A Virtual Ward to Reduce Readmissions After Hospital Discharge
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Ontario
-
Toronto, Ontario, Canada, M5B 1W8
- St. Michael's Hospital
-
Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre
-
Toronto, Ontario, Canada
- University Health Network
-
Toronto, Ontario, Canada
- Toronto Central Community Care Access Centre
-
Toronto, Ontario, Canada
- Women's College Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Discharge from medical service
- LACE score greater than or equal to 10
- Age greater than or equal or 18
- Resident in Toronto Central Local Health Integration Network catchment area
- Patient or designate able to speak English well enough for follow up telephone calls
Exclusion Criteria:
- Previously enrolled in study
- Discharged to a rehabilitation or complex continuing care facility
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Active Comparator: Usual Care
|
The usual care provided to patients after discharge from hospital
|
|
Experimental: Virtual Ward
|
A multidisciplinary team to optimize medical and social care for patients residing in their own homes
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Composite of readmission to hospital or death.
Time Frame: 30 days after hospital discharge
|
A binary outcome variable for each patient, representing either readmission to hospital or death within 30 days of hospital discharge.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
30 days after hospital discharge
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Composite of readmission or death
Time Frame: 90 days after discharge
|
A binary outcome variable for each patient, representing either readmission to hospital or death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
90 days after discharge
|
|
Composite of readmission or death
Time Frame: 6 months after discharge
|
A binary outcome variable for each patient, representing readmission to hospital within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
6 months after discharge
|
|
Composite of readmission or death
Time Frame: One year after discharge
|
A binary outcome variable for each patient, representing either readmission to hospital or death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Emergency department visits
Time Frame: 30 days after discharge
|
A binary outcome variable for each patient, representing an emergency department visit within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
30 days after discharge
|
|
Emergency department visits
Time Frame: 90 days after discharge
|
A binary outcome variable for each patient, representing an emergency department visit within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
90 days after discharge
|
|
Emergency department visits
Time Frame: 6 months after discharge
|
A binary outcome variable for each patient, representing an emergency department visit within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
6 months after discharge
|
|
Emergency department visits
Time Frame: One year after discharge
|
A binary outcome variable for each patient, representing an emergency department visit within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Long-term care admission
Time Frame: 30 days after discharge
|
A binary outcome variable for each patient, representing a long-term care admission within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
30 days after discharge
|
|
Long-term care admission
Time Frame: 90 days after discharge
|
A binary outcome variable for each patient, representing a long-term care admission within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
90 days after discharge
|
|
Long-term care admission
Time Frame: 6 months after discahrge
|
A binary outcome variable for each patient, representing a long-term care admission within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
6 months after discahrge
|
|
Long-term care admission
Time Frame: One year after discharge
|
A binary outcome variable for each patient, representing a long-term care admission within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Death
Time Frame: 90 days after discharge
|
A binary outcome variable for each patient, representing death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences
|
90 days after discharge
|
|
Death
Time Frame: 6 months after discharge
|
A binary outcome variable for each patient, representing death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences
|
6 months after discharge
|
|
Death
Time Frame: One year after discharge
|
A binary outcome variable for each patient, representing death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences
|
One year after discharge
|
|
Death
Time Frame: 30 days after discharge
|
A binary outcome variable for each patient, representing death within the time periods noted above.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences
|
30 days after discharge
|
|
Composite of readmission to hospital or death.
Time Frame: One year after discharge
|
Time to the composite outcome of either readmission to hospital or death.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Data will be censored on the date of the last follow up (i.e., 30 days, 90 days or 6 months).
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Readmission
Time Frame: One year after discharge
|
Time to readmission to hospital.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Data will be censored on the date of the last follow up (i.e., 30 days, 90 days or 6 months), or on death.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Emergency department visits
Time Frame: One year after discharge
|
Time to emergency department visit.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Data will be censored on the date of the last follow up (i.e., 30 days, 90 days or 6 months), or on readmission or death.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Long-term care admission
Time Frame: One year after discharge
|
Time to long-term care admission.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Data will be censored on the date of the last follow up (i.e., 30 days, 90 days or 6 months), or on death.
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
|
Death
Time Frame: One year after discharge
|
Time to death.
A research assistant blinded to the assignment will ascertain this information via telephone using a standardized script.
Data will be censored on the date of the last follow up (i.e., 30 days, 90 days or 6 months).
Second, we may also ascertain this information by linking the data we collect to administrative databases housed at the Institute for Clinical Evaluative Sciences.
|
One year after discharge
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Irfan Dhalla, MD, MSc, St. Michael's Hospital/University of Toronto
Publications and helpful links
General Publications
- van Walraven C, Dhalla IA, Bell C, Etchells E, Stiell IG, Zarnke K, Austin PC, Forster AJ. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ. 2010 Apr 6;182(6):551-7. doi: 10.1503/cmaj.091117. Epub 2010 Mar 1.
- Dhalla IA, O'Brien T, Morra D, Thorpe KE, Wong BM, Mehta R, Frost DW, Abrams H, Ko F, Van Rooyen P, Bell CM, Gruneir A, Lewis GH, Daub S, Anderson GM, Hawker GA, Rochon PA, Laupacis A. Effect of a postdischarge virtual ward on readmission or death for high-risk patients: a randomized clinical trial. JAMA. 2014 Oct 1;312(13):1305-12. doi: 10.1001/jama.2014.11492.
Study record dates
Study Major Dates
Study Start
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimate)
First Posted
Study Record Updates
Last Update Posted (Estimate)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 216852-PHE-CEAJ-25173
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.