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Emergency medicine physicians

Also called ER doctor, Emergency room doctor, EM physician, ED physician, Emergency physician

In brief

In May 2025, BLS counted 32,880 US emergency medicine physicians, with median pay of $335,550 a year. Of the BLS counts since 2021, the highest was 36,180, in May 2021. The earliest figure here is an estimate of 27,000 from 1999, not measured the same way as today's count. The last full technology era for emergency medicine physicians: AI imaging triage, FDA-cleared diagnostic algorithms, 2015 to 2022. AI imaging triage tools reduced time-to-treatment for stroke and large vessel occlusion without reducing physician headcount.

What the sources say

Official outlook

BLS projects employment to grow 3.2% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Emergency medicine physicians: jobs and pay since 1984 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/29-1214

Chicago

Future History. "Emergency medicine physicians: jobs and pay since 1984." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/29-1214.

BibTeX

@misc{futurehistory_29_1214, author = {{Future History}}, title = {Emergency medicine physicians: jobs and pay since 1984}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/29-1214}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
19752000now
2026
Known then as Emergency Physician (full-time ED practitioners, pre-specialty recognition)
Known then as Emergency Medicine Specialist / Emergency Physician (specialty recognized 1979, ABEM board certification from 1980)
Known then as Emergency Medicine Physicians (BLS SOC 29-1214)
Known today as Emergency Medicine Physicians (BLS SOC 29-1214)
Projected to still be called Emergency Medicine Physicians (BLS SOC 29-1214)
Data from the May 2025 survey
US Employment
33K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$335,550
Est.

≈ $326,947 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1968

On August 16, 1968, John Wiegenstein and seven colleagues -- all practicing full-time emergency physicians in Michigan -- met in Lansing to found the American College of Emergency Physicians. The eight founders drafted articles of incorporation, adopted a constitution and bylaws, and elected Wiegenstein as the first chairman. This founding meeting marked the organizational birth of emergency medicine as a defined professional community, 7 years before the specialty would be formally recognized by ABMS.

Beat · 1977

The American Board of Medical Specialties voted 100-5 against granting specialty recognition to emergency medicine in 1977, citing concerns about whether the field was truly distinct from other physician training. The vote did not stop the specialty's momentum. Two years later, in September 1979, ABMS reversed course and voted to recognize emergency medicine as the twenty-third medical specialty, a decision driven in large part by the demonstrated growth of residency programs and the demonstrated inadequacy of the rotating-staff staffing model for high-volume emergency departments.

Beat · 1986

The Emergency Medical Treatment and Labor Act (EMTALA), enacted as part of COBRA 1986, created a federal legal obligation for hospitals to screen and stabilize any patient presenting to an emergency department regardless of insurance status or ability to pay. EMTALA fundamentally changed the emergency physician's legal and ethical context: every ED presentation triggers a legal screening obligation, and transfer cannot occur until the patient is medically stabilized. This statute is why emergency medicine operates under a different moral and legal framework from elective specialties and why the specialty has consistently high malpractice exposure.

Beat · 2021

An ACEP-commissioned workforce analysis published in the Annals of Emergency Medicine in 2021 projected a surplus of 9,000-10,000 board-certified emergency physicians by 2030, driven by accelerating residency program expansion (55% more programs from 2010-2023), growing APP scope-of-practice in emergency settings, and post-COVID-19 demand uncertainty. The report was described in Annals as representing "a historically bad job market for emergency physicians" -- the first time in the specialty's history that supply was projected to substantially outpace demand in urban markets. The immediate practical effect was compression of sign-on bonuses and staffing-group contract leverage in major metropolitan areas.

Beat · 2025

ACEP's 2025 compensation survey (1,774 responses, closed May 2025) reported median total compensation of $330,000 for all emergency physician respondents and $360,000 for clinical emergency physicians specifically. The survey documented a persistent gender compensation gap: men earned $13 more per clinical hour than women ($225 vs. $212), translating to approximately $62,000 more annual compensation at the median. Regional variation was also substantial: Northeast physicians reported the lowest median at $210/hr and $300,300 total, while South, Midwest, and West physicians reported $225/hr and over $350,000 total. These figures represent total compensation including base and bonuses; BLS OEWS wages reflect W-2 base wages only.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace emergency medicine physicians? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+3.2%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 29-1214 (Emergency medicine physicians): 34.9 thousand jobs in 2025, projected 36.1 thousand in 2035, a change of +1.1 thousand (+3.2%). Matrix employment counts all jobs in the occupation, including self-employed workers (3.7% of this occupation in 2025). The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
35.3%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 29-1214.00 Emergency Medicine Physicians. Shown: human-rated β = 0.353, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.176 and γ (all LLM-assisted) 0.529; GPT-4-rated β 0.441. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for emergency medicine physicians

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereReview and approve ambient AI-drafted emergency department encounter notes and medical decision-making (MDM) documentation generated during patient visits, verifying accuracy of chief complaint, HPI, physical examination findings, differential diagnosis, and management plan against the clinical conversation and exam performed, then attesting the finalized note as the physician of record before it is filed to the EHR.

Review and approve ambient AI-drafted emergency department encounter notes and medical decision-making (MDM) documentation generated during patient visits, verifying accuracy of chief complaint, HPI, physical examination findings, differential diagnosis, and management plan against the clinical conversation and exam performed, then attesting the finalized note as the physician of record before it is filed to the EHR.[4],[3],[11]

Where your edge is

Ambient AI scribes (dragon-copilot) achieved a 28% reduction in on-shift documentation time in a 2025 emergency department study at a tertiary academic center (Annals of Emergency Medicine 2025), and health systems report burnout reduction after scribe deployment: critical in a specialty with triple the burnout rate of peers. Your value shifts to expert clinical review and final attestation. Emergency medicine notes require specific scrutiny of the medical decision-making level (MDM) for coding accuracy, and AI tools miss pertinent negatives, subtle timing details, and physical exam nuances that affect both clinical accuracy and billing compliance. Develop a fast, systematic review cadence focused on the elements that most affect downstream care decisions and reimbursement.

AI is sitting alongside you hereInterpret and triage AI-flagged critical imaging findings for immediate clinical action, receiving Aidoc alerts for CT-identified acute findings (pulmonary embolism, intracranial hemorrhage, large vessel occlusion, aortic dissection, pneumothorax) and Viz.ai LVO/PE/aortic alerts simultaneously with ordered study completion

Interpret and triage AI-flagged critical imaging findings for immediate clinical action, receiving Aidoc alerts for CT-identified acute findings (pulmonary embolism, intracranial hemorrhage, large vessel occlusion, aortic dissection, pneumothorax) and Viz.ai LVO/PE/aortic alerts simultaneously with ordered study completion; reviewing AI-flagged images and radiology context; determining immediate clinical response (anticoagulation initiation, neurosurgery activation, endovascular thrombectomy team mobilization); and integrating AI imaging alerts with the clinical presentation rather than acting on algorithm output in isolation.[5],[7],[8]

Where your edge is

Aidoc's January 2026 FDA clearance for a comprehensive CARE™ foundation model, several acute indications at 97% sensitivity / 98% specificity in the pivotal study, and Viz.ai's documented 44% reduction in door-to-neurointerventionalist notification time are fundamentally changing how critical imaging findings reach the ED attending. These tools do not replace your clinical decision; they compress the time between a critical finding appearing on the scanner and it reaching your attention. Build the clinical reflex to treat AI imaging alerts as the start of a time-sensitive workup: confirm the finding rapidly against the available images, integrate with the patient's clinical presentation and coagulation status, then mobilize the right team.

AI is sitting alongside you hereMonitor and respond to AI-assisted triage stratification for the ED patient population, receiving and evaluating KATE AI triage decision support alerts when the ESI acuity assignment is flagged as potentially undercategorized or when a high-risk condition (sepsis, septic shock, preeclampsia, high-acuity chest pain) is identified at triage

Monitor and respond to AI-assisted triage stratification for the ED patient population, receiving and evaluating KATE AI triage decision support alerts when the ESI acuity assignment is flagged as potentially undercategorized or when a high-risk condition (sepsis, septic shock, preeclampsia, high-acuity chest pain) is identified at triage; integrating KATE alerts with clinical context to accelerate evaluation of the highest-risk patients before they deteriorate in the waiting room; and overseeing overall ED patient flow and boarding management.[9],[13],[14]

Where your edge is

KATE AI fires within several seconds of triage form submission and is now deployed across many hospital sites managing 1.5M+ patient visits per year: the HIMSS25 Best in Show win signals rapid broader adoption. It doesn't replace the physician's assessment; it reduces the probability that a high-acuity patient is misclassified in the waiting room and deteriorates before you see them. Build familiarity with how KATE alerts integrate into your ED's triage workflow so you can act on high-priority alerts immediately and efficiently without creating new cognitive overhead. The Epic Sepsis Watch integration adds a parallel alert layer for sepsis detection in patients who have already been roomed.

Where emergency medicine physicians go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

Emergency medicine physicians have structural advantages over other specialists in the CMIO and clinical informatics career path. EM attendings work across every organ system, interact with virtually every clinical specialty's EHR workflows in a single shift, and operate in the highest-acuity, most technologically complex clinical environment in the hospital, giving them broad workflow knowledge that pure IT managers lack. As AI imaging triage (Aidoc, Viz.ai, RapidAI), ambient documentation scribes (dragon-copilot), and AI triage decision support (KATE) become core clinical infrastructure, health systems need physician leaders who understand both the clinical domain and the technology governance requirements. EMRA's Clinical Informatics Fellowship Guide documents the established career pathway: ACGME-accredited clinical informatics fellowship, ABPM board certification, and roles including CMIO, CIO, patient safety director, and health IT medical director. CMIO base salaries range. An MBA or graduate certificate in health informatics accelerates the transition without requiring a full fellowship.

What you'd add
  • · Clinical informatics credentials: AMIA 10×10 certificate (online) or 2-year ACGME-accredited Clinical Informatics Fellowship followed by ABPM board certification in Clinical Informatics
  • · EHR platform expertise: Epic build certification or equivalent, understanding configuration levers, AI module architecture, and workflow integration points that ED physicians interact with daily
  • · Clinical AI evaluation methodology: model validation (sensitivity, specificity, alert precision), algorithmic bias auditing for triage tools, FDA regulatory framework for AI-enabled medical devices
  • · HL7 FHIR interoperability: health data exchange standards that underpin AI tool integrations, imaging alert pipelines (Aidoc, Viz.ai), and population health data flows
  • · Change management: EHR rollout and AI tool implementation experience, clinician engagement and adoption strategy, and post-deployment monitoring program design
What it takesSome new skills to pick up
Tools of the era

How has the work of emergency medicine physicians changed since 1700?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Surgical instruments, splints, bandages (pre-hospital era: emergency care as battlefield or domestic response)

    Before the era of organized hospitals, emergency care meant treating the immediately life-threatening: controlling hemorrhage with tourniquets and ligatures, setting fractures with splints, managing airway obstruction by positioning, and administering laudanum (tincture of opium) for pain. Civil War military medicine was the most advanced emergency care of the nineteenth century: Jonathan Letterman's 1862 reorganization of the Union Army Medical Department created the first systematic triage and evacuation system, with surgeons stratified by skill level doing field amputations and primary wound closure. Civilian hospitals had emergency functions, but no distinct emergency physician class -- the surgeon on duty was whoever was available.

  • Hospital emergency room (rotating-staff model, anesthesia, X-ray from 1895)

    The modern hospital emergency room took shape in the late nineteenth century as hospitals transitioned from charitable institutions for the poor into the primary site of acute medical care for everyone. Antiseptic technique (Lister, 1867) and anesthesia (ether, 1846; chloroform, 1847) made operative intervention survivable. The X-ray, introduced clinically in 1895, gave the emergency physician the first non-invasive window into the body. Blood typing (Landsteiner, 1901) and transfusion made resuscitation possible. By the 1950s, an emergency room in a major hospital had access to all of these tools -- but it was staffed by rotating interns, residents from every other specialty, and part-time general practitioners who fit emergency coverage around their private practices. Quality was highly variable: the dermatologist on call had no particular expertise in trauma or resuscitation.

  • Full-time ED staffing model (Alexandria Plan 1961, group practice contracts)

    The Alexandria Plan was a technology in the organizational sense: it restructured who provided emergency care and under what contract, without any new medical instrument. James Mills and his three colleagues working full-time in the Alexandria Hospital ED developed clinical expertise that rotating staff could never accumulate. Within five years the model had spread nationally. The Pontiac Plan (Pontiac, Michigan) and similar group-practice contracts gave hospitals a staffing structure that would eventually become the dominant delivery model. In 1968, John Wiegenstein and seven colleagues founded ACEP in Lansing, Michigan, formalizing the movement. In 1970, the University of Cincinnati opened the first dedicated EM residency program. By 1981, 56 EM residency programs existed across the country.

    Effect on the work

    The shift from rotating-staff to full-time-group ED staffing created a new occupational category where none had existed before. By 1999, roughly 27,000 full-time equivalent emergency physicians were practicing nationally, a workforce that had grown essentially from zero in 1961.

  • ABEM board certification, EM residency expansion, EHR precursors (early paper charting to dictation)

    ABMS recognition of emergency medicine in 1979 and the first ABEM board certificates in 1980 created a credentialing structure that redefined the quality bar for emergency physicians. For the first time, a patient could ask whether the emergency physician at the bedside was board-certified in the relevant specialty. The 1980s and 1990s saw explosive growth in EM residency programs. Documentation in this era was paper-based: the emergency physician dictated a note, often after a busy shift, which was transcribed by a medical secretary. The EKG machine, portable ventilator, and bedside ultrasound arrived in emergency departments during this period, each adding diagnostic capability. Point-of-care ultrasound (POCUS), introduced in emergency medicine in the late 1980s and early 1990s, gave emergency physicians the first real-time procedural imaging tool they controlled directly at the bedside.

  • Electronic Health Records (EHR) mandatory adoption, HITECH Act 2009, Epic and Cerner rollout

    The Health Information Technology for Economic and Clinical Health Act (HITECH Act, 2009) attached $27 billion in Medicare and Medicaid incentives to "meaningful use" of certified electronic health records, accelerating EHR adoption from roughly 10% of hospitals in 2006 to over 96% by 2014. For emergency physicians, EHR rollout was double-edged: it ended illegible paper charts and enabled structured clinical decision support (drug interaction alerts, sepsis scoring), but it also massively increased documentation burden. The typical ED encounter required more clicks, fields, and attestation steps than the equivalent paper note. Physician dissatisfaction with EHR documentation became the dominant driver of burnout in emergency medicine through the 2010s, a problem that ambient AI scribes would later be deployed to solve.

    Effect on the work

    Documentation time in EHR systems consumed an estimated 40-50% of physician time in emergency departments by the mid-2010s, contributing to triple the burnout rate of other specialties. This was not a headcount effect but a quality-of-work-life crisis that would shape AI adoption strategies in the specialty from 2020 onward.

  • AI imaging triage, FDA-cleared diagnostic algorithms (Viz.ai 2017, RapidAI)

    Viz.ai launched in 2017 with FDA clearance for large vessel occlusion stroke detection from CT angiography, delivering real-time mobile alerts directly to the emergency physician and stroke team. RapidAI brought a competing platform for ischemic stroke core-penumbra mismatch analysis. Both represented the first FDA-cleared AI diagnostic tools purpose-built for emergency medicine workflows. The documented clinical impact was substantial: a 2025 meta-analysis found Viz.ai deployment reduced arrival-to-neurointerventionalist notification time by 39.5 minutes (44% reduction) compared to non-AI facilities. For the emergency physician, these tools changed the experience of critical imaging: instead of waiting for a radiologist to call, a time-sensitive finding arrived as a push notification within minutes of scan completion. The physician was still the clinical decision-maker but the latency between diagnosis and action collapsed.

    Effect on the work

    AI imaging triage tools reduced time-to-treatment for stroke and large vessel occlusion without reducing physician headcount. The effect was quality and outcome improvement, not substitution. These tools operate at the interface between radiology and emergency medicine, alerting both specialties simultaneously.

  • Ambient AI documentation scribes (Dragon Copilot, DAX, Abridge) and AI triage decision support (KATE)

    The deployment of ambient AI documentation scribes in emergency departments from 2022-2025 addressed the single largest quality-of-life problem in the specialty: the crushing documentation burden imposed by EHR systems. Ambient scribes (Dragon Copilot/DAX, Abridge) passively transcribe and structure the clinical encounter, generating a draft emergency department note that the physician reviews and attests rather than dictating or typing from scratch. A 2025 retrospective study at a tertiary academic ED (February through October) found a 28% reduction in on-shift documentation time when ambient AI was used. Health systems deploying these tools reported 40-63% reductions in physician burnout scores. KATE AI (Mednition), deployed across 34 hospital sites managing 1.5 million patient visits annually by 2025, added a parallel layer: real-time AI triage decision support that fires within 1-8 seconds of triage form submission when ESI acuity appears misclassified or a high-acuity condition is flagged. The combination of documentation relief and triage intelligence represents the most significant restructuring of the daily workflow since EHR adoption itself.

    Effect on the work

    Ambient AI scribes are projected to reduce documentation time per shift by 20-30%, effectively adding clinical capacity without adding physician headcount. The workforce implications are ambiguous: reduced per-physician burnout may improve retention, while increased throughput per physician could reduce the number of physicians needed for a given visit volume in high-efficiency departments.

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Emergency Medicine Physicians employment and pay by year

On record since1961
Latest US employment32,880 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$335,550 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+3.2% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 10 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
1984n/a$90,000Est., PMC 2014 Researched contextReport
1995n/a$158,100Est., PubMed Researched contextReport
199927,000n/aEst., PubMed Researched contextReport
2010n/a$265,000Est., ACEP Salary Surveys Researched contextReport
201333,034n/aEst., PMC 2022 Researched contextReport
202136,180n/aBLS OEWS May 2021 Official statisticReport
202229,260n/aBLS OEWS May 2022 Official statisticReport
202335,100n/aBLS OEWS May 2023 Official statisticReport
202433,680n/aBLS OEWS May 2024 Official statisticReport
202532,880$335,550BLS OEWS May 2025 Official statisticReport
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