ナースプラクティショナー
ヘルスケアAI露出度
- データ出典: BLS公表時点: 2026-08
高い· 相対
低い4段階の相対区分非常に高い職業群単位の値
尺度・母数・出典
4段階の相対区分（低い / 中程度 / 高い / 非常に高い）
BLS雇用見通し表の詳細職業831件が母数。値は NEM(全国雇用マトリクス)コード単位で付与されるため、同じ NEM コードの職業は同じバンドになります
- データ出典: Anthropic公表時点: 2026-03
0.094
0.000ここに掲載された値の範囲0.745尺度・母数・出典
- データ出典: ILO公表時点: 2025
0.25
0.09ここに掲載された値の範囲0.70職業群単位の値
尺度・母数・出典
生成AI露出度指数、公開されたまま0–1
ISCO-08の職業小分類単位 — 同じコードの職業はすべて同じ値
当サイトの算出であり、ILOが公表した数値ではありません。当サイトがILOデータセットに結び付けた職業1,012件のうち、この値以上のものは77%です。
この出典がどのような性格の値か
BLSの区分は絶対水準ではなく相対順位であり、一次測定でもありません。複数の既存研究が付けた職業別パーセンタイル順位を4段階にまとめた値です。雇用や賃金の予測でもなく、導入確率でもなく、自動化と増強を区別しません。
Task-level exposure
非表示の作業 19 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Analyze and interpret patients' histories, symptoms, physical findings, or diagnostic information to develop appropriate diagnoses.29-1171 | 0.067744.1 | 0.049388.1 |
Provide patients with information needed to promote health, reduce risk factors, or prevent disease or disability.29-1171 | 0.035723.2 | 0.00173.0 |
Counsel patients about drug regimens and possible side effects or interactions with other substances such as food supplements, over-the-counter (OTC) medications, or herbal remedies.29-1171 | 0.020913.6 | 0.00162.8 |
Provide patients or caregivers with assistance in locating health care resources.29-1171 | 0.01127.3 | —0 |
Develop treatment plans based on scientific rationale, standards of care, and professional practice guidelines.29-1171 | 0.00895.8 | 0.00346.0 |
Educate patients about self-management of acute or chronic illnesses, tailoring instructions to patients' individual circumstances.29-1171 | 0.00523.4 | —0 |
Advocate for accessible health care that minimizes environmental health risks.29-1171 | 0.00221.4 | —0 |
Prescribe medication dosages, routes, and frequencies based on patient characteristics such as age and gender.29-1171 | 0.00191.2 | —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 |
|---|---|
Maintain complete and detailed records of patients' health care plans and prognoses.O*NET Task ID 18399 | 1.0 |
Educate patients about self-management of acute or chronic illnesses, tailoring instructions to patients' individual circumstances.O*NET Task ID 18378 | 0.5 |
Schedule follow-up visits to monitor patients or evaluate health or illness care.O*NET Task ID 18379 | 0.5 |
Counsel patients about drug regimens and possible side effects or interactions with other substances, such as food supplements, over-the-counter (OTC) medications, or herbal remedies.O*NET Task ID 18380 | 0.5 |
Order, perform, or interpret the results of diagnostic tests, such as complete blood counts (CBCs), electrocardiograms (EKGs), and radiographs (x-rays).O*NET Task ID 18381 | 0.5 |
Analyze and interpret patients' histories, symptoms, physical findings, or diagnostic information to develop appropriate diagnoses.O*NET Task ID 18382 | 0.5 |
Diagnose or treat acute health care problems, such as illnesses, infections, or injuries.O*NET Task ID 18383 | 0.5 |
Diagnose or treat chronic health care problems, such as high blood pressure and diabetes.O*NET Task ID 18384 | 0.5 |
Diagnose or treat complex, unstable, comorbid, episodic, or emergency conditions in collaboration with other health care providers as necessary.O*NET Task ID 18385 | 0.5 |
Treat or refer patients for primary care conditions, such as headaches, hypertension, urinary tract infections, upper respiratory infections, and dermatological conditions.O*NET Task ID 18386 | 0.5 |
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