Using Novel Canadian Resources to Improve Medication Reconciliation at Discharge

Sponsor
McGill University (Other)
Overall Status
Completed
CT.gov ID
NCT01179867
Collaborator
Canadian Institutes of Health Research (CIHR) (Other)
4,014
1
2
58
69.2

Study Details

Study Description

Brief Summary

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.

Condition or Disease Intervention/Treatment Phase
  • Other: Electronic Medication Reconciliation
N/A

Detailed 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.

Study Design

Study Type:
Interventional
Actual Enrollment :
4014 participants
Allocation:
Randomized
Intervention Model:
Parallel Assignment
Masking:
Single (Outcomes Assessor)
Primary Purpose:
Prevention
Official Title:
Using Novel Canadian Resources to Improve Medication Reconciliation at Discharge
Study Start Date :
Oct 1, 2014
Actual Primary Completion Date :
Mar 1, 2017
Actual Study Completion Date :
Aug 1, 2019

Arms and Interventions

Arm Intervention/Treatment
Experimental: Electronic Medication Reconciliation

Electronic medication reconciliation includes: Electronic retrieval of the community drug list at admission Generation of discharge prescription using the discharge reconciliation module at discharge Transfer of information on discontinued and changed medication to respective dispensing pharmacies and prescribing physicians

Other: Electronic Medication Reconciliation
At admission the community drug list will be electronically retrieved from the public drug insurance administrative databases using a real-time interface, and the admitting team/pharmacist will verify the list, adding over-the-counter medications At discharge the attending physician/resident will write the discharge prescription using the discharge reconciliation module, allowing the physician to simultaneously view the validated community drug list and the hospital pharmacy drug list for the patient The discharge communication module will facilitate identification and transfer of information on discontinued and changed medication to the respective dispensing pharmacies and prescribing physicians along with the reasons for these changes

No Intervention: Usual practice medication reconciliation

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.

Outcome Measures

Primary Outcome Measures

  1. Adverse drug event [Withing the 30 days post-discharge from hospital]

    Adverse drug event: an injury resulting from medical intervention related to a drug. Assessed using: self-reported patient information 30 days post-discharge chart and administrative data on drugs that were started, stopped, or continued at discharge as well as acute and chronic health problems reviewing & adjudicating the presence of an adverse event and the probability of it being drug related by a blinded expert panel review of each patient's chart and post-discharge interview data using the Leape & Bates method, and the Naranjo criteria.

Secondary Outcome Measures

  1. Emergency room visit / Hospital readmission [Within the 30 days post-discharge from hospital]

    All visits to the emergency room and/or hospital re-admission in the 30 days post-discharge will be measured using the provincial health insurance administrative databases. This approach ensures that all ER visits and re-admissions are included, not just those occuring at the study hospitals. Almost all hospital-based physicians in Quebec are remunerated on a fee-for-service basis, and are required to record accurately the treating establishment and location of service, as this information determines the level of remuneration.

  2. Failure to re-start community medications used for chronic conditions after discharge from hospital. [90 days after discharge from hospital]

    Of all discharged patients who were on a medication used for a chronic condition in the community prior to their hospitalization, we will measure the proportion who do not re-start this medication within the 90 days after they are discharged from hospital. This will be measured through comparison of their dispensed community medications before and after hospitalization (from administrative insurance database).

  3. Readiness for hospital discharge [Within the 30 days post-discharge from hospital]

    This sub-study will examine the determinants and outcomes of patients' readiness for hospital discharge. Specifically, it will determine if: a) patient and hospital organizational characteristics are associated with patients' readiness for hospital discharge, b) lower levels of patients' readiness for hospital discharge are associated with an increased risk of ADEs and re-admissions 30-day post-discharge and, c) the effects of the medication reconciliation intervention on ADEs and readmissions 30-day post discharge is modified by level of patient's readiness for hospital discharge.

  4. Time to complete medication history and discharge medication reconciliation with prescription. [At admission to study unit, and upon discharge from hospital]

    We will measure the time it takes clinicians to complete the patient's medication history at admission, which includes time spent speaking with patients about medications, contacting patients' pharmacies for information on patients' community medications, and documenting the community medication list. We will also measure the time it takes clinicians to complete a medication reconciliation at discharge and write the discharge prescription. We will compare the intervention and control groups, to see if the intervention reduces the time it takes clinicians to complete either of these two tasks.

  5. Therapy duplication [Withing the 30 days post-discharge from hospital]

    We will measure the frequency at which therapy duplications occur in the discharge prescription, comparing intervention with control units. A therapy duplication will be defined as two or more drugs in the same therapeutic class being prescribed to the same patient.

  6. Unplanned dose changes [Withing the 30 days post-discharge from hospital]

    We will measure the frequency at which unplanned dose changes occur in the discharge prescription, comparing intervention with control units. An unplanned dose change will be defined as a change in dose from that at admission that was not documented as such in the discharge prescription.

  7. Errors of omission [Withing the 30 days post-discharge from hospital]

    We will measure the frequency at which errors of omission occur in the discharge prescription, comparing intervention with control units. An omission will be defined as a community medication (i.e. dispensed in the 3 months prior to admission) that is not present on the discharge prescription.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
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

Contacts and Locations

Locations

Site City State Country Postal Code
1 McGill University Health Centre Montreal Quebec Canada H3A 1A3

Sponsors and Collaborators

  • McGill University
  • Canadian Institutes of Health Research (CIHR)

Investigators

  • Principal Investigator: Robyn Tamblyn, PhD, McGill University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Robyn Tamblyn, Professor, McGill University
ClinicalTrials.gov Identifier:
NCT01179867
Other Study ID Numbers:
  • RN 0000086616 - 222163
First Posted:
Aug 11, 2010
Last Update Posted:
Aug 20, 2019
Last Verified:
Aug 1, 2019
Keywords provided by Robyn Tamblyn, Professor, McGill University
Additional relevant MeSH terms:

Study Results

No Results Posted as of Aug 20, 2019