診療録専門家
ヘルスケアAI露出度
- データ出典: BLS公表時点: '26.08
非常に高い· 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: '26.03
0.667
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: '25
0.52
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15%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
露出のある作業のみ| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Schedule medical appointments for patients.29-2072 | 0.00000.0 | 0.010033.3 |
Consult classification manuals to locate information about disease processes.29-2072 | 0.00000.0 | —0 |
Identify, compile, abstract, and code patient data, using standard classification systems. | —0 | 0.020066.7 |
Assign the patient to diagnosis-related groups (DRGs), using appropriate computer software. | —0 | 0.00000.0 |
Enter data, such as demographic characteristics, history and extent of disease, diagnostic procedures, or treatment into computer. | —0 | 0.00000.0 |
| Not observed on any surface — 12 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. | ||
Compile and maintain patients' medical records to document condition and treatment and to provide data for research or cost control and care improvement efforts. | —0 | —0 |
Maintain or operate a variety of health record indexes or storage and retrieval systems to collect, classify, store, or analyze information. | —0 | —0 |
Post medical insurance billings. | —0 | —0 |
Process and prepare business or government forms. | —0 | —0 |
Process patient admission or discharge documents. | —0 | —0 |
Protect the security of medical records to ensure that confidentiality is maintained. | —0 | —0 |
Release information to persons or agencies according to regulations. | —0 | —0 |
Resolve or clarify codes or diagnoses with conflicting, missing, or unclear information by consulting with doctors or others or by participating in the coding team's regular meetings. | —0 | —0 |
Retrieve patient medical records for physicians, technicians, or other medical personnel. | —0 | —0 |
Review records for completeness, accuracy, and compliance with regulations. | —0 | —0 |
Scan patients' health records into electronic formats. | —0 | —0 |
Transcribe medical reports. | —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 |
|---|---|
Assign the patient to diagnosis-related groups (DRGs), using appropriate computer software.O*NET Task ID 22877 | 1.0 |
Enter data, such as demographic characteristics, history and extent of disease, diagnostic procedures, or treatment into computer.O*NET Task ID 22880 | 1.0 |
Process and prepare business or government forms.O*NET Task ID 22884 | 1.0 |
Transcribe medical reports.O*NET Task ID 22893 | 1.0 |
Compile and maintain patients' medical records to document condition and treatment and to provide data for research or cost control and care improvement efforts.O*NET Task ID 22878 | 0.5 |
Consult classification manuals to locate information about disease processes.O*NET Task ID 22879 | 0.5 |
Identify, compile, abstract, and code patient data, using standard classification systems.O*NET Task ID 22881 | 0.5 |
Maintain or operate a variety of health record indexes or storage and retrieval systems to collect, classify, store, or analyze information.O*NET Task ID 22882 | 0.5 |
Post medical insurance billings.O*NET Task ID 22883 | 0.5 |
Process patient admission or discharge documents.O*NET Task ID 22885 | 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
Occupation information
この職業に関わる最近の変化
2026年4月: ATE 0.36 by 2026 in SF Bay Tier 1 — the earliest crossover within healthcare support category. By 2030, 57.9% of healthcare support occupations in Tier 1 cross moderate-risk threshold.
[出典: arXiv 2604.00186 (Gupta & Kumar, 2026)]2026年3月: Published blog post: highest-risk healthcare support role. Automation risk 62%, medical coding 70% automated.
[出典: AI Changing Work Blog]