Especialistas em Registros Médicos
SaúdeExposição à IA
- Fonte dos dados: BLSPublicado: '26.08
Muito alto· relativa
BaixoQuatro faixas relativasMuito altoValor por grupo ocupacional
Escala, base e fonte
Quatro faixas relativas (Baixo / Moderado / Alto / Muito alto)
831 ocupações detalhadas da tabela de projeções de emprego do BLS. O valor é atribuído por código da National Employment Matrix (NEM), pelo que as ocupações que partilham um código NEM recebem a mesma banda
- Fonte dos dados: AnthropicPublicado: '26.03
0.667
0.000Intervalo dos valores aqui apresentados0.745Escala, base e fonte
Índice de exposição observada, 0–1 tal como publicado
Mapeado sobre tarefas O*NET
- Fonte dos dados: ILOPublicado: '25
0.52
0.09Intervalo dos valores aqui apresentados0.70Valor por grupo ocupacional
Escala, base e fonte
Índice de exposição à IA generativa, 0–1 tal como publicado
Grupo de base CITP-08 — todas as ocupações com o mesmo código recebem este valor
Calculado por este site, não publicado pela OIT: das 1.012 ocupações que este site liga ao conjunto de dados da OIT, 15% atingem ou superam este valor.
Que tipo de valor esta fonte publica
A categoria de BLS é uma posição relativa, não um nível absoluto, e também não é uma medição de primeira mão: agrupa em quatro faixas as posições percentis da ocupação em vários estudos publicados. Não é uma previsão de emprego ou de salários, não é uma probabilidade de adoção e não distingue automação de aumento.
Task-level exposure
Apenas tarefas expostas| Task | Claude.aiRaw / share % |
|---|---|
Review records for completeness, accuracy, and compliance with regulations.29-2071 | 0.022423.3 |
Plan, develop, maintain, or operate a variety of health record indexes or storage and retrieval systems to collect, classify, store, or analyze information.29-2071 | 0.015816.4 |
Compile and maintain patients' medical records to document condition and treatment and to provide data for research or cost control and care improvement efforts.29-2071 | 0.00899.2 |
Identify, compile, abstract, and code patient data, using standard classification systems.29-2071 | 0.00869.0 |
Prepare statistical reports, narrative reports, or graphic presentations of information, such as tumor registry data for use by hospital staff, researchers, or other users.29-2071 | 0.00778.0 |
Develop in-service educational materials.29-2071 | 0.00666.9 |
Transcribe medical reports.29-2071 | 0.00636.5 |
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.29-2071 | 0.00464.7 |
Consult classification manuals to locate information about disease processes.29-2071 | 0.00404.2 |
Compile medical care and census data for statistical reports on diseases treated, surgery performed, or use of hospital beds.29-2071 | 0.00383.9 |
| Not observed on any surface — 7 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. | |
Protect the security of medical records to ensure that confidentiality is maintained. | —0 |
Retrieve patient medical records for physicians, technicians, or other medical personnel. | —0 |
Process patient admission or discharge documents. | —0 |
Manage the department or supervise clerical workers, directing or controlling activities of personnel in the medical records department. | —0 |
Train medical records staff. | —0 |
Assign the patient to diagnosis-related groups (DRGs), using appropriate computer software. | —0 |
Post medical insurance billings. | —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
Alterações recentes que afetam esta ocupação
abr. de 2026: 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.
[Fonte: arXiv 2604.00186 (Gupta & Kumar, 2026)]mar. de 2026: Published blog post: highest-risk healthcare support role. Automation risk 62%, medical coding 70% automated.
[Fonte: AI Changing Work Blog]