Proposed Competencies for the Use of AI-Based Tools in Primary Care Decision Making
| Domain | Bottom Line | Competency | Hypothetical Scenario |
|---|---|---|---|
| Foundational knowledge | What is this tool? | Clinicians will explain the fundamentals of AI, how AI-based tools are created and evaluated, the critical regulatory and socio-legal issues of the AI-based tools, and the current and emerging roles of AI in health care. | The FDA approved an AI tool that provides a differential diagnosis using photographs of skin conditions and medical history. It was developed using 16,000 cases and a convolutional neural network to output prediction scores across 400 skin diseases. |
| Critical appraisal | Should I use this tool? | Clinicians will appraise the evidence behind AI-based tools and assess their appropriate uses via validated evaluation frameworks for health care AI. | In a retrospective study, the AI tool was superior to primary care clinicians, for which use was associated with improved diagnoses for 1 in every 10 cases. A prospective study in a clinical setting has not been done yet. |
| Medical decision making | When should I use this tool? | Clinicians will identify the appropriate indications for and incorporate the outputs of AI-based tools into medical decision making such that effectiveness, value, equity, fairness, and justice are enhanced. | You decide to use this AI tool to augment your diagnostic ability for skin conditions where the diagnosis is unclear. You use it to inform, not override, your decisions regarding treatment, biopsies, and referrals in a way that boosts accuracy, quality of care, and resource stewardship. |
| Technical use | How do I use this tool? | Clinicians will execute the tasks needed to operate AI-based tools in a manner that supports efficiency and builds mastery. | You learn to take clinical photographs of skin conditions as required by the AI tool and generate a differential diagnosis using it. You do this seamlessly and efficiently during physical exams. |
| Patient communication | How should I communicate with patients regarding the use of the tool? | Clinicians will communicate what the tool is and why it is being used, answer questions about privacy and confidentiality, and engage in shared decision making, in a manner that preserves or augments the clinician-patient relationship. | You discuss with the patient why and how the tool is being used and answer questions regarding privacy, ultimately building trust and confidence. |
| Unintended consequences (cross-cutting) | What are the “side effects” of this tool? | Clinicians will anticipate and recognize the potential adverse effects of AI-based tools and take appropriate actions to mitigate or address unintended consequences. | Foundational knowledge: You recognize that a convolutional neural network is a “black box.” As a result, you will not consult the tool for a rationale behind the suggested diagnosis. You remind yourself to guard against cognitive biases that may arise from only seeing the final suggested diagnosis. Critical appraisal: You understand that Fitzpatrick skin types I and V are under-represented, and type VI is absent in the data set for this AI tool.a Medical decision making: You anticipate that the tool will be less accurate for patients with these skin types and adjust your utilization, choosing to learn more about patients with these skin types. Technical use: You take the appropriate steps when the tool delivers an error message. Patient communication: You explain to the patient why your diagnosis is not the same as the one suggested by the tool, engaging in a shared decision making process that engenders trust, confidence, and respect. |
AI = artificial intelligence; FDA = Food and Drug Administration.
Note: Fitzpatrick skin type 1 is pale white skin, while type VI is dark brown or black.
a The Fitzpatrick skin type classifies skin according to the amount of melanin pigment in the skin.