Improving Medication Reconciliation compliance at admission
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The objective of this research is to improve compliance of the medication reconciliation process at the time of patient admission in the Department of Pediatrics at King Faisal Specialist Hospital and Research Centre, Riyadh, Kingdom of Saudi Arabia using an innovative evidence-based approach. MATERIALS AND METHODS: Most of the recent efforts at our institution to revamp the medication reconciliation process have failed. Thus, we implemented an innovative evidence-based approach to improve the compliance of the reconciliation process at admission. This approach focused on the Department of Pediatrics at King Faisal Specialist Hospital and Research Centre (KFSH&RC). We established specific educational and monitoring programs that were run over a two-month period, from June to July 2015. The educational program consisted of focused hands-on daily interactive training sessions presented to a small group of residents, i.e., 5-6 residents per session, for a period of one week. One resident was identified as a "Super-User" to provide ongoing support for the other residents involved in the process. A close monitoring process was also implemented, which included daily follow up and encouragement from three assigned consultants. In addition, periodic independent audit report results prepared by Healthcare Information Technology Affairs (HITA) were communicated to the Department of Pediatrics regarding physician compliance in the medication reconciliation process. RESULTS: Physician compliance for admission medication reconciliation documentation in ICIS ranged from (0-15%) between the first quarter of 2012 and the first quarter 2015, we designated the official hospital audit for the first quarter of 2015 as a baseline audit report. Between the first quarter of 2012 and 2015, the physician compliance for admission medication reconciliation was ranged between 0 to 15% according to the official hospital audit. We implemented our initiative during the months of June and July 2015. During that time, there was a gradual improvement in the number of admission medication reconciliations reported by the independent audits of our general Pediatrics Ward (B1), which represents the majority of pediatric admissions. The 57% of 26 patients had medication reconciliation completed by the first report dated 16 June 2015. This percentage improved to 92% out of a total of 13 patients at the last report on 12 July 2015. This consistent improvement also occurred in other areas where pediatric patients were admitted including the B3-1 (from 88% to 90%), the NICU 1 (from 83% to 100%) and the NICU 2 (from 90% to 100%). CONCLUSIONS: By structuring and implementing intensive educational and monitoring programs, a marked improvement in the compliance of medication reconciliation at the time of admission for the pediatric patient population was achieved. We believe that our department-based results would be generalizable if a similar hospital-wide programme was to be rigorously implemented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".