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Ophthalmic medical technicians

Also called Ophthalmic medical technologist, Ophthalmic technician, Ophthalmic technologist, Ophthalmic tech, COT

In brief

In May 2025, BLS counted 71,010 US ophthalmic medical technicians, with median pay of $45,570 a year. The earliest figure here is an estimate of 5,000 from 1969, not measured the same way as today's count. The last full technology era for ophthalmic medical technicians: Optical coherence tomography commercial clinical use, 1996 to 2020. The OCT expansion drove the largest single increase in ophthalmic technician demand since the Humphrey perimeter.

What the sources say

Official outlook

BLS projects employment to grow 21.4% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Ophthalmic medical technicians: jobs and pay since 1969 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/29-2057

Chicago

Future History. "Ophthalmic medical technicians: jobs and pay since 1969." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/29-2057.

BibTeX

@misc{futurehistory_29_2057, author = {{Future History}}, title = {Ophthalmic medical technicians: jobs and pay since 1969}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/29-2057}}, 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
19001925195019752000now
2026
Known then as Ophthalmic Assistant (informal, no recognized credential)
Known then as Ophthalmic Medical Assistant (first formal training era, Georgetown)
Known then as Certified Ophthalmic Assistant / Ophthalmic Technician (JCAHPO certification era)
Known then as Ophthalmic Technician / Ophthalmic Medical Technologist (three-tier credential era)
Known then as Ophthalmic Medical Technicians (BLS SOC 29-2057)
Known today as Ophthalmic Medical Technicians (BLS SOC 29-2057)
Projected to still be called Ophthalmic Medical Technicians (BLS SOC 29-2057)
Data from the May 2025 survey
US Employment
71K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$45,570

≈ $44,402 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1963

Dr. Peter Evans at Georgetown University pilots the first formal two-year training program for ophthalmic medical assistants in the United States. The program was motivated by a practical recognition that growing ophthalmology practices were spending physician time on pre-testing tasks that trained staff could perform as well or better. The Georgetown program became a model that other universities and community colleges followed. Dr. Evans passed away in 2020; JCAHPO named a scholarship fund in his honor.

Beat · 1969

JCAHPO is incorporated in 1969 by six ophthalmologist-led societies, founding a credentialing body that would transform the occupation from informal assistant to certified allied health professional. Dr. Peter Evans of Georgetown University is among the founding members. JCAHPO develops its first multiple-choice and practical oral examinations to assess competency over the following decade. This is the organizational hinge point of the occupation's history.

Beat · 1984

The Humphrey Field Analyzer (HFA I) launches in 1984, replacing manual Goldmann perimetry as the clinical standard for visual field testing in glaucoma. Developed by Mike Patella (an aerospace engineer turned optometrist) and Swedish glaucoma specialist Prof. Anders Heijl after meeting at the International Perimetric Society in Sacramento in 1982. The HFA makes visual field testing fast enough for routine use at every glaucoma visit, dramatically expanding the volume of perimetry in ophthalmology practices and the demand for technicians trained to administer it reliably.

Beat · 1996

The first commercial optical coherence tomography (OCT) device launches in 1996. By 2000 only 180 units are in clinical use worldwide; by 2004 more than 10 million OCT procedures have been performed globally. OCT creates the single most important new scope expansion for ophthalmic technicians since the Humphrey perimeter: acquiring, reviewing, and managing OCT studies becomes a core OMT competency and eventually the most performed imaging task in ophthalmology.

Beat · 2010

The 2010 Standard Occupational Classification revision creates SOC 29-2057 as a distinct code for ophthalmic medical technicians. Before 2010, the occupation was enumerated within broader Health Technologists and Technicians groups, making the historical employment series fragmentary. The 2010 SOC change is administratively significant: it gives the occupation its first dedicated BLS tracking code and allows consistent measurement going forward.

Beat · 2018

The FDA issues the first De Novo authorization for an autonomous AI diagnostic device in any medical specialty: Digital Diagnostics' LumineticsCore (then IDx-DR) for diabetic retinopathy screening. The device analyzes fundus images and issues a binary refer or rescreen result without a clinician reviewing the image. At OMT-staffed practices, the technician operates the fundus camera and uploads the images; the AI produces the diagnostic determination. For the first time, a task that previously required a clinician's interpretive judgment is fully automated within the OMT's workflow.

Beat · 2011

JCAHPO renames itself the International Joint Commission on Allied Health Personnel in Ophthalmology (IJCAHPO), reflecting credential holders in more than 30 countries. By 2011, the organization reports more than 30,000 certified ophthalmic personnel globally, up from 8,000 in the 1980s. The renaming marks the occupation's transition from a US-centric allied health credential to an internationally recognized clinical standard.

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 ophthalmic medical technicians? 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
+21.4%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 29-2057 (Ophthalmic medical technicians): 72.5 thousand jobs in 2025, projected 88.0 thousand in 2035, a change of +15.5 thousand (+21.4%). Matrix employment counts all jobs in the occupation, including self-employed workers (0.4% 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)
10.5%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 29-2057.00 Ophthalmic Medical Technicians. Shown: human-rated β = 0.105, 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) 0.026 and γ (all LLM-assisted) 0.184; GPT-4-rated β 0.329. 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 ophthalmic medical technicians

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

AI is sitting alongside you hereAcquire fundus photographs and operate autonomous AI diabetic retinopathy screening platforms, positioning the patient at the fundus camera (Topcon NW400, Zeiss Visucam, or Canon CR-2), capturing non-mydriatic fundus images per AI screening protocol, uploading images to the autonomous DR AI (LumineticsCore or EyeArt), reviewing the AI-generated image quality flag for adequacy before releasing the study, and routing the AI result (refer / rescreen) to the supervising ophthalmologist, optometrist, or primary care provider with appropriate documentation under CPT 92229.

Acquire fundus photographs and operate autonomous AI diabetic retinopathy screening platforms, positioning the patient at the fundus camera (Topcon NW400, Zeiss Visucam, or Canon CR-2), capturing non-mydriatic fundus images per AI screening protocol, uploading images to the autonomous DR AI (LumineticsCore or EyeArt), reviewing the AI-generated image quality flag for adequacy before releasing the study, and routing the AI result (refer / rescreen) to the supervising ophthalmologist, optometrist, or primary care provider with appropriate documentation under CPT 92229.[4],[5],[10]

Where your edge is

LumineticsCore (formerly IDx-DR) and EyeArt are FDA-cleared autonomous AI systems that diagnose diabetic retinopathy without a clinician reviewing the image: the OMT's interpretation role on DR screening has effectively been replaced by the AI at equipped sites. Your contribution at this task shifts to acquisition quality: the AI's sensitivity and specificity are calibrated to images acquired according to specific protocol requirements (camera distance, pupil size, image quality score threshold). An OMT who can consistently achieve adequate-quality images in challenging acquisition cases (media opacity, poor dilation, small pupil, patient with limited neck mobility) is more valuable than one who submits high rates of "rescreen" results that defeat the efficiency purpose of AI screening. Develop proficiency in dilation decisions, image quality troubleshooting, and patient coaching for difficult-to-image diabetic patients: this is the irreducibly human contribution on an otherwise AI-automated task.

AI is sitting alongside you hereDocument pre-test results and manage EHR data entry for AI-assisted physician workflow, entering bilateral VA, IOP, autorefraction, lensometry, CCT (pachymetry), and chief complaint into the ophthalmology EHR (Modernizing Medicine EMA, Nextech, Epic OpTime) structured data fields

Document pre-test results and manage EHR data entry for AI-assisted physician workflow, entering bilateral VA, IOP, autorefraction, lensometry, CCT (pachymetry), and chief complaint into the ophthalmology EHR (Modernizing Medicine EMA, Nextech, Epic OpTime) structured data fields; reviewing the AI-generated pre-visit summary and coding suggestion prior to the physician encounter; flagging anomalous data points (IOP elevation, significant VA change from baseline) with clinical context notes; and verifying that AI-suggested diagnostic order triggers (OCT due for glaucoma monitoring, HVF overdue per AMD surveillance protocol) match the patient's actual clinical status.[7],[8],[13]

Where your edge is

EHR AI tools (ModMed EMA, Nextech, Epic) are automating significant parts of the documentation and coding workflow in ophthalmology: pre-test data entered by the OMT feeds AI note templates and coding suggestions that the physician reviews and attests. This reduces the OMT's role from data transcription toward data quality assurance and AI output verification. The VA drop in the right eye is documented as cataract-related per last month's physician note, not a new event. Develop systematic habits for reviewing the patient's prior-visit data before entering today's measurements: this contextual awareness is what transforms OMT documentation from mechanical data entry into genuinely useful clinical input. Practices that deploy AI documentation tools increasingly value OMTs who can verify AI outputs rather than generate them from scratch.

AI is sitting alongside you herePerform OCT image acquisition and review AI-generated diagnostic reports, operating Zeiss CIRRUS HD-OCT, Topcon Maestro2, or Heidelberg Spectralis at the bedside to capture macular thickness maps, RNFL thickness scans (optic disc and ganglion cell), and OCT angiography (OCTA) as indicated by the physician workflow

Perform OCT image acquisition and review AI-generated diagnostic reports, operating Zeiss CIRRUS HD-OCT, Topcon Maestro2, or Heidelberg Spectralis at the bedside to capture macular thickness maps, RNFL thickness scans (optic disc and ganglion cell), and OCT angiography (OCTA) as indicated by the physician workflow; coaching patient fixation on the internal fixation target throughout each scan; assessing AI-generated signal strength index and automated segmentation quality flags before releasing the study; and queuing the AI-assisted RNFL trend analysis (GPA) or AMD macular map for physician review.[9],[6],[1]

Where your edge is

AI-integrated OCT platforms (CIRRUS GPA, Maestro2 single-button automated capture, HEYEX AI segmentation) have automated most of the image processing, analysis, and report generation that OMTs previously performed manually. The OCT machine now generates the RNFL trend line, the macular map, and the AMD volume measurement without OMT intervention: your value is concentrated in acquisition quality and patient management. The single most common reason an OCT study requires repeat is fixation loss during acquisition: the patient looks away during a critical scan segment. A skilled OMT who can coach a visually impaired, elderly, or cognitively impaired patient through many seconds of steady fixation while monitoring the live signal strength index on the scanning console delivers measurably better study completeness rates than AI or lower-skill staff. Develop systematic fixation coaching technique, learn the specific fixation targets and patient instructions for each OCT device your practice operates, and document your repeat scan rate as a personal quality metric.

Where ophthalmic medical technicians go next

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

What each move takes

A direction you could grow

Medical and Health Services Managers

Senior ophthalmic medical technologists with lead tech, charge tech, or ASC coordination experience are well-positioned for ophthalmic practice manager, ASC administrator, and eye care operations coordinator roles, tracked under Medical and Health Services Managers. As ophthalmology practices deploy AI imaging tools (LumineticsCore, EyeArt, Maestro2, CIRRUS AI), AI-integrated EHRs (ModMed EMA, Nextech), and AI-assisted surgical scheduling at scale, health systems and multi-location ophthalmology groups need practice managers who understand both the clinical workflow and the vendor evaluation, protocol governance, staff training, and quality-assurance dimensions of responsible AI deployment. The OMT who has operated these tools, trained peers, and audited AI output quality is the natural internal candidate for these roles when they open at a growing ophthalmology group. A healthcare administration certificate (MHA or CMPE: Certified Medical Practice Executive from MGMA) and ASCRS or AAO practice management coursework are the credentialing bridges.

What you'd add
  • · Healthcare practice administration: MGMA CMPE (Certified Medical Practice Executive) or MHA program with ambulatory care concentration; ophthalmology-specific track through AAO/ASCRS practice management curriculum
  • · Ophthalmic practice finance: Medicare fee-schedule billing for diagnostic services (CPT 92134 OCT, 92083 HVF, 92229 autonomous AI DR screening), ASC facility fee management, vision plan fee schedule contracting, ophthalmic surgical coding
  • · AI vendor management for ophthalmology: evaluating autonomous DR screening AI platforms (LumineticsCore, EyeArt, AEYE-DS), AI EHR tools (ModMed EMA, Nextech), and ophthalmic imaging AI (Maestro2, CIRRUS, HEYEX), contract terms, performance metrics, payer documentation for physician oversight protocols
  • · Staff management for ophthalmic clinical teams: JCAHPO credential verification, OMT scope-of-practice compliance by state, performance evaluation design for clinical technologist teams, AI-integrated workflow training programs
  • · Ambulatory surgical center operations: CMS ASC conditions for coverage, infection control for ophthalmic procedures, sterile processing oversight, intravitreal injection clinic operations including medication handling (cold-chain for anti-VEGF agents)
What it takesSome new skills to pick up
Tools of the era

How has the work of ophthalmic medical technicians changed since 1900?

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

  • Snellen chart, trial lens set, direct ophthalmoscope (pre-formal-training era)

    The ophthalmic assistant of the early twentieth century worked primarily with instruments that required no special calibration and produced no printout: a Snellen visual acuity chart on the wall, a box of trial lenses for manual refraction, and a direct ophthalmoscope the doctor would use after the assistant positioned the patient. Tonometry meant Schiotz indentation tonometry, a handheld device requiring the patient to lie flat while the examiner placed a weighted plunger on the cornea, and the assistant's job was to read the scale and record the number. There was no standard training for any of this. Each ophthalmologist taught their own assistant, and the assistant's competence was bounded by what the physician had time to teach.

  • Goldmann applanation tonometer + slit lamp (contact measurement era)

    Hans Goldmann and Theo Schmidt introduced the applanation tonometer in the mid-1950s, replacing Schiotz indentation tonometry as the clinical standard for intraocular pressure measurement. Goldmann applanation tonometry requires the patient to sit upright at the slit lamp, topical anesthetic to be instilled, the patient's cornea to be stained with fluorescein, and the examiner to align a biprism against the corneal apex under blue light. The result is far more accurate than Schiotz but also requires trained physical technique. This instrument made the ophthalmic assistant's technical competence clinically meaningful for the first time: a poorly performed GAT reading could lead to undertreated glaucoma. The slit lamp biomicroscope, already in clinical use since the 1920s but increasingly central to ophthalmology by the 1960s, similarly required the assistant to position patients precisely and adjust the instrument before each examination.

    Effect on the work

    The shift from Schiotz to Goldmann tonometry raised the skill bar for ophthalmic assistants, creating demand for trained rather than informally supervised staff and directly motivating the Georgetown program (1963) and JCAHPO (1969).

  • Fundus camera + fluorescein angiography (retinal imaging era)

    David Alvis and Harold Novotny performed the first fluorescein angiography in 1959 using a Zeiss fundus camera, opening a new dimension of retinal imaging that required a skilled photographer to capture a reproducible retinal image through the pupil. Commercial fundus cameras from Zeiss, Canon, Topcon, and Nikon became clinic fixtures through the 1960s and 1970s. Ophthalmic photography emerged as a distinct subspecialty within the technician role: the photographer operated the camera, dilated the patient, timed the fluorescein injection, and captured a sequence of images during the dye's transit through the retinal circulation. This was technically demanding work that required both clinical and photographic knowledge. JCAHPO later codified ophthalmic photography as a sub-specialty certification.

  • JCAHPO credentialing (COA/COT/COMT three-tier framework)

    The 1969 founding of JCAHPO transformed the ophthalmic assistant role from informal office help into a credentialed allied health profession. The organization developed multiple-choice and practical oral examinations to verify competency, and by the 1980s established the three-tier ladder: COA (Certified Ophthalmic Assistant), COT (Certified Ophthalmic Technician), and COMT (Certified Ophthalmic Medical Technologist). Each tier added procedural scope and scope-of-practice distinctions. By the mid-1980s, roughly 8,000 allied ophthalmic personnel held JCAHPO credentials. The credential was, and remains, voluntary rather than required by federal law, but organized ophthalmology practices increasingly required it for mid-to-senior positions.

    Effect on the work

    JCAHPO credentialing formalized a career ladder that had not previously existed. Certified staff commanded higher wages, and ophthalmology practices increasingly used the credential tiers as a hiring filter. The JCAHPO framework is the structural reason the occupation grew steadily even as diagnostic technology evolved rapidly.

  • Humphrey Field Analyzer (automated perimetry, from 1984)

    The Humphrey Field Analyzer, developed by Mike Patella and Prof. Anders Heijl and launched in 1984 by Humphrey Instruments (later acquired by Zeiss), replaced the hand-kinetic Goldmann manual perimeter as the clinical standard for visual field testing in glaucoma. The HFA runs automated static perimetry: the patient fixates on a central target and presses a button when peripheral light stimuli appear. The machine records responses and generates a threshold map. But the technician's role was not automated away; it was redefined. Patient instruction, fixation monitoring, real-time coaching on response behavior, and the judgment call of whether a test with elevated fixation losses was reliable enough to report became core OMT competencies. A poor visual field from a poorly coached patient could lead to incorrect glaucoma staging and missed progression.

    Effect on the work

    The HFA made visual field testing fast enough to perform routinely at every glaucoma visit, dramatically increasing the volume of perimetry in ophthalmology practices and the demand for trained technicians who could administer reliable tests.

  • Optical coherence tomography (OCT) commercial clinical use, from 1996

    The first commercial OCT device, produced by Humphrey Instruments, launched in 1996 following research by David Huang and colleagues at MIT. Clinical adoption was slow at first; then the adoption curve accelerated sharply: by 2004 over 10 million OCT imaging procedures had been performed worldwide. OCT transformed the diagnostic basis for managing glaucoma (RNFL thickness), age-related macular degeneration (macular thickness maps), and diabetic macular edema. For the ophthalmic technician, OCT created an entirely new battery of tests to learn and perform: positioning the patient at the scanning device, aligning the scan beam to the fovea or optic disc, coaching fixation during the scan, and reviewing signal strength metrics before releasing the study. By the 2010s, OCT had become the single most performed imaging test in ophthalmology, making OCT proficiency the defining technical skill of the modern OMT.

    Effect on the work

    The OCT expansion drove the largest single increase in ophthalmic technician demand since the Humphrey perimeter. Retina subspecialty practices, which perform OCT on nearly every patient encounter, were among the fastest-growing ophthalmology practice formats of the 2000s-2010s, and each required trained OMT staff to operate the imaging suite.

  • AI-integrated diagnostic imaging (autonomous DR screening, AI OCT interpretation)

    The FDA De Novo authorization of Digital Diagnostics' LumineticsCore (formerly IDx-DR) in 2018 marked the first autonomous AI diagnostic cleared for clinical use in any specialty: the system analyzes fundus images of diabetic retinopathy and issues a refer or rescreen result without requiring a clinician to review the image. Eyenuk's EyeArt, FDA-cleared in 2020, added multi-camera compatibility and 96% sensitivity for more-than-mild DR. AI-integrated OCT platforms (Topcon Maestro2 with Hood Report, Zeiss CIRRUS with Guided Progression Analysis, Heidelberg HEYEX with automated segmentation) began automating the image analysis and report generation that OMTs had previously performed manually. The OMT's role at AI-equipped sites shifted toward patient setup, image acquisition quality control, and AI output verification rather than interpretive review. This is the current frontier: the profession is reorganizing around the tasks that remain irreducibly human (physical patient contact, fixation coaching, topical medication administration, surgical assistance) as AI absorbs the interpretive and documentation tasks.

    Effect on the work

    Early data from ophthalmology practices deploying AI diagnostic lanes show increased throughput per technician session (more patients per day) without proportional headcount increases, consistent with productivity augmentation rather than direct displacement. The longer-term employment effect depends on how practices use the freed capacity.

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Ophthalmic Medical Technicians employment and pay by year

On record since1900
Latest US employment71,010 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$45,570 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+21.4% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 17 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
19695,000n/aEst., EntoKey Researched contextReport
198512,000n/aEst., IJCAHPO History Milestones Researched contextReport
200022,000n/aEst., IJCAHPO History Researched contextReport
201229,170$34,240BLS OEWS May 2012 Official statisticReport
201333,740$34,940BLS OEWS May 2013 Official statisticReport
201436,470$35,230BLS OEWS May 2014 Official statisticReport
201539,160$35,350BLS OEWS May 2015 Official statisticReport
201643,990$35,530BLS OEWS May 2016 Official statisticReport
201748,060$35,910BLS OEWS May 2017 Official statisticReport
201852,890$36,530BLS OEWS May 2018 Official statisticReport
201958,600$36,940BLS OEWS May 2019 Official statisticReport
202059,960$37,940BLS OEWS May 2020 Official statisticReport
202165,700$37,180BLS OEWS May 2021 Official statisticReport
202266,060$38,860BLS OEWS May 2022 Official statisticReport
202373,390$41,780BLS OEWS May 2023 Official statisticReport
202476,520$44,080BLS OEWS May 2024 Official statisticReport
202571,010$45,570BLS OEWS May 2025 Official statisticReport
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