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A Virtual Ward to Reduce Readmissions After Hospital Discharge

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ClinicalTrials.gov Identifier: NCT01108172
Recruitment Status : Unknown
Verified December 2013 by Irfan Dhalla, St. Michael's Hospital, Toronto.
Recruitment status was:  Active, not recruiting
First Posted : April 21, 2010
Last Update Posted : December 9, 2013
Sponsor:
Collaborators:
Canadian Institutes of Health Research (CIHR)
Toronto Central Local Health Integration Network
Ontario Ministry of Health and Long Term Care
Toronto Central Community Care Access Centre
Women's College Hospital
University Health Network, Toronto
Sunnybrook Health Sciences Centre
Information provided by (Responsible Party):
Irfan Dhalla, St. Michael's Hospital, Toronto

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

Condition or disease Intervention/treatment
Acute Disease Other: Virtual Ward Other: Usual care

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  (Clinical Trial)
Estimated Enrollment : 1928 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single (Outcomes Assessor)
Primary Purpose: Health Services Research
Official Title: A Virtual Ward to Reduce Readmissions After Hospital Discharge
Study Start Date : June 2010
Primary Completion Date : June 2013
Estimated Study Completion Date : June 2014

Resource links provided by the National Library of Medicine

U.S. FDA Resources

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



Primary Outcome Measures :
  1. 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.


Secondary Outcome Measures :
  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.



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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01108172


Locations
Canada, Ontario
St. Michael's Hospital
Toronto, Ontario, Canada, M5B 1W8
Sunnybrook Health Sciences Centre
Toronto, Ontario, Canada
Toronto Central Community Care Access Centre
Toronto, Ontario, Canada
University Health Network
Toronto, Ontario, Canada
Women's College Hospital
Toronto, Ontario, Canada
Sponsors and Collaborators
St. Michael's Hospital, Toronto
Canadian Institutes of Health Research (CIHR)
Toronto Central Local Health Integration Network
Ontario Ministry of Health and Long Term Care
Toronto Central Community Care Access Centre
Women's College Hospital
University Health Network, Toronto
Sunnybrook Health Sciences Centre
Investigators
Principal Investigator: Irfan Dhalla, MD, MSc St. Michael's Hospital/University of Toronto