Nurse Practitioners
Healthcare Practitioners and Technical Occupations- رمز O*NET-SOC
- 29-1171.00
Diagnose and treat acute, episodic, or chronic illness, independently or as part of a healthcare team. May focus on health promotion and disease prevention. May order, perform, or interpret diagnostic tests such as lab work and x rays. May prescribe medication. Must be registered nurses who have specialized graduate education.
تُعرض أسماء المهن وأوصاف المهام بالإنجليزية كما نُشرت. أما التسميات، ومنها أنواع المهام، فمترجمة.
التعرّض للذكاء الاصطناعي
- مصدر البيانات: BLSتاريخ النشر: 2026-08
مرتفع· نسبي
منخفضأربع فئات نسبيةمرتفع جدًاقيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
أربع فئات نسبية (منخفض / متوسط / مرتفع / مرتفع جدًا)
831 مهنة تفصيلية في جدول توقعات التوظيف لدى BLS. وتُسند القيمة على مستوى رمز مصفوفة التوظيف الوطنية (NEM)، فالمهن التي تشترك في الرمز نفسه تأخذ النطاق نفسه
- مصدر البيانات: Anthropicتاريخ النشر: 2026-03
0.094
0.000نطاق القيم المعروضة هنا0.745المقياس والأساس والمصدر
مؤشر التعرّض المرصود، 0–1 كما نُشر
مربوط بمهام O*NET
منشورة لكل مهنة في SOC 2018؛ وكل مهنة في O*NET تحمل رمز SOC 2018 نفسه تأخذ هذه القيمة
- مصدر البيانات: ILOتاريخ النشر: 2025
0.25
0.09نطاق القيم المعروضة هنا0.70قيمة على مستوى المجموعة المهنية
المقياس والأساس والمصدر
مؤشر التعرّض للذكاء الاصطناعي التوليدي، 0–1 كما نُشر
قيمة منشورة على مستوى مجموعة الوحدة في ISCO-08. رُبطت بهذه المهنة بتطبيق جداول التناظر الرسمية لمكتب إحصاءات العمل الأمريكي (BLS) (من ISCO-08 إلى SOC 2010، ومن SOC 2010 إلى SOC 2018) كما نُشرت، والتناظر كلي أو جزئي
ما نوع القيمة التي ينشرها هذا المصدر
فئة BLS رتبة نسبية لا مستوى مطلق، وليست قياسًا مباشرًا: فهي تجمع الرتب المئينية للمهنة في عدة دراسات منشورة في أربع فئات. وهي ليست توقّعًا للتوظيف أو الأجور، ولا احتمالًا للتبني، ولا تفرّق بين الأتمتة والتعزيز.
التعرض للذكاء الاصطناعي (معيار OpenAI)
27 مهمة مقيَّمة · 25 مهمة بقيمة β ≥ 0.5 (92.6%)
β = التعرّض المباشر (E1) + 0.5 × التعرّض عند توفر الأدوات (E2)، وفق تعريف المستودع المصدري.
- وحدة المصدر: مهام O*NET 27.2 ← رمز المهنة في O*NET 31.0
- جميع المهام المقيَّمة موجودة في قائمة مهام O*NET 31.0.
- المصدر
- OpenAI "GPTs are GPTs" exposure rubric
- الإصدار
- gh-main-0471612
- الترخيص
- MIT License, Copyright (c) 2024 OpenAI
المهام
أوصاف المهام من O*NET® 31.0 Database، والمهام الأساسية أولًا.
| المهمة | النوع | β (OpenAI) |
|---|---|---|
| Educate patients about self-management of acute or chronic illnesses, tailoring instructions to patients' individual circumstances. | أساسية | 0.5 |
| Schedule follow-up visits to monitor patients or evaluate health or illness care. | أساسية | 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. | أساسية | 0.5 |
| Order, perform, or interpret the results of diagnostic tests, such as complete blood counts (CBCs), electrocardiograms (EKGs), and radiographs (x-rays). | أساسية | 0.5 |
| Analyze and interpret patients' histories, symptoms, physical findings, or diagnostic information to develop appropriate diagnoses. | أساسية | 0.5 |
| Diagnose or treat acute health care problems, such as illnesses, infections, or injuries. | أساسية | 0.5 |
| Diagnose or treat chronic health care problems, such as high blood pressure and diabetes. | أساسية | 0.5 |
| Diagnose or treat complex, unstable, comorbid, episodic, or emergency conditions in collaboration with other health care providers as necessary. | أساسية | 0.5 |
| Treat or refer patients for primary care conditions, such as headaches, hypertension, urinary tract infections, upper respiratory infections, and dermatological conditions. | أساسية | 0.5 |
| Consult with, or refer patients to, appropriate specialists when conditions exceed the scope of practice or expertise. | أساسية | 0.5 |
| Detect and respond to adverse drug reactions, with special attention to vulnerable populations such as infants, children, pregnant and lactating women, or older adults. | أساسية | 0.5 |
| Develop treatment plans, based on scientific rationale, standards of care, and professional practice guidelines. | أساسية | 0.5 |
| Perform primary care procedures such as suturing, splinting, administering immunizations, taking cultures, and debriding wounds. | أساسية | 0 |
| Perform routine or annual physical examinations. | أساسية | 0 |
| Prescribe medications based on efficacy, safety, and cost as legally authorized. | أساسية | 0.5 |
| Provide patients with information needed to promote health, reduce risk factors, or prevent disease or disability. | أساسية | 0.5 |
| Recommend diagnostic or therapeutic interventions with attention to safety, cost, invasiveness, simplicity, acceptability, adherence, and efficacy. | أساسية | 0.5 |
| Recommend interventions to modify behavior associated with health risks. | أساسية | 0.5 |
| Prescribe medication dosages, routes, and frequencies, based on such patient characteristics as age and gender. | أساسية | 0.5 |
| Advocate for accessible health care that minimizes environmental health risks. | أساسية | 0.5 |
| Provide patients or caregivers with assistance in locating health care resources. | أساسية | 0.5 |
| Maintain complete and detailed records of patients' health care plans and prognoses. | أساسية | 1 |
| Read current literature, talk with colleagues, or participate in professional organizations or conferences to keep abreast of developments in nursing. | أساسية | 0.5 |
| Keep abreast of regulatory processes and payer systems, such as Medicare, Medicaid, managed care, and private sources. | أساسية | 0.5 |
| Maintain current knowledge of state legal regulations for nurse practitioner practice, including reimbursement of services. | أساسية | 0.5 |
| Maintain departmental policies and procedures in areas such as safety and infection control. | أساسية | 0.5 |
| Supervise or coordinate patient care or support staff activities. | أساسية | 0.5 |
معلومات مهنية
المصادر والإسناد
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 29-1171.00 Nurse Practitioners
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.