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Condition-specific Streaming versus an Acuity-based Model of Cardiovascular Care: A Historically-controlled Quality
Derek P Chew1, Matthew Horsfall2, Andrew D McGavigan3
1School of Medicine, Flinders University of South Australia, Adelaide, SA, Australia; Department of Cardiovascular Medicine, Southern Adelaide Local Health Network, Adelaide, SA, Australia; Health Systems Research, South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
Insights
Redesigning cardiac care by streaming patients based on their condition, rather than acuity, improved patient outcomes and reduced hospital stays. This condition-based approach enhances efficiency and productivity in cardiac services.
Area of Science:
- Cardiology
- Health Services Research
- Clinical Redesign
Background:
- Health service design often lags behind medical advancements, impacting evidence translation.
- Discordant patient outcomes were observed when cardiac conditions did not align with cardiologist subspecialty.
- A prospective study explored a condition-based redesign of cardiac care in a tertiary hospital.
Purpose of the Study:
- To evaluate the clinical and health service implications of a condition-based cardiac care delivery model.
- To compare patient outcomes under a disease-specific streaming model versus historical controls.
- To assess the impact of service redesign on efficiency and patient results.
Main Methods:
- Prospective evaluation of a disease-specific streaming model in a tertiary hospital cardiology unit.
- Comparison with propensity-matched historical control patients.
- Outcome measures included 30-day death and readmission for myocardial infarction, cardiac arrhythmia, and heart failure.
Main Results:
- A total of 2018 patients were admitted post-implementation versus 1830 prior, with no significant difference in admission diagnoses or severity (Charlson index).
- Reduced use of angiography and echocardiography was noted post-implementation.
- A significant reduction in length of stay was observed (2.7 to 2.3 days).
- Propensity-adjusted analysis showed a reduced hazard ratio for major adverse cardiac events and death or cardiovascular admission (0.76, p=0.026).
Conclusions:
- Cardiac service redesign, streaming patients by presenting diagnosis into condition-specific teams, can improve outcomes and efficiency.
- This model offers potential capacity and productivity gains for healthcare services.
- Condition-based streaming is a viable strategy for optimizing cardiac care delivery.
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 (range 1.0-4.5) 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.
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