Bill Madigan is the Chief Revenue Officer at Komodo Health where he oversees the company’s customer-facing team and shapes business strategy to expand market impact. Madigan brings more than 25 years of experience commercializing software and services in the healthcare and Life Sciences industries. Prior to Komodo, he held leadership roles in Optum’s Life Sciences and provider businesses.

For years, data scientists have predicted that data would transform healthcare. In less than two years, we’ve seen the power of data play out in real-time when researchers developed, tested, and implemented multiple COVID-19 vaccinations with unprecedented speed. With the deployment of vaccine administration on a global scale, we’ve moved on to new clinical trials assessing the efficacy and safety of tests, treatments, and medical devices for both coronavirus variants and other diseases. The enormity of that accomplishment and its implications are profound. 

The scientific advances required to develop the COVID vaccines cannot be understated. But this achievement also speaks to the recent alignment of several key elements that set the foundation for this innovation. One thing is clear: the rapid growth of data-driven insights has become a driving force behind healthcare’s transformation.

The (Data) Stars Have Aligned

• The Reliability of Foundational Data ─ Until recently, researchers and pharmaceutical groups coped with data gaps caused by weaknesses like: an overreliance on singularly sourced data from payers or clearinghouses, a lack of open claims data, bias, and interoperability issues. These gaps lessen the fidelity of our longitudinal views of disease pathways and of real-life patient trajectories, limiting our insight and understanding.
  
  Real-world, near real-time evidence is now the gold standard: Data from multiple sources can be linked, patient journeys are mapped across HCOs and HCPs, and new clinical encounters can be added daily. The vastness, completeness, accuracy, and timeliness of foundational data is enabling healthcare leaders to identify far more opportunities where real-world evidence can reshape and help to optimize results.
  
  
• Enhanced Computing Power and Innovative Software ─ Data and analytics are symbiotic: without one, the other is stymied. Fortunately, as foundational data has evolved, so too has the power and sophistication of artificial intelligence (AI), machine learning (ML), and software. AI and ML require high volumes of complex data — something that legacy healthcare data aggregators couldn’t provide. Innovative functionality and advanced analytics powered by today’s foundational data enables users to obtain the answers they need, whether they’re assessing disease incidence in a specified population, mapping provider treatment patterns, identifying eligible patients for a clinical trial, or evaluating treatment adoption.
  
  
• The Consumerism of Healthcare ─ With the advent of high-deductible health plans and the rising cost of care, consumers are accepting greater responsibility for their healthcare decisions and are more proactive in seeking low-cost, high-quality treatments and providers. Thus, they’re more immersed in the healthcare ecosystem, accessing their medical data on portals via handheld devices and researching treatment options and costs online. Rapid uptake of these consumer-facing tools means we can reach more patients, faster, which can assist with clinical trial recruitment and treatment interventions.
  
  Simultaneously, a host of data-acquiring products are being introduced to consumers — from wearable fitness trackers, to at-home testing, to digital health monitors — and in many instances, the information can be transmitted, processed, and stored, enabling clinicians to retrieve it right away. We anticipate all types of consumer data will soon be used to enrich EMRs, producing greater insights on both consumers themselves as well as their patient journeys.

The Time is Now: Trends in Action 

We are in a new era of exponential, expedited change. We now know what’s possible when it comes to therapeutic development and clinical trials, and we’re questioning what this means for the future of healthcare.

As stakeholders embrace the power of data to inform decision making, we’re likely to see greater efficiency in all aspects of care. Provider organizations and patient-advocacy groups can use data to identify gaps in care that lead to poor outcomes, then work to close those gaps. Payers can leverage data to assess members’ preventive care behavior and partner with targeted providers to drive improvements. Pharma, biotech, and medtech organizations can identify key medical influencers for collaboration on initiatives. These examples barely scrape the surface of what’s possible as we move into the next stage of healthcare’s transformation.  

To learn more about how data insights can help reduce the burden of disease, read To Prevent a Post-Pandemic Surge in Chronic Disease, We Need Big Data Analytics — And Unprecedented Cooperation.

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