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Using Novel Canadian Resources to Improve Medication Reconciliation at Discharge

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McGill University

Status

Completed

Conditions

Adverse Drug Events
Medication Reconciliation

Treatments

Other: Electronic Medication Reconciliation

Study type

Interventional

Funder types

Other

Identifiers

NCT01179867
RN 0000086616 - 222163

Details and patient eligibility

About

The purpose of this study is to determine if a physician's use of electronic medication reconciliation software when writing a patient's discharge prescription will prevent adverse drug events and readmissions to the hospital. This electronic medication software will provide the physician with the most up-to-date list of medications the patient was taking before being admitted to the hospital, through a real-time link to the provincial drug insurance agency's administrative databases. It will also provide the list of medications the patient has taken while admitted to the hospital. With these two pieces of information, the physician will write the discharge prescription using the medication management software, print the discharge prescription for the patient, and the software will fax a copy of any prescriptions that should be stopped to the patient's community pharmacist.

Full description

Background:

  • Drug-related illness accounts for 5-23% of hospital admissions, 4-8% of ambulatory visits, and is now claimed to be the 6th leading cause of mortality.
  • At least 58% of adverse drug events (ADEs) are considered preventable.
  • Transitions in care, particularly between community and hospital, account for a substantial number of preventable ADEs. In fact, between 12% to 17% of patients will have an adverse drug event within 30 days of discharge from hospital, and 14.3% will be readmitted.
  • A major contributor to preventable ADEs is the failure to reconcile pre-admission medications with drugs prescribed at discharge. To avoid preventable ADEs, medication reconciliation is now a required organizational practice for hospital accreditation in Canada and the United States.
  • However, there are substantial challenges in implementing medication reconciliation, as 87% of patients do not know what drugs they are taking, and 63% of the time staff cannot access outside records from the community pharmacy or primary care physician. As a result, 60-70% of medication histories contain at least one error.
  • The time and resources required to obtain the community drug profile far outstrips the capacity to deliver this essential service for most patients.

Goal:

  • Providing the medical team with the capacity to electronically retrieve the most up-to-date community drug list from all pharmacies will optimize the accuracy of medication histories and reduce the time required to reconcile the community and hospital drug lists at discharge.
  • This strategy will also identify and advise the community pharmacies and physicians of the changes made during hospitalization, so that prescriptions for drugs that are discontinued because of adverse effects or ineffective treatment do not continue to be filled.

Preliminary work & novel opportunities:

  • We established a "real-time" linkage to the Quebec health insurance agency (RAMQ) to test the benefits of accessing the complete drug profile in primary care. In a pilot test, we showed that the use of this linkage to retrieve community drug profiles at admission identified 2 additional drugs per patient, and reduced medication history-taking by 2.5 minutes per patient.
  • There are unique opportunities to use existing drug insurance data to electronically access the community drug profile in Quebec. The province currently maintains comprehensive records of all dispensed medication for those insured through provincial drug program, providing information on 97.6% of medication used in the community.

Scientific objectives:

To determine if electronically facilitated reconciliation of community and hospital drugs at discharge and communication of treatment changes to the community-based prescribing physicians and pharmacists will reduce the risk of ADEs and re-admissions in the 30 days post-discharge.

Design:

A cluster randomized controlled trial will be used to evaluate the effects of electronic discharge reconciliation and communication on the occurrence of ADEs post-discharge. The study will be conducted at the McGill University Health Centre. We will stratify by medical and surgical unit, and then randomize the units into discharge medication reconciliation or usual care.

The discharge reconciliation intervention has three components:

  1. at admission, the community drug profile will be retrieved from RAMQ and the data will be transmitted to the hospital pharmacy information system;
  2. at discharge, the physician will use a community / hospital reconciliation module to write discharge prescriptions, discontinuation orders, and a rationale for all modified community medications;
  3. The updated medication list will be transmitted to the community-based prescribing physician(s), and dispensing pharmacy(ies) by fax.

Usual care typically includes a community drug history by the admission team when feasible, review by hospital pharmacist at the request of the treatment team, and manual reconciliation of community and hospital drug lists on the discharge prescription performed at the discretion of the discharging team.

The primary outcome will be ADEs, measured by follow-up interview 30 days post-discharge, and the secondary outcome-re-admission/ ER visit in 30 days, assessed by retrieving complete service utilization files from the RAMQ. Multivariate logistic regression will be used to assess the impact of discharge medication reconciliation. For both the primary and secondary outcome, we will assess whether adjustment for co-interventions and baseline differences between patients in the usual care and intervention arm confound the effect of the intervention. In a secondary analysis, we will assess whether the effect of the intervention is modified by hospital unit type (medicine versus surgery) or patient characteristics that are associated with a higher risk of adverse events (age, number of medications at discharge, number of medication changes at discharge) by including respective interaction terms in the logistic model and testing their significance using the Wald chi-square statistic.

Enrollment

4,014 patients

Sex

All

Ages

18+ years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • have public drug insurance: this includes all those 65 years and older in the province of Quebec, as well as those under 65 on social assistance or who do not have drug insurance available through their employer
  • admitted to the hospital from the community
  • admitted to a surgical or internal medicine unit
  • discharged alive

Exclusion criteria

  • none

Trial design

Primary purpose

Prevention

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

4,014 participants in 2 patient groups

Electronic Medication Reconciliation
Experimental group
Description:
Electronic medication reconciliation includes: 1. Electronic retrieval of the community drug list at admission 2. Generation of discharge prescription using the discharge reconciliation module at discharge 3. Transfer of information on discontinued and changed medication to respective dispensing pharmacies and prescribing physicians
Treatment:
Other: Electronic Medication Reconciliation
Usual practice medication reconciliation
No Intervention group
Description:
Usual practice in dealing with medication reconciliation. This includes viewing the hospital medications through the hospital electronic pharmacy system, and viewing the community drugs in the patient's chart, if it was collected at admission (not always the case). However not all physicians view the community drugs before writing the discharge prescription. The physician will write a paper discharge prescription to be given to the patient, but communications are generally not made directly to the community pharmacist or previous prescribing physicians.

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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