The fall and winter months present the healthcare system with a unique challenge: the simultaneous outbreak of influenza, Covid-19, and respiratory syncytial virus (RSV), a “tripledemic” that dominated last year’s headlines. Now, as healthcare organizations prepare for a potential repeat this season, it’s imperative to employ innovative solutions to navigate a complex predicament effectively. In the face of the unknown, data can be a potent tool for an organization to weather sudden surges of illness.
The pandemic taught us that data analytics are instrumental in helping healthcare organizations manage an increase in patient volume. During an event like a tripledemic, when the demands and patient load are high, such tools enable clinical and operational staff to quickly surface information and make decisions that save precious time and resources.
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Here’s how. When hospitals are inundated with acutely sick patients, data can help overwhelmed staff and providers allocate resources and care more efficiently. For example, stratification tools can group patients based on risk, enabling healthcare organizations to divert patients to the most appropriate site of care.
In practice, organizations can prioritize in-patient care for the sickest and most vulnerable patients who require immediate attention. At the same time, healthcare organizations can use outreach tools to proactively alert less critical patients to screening tools, outpatient clinics, and telehealth services. With this example, you can see how a high-quality data asset paired with effective patient engagement tools can make all the difference to alleviate pressure on overwhelmed systems and keep emergency departments less crowded.
Data analytics can also take the pressure off providers. Instead of parsing through dense medical records to search for comorbidities or relevant histories, technology can surface curated insights within existing workflows at the point of care. Consequently, providers can make faster, more informed decisions about an ideal course of treatment or next step.
Critically, data analytics is more than a response tool—it can help organizations achieve better outcomes before, during, and after a major public health event by serving as a window into who’s received regular, routine care (and who hasn’t). For example, a person might enter the healthcare system at a moment of acute need but require additional care once they’re discharged. Providers can identify needs like an annual wellness visit or cancer screening during an acute episode of care, then use transitional care management tools to continue outreach and work to address a patient’s health needs long after an acute episode has passed. Data analytics can help care teams prioritize these needs and track progress to deliver care needed to improve a patient’s outcome.
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The continuous collection and analysis of data also provides invaluable insights into population health needs. By curating historical and real-time data from multiple sources (like EHRs, census data, and claims), healthcare organizations can proactively identify high-risk groups, monitor ongoing disease trends, and assess the efficacy of programs like vaccination campaigns.
The adage “an ounce of prevention is worth a pound of cure” proves especially true with excellent data. When it’s wielded strategically, data can pinpoint opportunities to prevent patient bottlenecks, or streamline processes so that organizations can adapt to unforeseen circumstances. Longitudinal population health information can also help decision-makers use a limited budget toward the greatest good, and it can provide a clear picture of performance, whether that’s a particular campaign or the historic success rate of a certain intervention.
Investing in data infrastructure and analytics capabilities enables healthcare organizations to build resilience within their systems, ensuring readiness not only for an onslaught of seasonal illnesses but also for any future health challenges that may arise. It empowers institutions to prioritize patient care, allocate resources effectively, plan for the future, and maintain and improve population health. Embracing data analytics is an investment in the well-being of our communities and the long-term success of healthcare institutions, charting a course toward a more resilient, results-driven healthcare system.
Photo: metamorworks, Getty Images
Kate Behan, MD, FACP, is the Chief Medical Officer at Arcadia, a leading data analytics platform for healthcare, where she applies a clinical perspective to the design and implementation of strategies that enable healthcare organizations to succeed in value-based care. In addition to serving as a strategic advisor to physician leaders at Arcadia’s clients, she provides clinical input into the development of Arcadia’s technology and service programs.
Dr. Behan has more than two decades of healthcare experience in both clinical and administrative leadership roles at academic, large health system, and payer organizations. She received her bachelor’s degree from Providence College and her medical degree from MCP Hahnemann School of Medicine. She’s also certified by the American Board of Internal Medicine, a fellow of the American College of Physicians, and a member of the Pennsylvania State Medical Society.
