Standards › ASF Health Standards v10 › Standard 2D
Standard 2D
Digital Care and AI
Digital care and artificial intelligence: how systems are introduced, monitored and made accountable.
Before any digital care system — telehealth platform, remote monitoring tool, patient-facing app — is introduced, the facility assesses its costs and benefits, manages its implementation, and continues to manage it afterwards — not adopted because a vendor made a compelling pitch, with no internal evaluation.
Why it matters. A digital tool introduced into care without a check can slow care down, expose data, or fail when most needed. Assessing a tool before it is used, and managing it afterwards, protects the patient and the service.
What the surveyor checks
- Is a cost/benefit analysis conducted before any digital care system is implemented, not adopted on vendor assurance alone?
- Is interoperability between the new system and existing clinical systems assessed, with risks from non-interoperability mitigated?
- Are potential unintended consequences of introducing the system considered before implementation, not discovered only afterwards?
Documents
E-learning
Planned course: Digital care assessment and management process. New course planned.
References
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
- Accréditation Sans Frontières (2026). ASF Policy Framework v1.2. (E-006)
A process ensures that patients who cannot use digital devices, lack internet access, or are otherwise unable to engage with digital approaches are never disadvantaged by the facility’s use of digital care — not digital convenience for most patients purchased at the cost of access for the patients least able to adapt.
Why it matters. Some patients cannot use a phone app, do not have internet, or find video calls hard. A service that moves everything online without an alternative leaves those patients without care.
What the surveyor checks
- Is there a defined alternative for patients who cannot or do not want to use a digital care approach?
- Was the introduction of a new digital care service pre-tested with representatives of patients who might struggle to use it?
- Is there evidence that a patient unable to use digital care received equivalent, undiminished service through the alternative route?
Documents
E-learning
No course linked yet.
Planned course: Digital inclusion: care that never disadvantages a patient who cannot use digital tools. New course planned.
References
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
- Accréditation Sans Frontières (2026). ASF Policy Framework v1.2. (E-006)
The facility has access to technical expertise — in-house, vendor-provided, or contracted — to support the effective use of its digital care systems, including testing and quality checks before full implementation, not digital systems left running with no technical support behind them.
Why it matters. A digital system that no one can support when it fails leaves staff stuck and patients unseen. Access to technical expertise, in-house or from a vendor, keeps the system working when it matters.
What the surveyor checks
- Does the facility have accessible technical expertise, in-house or contracted, for its digital care systems?
- Were new testing and quality checks performed before full implementation of a digital care system?
- When a digital system issue arises, is there a known route to technical support, not staff left to troubleshoot alone?
Documents
E-learning
No course linked yet.
Planned course: Technical expertise for digital care systems. New course planned.
References
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
- Accréditation Sans Frontières (2026). ASF Policy Framework v1.2. (E-006)
Any artificial intelligence system used to support diagnosis, triage, or care decisions is introduced and managed in accordance with WHO’s Ethics and governance of artificial intelligence for health (2021). No such system is adopted without reference to this standard of responsible use.
Why it matters. Artificial intelligence can help with diagnosis and triage, but it can also make errors that look confident. WHO’s guidance on AI in health asks for safety, transparency and human oversight, and a facility that introduces AI must follow it.
What the surveyor checks
- Is any AI system in clinical use introduced in line with WHO guidance on the ethics and governance of AI for health?
- Where no specific legislation exists, is the AI system’s introduction informed by recognised best-practice guidance, such as WHO’s Ethics and governance of artificial intelligence for health: WHO guidance (2021)?
- Can the facility identify, when asked, the specific guidance basis for how a given AI system is governed?
Documents
E-learning
- Artificial Intelligence in Healthcare Safety (AI-001)
- Artificial Intelligence Systems for Care (TELE-10)
References
- World Health Organization (2021). Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: WHO. Open source (E-011)
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
The facility monitors and evaluates its AI systems — auditing results for over-diagnosis or missed diagnosis, tracking patient complaints related to AI-assisted care, and checking for other unintended consequences — not deploying an AI tool and assuming it works as intended with no ongoing scrutiny.
Why it matters. An AI system can work well at first and then drift, missing diagnoses or over-diagnosing as the patients change. Auditing its results regularly is the only way to notice.
What the surveyor checks
- Is the output of AI-assisted diagnosis or care decisions audited for over-diagnosis or missed diagnosis, not assumed reliable without checking?
- Are patient complaints or concerns related to AI-assisted care tracked and reviewed?
- Can the facility show a recorded case where monitoring identified an issue with an AI system’s performance, and a response followed?
Documents
E-learning
References
- World Health Organization (2021). Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: WHO. Open source (E-011)
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
Staff who will deliver care using a new AI system are consulted before it is introduced, to understand the practical implications and identify training needs — not an AI tool rolled out to clinical staff with no engagement beyond a brief notification that it now exists.
Why it matters. Staff who will use an AI system every day know the practical problems that a manager may not. Consulting them before it is introduced finds those problems early.
What the surveyor checks
- Are staff who will use a new AI system consulted before its introduction, not informed only after the decision is finalised?
- Does this consultation identify practical training needs, which are then addressed before go-live?
- Can staff asked directly describe having been consulted about a recent AI system introduction?
Documents
E-learning
References
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
- World Health Organization (2021). Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: WHO. Open source (E-011)
The facility has considered and documented accountability arrangements for care and treatment delivered with AI support — who is responsible when an AI-assisted decision is wrong — not leaving this as an unexamined question until the first time it matters.
Why it matters. When an AI system contributes to a wrong decision, it is not clear who is responsible: the clinician, the vendor or the facility. A documented accountability arrangement answers that question before there is an incident.
What the surveyor checks
- Is clinical accountability for a decision made with AI support explicitly documented, not left ambiguous between clinician and system?
- Do clinicians using AI-supported tools understand their own accountability for the final care decision?
- Is there a defined process for reviewing accountability when an AI-assisted decision contributes to a safety incident?
Documents
E-learning
References
- World Health Organization (2021). Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: WHO. Open source (E-011)
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
A patient whose care involves an aspect delivered with AI system support is informed of this — not left to assume every decision was made by a human clinician alone, with disclosure treated as optional rather than a standard part of informed care.
Why it matters. A patient who is treated with the help of AI has a right to know. Telling them, rather than leaving them to assume, is part of informed consent and trust.
What the surveyor checks
- Is a patient informed when an aspect of their care involves AI system support?
- Is this disclosure understandable, not buried in technical language or a general consent form a patient never reads?
- Can a patient asked directly confirm they were told AI was involved in an aspect of their care?
Documents
E-learning
References
- World Health Organization (2021). Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: WHO. Open source (E-011)
- Accréditation Sans Frontières (2026). ASF Expert Committee consensus on Standard 1. (E-009)
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