Medicos de Urgencias
SaludExposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Alto· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: ILOPublicado: 2025
0.27
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Grupo primario de la CIUO-08 — todas las ocupaciones con ese código reciben este valor
Calculado por este sitio, no publicado por la OIT: de las 1012 ocupaciones que este sitio vincula al conjunto de datos de la OIT, un 74% alcanza o supera este valor.
- Fuente de datos: OpenAIPublicado: 2023
0.353
0.000Rango de los valores aquí recogidos0.844Escala, base y fuente
β de evaluadores humanos, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Task-level exposure
Solo tareas expuestas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives.29-1214 | 0.080088.9 | 0.00000.0 |
Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease.29-1214 | 0.010011.1 | 0.0100100.0 |
Analyze records, examination information, or test results to diagnose medical conditions.29-1214 | 0.00000.0 | 0.00000.0 |
Conduct primary patient assessments that include information from prior medical care.29-1214 | 0.00000.0 | 0.00000.0 |
Evaluate patients' vital signs or laboratory data to determine emergency intervention needs and priority of treatment.29-1214 | 0.00000.0 | 0.00000.0 |
Refer patients to specialists or other practitioners.29-1214 | 0.00000.0 | 0.00000.0 |
Collect and record patient information, such as medical history or examination results, in electronic or handwritten medical records. | —0 | 0.00000.0 |
| Not observed on any surface — 10 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Assess patients' pain levels or sedation requirements. | —0 | —0 |
Consult with hospitalists and other professionals, such as social workers, regarding patients' hospital admission, continued observation, transition of care, or discharge. | —0 | —0 |
Direct and coordinate activities of nurses, assistants, specialists, residents, and other medical staff. | —0 | —0 |
Discuss patients' treatment plans with physicians and other medical professionals. | —0 | —0 |
Monitor patients' conditions, and reevaluate treatments, as necessary. | —0 | —0 |
Perform emergency resuscitations on patients. | —0 | —0 |
Perform such medical procedures as emergent cricothyrotomy, endotracheal intubation, and emergency thoracotomy. | —0 | —0 |
Select and prescribe medications to address patient needs. | —0 | —0 |
Select, request, perform, or interpret diagnostic procedures, such as laboratory tests, electrocardiograms, emergency ultrasounds, and radiographs. | —0 | —0 |
Stabilize patients in critical condition. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Collect and record patient information, such as medical history or examination results, in electronic or handwritten medical records.O*NET Task ID 22717 | 1.0 |
Analyze records, examination information, or test results to diagnose medical conditions.O*NET Task ID 22715 | 0.5 |
Assess patients' pain levels or sedation requirements.O*NET Task ID 22716 | 0.5 |
Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives.O*NET Task ID 22718 | 0.5 |
Conduct primary patient assessments that include information from prior medical care.O*NET Task ID 22719 | 0.5 |
Consult with hospitalists and other professionals, such as social workers, regarding patients' hospital admission, continued observation, transition of care, or discharge.O*NET Task ID 22720 | 0.5 |
Direct and coordinate activities of nurses, assistants, specialists, residents, and other medical staff.O*NET Task ID 22721 | 0.5 |
Discuss patients' treatment plans with physicians and other medical professionals.O*NET Task ID 22722 | 0.5 |
Evaluate patients' vital signs or laboratory data to determine emergency intervention needs and priority of treatment.O*NET Task ID 22723 | 0.5 |
Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease.O*NET Task ID 22724 | 0.5 |
Perform emergency resuscitations on patients.O*NET Task ID 22726 | 0.0 |
Perform such medical procedures as emergent cricothyrotomy, endotracheal intubation, and emergency thoracotomy.O*NET Task ID 22727 | 0.0 |
Stabilize patients in critical condition.O*NET Task ID 22731 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page