Patient ReadmissionNCT03256734
Does a Complex Care Discharge Planning Initiative Reduce Unplanned Hospital Readmissions? (G78717-Readmits)
An observational study of Patient Readmission, run by University of British Columbia at 1 site in Canada.
Trial summary
Unplanned hospital readmissions are associated with increases in morbidity, mortality, cost and patient dissatisfaction,. Policymakers continue to seek effective policy solutions to avoid readmissions in order to improve quality of care and reduce unnecessary expenditures,. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Patient Readmission
- What is being tested?
- Policy intervention
- How many people
- 300,000 participants
- Where
- 1 siteCanada
- Study dates
- 1 Jul 2018to Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Our study population will be representative of medical and surgical hospital admissions in BC. The Interrupted time series (ITS) cohort will be comprised of hospital separations eligible for submission of fee code G78717. We will include all urgent admissions to BC hospitals with discharge dates between 1 Jan 2002 and 30 June 2017 that had a length of stay (LOS) of >4 days and are associated with a specialist Most Responsible Physician (MRP). The regression analysis cohort study will be identical to the ITS cohort but will be restricted to index hospitalization discharge dates between 1 Jun 2012 and 31 Jul 2017 (ie. the post-G78717 period). The unit of analysis is the index hospital admission (ie. the initial hospital admission of interest). Individual patients can contribute multiple hospital admissions to the cohort over time (although only hospital admissions occurring >30 days after a prior discharge are eligible as index hospital admissions).
Who may be able to join
- The study population will be comprised of all hospital discharges in British Columbia between 1 Jan 2002 and 30 June 2017.
Who cannot join
- We will exclude separations with the following International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) codes as the Most Responsible Diagnosis:
- Codes O00 - O99 [Pregnancy, childbirth and the puerperium]
- Codes P00 - P96 [Certain conditions originating in the perinatal period]
Trial locations and contacts
1 site in 1 country.
Canada1 site, 1 recruiting
- Recruiting
Population Data BC
Vancouver, British Columbia, V6T 1Z3
Tim Choi
About this study
Official title: Does a Complex Care Discharge Planning Initiative Reduce Unplanned Hospital Readmissions?
Unplanned hospital readmissions are associated with increases in morbidity, mortality, cost and patient dissatisfaction,. Policymakers continue to seek effective policy solutions to avoid readmissions in order to improve quality of care and reduce unnecessary expenditures,. One attempt to reduce readmissions was implemented on June 1 2012, when the Specialist Services Committee of British Columbia (a partnership of Doctors of BC and the Ministry of Health) introduced the new "G78717" fee code for physicians. The objective of the fee code was to create a financial incentive for physicians to provide a point-of-care supplemental discharge summary to patients and their primary care providers prior to discharge from hospital. Initially, only urgent hospital admissions were eligible for this incentive payment but on Nov 1 2015 the incentive was extended to include elective admissions as well. The other eligibility criteria remained unchanged.
The effectiveness and cost-effectiveness of the fee code intervention is unknown. This study will address important questions relevant to this policy intervention using rigorous methods and empirical data.
Read more
This study will employ two methods for measuring changes in readmission risk. First, we will use interrupted (multivariate) time series to measure whether there was a temporal change in provincial readmission risk associated with the implementation of the new fee code.
We will complement the above analyses with a stronger design, comparing hospitalizations for which the fee code was charged (intervention group) with a cohort of clinically similar hospitalizations for which the fee code was not charged (control group). For this approach, multivariate logistic regression will be the primary statistical method. Using this analytic strategy, 30-day readmission risk between the intervention and control group will be measured over time, adjusted for patient-, provider-, and hospitalization-level covariates.
- Conditions
- Patient Readmission
- Being tested
- Policy intervention
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Policy interventionOther
Incentive payment for physicians
What is being measured
The primary outcome is the main question the study is designed to answer.
Unplanned hospital readmission within 30 days
Unplanned hospital readmission within 30 days
Measured: 30 days
Secondary outcomes (7)
Unplanned (urgent) hospital readmission within 1 year of index hospital discharge
Unplanned (urgent) hospital readmission within 1 year of index hospital discharge
Measured: 1 year
Primary care visits within 30 days and 1 year of index hospital discharge
Primary care visits within 30 days and 1 year of index hospital discharge
Measured: 30 days and 1 year
Emergency department visit
Emergency department visit within 30 days and 1 year of index hospital discharge
Measured: 30 days and 1 year
Death
Death within 30 days and 1 year of index hospital discharge
Measured: 30 days and 1 year
Use of transitional or stepdown care
Use of transitional or stepdown care (eg. rehabilitation, extended care, intermediate /personal care) after discharge from acute care but prior to return home
Measured: 30 days and 1 year
Improvements in appropriate population-level post-discharge prescription prevalence of an indicated medication
Using health services records, we will identify a sub-cohort of patients with an index admission for acute coronary syndrome, heart failure, or chronic ischemic heart disease. Within this subcohort, we will determine the proportion of patients who filled at least one prescription for beta-blockers within 60 days of index hospital discharge date.
Measured: 60 days
Improvements in appropriate population-level post-discharge prescription prevalence of a contraindicated medication
Using health services records, we will identify a sub-cohort of older adults (aged >/=65 years at date of index hospital discharge date). Within this subcohort, we will determine the proportion of patients who filled at least one prescription for a "potentially inappropriate medication" within 60 days of index hospital discharge date. Our list of "potentially inappropriate medications" has been adapted from those listed in the American Geriatrics Society 2015 Updated Beers Criteria.
Measured: 60 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Aug 2017
- Study start1 Jul 2018
- Primary completion1 Sep 2018
- Study completionDec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Patient ReadmissionStudies of the same condition, open and under way.
- More trials run by University of British ColumbiaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 300,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of British Columbia
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, John Staples, University of British Columbia
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03256734
- Sponsor's protocol ID
- H17-01039
- Status last verified
- May 2023
- First submitted
- 18 Aug 2017
- Last updated
- 10 May 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Data stewards are legally prohibited from sharing IPD.
Publications
Staples JA, Yu Y, Khan M, Naik H, Liu G, Brubacher JR, Karimuddin A, Sutherland JM. Physician Financial Incentives to Reduce Unplanned Hospital Readmissions: A Propensity Score Weighted Cohort Study. Am J Med. 2024 Sep;137(9):847-856.e11. doi: 10.1016/j.amjmed.2024.04.042. Epub 2024 May 14.
PubMed 38750712Staples JA, Liu G, Brubacher JR, Karimuddin A, Sutherland JM. Physician Financial Incentives to Reduce Unplanned Hospital Readmissions: an Interrupted Time Series Analysis. J Gen Intern Med. 2021 Nov;36(11):3431-3440. doi: 10.1007/s11606-021-06803-8. Epub 2021 May 4.
PubMed 33948803
Study at a glance
From the registry record, last updated by the sponsor on 10 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Does a Complex Care Discharge Planning Initiative Reduce Unplanned Hospital Readmissions?
- ClinicalTrials.gov ID
- NCT03256734
- Acronym / sponsor ID
- H17-01039
- Conditions
- Patient Readmission
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300,000 participants (estimated)
- Lead sponsor
- University of British ColumbiaUniversity, hospital or other
- Study start
- 1 Jul 2018 (actual)
- Primary completion
- 1 Sep 2018 (actual)
- Study completion
- Dec 2023 (estimated)
- First posted
- 22 Aug 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Unplanned hospital readmissions are associated with increases in morbidity, mortality, cost and patient dissatisfaction,. Policymakers continue to seek effective policy solutions to avoid readmissions in order to improve quality of care and reduce unnecessary expenditures,. One attempt to reduce readmissions was implemented on June 1 2012, when the Specialist Services Committee of British Columbia (a partnership of Doctors of BC and the Ministry of Health) introduced the new "G78717" fee code for physicians. The objective of the fee code was to create a financial incentive for physicians to provide a point-of-care supplemental discharge summary to patients and their primary care providers prior to discharge from hospital. Initially, only urgent hospital admissions were eligible for this incentive payment but on Nov 1 2015 the incentive was extended to include elective admissions as well. The other eligibility criteria remained unchanged.
The effectiveness and cost-effectiveness of the fee code intervention is unknown. This study will address important questions relevant to this policy intervention using rigorous methods and empirical data.
This study will employ two methods for measuring changes in readmission risk. First, we will use interrupted (multivariate) time series to measure whether there was a temporal change in provincial readmission risk associated with the implementation of the new fee code.
We will complement the above analyses with a stronger design, comparing hospitalizations for which the fee code was charged (intervention group) with a cohort of clinically similar hospitalizations for which the fee code was not charged (control group). For this approach, multivariate logistic regression will be the primary statistical method. Using this analytic strategy, 30-day readmission risk between the intervention and control group will be measured over time, adjusted for patient-, provider-, and hospitalization-level covariates.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Our study population will be representative of medical and surgical hospital admissions in BC. The Interrupted time series (ITS) cohort will be comprised of hospital separations eligible for submission of fee code G78717. We will include all urgent admissions to BC hospitals with discharge dates between 1 Jan 2002 and 30 June 2017 that had a length of stay (LOS) of >4 days and are associated with a specialist Most Responsible Physician (MRP). The regression analysis cohort study will be identical to the ITS cohort but will be restricted to index hospitalization discharge dates between 1 Jun 2012 and 31 Jul 2017 (ie. the post-G78717 period). The unit of analysis is the index hospital admission (ie. the initial hospital admission of interest). Individual patients can contribute multiple hospital admissions to the cohort over time (although only hospital admissions occurring >30 days after a prior discharge are eligible as index hospital admissions).
Key inclusion criteria (1 listed)
- The study population will be comprised of all hospital discharges in British Columbia between 1 Jan 2002 and 30 June 2017.
Key exclusion criteria (3 listed)
- We will exclude separations with the following International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) codes as the Most Responsible Diagnosis:
- Codes O00 - O99 [Pregnancy, childbirth and the puerperium]
- Codes P00 - P96 [Certain conditions originating in the perinatal period]
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Policy interventionIncentive payment for physicians | Other | – |
Primary outcome
Unplanned hospital readmission within 30 days
Time frame: 30 days
Unplanned hospital readmission within 30 days
7 secondary outcomes
Unplanned (urgent) hospital readmission within 1 year of index hospital discharge
Time frame: 1 year
Primary care visits within 30 days and 1 year of index hospital discharge
Time frame: 30 days and 1 year
Emergency department visit
Time frame: 30 days and 1 year
Death
Time frame: 30 days and 1 year
Use of transitional or stepdown care
Time frame: 30 days and 1 year
Improvements in appropriate population-level post-discharge prescription prevalence of an indicated medication
Time frame: 60 days
Improvements in appropriate population-level post-discharge prescription prevalence of a contraindicated medication
Time frame: 60 days
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 May 2023.
- Derived from this study: PubMed 38750712Staples JA, Yu Y, Khan M, Naik H, Liu G, Brubacher JR, Karimuddin A, Sutherland JM. Physician Financial Incentives to Reduce Unplanned Hospital Readmissions: A Propensity Score Weighted Cohort Study. Am J Med. 2024 Sep;137(9):847-856.e11. doi: 10.1016/j.amjmed.2024.04.042. Epub 2024 May 14.
- Derived from this study: PubMed 33948803Staples JA, Liu G, Brubacher JR, Karimuddin A, Sutherland JM. Physician Financial Incentives to Reduce Unplanned Hospital Readmissions: an Interrupted Time Series Analysis. J Gen Intern Med. 2021 Nov;36(11):3431-3440. doi: 10.1007/s11606-021-06803-8. Epub 2021 May 4.
- Individual participant dataSharing planned: No. Data stewards are legally prohibited from sharing IPD.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Patient Readmission, run by University of British Columbia at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 10 May 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact John A Staples, MD (604-682-2344, john.a.staples@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Unplanned hospital readmission within 30 days (time frame: 30 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03256734, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 May 2023.