Does a Complex Care Discharge Planning Initiative Reduce Unplanned Hospital Readmissions? (G78717-Readmits)

University of British Columbia

Status: Enrolling

Conditions: Patient Readmission

Treatments: Other: Policy intervention

Study type: Observational

Funder types: Other

Identifiers

NCT03256734

H17-01039

Details and patient eligibility

About

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.

Enrollment: 300,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

The study population will be comprised of all hospital discharges in British Columbia between 1 Jan 2002 and 30 June 2017.

Exclusion criteria

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]