Insights into the Impact of Med Rec Implementation at admission in Acute and Long Term Care Settings in Alberta
Bibliographic record
Abstract
Introduction: In Canada, adverse drug events (ADEs) pose a significant public health problem. Various clinical tools have been created to mitigate ADEs and/or their impacts. Medication reconciliation (Med Rec) has been created as a clinical process intended to address the limitations associated with the use of previous clinical tools. Typically, Med Rec interventions have been implemented and evaluated at a single hospital ward and/or among vulnerable patient populations, thus limiting the generalizability of findings. In Alberta, a medication reconciliation intervention, the Medication Reconciliation Alberta (MRQA Med Rec), has been concurrently implemented in acute care hospitals and continuing care facilities with the aim of enhancing medication safety. The intervention has the potential to reduce ADE-related healthcare utilization by ensuring that all medication changes are adequately documented. Primary Objective: To evaluate the effectiveness of MRQA Med Rec in Alberta’s healthcare settings. Secondary Objectives: 1) To characterize Alberta’s healthcare institutions participating in the MRQA Med Rec intervention and compare with non-participating institutions; 2) To determine the consistency (fidelity) of MRQA Med Rec implementation by assessing the Quality Audit Bundle Compliance at Admission; 3) To evaluate whether the impact of the MRQA Med Rec intervention differs among care settings; and 4) To assess the impact of organizational factors on the effectiveness of MRQA Med Rec interventions both between and within healthcare settings. Study population: Cohort consisted of Alberta’s acute care hospital units and LTC facilities, participating in the initiative as of June 2014. Data collection: Administrative data from the following sources were linked by facility identifier: NACRS; DAD; Guide to Canadian Health facilities database; and MRQA Med Rec dataset. Data was obtained from the period between June 1st 2013 and March 31st, 2015. Analysis: Continuous variables were described with measures of central tendency and dispersion and categorical variables were described using contingency tables. Outcomes associated with ADE related healthcare utilization (ADE related ED visits and ADE related hospitalizations), consistently measured over time, were analyzed using repeated measures with the generalized linear mixed model procedures in SAS. For all parameter tests, α level was set to 0.05. Results: Alberta has 328 healthcare facilities, whereas as of June 2014, 116 healthcare organizations have implemented MRQA Med Rec including: hospitals (n=52); hospice (n=1) and publicly funded LTC facilities (n=63). MRQA Med Rec implementation in hospitals was not associated with changes in number of ADE related ED visits (p-value =0.1090) yet organizational factor analysis found that intervention’s positive effect may be more pronounced in hospitals with fewer than 50 beds (p-value
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".