Use of Health-Record Abstracting to Document Pharmaceutical Care Activities
Bibliographic record
Abstract
ABSTRACT Objectives: The purpose of this study was to develop a system of pharmacy documentation and information retrieval that would avoid duplication of information and result in accurate workload measurements. This pilot project assessed the resources needed to implement the system throughout the Royal Columbian Hospital, New Westminster, British Columbia. Methods: Two pharmacists, working in the Coronary Care Unit, documented drug-related problems directly in the patient health-care record and coded each note with the following information: a number representing the pharmacist, the ward where the note was written, and the type of drug-related problem. The Health Records Department, upon abstracting the health-care record, retrieved and reported this information. Duplicate records were kept in the Pharmacy Department for audit purposes. Results: Reports generated by the Health Records Department included the number and types of notes written, classified by both patient and pharmacist. The information reported by the Health Records Department was more accurate than the information reported by the Pharmacy Department. It was calculated that the future cost of implementing this system throughout the entire institution would be 0.08 full-time equivalents. Conclusions: This project demonstrated that when pharmacists document drug-related problems directly into the patient health-care record, the information can be accurately retrieved and reported by the Health Records Department. RESUME Objectifs : Le but de cette etude etait de mettre sur pied un systeme de recherche documentaire et d’information pharmaceutiques qui eliminerait la duplication de l’information et permettrait de mesurer precisement la charge de travail. Ce projet pilote a evalue les ressources necessaires a la mise en oeuvre de ce systeme a la grandeur du Royal Columbian Hospital, a New Westminster, en Colombie-Britannique. Methode : Deux pharmaciens travaillant a l’Unite de soins coronariens ont documente les problemes pharmacotherapeutiques directement dans le dossier medical des patients et ont assigne un code a chaque note portee au dossier avec l’information suivante : un numero representant le pharmacien, le service ou la note a ete redigee, et le type de probleme pharmacotherapeutique. Le Service des dossiers medicaux, apres avoir depouille les dossiers, a recupere l’information puis en a redige un rapport. Des doubles ont ete conserves au Service de pharmacie aux fins de verification. Resultats : Les rapports rediges par le Service des dossiers medicaux comprenaient le numbre et le type de notes classees a la fois par patient et par pharmacien. L’information presentee par le Service des dossiers medicaux etait plus precise que celle consignee par le Service de pharmacie. On a calcule qu’il en couterait 0,08 equivalent temps plein pour mettre en oeuvre ce systeme a la grandeur de l’etablissement. Conclusions : Ce projet a montre que lorsque les pharmaciens documentaient les problemes pharmacotherapeutiques directement dans le dossier medical du patient, le Service des dossiers medicaux pouvait de facon precise en extraire l’information et en rediger un rapport.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".