XI. Allied Health & Select Other Occupations Model Components

Published 2025

In this module:

Modeling supply
Modeling demand

This module summarizes adaptation of the Health Workforce Simulation Model (HWSM) to project supply and demand for select allied health occupations and several other occupations (for example, pharmacists, podiatrists, and audiologists). Because of data limitations, which are discussed later, supply projections could only be made for 27 of the 35 occupations included in this component of the workforce modeling effort (Exhibit XI-1).

Exhibit XI-1: Allied Health and Select Other Occupations Modeled

**Pharmacy Services**
Occupation Categories	Supply Modeled	Demand Modeled
Pharmacists	Yes	Yes
Pharmacy technicians	Yes	Yes
Pharmacy aides	No	Yes

**Therapeutic and Respiratory Services**
Occupation Categories	Supply Modeled	Demand Modeled
Chiropractors	Yes	Yes
Podiatrists	Yes	Yes
Radiation therapists	Yes	Yes
Recreational therapists	Yes	Yes
Respiratory therapists	Yes	Yes

**Rehabilitation Services**
Occupation Categories	Supply Modeled	Demand Modeled
Occupational therapists	Yes	Yes
Occupational therapy assistants	Yes	Yes
Occupational therapy aides	No	Yes
Physical therapists	Yes	Yes
Physical therapist assistants	Yes	Yes
Physical therapist aides	No	Yes

**Dietary and Nutrition Services**
Occupation Categories	Supply Modeled	Demand Modeled
Registered dietitians	Yes	Yes
Dietetic technicians	No	Yes

**Vision and Hearing Services**
Occupation Categories	Supply Modeled	Demand Modeled
Optometrists	Yes	Yes
Opticians	Yes	Yes
Audiologists	Yes	Yes
Speech-language pathologists	Yes	Yes

**Diagnostic Laboratory Services**
Occupation Categories	Supply Modeled	Demand Modeled
Medical and clinical laboratory technologists	Yes	Yes
Medical and clinical laboratory technicians	Yes	Yes

**Diagnostic Imaging Services**
Occupation Categories	Supply Modeled	Demand Modeled
Diagnostic medical sonographers	Yes	Yes
Nuclear medicine technologists	Yes	Yes
Radiologic technologists and technicians	Yes	Yes
Magnetic resonance imaging technologists	Yes	Yes

**Other Treatment Support Occupations**
Occupation Categories	Supply Modeled	Demand Modeled
Cardiovascular technologists and technicians	Yes	Yes
Surgical technologists	Yes	Yes
Ophthalmic medical technicians	No	Yes

**Other Support Occupations**
Occupation Categories	Supply Modeled	Demand Modeled
Phlebotomists	Yes	Yes
Medical Assistants	No	Yes
Medical Transcriptionists	No	Yes

**Other**
Occupation Categories	Supply Modeled	Demand Modeled
Community health care worker services	No	Yes
Emergency medical technicians	Yes	Yes
Paramedics	Yes	Yes

The research team reaches out to professional associations representing various health professions, with associations representing the modeled health professions contacted approximately every 2-3 years. The team seeks to identify the best available data sources, discuss trends affecting workforce supply and demand, and provide the opportunity for feedback on preliminary findings. The information provided in this technical documentation and in HRSA reports does not necessarily reflect the views of the associations that responded. There may not be clear consensus on all assumptions.

Individuals from the following associations have participated:

American Association for Respiratory Care (AARC)
American Association of Medical Assistants (AAMA)
American Occupational Therapy Association (AOTA)
American Optometric Association (AOA)
American Physical Therapy Association (APTA)
American Podiatric Medical Association (APMA)
National Association of Boards of Pharmacy (NABT)
National Association of Community Health Workers (NACHW)
National Registry of Emergency Medical Technicians (NREMT)
Pharmacy Technician Certification Board (PTCB)
Society of Nuclear Medicine and Molecular Imaging (SNMMI)

Modeling supply

For the occupations where sufficient data is available to project future supply, multiple scenarios were modeled.

A Status Quo scenario extrapolates current trends in supply determinants:

Number and characteristics of current and new providers
Hours worked patterns
Attrition patterns

Alternative scenarios modeled the sensitivity of future supply to changes in key trends and assumptions. One set of scenarios models a ±10% change in the annual numbers of new graduates entering the workforce. Another set of scenarios reflects if attrition patterns were to change such that providers retire up to two years earlier or delay retirement by up to two years, on average, relative to historical retirement patterns.

A key challenge with modeling supply for allied health occupations is that many occupations have multiple channels for entry to the occupation (including on-the-job-training) so there is a lack of data on the number of new entrants. For many of these occupations (particularly aide occupations), pay is relatively low so there is easy exit from the occupation.

Estimating the base year workforce supply

The primary sources for data on current number and characteristics for the occupations modeled is the pooled 2019–2023 American Community Survey (ACS) supplemented with the Occupational Employment and Wage Statistics (OEWS) data and licensure counts from specialty associations. Multiple years of ACS or OEWS data were used to create a larger sample for each state to produce estimates of current supply by age, sex, and race/ethnicity. For ACS, a weighted average of twice the 2023 count plus the 2022 count divided by three was used. For OEWS, the average included twice the 2023 employment estimate plus the 2022 and 2024 employment estimate divided by four. This approach gave extra weight to the base year (2023) numbers, but also included data from adjacent years to smooth fluctuations that can be caused by sampling. Counts for the number of dietitians came from the Commission on Dietetic Registration. This allows for modeling a more precise category than the Standard Occupation Code category (dieticians and nutritionists) in ACS or OEWS. An estimate of the number of podiatrists came from the American Podiatric Medical Association (APMA) which is based on licensure files. An estimate for the number of radiation therapists came from the American Registry of Radiologic Technologists’ (ARRT) census of March 2024. Historical 2012–2016 OEWS data was used to reach separate starting supply numbers for medical and clinical laboratory technologists and medical and clinical laboratory technicians. In more recent OEWS and ACS data, these two occupations were combined. The starting estimate for Physical Therapists in 2023 came from the Federation of State Boards of Physical Therapy (FSBPT).

Modeling new entrants

New entrants were added to the workforce via a “synthetic” cohort. The size of the cohort is based on the number and characteristics of recent graduates in each occupation. The primary source for estimating new entrants in each occupation is the 2023 Integrated Postsecondary Education Data System (IPEDS). Data provided by associations is used instead if such data is available. The number of new entrants for registered dietitians is based on 2023 graduates' data from the Accreditation Council for Education in Nutrition and Dietetics. Physical therapist new entrant numbers in 2023 come from the Commission on Accreditation in Physical Therapy Education plus an estimate for the number of internationally educated physical therapists from the FSBPT. The number of new entrants for radiation therapists, nuclear medicine technologists, radiologic technologists and technicians, and magnetic resonance imaging technologists used the American Registry of Radiologic Technologists’ data on radiation therapy exams taken in 2023. The respiratory therapist number of entrants comes from 2023 accreditation data from the Commission on Accreditation for Respiratory Care. Finally, the number of new entrants for audiologists and speech-language pathologists is based on the 2022–2023 Communication Sciences and Disorders Education Survey.

Starting in 2023, there are new approaches for calculating the number of new entrants for pharmacy occupations and occupational therapists. For pharmacists, data on the sizes of upcoming classes were provided by the American Association of Colleges of Pharmacy. These data show that the number of pharmacist enrollments has declined significantly over the last several years. Using the ratio of enrollments to graduates in the latest year for which data is available, it is possible to calculate a predicted number of new pharmacists in future years. The model uses 11,968 for 2024, 11,163 for 2025, 9,927 for 2026, and 9,262 for 2027 through 2038. The model uses the same method with data from the American Occupational Therapy Association (AOTA) to decrease the number of new occupational therapists from 8,211 in 2024 to 7,623 in 2025 and later years. For pharmacy technicians, the data source for the number of new graduates is 2023 data on the number of pharmacy technician exams passed by the Pharmacy Technician Certification Board (PTCB) and the National Healthcareer Association (NHA).

Furthermore, the phlebotomist and medical and clinical laboratory technologists and technician new entrants' numbers are based on the 2023 IPEDS but also include analysis estimating how many people enter these occupations annually through on-the-job training.

Each new worker is assigned age, sex, and race that reflect the distributions seen in recent years (Exhibit XI‑2). For race and sex, 2023 IPEDS data on graduates by race and sex was used. To calculate the age distribution of new entrants to the workforce, consecutive years of 1-year ACS data were compared. The number of providers of a particular age (for example, age 29) were compared to the number of providers in the subsequent ACS annual file who were one year older (for example, age 30). The subsequent ACS file contains information on the workforce from the previous year plus any additions or subtractions to the workforce. In the above example, the difference between the number of providers at age 30 and the number of providers at age 29 in the previous year reflects the net number of new providers entering the workforce at age 29-30. With this information, the age distribution of new net entrants to the workforce was estimated. Multiple years of data were used to increase sample size by individual age and occupation. The number of new entrants and their age-sex distribution were assumed to remain constant during the projection period.

Some occupations (usually those titled as aides, technologists, or technicians) have data limitations that preclude projecting future supply. For occupations that do not require licensure or that have few educational or training requirements, there is insufficient data on the number of people newly entering these occupations. Likewise, occupations with easy entry often have high turnover rates. This creates challenges to obtain reliable supply forecasts.

Exhibit XI-2: Number and Demographics of New Entrants to Select Health Care Occupations

Dietary and Nutrition Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Registered Dietitians	4,248	89	72	5	9	14	62	34	0	4

Pharmacy Occupations
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Pharmacists	11,968-9,262	66	51	10	29	10	54	41	4	1
Pharmacy technicians	39,692	82	27	20	12	41	91	8	0	1

Rehabilitation Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Occupational therapists	8,211-7,623	91	71	6	12	11	60	37	2	1
Occupational therapy assistants	4,259	88	61	10	10	19	62	24	3	11
Physical therapists	12,899	63	70	4	16	10	51	46	1	2
Physical therapist assistants	6,312	62	62	7	11	20	89	1	0	10

Respiratory Care Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Respiratory therapists	6,305	73	49	15	14	22	41	38	16	5

Therapeutic Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Chiropractors	2,746	46	68	8	11	13	21	47	17	15
Podiatrists	545	43	51	10	31	8	3	33	39	25
Radiation therapists	945	79	67	7	10	16	40	21	32	7
Recreational therapists	707	88	70	13	5	12	59	8	10	23

Vision and Hearing Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Opticians	451	71	31	12	17	40	44	28	6	22
Optometrists	1,770	71	50	4	36	10	16	57	18	9
Audiologists	790	88	77	4	9	10	28	45	7	20
Speech-language pathologists	10,027	96	72	5	7	16	65	35	0	0

Diagnostic Laboratory Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Medical and Clinical Laboratory Technologists	6,331	78	55	10	17	18	93	4	0	3
Medical and Clinical Laboratory Technicians	6,871	84	51	15	11	23	93	4	0	3
Phlebotomists	13,518	89	39	16	11	34	74	3	9	14

Diagnostic Imaging Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Diagnostic Medical Sonographers	4,609	93	52	7	11	30	55	29	12	4
Nuclear Medicine Technologists	390	68	60	9	12	19	35	33	28	4
Radiologic Technologists and Technicians	11,489	76	61	7	9	23	68	21	10	1
Magnetic Resonance Imaging Technologists	2,768	59	29	7	20	44	41	31	23	5

Other Treatment Support Occupations
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Cardiovascular Technologists and Technicians	1,044	83	51	9	10	30	68	13	17	2
Surgical Technologists	6,508	85	50	14	9	27	76	22	2	0

Emergency Medical Services
Occupation	Annual Graduates ^a	Female %	White %	Black %	Other %	Hispanic %	<26 %	26-30 %	31-40 %	>40 %
Emergency Medical Technicians	17,639	38	64	6	7	23	94	0	0	6
Paramedics	9,271	33	71	5	6	18	67	27	6	0

Source: ^a2023 IPEDS for annual new graduates, except registered dietitians, pharmacists, physical therapists, radiation therapists, respiratory therapists, audiologists, speech-language pathologists, nuclear medicine technologists, radiologic technologists and technicians, magnetic resonance imaging technologists, and pharmacy technicians which use association data (see text). ^b2019–2023 ACS analysis.

Modeling workforce participation and workers leaving the workforce

Labor force participation rates for health care workers were calculated directly for individuals under age 50 using 2019–2023 ACS data. The analysis used information on whether the person is active in the workforce. Active is defined as working at least one hour per week in their profession. Each simulation year, HWSM models the propensity that a health care worker under age 50 becomes inactive and thus counts for 0 FTE supply. However, these individuals remain part of the supply model and are eligible to become active again in the following simulation year. The same process was used for physical therapists and physical therapy assistants using survey responses from the 2025 APTA Profile survey.

Health care workers can also leave the workforce of their current occupation permanently by changing careers. Each year, workers under age 50 have a small probability of being removed from the workforce based on observed career change using the Current Population Survey (CPS) Annual Social and Economic Supplement survey data. For audiologists and podiatrists, the sample size was too small for reliable estimates, so physicians were used as a proxy for podiatrists and speech-language pathologists were used as a proxy for audiologists. Pharmacy technicians were also used as a proxy for phlebotomists and registered dieticians as a proxy for medical and clinical laboratory technicians. While these workers may join other health care occupations, it is assumed that they are captured in the new graduate data for that occupation.

For health care workers at age 50 and over, the probability of retiring was modeled, with retirement probability increasing with age. Attrition patterns for each profession were based on 2019–2023 ACS data. These patterns were constructed based on a question asking whether the person is currently employed and whether they were employed last year. Health care workers flagged for attrition drop out of the supply entirely and do not return in later years.

Modeling hours worked

Ordinary Least Squares regression was used to model hours worked patterns for each health occupation. The dependent variable is total hours worked in the previous week. Explanatory variables consisted of age group, sex, race, and ACS survey year (2019–2023). The same process was used for physical therapists and physical therapy assistants using survey responses from the 2025 APTA Profile survey.

Estimates and projections consider the changing demographics of the workforce. They also account for average hours worked per week differing by age, sex, race, and occupation. Then, the expected number of hours worked by each professional is converted to FTE supply by dividing the total person-hours worked by 40. This creates a uniform standard of 1 FTE as working 40 hours per week regardless of the occupation. It also means that the initial FTE of an occupation can differ from the actual count of persons employed in the occupation.

Modeling state-level supply and migration

States differ in estimated level of supply adequacy for various health occupations. Supply modeling is done at the state level where sufficient data are available, though for some smaller occupations the workforce projections are only reported at the national level. In the ACS and OEWS, some occupations do not have totals reported in every U.S. state. Occupations affected include chiropractors, podiatrists, radiation therapists, audiologists, and occupational therapy assistants.

For occupations with sufficient state-level data, HWSM models the movement of health care workers across states. This is accomplished in two steps. First, a logistic regression1 on 2019–2023 ACS data estimates the probability of migrating to another state for the under 50 population. This regression is a function of age group, sex, race, the current state’s population, and a year indicator. Applying the prediction equation, HWSM calculates probabilities for each health care worker and compares probabilities to a random number generated on a uniform distribution to simulate moving to another state. Based on the destination state distribution observed in 2014-2023 ACS data for health care workers who changed their residence states, a new state is assigned to individuals who relocated. The model uses more years of ACS data to increase sample size for this distribution because the number of individuals observed moving into each state in the ACS is small.

Supply scenarios

A Status Quo scenario models the supply implications if current patterns continue through the projection period.

Specifically, this scenario holds constant:

Number and characteristics of current and new providers
Patterns of hours worked
Patterns of workers leaving the workforce

Alternative scenarios allow us to gauge the sensitivity of future supply to key trends and assumptions. These scenarios reflect future uncertainty.

These scenarios include:

10% higher annual numbers of new graduates entering the workforce
10% lower annual numbers of new graduates entering the workforce
Workers retire two years earlier than current patterns
Workers retire two years later than current patterns

Concerns about provider burnout throughout the health care workforce have been prevalent in recent years, including among the allied health workforces.2 3 4 Hence, there is likely higher probability of allied health providers accelerating retirement versus delaying retirement.

Modeling demand

The Demand Modeling Overview module provides an overview of the data sources and approaches used to model demand for health care services and providers. Here, additional details are provided specific to modeling demand for the health occupations covered in this analysis.

Demand for workers in many occupation categories is based on rates of patient-clinician encounters across employment settings. This starts with the industry distribution estimated from analysis of ACS mapped to employment settings (Exhibit XI‑3). For occupations that work in provider office, outpatient, and home health settings the growth in demand for health care workers is tied to growth in demand for visits in those respective settings (Exhibit XI‑4). For some occupations total visits are the proxy for demand, while for other occupations a subset of visits is the proxy for demand. For example, demand for chiropractors is driven by the projected number of visits to the offices of chiropractors. Due to a lack of data on visits to opticians, optometrist visits are used as a proxy for demand for both opticians and optometrists. That is, the growth rate in demand for eye care (as modeled by projected growth in patients seeking optometrist services) is used as a proxy for growth rate in demand for both optometrists and opticians. Demand for health care workers in hospital inpatient settings is modeled using either total inpatient days or a subset of inpatient days directly tied to the occupation.

Dividing (a) total national health care utilization by (b) total health care workers (plus estimated starting year shortages), by delivery site, provides a national ratio (Exhibit XI‑5). Under the Status Quo scenario, these ratios are assumed to be constant over time. These ratios are not estimates of the number of patient encounters with the health care worker during the course of the year. Rather, these ratios simply relate growth in demand for health care workers to the growth in demand for health care services in the setting in which they work.

Demand for pharmacists, pharmacy technicians, and pharmacy aides is tied to the number of prescriptions written. Using the pooled files of the latest available data from the National Ambulatory Medical Care Survey (NAMCS) and the outpatient National Hospital Ambulatory Medical Survey (NHAMCS), the average number of prescriptions written during an office, outpatient, or emergency visit by medical specialty or diagnosis category associated with the visit were modeled.5 The 2014-2016 NAMCS files were pooled, which report detailed physician specialty, to model prescriptions by visit to a particular specialty. Later years of NAMCS do not include detailed physician specialties, so the distribution of detailed specialties in the pooled 2014-2016 NAMCS data were applied to the overall weighted estimates of the recent 2019 NAMCS. The most recent NHAMCS outpatient public use files available for analyzing prescriptions are 2007-2011. The 2012-2017 NHAMCS outpatient survey data is currently on hold due to data quality issues, and data was not collected for 2018-2020.

When multiplied by the projected number of visits, this provides a projection of future prescriptions written. The assumption is that the ratio of filled to written prescriptions will remain constant over time. Medications prescribed for hospital inpatient is modeled as a ratio of national inpatient days to national number of pharmacists working in hospitals. The projected growth in demand for prescriptions in ambulatory settings is used to project growth in demand for community-based pharmacists and those working in mail-order pharmacies. The projected growth in hospital inpatient days is used to project growth in demand for hospital-based pharmacists.

Emergency medical technicians (EMTs) and paramedics provide a wide range of services—many of which do not show up in medical billing records. The number of ambulance arrivals and transfers between hospitals is used as a proxy for demand for EMTs and paramedics, based on analysis of the 2021-2022 NHAMCS emergency department file and the 2022 NIS which has discharge information indicating if a patient was transferred to another hospital.

The Status Quo scenario starts with the assumption that national demand equals supply plus a current shortfall. The magnitude of the current shortfall is calculated as the estimated shift up in demand caused by COVID-19 becoming endemic. Additionally, selected allied health occupations have revised shortage estimates to incorporate both increased demand and supply-side constraints. As described in the Demand Modeling Overview module, an increase in demand is estimated for ambulatory care and hospital inpatient care associated with COVID-19 becoming endemic. In general, increase in demand due to COVID-19 hospitalizations and ambulatory visits were adjusted downwards for allied health occupations compared to previous years. This revision reflects recent trends in lower hospitalizations based on estimates published by CDC.6

The supply-side shortage estimates are based on an analysis of the combined 2019-2024 BLS OEWS data.7 By reviewing annual employment trends, employment levels for certain occupations (including dietetic technicians, nuclear medicine technologists, occupational therapy aides, physical therapy aides, podiatrists, radiation therapists, recreational therapists, & medical transcriptionists) were observed to consistently decrease. For these occupations, a shortfall was calculated by comparing recent employment levels to the 2019 estimates, which provided a conservative estimate of shortages due to supply constraints. Additionally, for some occupations, the supply-side shortage estimate was adjusted to account for reduced demand. This reduction was primarily seen in nursing home settings, where a decline in the number of residents occurred between 2019 and 2023. Adjustments were applied to occupations such as dietetic technicians, occupational and physical therapy aides, and recreational therapists which have a significant presence in nursing home settings. These adjustments account for the demand reduction linked to the decline in nursing home residents between 2019 and 2023. However, the impact of this demand reduction on the overall shortage estimates for these occupations were minimal. Shortage estimates for physical therapists comes from literature-based shortage assumptions based on a recent workforce study published by the APTA.8

For allied health occupations, the estimated increase varies by occupation but is about 1-2% increase for most allied health occupations. This shift up in demand, despite supply being relatively static, creates a small shortfall that is likely a conservative estimate of shortfall as there is a growing perception of shortfall across many allied health occupations but little data to quantify the shortfall.9 The Status Quo scenario then extrapolates current patterns of care into the future. Predicted probabilities of health care use were applied to project health care service use specific to the settings where these professionals are employed.

Modeling demand for community health workers (CHWs) is challenging because CHWs work in many different capacities—with approximately 62% working in state or local government programs. Employment opportunities for CHWS are driven largely by government funding, while the need for CHWs is substantial as indicated by disparities in health outcomes by socioeconomic circumstances, by race/ethnicity, and by other dimensions such as geographic location and studies showing the cost-effectiveness of using CHWs.10 11 12 13 For CHWs working in hospital inpatient settings, total inpatient days are used as the proxy for service demand. For CHWs working in ambulatory settings or home health, visits for clinical social workers are used as proxy for demand. For CHWs working in government programs, total population is used as the proxy for demand. Hence, projected growth in demand for CHWs is a weighted average of growth in demand for hospital inpatient days, ambulatory visits, home health visits, and population growth with the weights corresponding to the number of FTEs working in the various employment settings.

Exhibit XI-3: Distribution (%) and FTEs by Employment Setting: Allied Health and Select Other Occupations

Pharmacy Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Pharmacists ^a	100%	58%	33%	-	-	-	-	1%	8%	-
Pharmacists ^a	357,940	208,288	116,390	-	-	-	-	3,739	29,523	-
Pharmacy technicians ^a	100%	77%	17%	<1%	-	-	-	-	5%	-
Pharmacy technicians ^a	419,370	324,061	70,240	2,057	-	-	-	-	23,012	-
Pharmacy aides^b	100%	90%	7%	-	-	-	-	-	3%	-
Pharmacy aides^b	41,820	37,733	2,732	-	-	-	-	-	1,354	-

Therapeutic and Respiratory Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Chiropractor ^a	100%	97%	<1%	-	-	-	-	-	2%	-
Chiropractor ^a	72,550	70,670	371	-	-	-	-	-	1,509	-
Podiatrists ^a	100%	81%	17%	-	-	-	-	<1%	<1%	-
Podiatrists ^a	20,530	16,645	3,529	-	-	-	-	179	177	-
Radiation therapists^a	100%	22%	71%	-	-	-	-	<1%	7%	-
Radiation therapists^a	21,500	4,660	15,208	-	-	-	-	115	1,517	-
Recreational therapists ^b	100%	6%	42%	<1%	13%	11%	1%	<1%	25%	-
Recreational therapists ^b	16,680	1,057	7,069	146	2,096	1,844	176	95	4,197	-
Respiratory therapists ^a	100%	6%	84%	2%	2%	<1%	-	-	6%	-
Respiratory therapists ^a	123,710	7,257	103,761	2,086	2,827	856	-	-	6,923	-

Rehabilitation Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Occupational therapists ^a	100%	31%	27%	7%	6%	4%	16%	<1%	8%	-
Occupational therapists ^a	150,380	46,858	40,860	10,146	9,690	6,762	23,779	761	11,524	-
Occupational therapy assistants ^b	100%	46%	18%	6%	16%	2%	5%	-	6%	-
Occupational therapy assistants ^b	40,030	18,559	7,181	2,518	6,502	823	2,115	-	2,331	-
Occupational therapy aides ^b	100%	52%	31%	2%	10%	-	1%	-	4%	-
Occupational therapy aides ^b	7,180	3,751	2,223	109	747	-	92	-	258	-
Physical therapists ^a	100%	51%	26%	7%	4%	3%	3%	-	7%	-
Physical therapists ^a	350,280	177,094	90,845	24,443	14,071	10,583	9,701	-	23,545	-
Physical therapy assistants ^b	100%	54%	21%	12%	9%	1%	-	-	3%	-
Physical therapy assistants ^b	116,540	63,470	24,292	13,582	10,869	1,322	-	-	3,005	-
Physical therapy aides^b	100%	79%	17%	-	2%	-	-	-	2%	-
Physical therapy aides^b	48,130	37,812	8,218	-	1,080	-	-	-	1,020	-

Dietary and Nutrition Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Dietitians and nutritionists ^a	100%	23%	32%	-	7%	3%	9%	2%	24%	-
Dietitians and nutritionists ^a	92,400	20,872	29,704	-	6,866	2,757	8,001	1,818	22,383	-
Dietetic technicians ^b	100%	3%	46%	-	27%	10%	<1%	-	14%	-
Dietetic technicians ^b	27,870	817	12,849	-	7,437	2,755	245	-	3,766	-

Vision and Hearing Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Optometrist ^a	100%	94%	3%	-	-	-	-	2%	1%	-
Optometrist ^a	43,540	40,764	1,463	-	-	-	-	672	641	-
Opticians ^a	100%	99%	-	-	-	-	-	-	<1%	-
Opticians ^a	71,000	70,494	-	-	-	-	-	-	506	-
Audiologist ^c	100%	46%	28%	-	-	<1%	8%	6%	12%	-
Audiologist ^c	18,560	8,547	5,141	-	-	139	1,401	1,179	2,153	-
Speech-Language pathologists ^a	100%	14%	12%	5%	7%	1%	51%	3%	7%	-
Speech-Language pathologists ^a	183,810	25,366	22,425	9,742	12,775	2,481	93,100	4,687	13,234	-

Diagnostic Laboratory Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Medical and clinical laboratory technologists ^b	100%	39%	45%	-	-	<1%	-	4%	12%	-
Medical and clinical laboratory technologists ^b	164,790	64,358	73,865	-	-	1,044	-	6,171	19,734	-
Medical and clinical laboratory technicians ^b	100%	39%	45%	-	-	<1%	-	4%	12%	-
Medical and clinical laboratory technicians ^b	160,510	62,314	71,947	-	-	1,017	-	6,011	19,221	-

Diagnostic Imaging Services
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Diagnostic medical sonographers ^b	100%	38%	59%	-	-	-	-	<1%	2%	-
Diagnostic medical sonographers ^b	79,440	29,982	47,091	-	-	-	-	708	1,659	-
Nuclear medicine technologists ^b	100%	25%	73%	-	-	-	-	<1%	<1%	-
Nuclear medicine technologists ^b	20,350	5,091	14,934	-	-	-	-	148	177	-
Radiologic technologists ^b	100%	33%	61%	-	-	-	-	<1%	5%	-
Radiologic technologists ^b	215,420	72,029	130,998	-	-	-	-	1,565	10,828	-
Magnetic resonance imaging technologists ^b	100%	37%	61%	-	-	-	-	<1%	1%	-
Magnetic resonance imaging technologists ^b	43,650	16,019	26,703	-	-	-	-	341	588	-

Other Treatment Support Occupations
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Cardiovascular technologists and technicians ^b	100%	19%	79%	-	-	-	-	<1%	1%	-
Cardiovascular technologists and technicians ^b	57,730	11,095	45,510	-	-	-	-	488	637	-
Surgical technologists ^b	100%	26%	70%	-	-	-	-	<1%	4%	-
Surgical technologists ^b	106,280	27,161	74,231	-	-	-	-	603	4,286	-
Ophthalmic medical technicians ^b	100%	95%	4%	-	-	-	-	-	<1%	-
Ophthalmic medical technicians ^b	72,400	68,842	2,984	-	-	-	-	-	574	-

Other Support Occupations
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Phlebotomists ^b	100%	60%	36%	-	-	-	-	-	5%	-
Phlebotomists ^b	135,530	81,164	48,193	-	-	-	-	-	6,173	-
Medical assistants ^b	100%	76%	16%	-	<1%	1%	-	<1%	5%	-
Medical assistants ^b	770,540	585,010	124,447	-	6,293	10,256	-	7,579	36,955	-
Medical transcriptionists ^b	100%	51%	11%	-	-	-	-	-	39%	-
Medical transcriptionists ^b	76,810	38,829	8,381	-	-	-	-	-	29,600	-

Other
Occupation	Total	Ambulatory	Hospital	Home Health	Nursing Home	Residential Care	School Health	Academia	Other	Emergency Services
Community health workers ^b	100%	20%	11%	2%	<1%	3%	1%	2%	61%	-
Community health workers ^b	58,980	11,620	6,600	950	202	1,535	744	1,310	36,019	-
Emergency medical technicians ^a	100%	-	-	-	-	-	-	-	-	100%
Emergency medical technicians ^a	141,140	-	-	-	-	-	-	-	-	141,140
Paramedics ^a	100%	-	-	-	-	-	-	-	-	100%
Paramedics ^a	152,150	-	-	-	-	-	-	-	-	152,150

Note: Estimates represent FTEs defined as working 40 hours/week. Numbers may not sum to 100% and totals may differ from the online HRSA projections dashboard because of rounding. Total FTE demand includes estimated starting year shortages across the allied health occupations.

Employment Distribution Source: ^a2022 & 2023 1-year American Community Survey; ^b2022 & 2024 BLS Occupational Employment and Wage Statistics; ^c2022 & 2023 American Speech-Language-Hearing Association Member and Affiliate Profile

Exhibit XI-4: Health Care Workload Driver, by Care Delivery Site and Occupation

Delivery Sites (Units)
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)	Nursing Home (Residents)	Residential Care (Residents)	School Health (Population age 5-17)	Academia (Population age 18-25)	Other (Population total)	Emergency Services (Visits & Discharges)
All occupations working in care delivery site	Varies by occupation	Varies by occupation	Varies by occupation	1,249,180	1,119,590	53,302,600	35,883,820	334,914,900	4,514,000

Pharmacy Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)
Pharmacy technicians	3,161,120,000 ^a	169,306,000 ^p
Pharmacy aides
Pharmacists

Therapeutic and Respiratory Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Chiropractor	172,490,000 ^b	1,358,000 ^q	-
Podiatrists	14,250,000 ^c	1,358,000 ^q	-
Radiation therapists	33,107,000 ^d	37,900 ^r	-
Recreational therapists	1,121,913,000 ^e	169,306,000 ^p	48,428,000 ^y
Respiratory therapists	8,757,000 ^f	8,711,000	48,428,000 ^y

Rehabilitation Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Occupational therapists	256,766,000^g	1,358,000 ^q	2,153,000 ^z.i
Occupational therapy assistants
Occupational therapy aides
Physical therapists		19,327,007 ^q.i	1,291,000 ^z.ii
Physical therapy assistants
Physical therapy aides

Dietary and Nutrition Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Dietitians and Nutritionists	972,246,000 ^h	169,306,000 ^p	48,428,000 ^y
Dietitians technicians	972,246,000 ^h	169,306,000 ^p	-

Vision and Hearing Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Optometrist	41,694,000 ⁱ	94,000 ^t	-
Opticians	41,694,000 ⁱ	94,000 ^t	-
Audiologist	20,384,000 ^j	189,000 ^u	-
Speech-Language Pathologist	20,384,000 ^j	189,000 ^u	48,428,000 ^y

Diagnostic Laboratory Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)
Medical and clinical laboratory technicians	972,246,000 ^h	314,221,000 ^x
Medical and clinical laboratory technologists	972,246,000 ^h	314,221,000 ^x

Diagnostic Imaging Services
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)
Diagnostic medical sonographers	972,246,000 ^h	314,221,000 ^x
Nuclear medicine technologists	7,008,000 ⁿ	37,900 ^r
Radiologic technologists	7,008,000 ⁿ	37,900 ^r
Magnetic resonance imaging technologists	1,121,913,000 ^e	314,221,000 ^x

Other Treatment Support Occupations
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)
Cardiovascular technologists and technicians	26,302,000 ^k	34,494,000 ^v
Surgical technologists	268,733,000 ^l	50,732,000 ^w
Ophthalmic medical technicians	91,069,000 ^m	94,000 ^t

Other Support Occupations
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Phlebotomists	1,121,913,000 ^e	169,306,000 ^p	-
Medical assistants		314,221,000^x	48,428,000 ^y

Other
Occupation	Ambulatory (Visits)	Hospital (Inpatient Days & Emergency Visits)	Home Health (Visits)
Community health workers	53,167,000 ^o	169,306,000 ^p	5,587,000 ^z.iii

Source: 2023 HWSM status quo results. Growth in demand for health care use (for example, ambulatory visits, inpatient days) is used as a proxy for growth in demand for diagnostic services. Growth in demand for arrivals by ambulance and ambulance-driven patient transfers is used as a proxy for growth in demand for EMT/paramedic emergency services.

Ambulatory drivers – ^aNumber of prescriptions associated with office & outpatient visits; ^bChiropractor office & outpatient visits; ^cPodiatrist visits; ^d Hematology & Oncology visits; ^eTotal physician office & outpatient visits; ^fPulmonology visits; ^gOccupational therapist & physical therapist visits; ^hTotal physician office visits; ⁱOptometrist visits; ^jOtolaryngology visits; ^kCardiology related service visits; ^lSurgery service visits; ^mOphthalmology visits; ⁿRadiology visits; ^oSocial worker visits

Inpatient drivers – ^pTotal inpatient days; ^qPMR inpatient days; ^q.i Cardiology, Neurology & PMR inpatient days; ^r Radiology physician FTE;^sPulmonology inpatient days; ^tOphthalmology inpatient days; ^uOtolaryngology inpatient days; ^vCardiology related inpatient days; ^wSurgery related inpatient days; ^xTotal inpatient days and emergency visits

Home Health drivers – ^yTotal home health visits; ^z.iOccupational therapist visits; ^z.iiPhysical therapist visits; ^z.iiiSocial worker visits

Exhibit XI-5: Health Workforce Staffing Ratios by Care Delivery Site (national volume ÷ national FTEs in employment setting)

Delivery Sites (Units per Provider)
Occupation	Ambulatory (Visits)	Hospital (Days)	Home Health (Visits)	Nursing Home (Residents)	Residential Care (Residents)	School Health (Population age 5-17)	Academia (Population age 18-25)	Other (Population total)	Emergency Services (Visits & Discharges)
Pharmacists	14,626	1,402	-	-	-	-	9,249	10,932	-
Pharmacy technicians	8,881	2,194	21,435	-	-	-	-	13,250	-
Pharmacy aides	84,188	62,264	-	-	-	-	-	248,488	-
Chiropractors	2,298	3,444	-	-	-	-	-	208,969	-
Podiatrists	977	439	-	-	-	-	228,895	2,156,817	-
Radiation therapists	7,220	3	-	-	-	-	316,376	224,409	-
Recreational therapists	1,190,521	26,874	371,286	669	681	340,551	42,626	89,546	-
Respiratory therapists	1,158	81	22,287	424	1,255	-	-	46,439	-
Occupational therapists	4,956	30	192	117	150	2,027	-	26,285	-
Occupational therapy assistants	11,941	163	738	166	1,174	21,747	-	123,988	-
Occupational therapy aides	123,963	1,107	35,726	3,029	-	1,050,256	-	2,346,328	-
Physical therapists	1,578	232	57	97	115	5,980	-	15,480	-
Physical therapist assistants	4,453	876	105	127	933	-	-	122,683	-
Physical therapist aides	7,695	2,665	-	1,310	-	-	-	372,171	-
Dietitians and Nutritionists	43,725	5,350	-	171	381	6,253	18,530	14,046	-
Dietetic technicians	1,389,541	15,394	-	196	475	254,693	-	103,896	-
Optometrists	950	60	-	-	-	-	49,612	485,039	-
Opticians, dispensing	545	-	-	-	-	-	-	608,929	-
Audiologists	2,339	36	-	-	7,890	37,313	29,866	152,592	-
Speech-Language Pathologists	737	8	4,557	90	414	525	7,018	23,199	-
Cardiovascular technologists and technicians	2,463	788	-	-	-	-	76,348	546,691	-
Surgical technologists	9,426	651	-	-	-	-	56,728	74,455	-
Ophthalmic medical technicians	1,331	32	-	-	-	-	-	586,939	-
Medical & clinical technologists	14,757	4,131	-	-	1,041	-	5,646	16,481	-
Medical & clinical technicians	15,146	4,240	-	-	1,068	-	5,795	16,915	-
Diagnostic medical sonographers	31,133	6,406	-	-	-	-	48,666	193,799	-
Nuclear medicine technologists	1,690	3	-	-	-	-	297,199	2,322,294	-
Radiologic Technologists and Technicians	94	0	-	-	-	-	22,264	30,027	-
Magnetic resonance imaging technologists	74,174	12,462	-	-	-	-	111,479	603,728	-
Phlebotomists	13,269	3,372	-	-	-	-	-	52,078	-
Medical assistants	1,928	2,539	-	200	110	-	4,761	9,113	-
Medical transcriptionists	32,241	41,834	-	-	-	-	-	12,626	-
Community health workers	4,584	25,702	5,895	6,195	731	71,765	27,448	9,316	-
Emergency medical technician	-	-	-	-	-	-	-	-	228
Paramedics	-	-	-	-	-	-	-	-	241

Source: 2022 & 2023 1-year American Community Survey; 2022 - 2024 BLS Occupational Employment and Wage Statistics; HWSM projections

Note: Staffing Ratio denominators are based on active supply headcount for each health occupation and not FTEs, defined as working 40 hours/week. Final demand projections for all occupations reported in Exhibit XI-3 are scaled to supply FTEs, defined as working 40 hours/week, plus estimated starting year shortages.

Not all patients will encounter the health care worker during a visit or stay. Consequently, these ratios are not estimates of provider-patient encounters but simply national volume of the workload measure in each setting divided by national FTEs working in that setting.

Demand scenarios

As with other health occupations, HWSM models demand for allied health workers under two scenarios—a Status Quo scenario and a Reduced Barriers scenario.

The Status Quo scenario models a combination of pre and post-pandemic (2018-2022) national patterns of how people seek health care services plus estimates of demand for acute and Long COVID care as COVID-19 becomes endemic. Care seeking patterns are based on peoples’ characteristics and are projected to continue over the projection period. This scenario captures geographic variation in demographics, health risk factors, disease prevalence, insurance coverage, level of rurality, and household income that can affect demand for health care services. Similarly, the scenario captures population growth and aging—and the associated implications for disease prevalence and other health risk factors—over the projection horizon. This scenario evaluates whether the nation’s future allied health workforce is sufficient to provide at least the base year level of care.

The Reduced Barriers scenario estimates the number of allied health worker FTEs required if populations that historically faced barriers to accessing health care services demonstrated care use patterns comparable to populations perceived to have fewer barriers to accessing care. It models if everyone in the United States used health care services at the same rate as a population with the lowest level of barriers to accessing care.

This population is:

Non-Hispanic white
Living in metropolitan areas
With medical insurance

This scenario highlights that national efforts to improve health equity could require a larger allied health workforce as demand for diagnostic services, pharmaceuticals, and other health care services would rise under the modeled scenario.

Fecha de la última revisión:

December 2025

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