Completeness of Medication Reconciliation Performed by Pediatric Resident Physicians at Hospital Admission for Asthma.
Bibliographic record
Abstract
BACKGROUND: Medication errors at hospital admission, though preventable, continue to be common. The process of medication reconciliation has been identified as an important tool in reducing medication errors. The first step in medication reconciliation involves documenting a patient's best possible medication history (BPMH); at the authors' tertiary pediatric hospital, this step is completed at time of admission by resident physicians. OBJECTIVES: To describe and quantify the completeness of admission BPMH by resident physicians for pediatric inpatients with asthma. METHODS: This single-centre, retrospective chart review evaluated documentation of admission medication reconciliation for pediatric inpatients with asthma who were admitted between January 2016 and December 2017. Medication reconciliation forms were deemed incomplete if records for asthma medications were missing drug name, inhaler strength or oral drug dose, directions for use, or evidence of reconciliation. RESULTS: A total of 241 charts were evaluated, of which 97 (40%) had incomplete documentation for at least 1 medication; in particular, 48 (37%) of the 130 inhaled corticosteroid orders were missing inhaler strength. For most of the charts with incomplete medication history (68% [66/97]), no reason was documented; however, review of the medication reconciliation forms and physician notes revealed that families might have been unsure of a patient's home medications or physicians might have left it to the pharmacy to clarify medication doses. CONCLUSIONS: Documentation of inhaler medications on admission medication reconciliation forms completed by resident physicians for pediatric patients with asthma was often incomplete. Future quality improvement interventions, including resident and patient education, are required at the study institution. Collaboration with pharmacy services is also likely to improve completeness of the medication reconciliation process.
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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 | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".