Artificial intelligence (AI) is rapidly reshaping remote care management programs like remote patient monitoring (RPM), chronic care management (CCM), and advanced primary care management (APCM). The use of AI is enabling smarter triage, earlier intervention, and more personalized care. But with implementation of AI solutions comes the need for providers to take a thoughtful approach to the evolving ethical, privacy, and regulatory considerations that shape remote care today.
Balancing Innovation With Patient Privacy
AI-enabled remote care systems require data to function properly. That means feeding algorithms streams of physiological readings, patient-reported outcomes, behavioral patterns, and sometimes even information from wearables or third-party sources. Such a wealth of information makes care more timely, personalized, and proactive. At the same time, it raises critical questions around the likes of HIPAA compliance, informed consent, and data security.
It’s not enough to comply with requirements during the initial deployment of AI technologies. Providers must ensure their AI-enabled platforms safeguard patient information throughout the system’s lifecycle. That means working with remote care software vendors who are clear about how data is collected, stored, and used, and making sure patients know how their data supports their care. Trust in AI starts with trust in how data is handled.
Building Trust Through Transparency and Explainability
For clinicians to trust AI, the system must be able to explain itself. That is where “explainable AI” makes the difference. Explainable AI gives care teams visibility into the “why” behind each recommendation, whether it is flagging a patient for escalation, suggesting a medication review, or identifying early signs of risk.
When AI shows the data it used and the patterns it recognized, providers feel more confident incorporating those insights into patient care. Without this level of clarity, platforms risk falling into the “black box” trap, producing alerts that no one fully understands and therefore no one trusts.
As I recently discussed with Healthcare IT News, a black-box model that simply labels a patient “high risk” should never be acceptable. Clinicians need to see which trends triggered the alert and understand how the algorithm reached that conclusion. Without transparency and explainability, AI tools will struggle to provide clear, trusted clinical value.
Regulators are paying attention here as well. The FDA has stressed that transparency and explainability are essential for AI used in clinical decision support. Providers should seek platforms that clearly surface the inputs and reasoning behind each recommendation.
Maintaining Clinical Oversight
AI should be viewed as decision support, not decision-making. It can process data at a scale no human could, but it cannot replace the clinical judgment of providers who know a patient’s history, values, and goals.
That is why human-in-the-loop oversight is essential. Clinicians must be able to validate or override AI recommendations, ensuring accountability and protecting care quality. This oversight also provides documentation that can help mitigate liability in the event of an adverse outcome.
As I discussed in a column for Healthcare IT Today covering AI in RPM, every system needs to maintain clear human oversight, with clinicians holding ultimate responsibility for validating information before acting on it. This approach ensures that AI strengthens care delivery without undermining the clinical judgment that patients rely on.
Adapting to a Shifting Regulatory Landscape
The regulatory framework for AI in remote care is still evolving. The FDA’s Software as a Medical Device (SaMD) guidance provides rules for AI tools that directly influence diagnosis or treatment. At the same time, state-level privacy laws, such as California’s Consumer Privacy Act (CCPA), are shaping how health data is processed and secured by AI platforms.
These laws, combined with the OIG’s increased auditing of RPM programs in 2025, mean that providers need to choose partners committed to staying abreast of and compliant with regulatory changes. As stated earlier, compliance in AI is not a one-time box to check; it is an ongoing responsibility.
Looking for an AI-Enabled Remote Care Platform Built for Privacy and Trust?
By prioritizing privacy, transparency, clinical oversight, and regulatory readiness, healthcare organizations can harness AI in remote care responsibly — and implementing the right platform backed by AI and remote care experts makes that possible.
Curious how Prevounce Health’s AI-powered technology will help you stay compliant while innovating? Book a demo with one of our experts to learn how our solutions align with today’s ethical and regulatory standards.