets and balances.A simple model has been described to structure the registration of the HP procedures performed by the clinical staff. The model consists of two parts; first part includes motivational counselling (7 codes) and the second part comprehends intervention, rehabilitation and after treatment (8 codes).The objective was to evaluate in an international study the usefulness, applicability and sufficiency of a simple model for the systematic registration of clinical HP procedures in day life. METHODS: The multi centre project was carried out in 19 departments/hospitals in 6 countries in a clinical setup. The study consisted of three parts in accordance with the objectives.A: Individual test. 20 consecutive medical records from each participating department/hospital were coded by the (coding) specialists at local department/hospital, exclusively (n = 5,529 of 5,700 possible tests in total).B: Common test. 14 standardized medical records were coded by all the specialists from 17 departments/hospitals, who returned 3,046 of 3,570 tests.C: Specialist evaluation. The specialists from the 19 departments/hospitals evaluated if the codes were useful, applicable and sufficient for the registration in their own department/hospital (239 of 285). RESULTS: A: In 97 to 100% of the local patient pathways the specialists were able to evaluate if there was documentation of HP activities in the medical record to be coded.B: Inter rater reliability on the use of the codes were 93% (57 to 100%) and 71% (31 to 100%), respectively.C: The majority of the study participants found the codes to be useful (71%), applicable (92%) and sufficient (92%). CONCLUSION: Systematic registration of HP activities is relevant in clinical day life and the suggested codes proved to be applicable for international use. HP is an essential part of the clinical pathway or the value chain. This model promises to improve the documentation and thereby facilitate analysis of records for evidence based medicine as well as cost and policy analyses.
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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 | 0.058 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".