Standards of Care

Standards of Care and Regulatory Landscape

The era of "wild west" digital health innovation is ending. The period of 2025-2030 is characterised by strict standardisation, interoperability mandates, and the integration of digital tools into official clinical guidelines. The focus has shifted from whether to use digital tools to how to standardise them for safety and efficacy.

Interoperability: From Volition to Mandate

Data silos have historically been the primary obstacle to connected health. Governments are now intervening to force data fluidity, recognizing that interoperability is a prerequisite for value-based care.

• United States: TEFCA (Trusted Exchange Framework and Common Agreement): TEFCA creates a "network of networks" for health data exchange. By 2025, the onboarding of Qualified Health Information Networks (QHINs) has operationalized a national backbone for data sharing. The goal is to enable a patient's record to follow them seamlessly across the country, regardless of the provider's EHR vendor. By 2030, interoperability will be "table stakes"—providers and vendors who cannot exchange data via standardized APIs (like FHIR) will be commercially non-viable.
• Europe: The European Health Data Space (EHDS): The EHDS represents a more ambitious, centralized approach. Entering force in 2025, with full implementation of primary data use (patient summaries, ePrescriptions) targeted for 2029, the EHDS creates a single market for digital health services. Beyond care delivery, it establishes a massive, unified dataset for secondary research, positioning the EU as a potential superpower in AI-driven health research.

Clinical Guidelines and Standards of Care

Digital tools are graduating from "experimental" status to "Standard of Care." This designation is critical because it mandates provider adoption and payer reimbursement.

• Diabetes Management (ADA 2025 Guidelines): The American Diabetes Association's 2025 Standards of Care mark a massive shift in protocol. Continuous Glucose Monitoring (CGM) is now recommended not just for Type 1 diabetes, but for Type 2 patients on non-insulin therapies. Furthermore, the guidelines recommend starting CGM at the time of diagnosis, cementing technology as a first-line intervention rather than a tool for advanced disease. This change effectively mandates the use of connected sensors for a massive patient population, vastly expanding the market.
• Cardiology (AHA & ESC Guidelines): The American Heart Association (AHA) and European Society of Cardiology (ESC) are integrating RPM into guidelines for Heart Failure management. Evidence indicates that RPM increases the percentage of patients achieving "Guideline-Directed Medical Therapy" (GDMT) goals by over 200% compared to standard care. This clinical validation forces payers to reimburse these technologies, as denying them becomes tantamount to denying the standard of care.

Addressing Alarm Fatigue

With the integration of these devices comes the risk of "alarm fatigue," where clinicians become desensitised to frequent alerts. New standards are emerging to govern alarm management, requiring devices to use AI to filter "noise" and present only actionable intelligence. Studies show that customisable alarm thresholds can significantly reduce false alarms in postoperative care, improving patient safety.

Ethical and Trust Frameworks

As AI takes on clinical roles, ethics becomes a regulatory field. The "black box" nature of deep learning algorithms poses challenges for liability and trust.

• Algorithmic Bias: There is growing scrutiny on the training data of AI models to ensure they do not perpetuate racial or socioeconomic biases. Regulatory bodies are beginning to require "fairness" metrics as part of the validation process for new algorithms.
• Consumer Trust: Surveys in 2025 reveal a "trust gap." While patients trust doctors using AI, they are skeptical of AI acting alone. Maintaining the "human in the loop" is essential for patient acceptance.

Prototyping Process Models

This section requires the development of prototypes to understand how best process models can be presented to healthcare professionals. Access to experts who have knowledge and experience of prototyping tools and system environments is critical to promote communication and develop the best process model. This can only be achieved in its largest and most comprehensive manner by this Action network.

Optimising Clinical Workflows

In the context of Connected Health, Standards of Care will evolve to allow the clinician to make decisions in a context and to communicate better with patients. The forecast indicates that care will be delivered in the best location, by the best person, using the most relevant methods. This means more care in the patient’s home and less waiting time in hospitals. While this offers the advantage of minimising hospitalisations, a potential disadvantage is the need to train staff on new prototyping tools and ensure that remote care standards match the quality of in-person visits.