Phoenix Children’s Health System achieved remarkable success by leveraging its homegrown data warehouse and innovative apps to enhance patient care. These apps, supported by over 50 custom-built clinical dashboards, have revolutionized care coordination across various healthcare domains. Notably, the WATCHER program proactively identifies high-risk cases, leading to zero preventable code events. The Malnutrition App, Cleft Palate App, and Leukemia Home Monitoring App have also yielded substantial improvements. Dr. Vinay Vaidya advises others to embark on their data analytics journey, emphasizing actionable insights and patient-generated data from remote monitoring.
In a remarkable success story, Phoenix Children’s Health System has harnessed the power of its homegrown data warehouse and innovative apps to revolutionize patient care. One of the standout achievements is an app that identifies more than 10 potential malnutrition cases each week, leading to prompt referrals to nutritionists.
Over the past decade, the healthcare industry has witnessed a massive shift toward electronic health records (EHRs). However, while EHRs promised improved clinical care and patient outcomes, they often resulted in additional documentation burdens, contributing to provider burnout.
Dr. Vinay Vaidya, Chief Medical Information Officer at Phoenix Children’s, noted, “The initial promise of EHRs didn’t materialize, and we lost sight of their potential. Instead of enhancing efficiencies, they became a focus of optimization, overshadowing their original purpose.”
Phoenix Children’s took a balanced approach, shifting the focus towards meaningful clinical outcomes and utilizing EHR data. The goal was to empower clinicians with actionable insights, giving back valuable time spent on data entry.
The health system’s robust, internally developed data warehouse, powered by Microsoft technologies, played a pivotal role in their transformation. Real-time data from various electronic systems within the organization contributed to the warehouse’s wealth of interconnected data.
Recognizing that data alone was not the solution, Phoenix Children’s established a close collaboration between its data team and clinicians to create clinically intuitive dashboards. These dashboards became indispensable tools for care coordination and improved patient outcomes.
The journey began with a dashboard for chronic disease management, which rapidly gained widespread adoption. Today, Phoenix Children’s boasts over 50 custom-built clinical dashboards, spanning various domains, from ambulatory care to intensive care units.
During the COVID-19 pandemic, these dashboards played a crucial role in addressing the backlog of delayed surgeries. They continue to support complex cases, including epilepsy, scoliosis surgery, chemotherapy oversight, fetal care, and more.
One of the standout successes is the WATCHER program, which proactively identifies children needing elevated care levels, resulting in zero preventable code events. The Malnutrition App consistently identifies patients with potential malnutrition, with a high rate of confirmed diagnoses. The Cleft Palate App reduced in-person visits and lowered the incidence of malnutrition. The Leukemia Home Monitoring App reduced hospitalization days during the first month since diagnosis.
These apps and dashboards, powered by the robust data warehouse and Microsoft’s Power BI, have become integral to clinical workflows, with various stakeholders incorporating them into their daily routines.
Phoenix Children’s emphasizes the importance of integrated metrics within these solutions. Metrics not only provide objective measurements but also guide actions, enhancing quality and safety.
Dr. Vaidya’s advice to other healthcare organizations is to start the data analytics journey without waiting for perfect data, focusing on actionable insights that drive meaningful outcomes. He encourages organizations to tap into patient-generated data from remote monitoring and to consider custom solutions for analytics.
Ultimately, the transformation towards AI and machine learning in healthcare should be guided by a thoughtful strategy, with an acknowledgment that it’s a journey that requires time and investment. Traditional business intelligence projects still hold tremendous value alongside predictive analytics efforts.
