The Effects of a Multifaceted Intervention to Improve Care Transitions Within an Accountable Care Organization: Results of a Stepped-Wedge Cluster-Randomized Trial
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BACKGROUND: Transitions from hospital to the ambulatory setting are high risk for patients in terms of adverse events, poor clinical outcomes, and readmission.
OBJECTIVES: To develop, implement, and refine a multifaceted care transitions intervention and evaluate its effects on postdischarge adverse events.
DESIGN, SETTING, AND PARTICIPANTS: Two-arm, single-blind (blinded outcomes assessor), stepped-wedge, cluster-randomized clinical trial. Participants were 1,679 adult patients who belonged to one of 17 primary care practices and were admitted to a medical or surgical service at either of two participating hospitals within a pioneer accountable care organization (ACO).
INTERVENTIONS: Multicomponent intervention in the 30 days following hospitalization, including: inpatient pharmacist-led medication reconciliation, coordination of care between an inpatient “discharge advocate” and a primary care “responsible outpatient clinician,” postdischarge phone calls, and postdischarge primary care visit.
MAIN OUTCOMES AND MEASURES: The primary outcome was rate of postdischarge adverse events, as assessed by a 30-day postdischarge phone call and medical record review and adjudicated by two blinded physician reviewers. Secondary outcomes included preventable adverse events, new or worsening symptoms after discharge, and 30-day nonelective hospital readmission.
RESULTS: Among patients included in the study, 692 were assigned to usual care and 987 to the intervention. Patients in the intervention arm had a 45% relative reduction in postdischarge adverse events (18 vs 23 events per 100 patients; adjusted incidence rate ratio, 0.55; 95% CI, 0.35-0.84). Significant reductions were also seen in preventable adverse events and in new or worsening symptoms, but there was no difference in readmission rates.
CONCLUSION: A multifaceted intervention was associated with a significant reduction in postdischarge adverse events but no difference in 30-day readmission rates.
© 2021 Society of Hospital Medicine
Outcome Assessment
Postdischarge Follow-up
Based on previous studies,2,21 a trained research assistant attempted to contact all study subjects 30 days (±5 days) after discharge and administered a questionnaire to identify any new or worsening symptoms since discharge, any healthcare use since discharge, and functional status in the previous week. Follow-up questions used branching logic to determine the relationship of any new or worsening symptoms to medications or other aspects of medical management. Research assistants followed up any positive responses with directed medical record review for objective findings, diagnoses, treatments, and responses. If patients could not be reached after five attempts, the research assistant instead conducted a thorough review of the outpatient medical record alone for provider reports of any new or worsening symptoms noted during follow-up within the 30-day postdischarge period. Research assistants also reviewed laboratory test results in all patients for evidence of postdischarge renal failure, elevated liver function tests, or new/worsening anemia.
Hospital Readmissions
We measured nonelective hospital readmissions within 30 days of discharge using a combination of administrative data for hospitalizations within the ACO network plus patient report during the 30-day phone call for all other readmissions.22
Adjudication of Outcomes
Adverse events and preventable adverse events: All cases of new or worsening symptoms or signs, along with all supporting documentation, were then presented to teams of two trained blinded physician adjudicators through application of methods established in previous studies.4,21 Each of the two adjudicators independently reviewed the information, along with the medical record, and completed a standardized form to confirm or deny the presence of any adverse events (ie, patient injury due to medical management) and to classify the type of event (eg, adverse drug event, hospital-acquired infection, procedural complication, diagnostic or management error), the severity and duration of the event, and whether the event was preventable or ameliorable. The two adjudicators then met to resolve any differences in their findings and come to consensus.
Preventable readmissions: If patients were readmitted to either study hospital, we conducted an evaluation, based on previous studies,23 to determine if and how the readmission could have been prevented including (a) a standardized patient and caregiver interview to identify possible problems with the transitions process and (b) an email questionnaire to the patient’s PCP and the inpatient teams who cared for the patient during the index admission and readmission regarding possible deficiencies with the transitions process. As with adverse event adjudications, two physician adjudicators worked independently to classify the preventability of the readmission and then met to come to consensus. Conflicts were resolved by a third adjudicator.
Analysis Plan
To evaluate the effects of the intervention on the primary outcome, the number of postdischarge adverse events per patient, we used multivariable Poisson regression, with study arm as the main predictor. A similar approach was used to evaluate the number of new or worsening postdischarge signs or symptoms and the number of preventable adverse events per patient. We used an intention-to-treat analysis: If a practice did not start the intervention when they were scheduled to, based on our randomization, we counted all patients in that practice admitted after that point as intervention patients. We adjusted for patient demographics, clinical characteristics, month, inpatient unit, and primary care practice as fixed effects. We clustered by PCP using general linear models. Intervention effects were expressed as both unadjusted and adjusted incidence rate ratios (IRRs). We also conducted a limited number of subgroup analyses, determined a priori, to determine whether the intervention was more effective in certain patient populations; we used interaction terms (intervention × subgroup) to determine the statistical significance of any effect modification.
