Condition-specific Streaming versus an Acuity-based Model of Cardiovascular Care: A Historically-controlled Quality Improvement Study Evaluating the Association with Early Clinical Events

Background: Ensuring optimal evidence translation is challenging when health-service design has not kept pace with developments in care. Differences in patient outcomes were evident when specific cardiac conditions were discordant with the subspecialty of the cardiologists managing their care. We prospectively explored the clinical and health service implications of a "condition-based" redesign in cardiac care delivery, rather than acuity-based, within a tertiary hospital. Methods: Prospective evaluation of a disease-specific streaming model of care compared to propensity-matched historical controls, among cardiac patients admitted to a tertiary hospital cardiology unit was undertaken. The outcome measures of 30-day death, and readmission for myocardial infarction, cardiac arrhythmia, and heart failure were explored. Results: In total, 2018 patients admitted subsequent to the implementation of the streaming model were compared with 1830 patients admitted prior. The median age was 68.9 years, and 39.5% were female. There was no significant difference in the overall proportion of patients admitted with an acute coronary syndrome, arrthythmia or heart failure, nor their Charlson index before and after streaming. Subsequent to the implementation, there was a reduction in the use of angiography (pre: 35.4% vs. post: 31.2%, p=0.007) and echocardiography (pre: 59.4% vs. post: 55.6%, p=0.007). A reduction in length of length-of-stay was observed in the entire cohort (pre: 2.7 (range: 1.2-5.0) days vs. post: 2.3 (range1.0-4.5) days, p=0.0003). By 30 days, the propensity-adjusted hazard ratio for major adverse cardiac events and death or any cardiovascular admission was 0.76 (95% C.I. 0.59-0.97, p=0.026). Conclusion: Cardiac service redesign that streams cardiac patients by presenting diagnosis into teams designed to treat that condition may provide capacity and productivity gains for health services striving to improve outcome and efficiency.