The software used daily by doctors, surgeons, and other healthcare professionals has recently integrated technological components that profoundly change the management of consultations, patient follow-up, and the production of medical documents. Between the generative AI tools embedded in business software, European regulatory constraints, and specialized telemedicine platforms, the landscape of digital health solutions is being restructured.
Embedded generative AI in business software: what the embedded component changes
The most recent movement in digital health tools does not come from standalone applications, but from the direct integration of generative AI into practice management software and electronic patient records (EPRs). Since 2024, several French publishers have been testing or deploying features to assist in writing letters, structured reports, and CCAM/ICD-10 coding suggestions.
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The High Authority of Health (HAS) published a guidance report in 2024 on the use of generative AIs in health. The central point: the professional must remain “in the loop” at every stage, and the uses must be traceable. This framework clearly distinguishes French solutions from public AI assistants that operate without clinical supervision.
For professionals looking to evaluate these tools, it is possible to find more information on Zone Santé, particularly about platforms and digital services suited for online medical practice.
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In practical terms, the AI embedded in business software does not replace the practitioner. It accelerates the entry of structured data and reduces the time spent on administrative tasks, freeing up time for care. The nuance is technical but decisive: an AI integrated into the EPR accesses the patient context, whereas an external tool works from partial or anonymized data.
European Regulation AI Act and digital health solutions
The adoption of the AI Act by the European Parliament in 2024 introduces a classification of AI systems according to their risk level. Tools used for diagnosis, clinical decision support, or patient prioritization fall into the “high risk” category.
The resulting obligations are precise:
- Documented management of risks related to the algorithm’s operation, with complete traceability of AI-assisted decisions
- Requirements on the quality of training data to limit biases that may affect certain patient profiles
- Technical documentation accessible to regulatory authorities and user establishments
- Enhanced human oversight, meaning the possibility for the doctor or surgeon to correct or reject any automated suggestion
These rules will gradually apply to digital solutions used by online healthcare professionals. Few resources aimed at practitioners currently detail these constraints, even though they will condition the choice of platforms in the coming months.
Comparison of digital approaches for healthcare professionals
The available solutions do not all meet the same needs. The table below contrasts three categories of tools based on operational criteria.
| Criterion | Embedded generative AI in EPR | Telemedicine platform | e-health label (ANS) |
|---|---|---|---|
| Main function | Assistance in writing, coding, reports | Remote consultation, patient follow-up | Certification of functional compliance |
| AI Act compliance | Classified as “high risk” if decision support is provided | Variable depending on embedded functions | Specific requirements of the ANS framework |
| Practitioner supervision | Mandatory (HAS 2024) | Direct during the consultation | Not applicable (publisher criterion) |
| Access to patient context | Complete (EPR data) | Partial (data provided by the patient) | Depends on the labeled software |
| Covered specialties | General practitioners and specialties (surgery, oncology) | Mainly general medicine, dermatology, psychiatry | All specialties according to the publisher |
The most significant gap concerns access to patient context. A telemedicine platform only has the data provided by the patient at the time of the consultation, whereas a tool integrated into the EPR utilizes the complete medical history. For specialties like surgery or oncology, this difference affects the reliability of automated suggestions.
e-health label from ANS: a filter, not a guarantee
The Digital Health Agency (ANS) offers a two-tier labeling system (standard and advanced) that certifies a software’s compliance with a set of functional requirements. This label verifies the adequacy to the needs of professionals and data security.
However, the ANS label does not cover generative AI functions. A software can be labeled for its management of patient records while integrating an AI component not yet evaluated by this framework. Professionals must therefore cross-reference two analysis grids: the ANS labeling for traditional functions and the AI Act compliance for artificial intelligence modules.
Telemedicine and digital patient support: the blind spots
Telemedicine platforms have widely deployed in recent years, but their use remains concentrated in a few specialties. The majority of teleconsultations concern general medicine and mental health. Disciplines like surgery or oncology remain sidelined due to a lack of solutions suitable for remote clinical examination.
Digital patient support is progressing through another channel: applications for post-operative follow-up and management of chronic treatments. These tools collect data between two consultations (vital signs, quality of life questionnaires, symptom reporting) and transmit them to the treating physician or specialist.
The real challenge remains interoperability between these tools and the practitioner’s EPR. Without a smooth connection, the data collected by the patient remains in a silo, and the doctor must re-enter it manually, negating the expected time savings.
The decisive criterion for a healthcare professional evaluating these digital solutions is neither the price nor the interface, but the tool’s ability to integrate into their existing workflow. A high-performing software that is isolated from the care chain creates more friction than it removes.