A Virtual Ward to Reduce Readmissions After Hospital Discharge

The purpose of this study is to see whether a Virtual Ward reduces readmissions after hospital discharge.

Study Overview

• Status: Unknown
• Conditions: Acute Disease
• Intervention / Treatment: Other: Usual care; Other: Virtual Ward

Detailed Description

We will conduct a pragmatic, randomized controlled trial to evaluate a new model of care for high-risk medical patients after discharge from hospital. This new model of care has two key elements. First, we will use the LACE index (see citation below for details) to identify patients who are at high risk of readmission or death after hospital discharge. These patients will be randomized to either the Virtual Ward or usual care on the day of discharge. Although patients being cared for in the Virtual Ward will reside at home, they will benefit from a hospital-like interdisciplinary team, a shared set of notes, a single point of contact, round-the-clock physician availability and increased co-ordination of specialist, primary and home-based community care for several weeks after hospital discharge.

• Study Type: Interventional
• Enrollment (Anticipated): 1928
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Canada
  • 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

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

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

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Usual Care	Other: Usual care; The usual care provided to patients after discharge from hospital
Experimental: Virtual Ward	Other: 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

Outcome Measure	Measure Description	Time Frame
Composite of readmission to hospital or death.	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

Outcome Measure	Measure Description	Time Frame
Composite of readmission or death	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	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	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	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	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	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	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	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	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	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	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	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	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	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	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 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 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 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 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 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: Unity Health Toronto
• Collaborators: University Health Network, Toronto; Sunnybrook Health Sciences Centre; Canadian Institutes of Health Research (CIHR); Ontario Ministry of Health and Long Term Care; Women's College Hospital; Toronto Central Local Health Integration Network; Toronto Central Community Care Access Centre
• 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: June 1, 2010
• Primary Completion (Actual): June 1, 2013
• Study Completion (Anticipated): June 1, 2014

Study Registration Dates

• First Submitted: April 13, 2010
• First Submitted That Met QC Criteria: April 19, 2010
• First Posted (Estimate): April 21, 2010

Study Record Updates

• Last Update Posted (Estimate): December 9, 2013
• Last Update Submitted That Met QC Criteria: December 6, 2013
• Last Verified: December 1, 2013

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Disease Attributes; Acute Disease
• Other Study ID Numbers: 216852-PHE-CEAJ-25173