Medication reconciliation at admission and discharge: a time and motion study
Bibliographic record
Abstract
BACKGROUND: Medication reconciliation at admission, transfer and discharge has been designated as a required hospital practice to reduce adverse drug events. However, implementation challenges have resulted in poor hospital adherence. The aim of this study was to assess the processes required to carry out medication reconciliation: the health professionals involved, the tasks and time devoted to medication reconciliation in general hospital settings. METHODS: A time-and-motion study design was used. Using a systematic sample of patients admitted and discharged from geriatric, medical and surgical units in two academic centers, health professionals involved in medication reconciliation were observed and timed. Descriptive statistics were used to summarize the number of professionals involved, tasks performed, and mean time devoted. RESULTS: Up to 3 professionals from 2 disciplines (medicine and pharmacy) were involved in the medication reconciliation process. Geriatric reconciliations took the most time to complete at admission (mean: 92.2 minutes (SD = 44.3)) and discharge (mean: 29.0 minutes (SD = 23.8)), followed by internal medicine at admission (mean: 46.2 minutes (SD = 21.1)) and 19.4 (SD = 11.7) minutes at discharge) and general surgery minutes at discharge (mean: 9.9 minutes (SD = 18.2)). Considerable differences in order, type and number of tasks performed were noted between and within units. Tasks independent of direct patient interaction took more than twice the time required to complete than tasks requiring patient interaction. CONCLUSION: Lack of coordination, specialized training and agreement on the roles and responsibilities of professionals are among the most probable reasons for work-flow inefficiencies, possibly variability in quality, and time required for the current medication reconciliation process. A better understanding of the admission processes in general surgery is required. Standardization and use of electronic tools could improve efficiency and hospital adherence.
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 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".