Insights into the Impact of Med Rec Implementation at admission in Acute and Long Term Care Settings in Alberta
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».