As industries around the world harness the power of AI and automation, few face as complex a challenge—or as urgent a need for digitization—as American healthcare. Outdated legacy systems and decades of fragmented patient data have left the sector lagging in adoption. The question looms: how can healthcare bridge its widening digital divide?
Harsha Penubadi, a leading authority in cloud infrastructure, has spent his career unravelling this question. After optimizing cloud systems for global tech giants, from leading large-scale cloud migrations at ClearObject Inc. to enhancing technologies for early childhood education at TCC Solutions, he channeled his expertise into genetic testing infrastructure. Today, he shares his insights into healthcare’s digital future and the challenges that must be addressed to achieve it.
Overhauling Healthcare’s Digital Foundations
“It’s rebuilding the house while you’re living in it,” Penubadi says, describing the monumental effort required to modernize healthcare’s digital infrastructure. While other industries—like manufacturing and retail—grapple with similar hurdles, the stakes in medicine are uniquely high: inefficiencies can directly impact patient outcomes.
Penubadi’s success at Myriad Genetics illustrates how modern infrastructure can transform healthcare delivery. Through improvements to their infrastructure, he reduced the time-to-market for their genetic testing applications by 40%, enabling earlier disease detection and faster clinical decisions. Remarkably, these gains were achieved without altering testing procedures—hinting at the untapped potential in healthcare’s digital groundwork.
“Patient journeys are highly standardized, which make them great candidates for machine learning,” Penubadi explains. “But most current systems are a patchwork of outdated platforms and tools. There’s a lot to be gained just by improving what’s under the hood.” Strengthening these foundations, he says, is essential to unlocking the potential of AI.
This principle extends to notoriously inefficient systems like electronic health records, where infrastructure shortcomings can compromise patient safety. Robust infrastructure can lower error rates and enhance data integration—all while laying the groundwork for more ambitious, integrated solutions.
Scale & Resilience for Better Patient Outcomes
“Healthcare has always been a data-intensive industry,” Penubadi observes. “What’s changed is the scale and speed.” Centralizing this data and facilitating rapid retrieval—whether it’s during critical patient care or from long-term archives—is where infrastructure modernization needs the most attention, he continues.
Penubadi’s previous work managing the infrastructure which handled large-scale genetic datasets highlights this balance. At Myriad, he introduced fault-tolerant infrastructure that reduced detection and resolution times by over 35%, preventing service disruptions that could endanger patients.
This scalability is also key to emerging solutions like telemedicine and predictive health analytics, which surged in importance during the COVID-19 pandemic. These technologies promise to expand access to care, but their success hinges on platforms that can manage unpredictable surges in demand without compromising performance or reliability.
AI as a Pillar of Infrastructure
While AI often grabs headlines for its cost-saving potential, Penubadi emphasizes its role as an integral part of the infrastructure itself. “Every efficiency gain we achieve has a ripple effect on patient outcomes,” he explains. From predicting system failures to optimizing critical care backend processes, AI can improve operational reliability while freeing up resources for clinicians.
Cloud-based AI systems, in particular, offer scalability and flexibility, removing the constraints of physical infrastructure. These systems also support public health initiatives, such as smart diagnostic platforms and remote clinical deployments, while generating new opportunities in fields like data science and AI engineering.
On the clinical side, Penubadi points to partnerships like OpenAI’s collaboration with Color Health, which demonstrates the potential of AI in personalizing patient care. Generative AI can help in the development of treatment plans—a crucial advancement in fields like oncology, where individualized care can improve survival rates.
Innovation Meets Responsibility
As automation and AI take center stage, regulatory and ethical considerations grow increasingly important. Federal initiatives, including the Executive Order on Advancing Biotechnology and Biomanufacturing Innovation, reflect the growing need for equitable and secure development. Meanwhile, reports from the Government Accountability Office have long emphasized the importance of transparency and effective oversight in AI-driven healthcare. Penubadi emphasizes that these regulatory frameworks must treat the underlying infrastructure with equal weight.
“Regulation is really an extension of infrastructure,” he explains. “Systems must be designed to safeguard patient data and ensure AI transparency. They directly enable accountability.” By embedding these principles into infrastructure design, Penubadi says, the healthcare industry can build stronger public trust—a critical factor in its digital transformation.
A Networked Future for U.S. Healthcare
The future of American healthcare, according to Penubadi, will largely depend on its ability to embrace modern infrastructure. While he expresses optimism about the road ahead, he emphasizes the importance of building resilient systems that support innovation without compromising safety or reliability.
“The technologies we adopt today will determine what kind of care we can deliver tomorrow,” he says. “If we focus on strengthening the foundation now, we can build a healthcare system that’s prepared for the challenges—and opportunities—that come next.”
Source: Rewiring U.S. Healthcare: The Digital Infrastructure for Tomorrow’s Medicine
