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Clinical decision support (CDS) and predictive AI are not mutually exclusive product categories. CDS describes a software function that helps inform care decisions; predictive AI describes a way of producing outputs from data. A predictive model can be part of a CDS function, so hospitals should compare each function’s intended use, evidence, workflow, clinician oversight, regulatory status, and ongoing governance—not rely on a product’s “AI” or “CDS” label. FDA’s FAQ explains how predictive decision support interventions and CDS relate, while its policy navigator describes the criteria relevant to certain non-device CDS functions.
What the two terms mean—and why they overlap
CDS is a role a software function performs in care. The U.S. Food and Drug Administration (FDA) defines it as software that provides health professionals and patients with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care. A clinical guideline surfaced in a patient’s chart is one kind of decision support; so is a model-generated risk estimate presented to a clinician.
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Predictive AI describes a modeling approach, not necessarily a particular place in the workflow or regulatory category. FDA’s FAQ quotes the Office of the National Coordinator for Health Information Technology’s definition of predictive decision support interventions (DSIs): technology using algorithms or models derived from training or example data to produce outputs such as predictions, classifications, recommendations, evaluations, or analyses. Some predictive DSIs may be medical devices under the Federal Food, Drug, and Cosmetic Act; others may not. The terms therefore answer different questions: what the software does for a care decision, and how it generates an output.
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What hospitals should compare
Use the following questions for each proposed function and intended use. The framework applies whether the output comes from a predictive model, a rules-based system, or another method.
| Comparison area | Questions to ask | Why it matters |
|---|---|---|
| Intended use and users | Which clinical decision is supported? Who is the intended user, and which patient population and care setting are in scope? | The purpose, user, and population inform both clinical fit and regulatory assessment. FDA recommends making them clear in the software or labeling. FDA policy navigator |
| Inputs and data quality | Which patient information is required? How is it collected and refreshed? How does the function handle missing, stale, or out-of-range inputs? | An output is only interpretable in light of the information used to produce it. FDA recommends describing relevant inputs, collection instructions, and data-quality needs. FDA policy navigator |
| Output and actionability | Does the function retrieve context, show evidence or options, calculate a score, issue an alert, or direct a specific action? | Output type is relevant to FDA’s analysis of certain non-device CDS criteria. A score or specific directive is not equivalent to a reference or a recommendation that a clinician can independently assess. FDA policy navigator |
| Urgency and workflow | Where will the output appear, how quickly must a clinician act, and how much time is available to inspect its basis? | Time pressure affects whether independent review is practical. FDA says time-critical decision-support functions generally cannot satisfy all the criteria for non-device CDS, though contextual retrieval of patient information in an emergency department may still qualify. FDA FAQ |
| Evidence and local applicability | What data and methods were used for development and validation? What clinical validation results are available? Do the study population, setting, and intended use fit the hospital’s own? | Validation results need to be interpreted against the population and setting in which the hospital plans to use the function. Local fit is a procurement question, not something established by a general product label. FDA policy navigator |
| Human oversight | Can clinicians review the basis for an output, exercise their own judgment, and override, defer, or escalate when needed? | For certain non-device CDS functions, FDA’s criteria include enabling independent review so health professionals are not intended to rely primarily on the software’s recommendation. FDA policy navigator |
| Regulatory status and accountability | What is the status of each function in each applicable jurisdiction? Who is responsible for changes, safety reporting, and communicating updates? | “Predictive DSI,” “CDS,” “AI,” and “FDA-cleared” are not interchangeable regulatory conclusions. Status depends on the function and its intended purpose; FDA advises considering other applicable digital-health policies as well. FDA FAQ |
| Lifecycle governance | Who monitors performance and incidents, reviews changes, and decides whether the hospital should adjust or stop use? | Oversight must continue through design, deployment, use, and evaluation—not end at procurement. NIST’s AI Risk Management Framework and WHO’s health AI guidance offer governance principles for that lifecycle. |
How to assess the output and time pressure
For U.S. regulatory analysis, the output is not a stand-alone test of whether software is a device. FDA’s policy navigator identifies recommendations and contextual information as examples that can meet one criterion for certain non-device CDS functions; it also distinguishes these from specific diagnostic or treatment directives, time-critical alarms, and disease-specific risk scores. The criterion is only one part of the analysis, so a hospital should not classify a function from its output format alone.
Workflow matters alongside output. A clinician may have a meaningful opportunity to inspect contextual information retrieved during an encounter, while a time-critical alert may require action before its basis can be independently reviewed. FDA says time-critical decision-support functions generally cannot meet all the non-device CDS criteria; that does not mean every emergency-department information function is a device. Intended use and the full set of criteria still matter. FDA’s navigator and FAQ explain these distinctions.
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What evidence to request before adoption
Ask the supplier for materials that let the hospital assess the function’s basis and intended use, not just a performance claim or a regulatory label. FDA recommends that software or labeling explain the following so clinicians can independently review the basis for a recommendation:
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- Intended use, intended users, and patient population.
- Required medical information, its relevance, how it should be collected, and data-quality requirements.
- How the algorithm was developed, including the methods and data used, and how it was validated.
- Clinical-validation results and the knowns and unknowns relevant to an individual patient.
Then compare the evidence with the hospital’s actual patient population, care setting, available inputs, and decision workflow. The official sources considered here do not establish head-to-head performance for specific products, clinical specialties, or local populations, nor do they support a general claim that predictive AI or conventional CDS is more accurate or safer. FDA’s recommendations on information supporting independent review provide a practical basis for those questions.
How to read U.S. FDA status
FDA’s final Clinical Decision Support Software Guidance for Industry and Food and Drug Administration Staff, dated January 2026, interprets the statutory criteria in section 520(o)(1)(E) of the Federal Food, Drug, and Cosmetic Act for certain software functions excluded from the device definition. FDA’s policy navigator describes four criteria for those non-device CDS functions:
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- The function does not acquire, process, or analyze certain medical images or signals.
- It displays, analyzes, or prints relevant medical information.
- It provides recommendations to health professionals about prevention, diagnosis, or treatment.
- It enables independent review of the basis for a recommendation so the health professional is not intended to rely primarily on it.
The criteria apply to the function, not automatically to an entire product. A function that does not meet the criteria is not thereby fully classified by this summary; other FDA policies and the specific intended use may be relevant. This is a U.S.-focused explanation, not a global regulatory map or legal advice. FDA says its CDS guidance should not be the sole reference where other digital-health policies apply. See the January 2026 final guidance, policy navigator, and FAQ.
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Approval to purchase or deploy a function is not a substitute for a plan to oversee its use. NIST’s AI Risk Management Framework, released January 26, 2023, is voluntary and frames trustworthiness considerations across AI design, development, use, and evaluation. WHO’s 2021 guidance emphasizes ethics, human rights, and stakeholder accountability in health AI, stating that such technologies “must put ethics and human rights at the heart of its design, deployment, and use.” NIST AI RMF and the WHO guidance offer complementary governance references.
Hospitals can translate those principles into assigned responsibilities: decide who monitors performance and incidents, who reviews supplier updates, how clinicians are informed of changes, and who can pause or modify use when concerns arise. The reviewed sources provide governance principles, not a standardized hospital procurement scorecard; local policies should specify the operational process.
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