The question in healthcare AI is no longer whether the technology works; it’s whether it delivers. Health systems, under mounting pressure from labor shortages, reimbursement reform, and rising patient expectations, are asking for more than pilots and proofs of concept. They want measurable returns: hours reclaimed, throughput improved, errors reduced. And they want it not in theory, but on the floor.
The shift from innovation as promise to innovation as performance has recentered the conversation around operations. Not the flash of a product demo, but the rigor of execution: how tools are configured, how clinicians adopt them, and how systems scale.
Few figures in health tech embody that operational mindset more than Pritesh Patel, Chief Operating Officer of Andor Health. Since joining the company in 2018, Patel has led the complex work of translating Andor’s AI infrastructure, most notably the ThinkAndor® platform, into repeatable value for hospitals under strain.
In the current market, that value is not judged on features. It’s judged on outcomes.
After several volatile funding cycles, digital health investment has started to stabilize, with capital increasingly directed toward technologies that demonstrate measurable performance and financial return. Across the sector, there is growing interest in AI solutions that reduce administrative burden, enhance care coordination, and improve clinician well-being. Categories such as ambient documentation, care team orchestration, and virtual nursing have gained attention not for their novelty but for their ability to translate automation into tangible time savings and higher provider satisfaction. However, none of that matters if the technology doesn’t scale.
That’s where Patel’s focus lies: not on AI as a tool, but on AI as a system. In his view, real ROI begins when ambient orchestration, documentation, and observation agents are embedded within clinical workflows, not merely layered on top of them. That means mapping capabilities not just to departments, but to roles and resources. It means integration with EHRs, along with staffing systems, telehealth infrastructure, and in some cases, physical layout.
This approach is highly operational and deeply contextual. It is also paradigmatic of the way ThinkAndor® has been deployed across health systems like Orlando Health, the Medical University of South Carolina (MUSC), and more.
Here, Patel and his team have helped implement AI-driven workflows with published results that reduce Left Without Being Seen (LWBS) percentages, improve door-to-disposition times, and coordinate bedside and virtual staff through real-time orchestration. It’s not just the technology that enables this, but the implementation model: configuration by service line, detailed change management, and what Patel describes as “deployment by function, not feature.”
“The question is no longer whether AI can work in healthcare, but whether it can scale to deliver measurable results. ROI is not achieved in proofs of concept, but in reclaiming hours for nurses, reducing delays for patients, and aligning clinical workflows to operate more efficiently. AI must move from being a tool to being an operational system—and that’s where the true value emerges,” explained Patel.
This perspective also informs Andor’s internal metrics. The company doesn’t just track how many notes are generated or how many encounters are recorded ambiently. It tracks what that documentation translates into: how many nursing hours are reclaimed per shift, how many tasks are resolved without escalation, and how often care teams can respond in parallel instead of in sequence.
In a previous Benzinga feature, Patel described ThinkAndor®’s ambient and orchestration agents as a “scalable ROI engine,” but one that only works when each site’s workflows are fully mapped and tailored. He emphasized the importance of human-in-the-loop oversight, EHR-native interface embedding, and the ability to evolve deployment strategy as health system needs change.
Before joining Andor, Patel served as a general partner at Stratecore Bioventures and led clinical-business optimization efforts through his consulting firm, Aventive Healthcare. That dual fluency in clinical systems and business performance now underpins his work at Andor: architecting go-to-market strategies that prioritize scale, alignment, and margin-positive delivery.
The result is a platform that doesn’t ask health systems to trust in potential. It invites them to measure performance.
In a market where most AI deployments still struggle to get beyond the pilot phase, Patel’s team has pushed Andor into the realm of scaled adoption: enabled by careful segmentation, agile rollout sequencing, and ROI reporting designed for both clinical and financial stakeholders.
This is not the language of hype. It’s the language of healthcare operations: patient throughput, task latency, staffing ratios, revenue cycle impact. In 2025, it may be the only language that matters.
