Health tech is a broad term for any technology designed to improve how healthcare is delivered, managed, or experienced. It covers everything from the fitness tracker on your wrist to the AI systems that help radiologists spot cancer in medical scans. The global healthcare IT market was valued at roughly $866 billion in 2025 and is projected to nearly triple by 2033, growing at about 16% per year. That rapid expansion reflects just how deeply technology is reshaping medicine.
Health Tech vs. Medical Tech
The terms “health tech” and “medical tech” overlap, and people sometimes use them interchangeably. But they have slightly different centers of gravity. Medical technology, or medtech, traditionally refers to physical tools, devices, and equipment designed to diagnose, treat, or monitor health conditions. Think surgical robots, pacemakers, MRI machines, and prosthetics.
Health tech leans more toward digital solutions that improve the delivery and management of care. Electronic health records, telehealth platforms, mobile health apps, AI diagnostic tools, and remote monitoring systems all fall under this umbrella. In practice, the two fields blur together constantly. A smartwatch that detects an irregular heart rhythm is both a consumer device and a medical monitoring tool. The distinction matters mostly when you’re trying to understand the industry landscape or career paths within it.
Wearable Devices and Remote Monitoring
Wearable health devices are one of the most visible pieces of health tech. Fitness trackers and smartwatches dominate the space, with the most common measurements being step counts (tracked in about 53% of health research using wearables), heart rate (31%), and sleep duration (29%). But the capabilities are expanding fast. Newer devices can measure blood oxygen levels, skin temperature, respiratory rate, and even blood pressure.
Some wearables have crossed into genuinely clinical territory. The Apple Heart Study demonstrated that a consumer smartwatch could detect atrial fibrillation, a common heart rhythm disorder that often goes undiagnosed. Wearable ECG patches, worn on the chest for days or weeks at a time, can catch irregular rhythms that a brief office visit would miss. Other emerging devices include smart inhalers that track asthma patterns and wearable rings that provide early warnings of heart rhythm problems.
Remote patient monitoring takes this further by connecting patients at home to their care teams. In a study of high-risk patients discharged from the hospital with conditions like heart failure, COPD, and pneumonia, home digital monitoring cut hospitalizations by about 58% over both three and six months. Emergency department visits dropped even more dramatically. This kind of technology is especially valuable for people with chronic conditions who would otherwise cycle in and out of the hospital.
Telehealth and Virtual Care
Telehealth, the ability to see a doctor through video or phone, existed before the pandemic but became mainstream during it. Usage patterns vary widely by specialty. Psychiatrists lead by a wide margin: nearly 86% report conducting video visits in a given week, and more than half use telehealth for over 20% of their appointments. Mental health care translates well to a screen because it relies primarily on conversation rather than physical examination.
Other specialties use telehealth at lower but still significant rates. About 32% of neurologists, 24% of endocrinologists, and 20% of family medicine physicians conduct more than a fifth of their visits virtually. For patients managing ongoing conditions like diabetes or thyroid disorders, virtual check-ins can replace many in-person appointments, saving travel time and making it easier to stay on top of care.
AI in Diagnostics
Artificial intelligence is changing how diseases are detected, particularly in fields like radiology and pathology that involve analyzing large volumes of images. The speed gains are staggering. AI systems have reduced diagnostic time by 95% or more across several types of imaging, including breast cancer detection (nearly 100% time reduction in one study), rib fracture identification (95%), and lung nodule screening (95%). In pathology, AI models cut the time to diagnose gastric cancer by up to 99%.
These tools don’t replace doctors. They flag areas of concern, prioritize urgent cases, and handle the repetitive scanning work that contributes to fatigue. Across multiple validation studies, AI systems matched or exceeded clinician accuracy while processing images in a fraction of the time. The practical effect is that a radiologist who might take several minutes reviewing a scan can receive an AI-generated analysis almost instantly, then spend their time on the cases that genuinely need human judgment.
AI for Clinical Documentation
One of the quieter but potentially most impactful uses of AI in healthcare targets paperwork. Physicians currently spend roughly two hours on documentation for every hour of direct patient care, a major driver of burnout. AI scribes, tools that listen to patient visits and draft clinical notes automatically, aim to reclaim some of that time.
A UCLA study tested AI scribes in clinical settings and found that one tool reduced the average time physicians spent writing each note by about 41 seconds compared to 18 seconds in the control group. That’s a modest per-note savings, but it compounds across dozens of patient encounters each day. The technology is still maturing, with different products showing varying levels of effectiveness, but the direction is clear: offloading documentation so clinicians can focus on patients.
How Health Data Moves Between Systems
One of the biggest challenges in health tech is getting different systems to talk to each other. Your primary care doctor, your specialist, your hospital, and your pharmacy may all use different electronic health record systems that store your information in incompatible formats. A standard called FHIR (Fast Healthcare Interoperability Resources) is designed to solve this. It provides a common language for representing health data, whether that’s medications, lab results, or visit notes, so systems can share information in real time regardless of how they store it internally.
FHIR uses the same web technologies that power everyday internet applications, which makes it relatively easy for developers to build on. The practical benefit for patients is faster, more seamless data sharing. When your cardiologist can instantly pull up the lab results your primary care doctor ordered last week, you avoid redundant tests, conflicting prescriptions, and the frustrating experience of repeating your medical history at every new appointment.
Privacy and Regulation
Health data is among the most sensitive information that exists, and health tech companies operating in the U.S. must comply with HIPAA, the federal law governing electronic health information. HIPAA’s Security Rule requires organizations to assess vulnerabilities in how they store and transmit patient data, implement safeguards against unauthorized access, and encrypt data sent over electronic networks.
Software that performs medical functions faces additional scrutiny. The FDA classifies “Software as a Medical Device,” or SaMD, as any software intended for medical purposes that operates independently of a hardware device. An app that analyzes heart rhythm data to detect atrial fibrillation, for example, would qualify. This means it must meet regulatory standards for safety and effectiveness before reaching patients, similar to a physical medical device. Not all health apps fall under this classification. A simple step counter or meditation timer typically does not. The line depends on whether the software is making or supporting clinical decisions.