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Standardising practice in cardiology: reducing clinical variation and cost at Ochsner Health System
Phil Oravetz1, Christopher J White1, David Carmouche1
1Ochsner Health System, New Orleans, Louisiana, USA.
Insights
Utilizing simulated patient cases to provide cardiology feedback significantly improved care quality and reduced costs. This approach lowered practice variation and saved $4.34 million annually without impacting patient outcomes.
Area of Science:
- Cardiology
- Health Economics
- Medical Education
Background:
- Unwarranted clinical variation leads to poor patient outcomes and increased healthcare expenses.
- Developing effective strategies to enhance clinical quality and economic value in cardiology has been challenging.
- Ochsner Health System aimed to improve cardiology care quality and reduce costs through active measurement and tailored feedback.
Purpose of the Study:
- To assess the impact of serial measurement and individualized feedback using simulated cardiology cases on clinical practice.
- To evaluate changes in quality of care, practice variation, patient outcomes, and costs within a cardiology department.
Main Methods:
- Fifty cardiologists participated in six rounds of assessments over 16 months, managing simulated patients with conditions like heart failure, coronary artery disease, and supraventricular tachyarrhythmia.
- Online simulated cases were used to capture clinical decision-making, providing individualized feedback to participants.
- Real-world pre-post analyses of physician practice changes, patient outcomes, and costs were conducted using Ochsner's patient-level data.
Main Results:
- Simulated quality-of-care scores improved by 14.1% (p<0.001) from baseline to the final round.
- Cost-of-care variation decreased, with significant reductions in per-patient direct costs for supraventricular tachyarrhythmia ($493) and heart failure ($305).
- Readmission rates significantly decreased for heart failure (20.0% to 11.9%) and supraventricular tachyarrhythmia (14.5% to 7.8%), contributing to an estimated annual savings of $4.34 million.
Conclusions:
- Serial measurement and individualized feedback via simulated patients effectively enhance clinical quality in cardiology.
- This intervention demonstrably reduces practice variation and healthcare costs without adversely affecting patient outcomes.
- The findings support the use of simulated patient scenarios as a valuable tool for continuous quality improvement in medical practice.
Objective:
Low quality and unwarranted clinical variation harm patients and increase unnecessary costs. Effective approaches to improve clinical and economic value have been difficult. The Ochsner Health System looked to improve clinical care quality and reduce unnecessary costs in cardiology using active measurement and customised feedback.
Methods:
We serially measured care decisions using online, simulated cases to capture clinical details of cardiology practice and provide individual feedback. Fifty cardiologists cared for two simulated patients in each of six assessment rounds occurring 4 months apart. Simulated patients presented with heart failure (HF), coronary artery disease (CAD), supraventricular tachyarrhythmia (SVT) or valvular heart disease. Using Ochsner's patient-level data, we performed real-world pre-post analyses of physician practice changes, patient outcomes and costs.
Results:
Between baseline and final rounds, overall simulated quality-of-care scores improved 14.1% (p<0.001). In the same period, we found cost-of-care variation decreased in patient-level data, with larger decreases for more severely ill patients. The total per-patient direct costs decreased $493 in SVT, $305 in HF and $55 in CAD (p<0.05 for SVT and HF). Readmission rates fell significantly for HF (from 20.0% to 11.9%) and SVT (from 14.5% to 7.8%) (both p<0.001) and non-significantly for CAD (from 13.7% to 11.3%, p=0.112). The cost avoidance/revenue generation opportunity from reduced readmissions and direct costs amounted to annual savings of $4.34 million, with no significant changes to in-hospital mortality rates (p>0.05).
Conclusions:
Using simulated patients to serially measure and provide individual feedback on clinical practice significantly raises quality and reduces practice variation and costs without negatively impacting outcomes.
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