Digital health is a broad term covering any technology that uses computing platforms, connectivity, software, or sensors to deliver or improve health care. It spans everything from the fitness tracker on your wrist to the artificial intelligence software that helps a radiologist spot cancer on a chest X-ray. The field includes mobile health apps, telehealth, wearable devices, electronic health records, personalized medicine, and AI-powered diagnostics. Valued at roughly $289 billion globally in 2024 and projected to reach $946 billion by 2030, digital health is reshaping how care is delivered, monitored, and paid for.
What Digital Health Actually Covers
The FDA groups digital health into several overlapping categories: mobile health (mHealth), health information technology, wearable devices, telehealth and telemedicine, and personalized medicine. Within those categories, the agency regulates specific areas like software classified as a medical device, AI and machine learning in diagnostic tools, cybersecurity for connected devices, and wireless medical equipment.
What ties all of it together is the shift from care that happens only inside a clinic to care that follows you home, tracks your health in the background, and surfaces problems before they become emergencies. A blood pressure cuff that sends readings to your cardiologist, a therapy app that walks you through cognitive behavioral exercises, a smartwatch that detects an irregular heart rhythm: these are all digital health in practice.
Mobile Health Apps
Your phone is probably the most common digital health tool you already use. Mobile health apps range from simple step counters to clinically designed tools for managing chronic conditions. Diabetes management apps, for example, can track blood sugar, send medication reminders, provide dietary feedback, and offer motivational support. Apps for PTSD help users log episodes and triggers, access relaxation exercises, and learn about their condition through built-in educational content.
Some apps go further. DynamiCare, designed for substance use recovery, includes a virtual recovery coach, appointment reminders, at-home substance testing, and a reward system rooted in behavioral therapy principles. These aren’t just wellness trackers. They function as lightweight clinical tools that extend the reach of a treatment plan between appointments.
Telehealth’s Rapid Expansion
Telehealth existed before 2020, but the pandemic turned it from a niche convenience into a default mode of care. Among U.S. physicians, telemedicine use jumped from 15.4% in 2019 to 86.5% in 2021, according to CDC data. That surge has settled into a new normal where video and phone visits are a routine option for many types of care.
Usage patterns vary by specialty. About 27% of medical specialists (think cardiologists, endocrinologists, psychiatrists) used telemedicine for at least half their patient visits, compared with roughly 15% of primary care physicians and an even smaller share of surgical specialists. That makes sense: a psychiatry follow-up translates well to video, while a surgeon often needs hands-on examination. For patients, the practical benefit is fewer trips to the office for straightforward check-ins, prescription renewals, and follow-up conversations.
Remote Patient Monitoring
Remote patient monitoring, or RPM, uses connected devices to track a patient’s health data at home and send it to their care team. It’s used for a wide range of conditions: COPD, heart failure, diabetes, cancer recovery, kidney dialysis, and post-surgical rehabilitation, among others.
The evidence on RPM’s impact is strongest in two areas. First, it improves adherence. In one study, COPD patients who were monitored remotely stuck more consistently to prescribed exercise routines than those managed through standard visits alone. Second, it reduces hospitalizations and shortens stays. Heart failure patients monitored with smartphone apps showed better functional status and higher satisfaction with their care. Patients with cardiac devices experienced shorter delays between a detected event and a clinical decision when monitored remotely. Across multiple studies, RPM was linked to fewer hospital admissions, shorter lengths of stay, and lower non-hospitalization costs.
The picture is more mixed for mental health symptoms and overall quality of life, where RPM hasn’t shown consistent improvements. But for keeping people out of the hospital and catching problems early, the technology delivers measurable results.
AI in Diagnostics
Artificial intelligence in health care works less like a thinking doctor and more like an extremely fast pattern-recognition engine trained on massive datasets. Its most mature application is medical imaging. Between 2015 and 2020, more than half of all AI-based medical devices approved in both the U.S. and Europe were designed for radiology.
In studies, AI systems have matched or outperformed human experts in several areas: detecting pneumonia on chest X-rays, classifying skin lesions in dermatology, identifying breast cancer metastases in pathology slides, and diagnosing heart attacks from cardiac imaging. One FDA-approved AI system for diabetic retinopathy screening achieved 87% sensitivity and 90% specificity for detecting vision-threatening disease, a meaningful tool given that there aren’t enough eye care specialists worldwide to screen every person with diabetes.
These systems don’t replace physicians. They handle high-volume, repetitive image analysis so clinicians can focus on complex cases and treatment decisions. For patients, AI mostly works in the background, speeding up the time between a scan and a result.
How Health Data Gets Shared
For digital health tools to work together, they need a common language for exchanging patient data. The current standard gaining the most traction is called FHIR (Fast Healthcare Interoperability Resources). Developed starting in 2011 and built on modern web technology, FHIR breaks health information into small, standardized building blocks called “resources,” each representing a common concept like a patient, a lab result, a practitioner, or a condition.
What makes FHIR different from older health data standards is that it works the way modern apps and websites do, using web-based interfaces that let different systems request and share specific pieces of data rather than transferring entire medical records at once. This is what allows, for example, a blood glucose monitor to send a reading directly into your electronic health record, or a hospital to share your discharge summary with your primary care doctor’s system automatically.
Privacy Gaps to Know About
Health data privacy in digital health is more complicated than most people realize. If your doctor’s office or hospital shares your records through a system it controls, that data is protected under HIPAA. But once you voluntarily direct your health information to a third-party app that isn’t working on behalf of your health care provider, HIPAA protections no longer apply to that data.
This means the meditation app tracking your mood, the fertility tracker logging your cycle, or the fitness platform storing your heart rate data may not be bound by the same rules as your doctor’s office. Your provider can’t refuse to share your records with an app you’ve chosen just because that app doesn’t encrypt data or might use it for research. The responsibility for vetting an app’s privacy practices falls largely on you. Reading an app’s privacy policy, checking whether it sells or shares data with third parties, and understanding what happens to your information if the company is acquired or shut down are all worth doing before you hand over sensitive health details.
Who Gets Left Out
Digital health tools only work for people who can access them, and access is far from universal. In a study of underserved communities in the southeastern U.S., 53% of respondents cited time and 51% cited cost as barriers to using digital health technology. Lack of reliable internet or broadband was a consistent problem, particularly for Black, Hispanic, and rural households. Nearly half of Americans without home internet access belonged to Black and Hispanic households.
The barriers compound each other. Language limitations make apps designed only in English unusable for many patients. Clinicians in small practices and rural settings face high costs to purchase, integrate, and train staff on new technology. Poor connectivity makes video visits unreliable in the areas that would benefit most from remote care. And while reimbursement for digital health services has expanded, cost remains one of the top obstacles for both patients and providers. Without deliberate investment in infrastructure and affordability, digital health risks widening the same gaps it has the potential to close.