Federal Practitioner

Often disguised as comorbid conditions, nonhealing and chronic wounds have emerged as a silent epidemic that affects about 6.5 million Americans.^1-3 In 2023, estimated US wound care costs were $126.86 billion.⁴ About 1% to 2% of individuals worldwide will experience a chronic wound in their lifetime. The Veterans Health Administration reported 277,000 inpatient and outpatient encounters for ulcers in 2011, including chronic ulcers of the lower extremity due to diabetes, venous disease, or arterial disease.⁵ Associated costs of chronic wounds are expected to increase as the populations of developed countries age.⁶ Effective treatment of chronic wounds requires a nuanced understanding of complex wound pathophysiology, best practices in interdisciplinary and multidisciplinary wound care, and advanced wound care technologies.^7,8

The typical 4-year medical school curriculum, followed by residency, offers little in the way of formal didactic training in wound care.^9,10 Without specialized and advanced fellowship training dedicated to wound care, health care will lack specialists prepared to manage complex wounds. As a result, wound care-related difficulties may be exacerbated by prolonged recovery time, increased costs, productivity loss, and increased mortality risk.⁸ Wound care is a growing field of study and practice, and there is a critical need for rigorous training, research, and quality improvement efforts to enhance outcomes for patients with nonhealing wounds.⁵

One of the most direct ways to address the need for more physicians with specialty training in wound medicine is to implement a comprehensive training curriculum for advanced wound care practice. Although specialized advanced wound care fellowships are available, the curricula primarily detail rotation names and areas for practice without accompanying competencies, milestones, or entrustable professional activities.¹¹ Furthermore, wound care is not recognized as a subspecialty by the Accreditation Council for Graduate Medical Education (ACGME).

This article synthesized the literature and integrated innovative, evidence-based practices into a curriculum for a formal advanced fellowship training program. To our knowledge, no comprehensive wound care curriculum is publicly available that includes rotations, competencies, milestones, entrustable professional activities, and 360-degree evaluation forms.

Program Development

The advanced wound care fellowship program started in January 2014 at the Michael E. DeBakey Veterans Affairs Medical Center in affiliation with the Baylor College of Medicine. The fellowship program was originally designed for geriatrics fellows to extend the 1-year fellowship for an additional year to learn wound care. It has been adjusted to address formal program goals and objectives, competencies, milestones, entrustable professional activities, and evaluations, with the goal of developing an example curriculum for wound care fellowships across specialties. Although the ACGME does not recognize a wound care subspecialty, this curriculum complies with the ACGME 1-year fellowship common program requirements.^12,13

Scoping Review

A scoping literature review of Google Scholar and PubMed was performed using the medical subject heading terms “wound care + curriculum” and “wound + care + curriculum” to find advanced wound care medical training, fellowship programs, boards, and related ACGME-accredited specialty curricula. The local wound care fellowship program was initially implemented based on an informal literature review by faculty and their respective contributions to curriculum (ie, process establishing wound care-specific competency domains in accordance with ACGME accreditation competency requirements of 1-year fellowships). ^12,13 Standing program practice-based competencies and activities were examined and determined to align with best practices. This scoping review considered additional competencies, competency domains, and entrustable professional activities of reputable wound care fellowship training programs (eg, University of Chicago at Illinois and Wake Forest School of Medicine),^8,11,14 a specialty wound care board (American Board of Wound Medicine and Surgery),¹⁵ an international wound specialist professional society (European Union of Medical Specialists), ¹⁶ and recommended curriculum guidelines for wound care residency programs.¹⁷ ACGME-accredited specialty and subspecialty milestones professional activities were examined, including vascular surgery,¹⁸ plastic surgery,¹⁹ dermatology, ²⁰ foot and ankle,²¹ orthopedic surgery,²² spinal cord injury,²³ and geriatric medicine.²⁴

The competencies, milestones, and entrustable professional activities were compiled and redundancies were eliminated. Wound care specialists from geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy examined the findings and suggested eliminating redundancies, irrelevant content, and content that fell below the minimal expected level of competence for an advanced medical specialist in wound care. An expert consensus meeting further refined items presented to the panel before unanimous consensus resulted in the final set of curriculum competencies, milestones, and entrustable professional activities.

Training Program Feedback

We developed a comprehensive wound care curriculum for an advanced physician fellowship training program based on the streamlined competencies, milestones, and entrustable professional activities (Appendix). Multiple wound care experts from various interdisciplinary backgrounds reached consensus to establish this fellowship curriculum as adaptable for use across training settings. The training program is 12 core rotations and 2 elective rotations (Table 1). Additionally, we developed wound care evaluation forms for faculty-, peer-, and self-assessment of trainees which were adapted from an evidence-based 360-degree evaluation template.²⁵ Suggestions for structured, advanced didactics are in Table 2.

Seventeen fellows have successfully matriculated through the wound care training program. Although wound care certification is not required to work as a wound care specialist, after completion of this fellowship, graduates are able to sit for a wound care certification examination. The American Board of Wound Medicine and Surgery (ABWMS) and the American Board of Wound Management (ABWM) allow physicians to take a certification examination after 1 year of a dedicated wound fellowship program, instead of the typical wound care practice experience ≥ 3 years.

The Clinical Wound Care Fellowship Program collected data for program improvement, and 15 alumni responded (response rate, 88%) to a survey using a 5-point Likert scale. Respondents indicated high mean scores for overall satisfaction (4.7), instructional methods (4.7), program enjoyment (4.7), teaching materials (4.6), and relevance (4.6). All respondents indicated that the fellowship prepared them for a career in wound care as well as their current employment, and 13 of 15 (87%) reported they obtained immediate relevant postfellowship wound care positions and stated that the fellowship prepared them for their current roles. Nine respondents (69%) reported that they were engaged in wound care ≥ 26% of work time. Six respondents (46%) worked in private practice, 3 (23%) at academic medical centers, and 2 (15%) at government- funded hospitals. Four respondents indicated they were board certified in wound care. Program alumni are currently involved in scholarly activities, including 8 in quality improvement and 3 in research.

Discussion

An easily accessible, comprehensive wound care fellowship curriculum has not been previously developed or published. This limited the sources that informed this curriculum. However, the developmental process for this curriculum was robust, as the authors reviewed previously published materials related to wound care, including: 1) descriptive overviews of wound care fellowships; 2) details of month-long rotations for medical students and residents; and 3) practices of the specific environment in which this curriculum was created. Confidence in the practical nature of the curriculum can be assumed, as the experts involved in the development process represented diverse physician specializations, including geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy.

Most wound care clinicians have not completed a formal comprehensive fellowship program. Instead, due to the lack of a comprehensive training curriculum, clinicians have had to use various continuing medical education programs and practice in a wound care setting for ≥ 3 years to be eligible for certification in the specialty. This curriculum will help academic medical centers develop their own fellowship programs, enabling new wound care clinicians to attain certifications more efficiently. As more fellowship programs develop, the goal would be to obtain recognition as an ACGME specialty and standardize the training and competencies for graduates of wound care fellowships.

Conclusions

As new wound care fellowships develop, wound care may become formally acknowledged as its own specialty within medicine and surgery. This will provide wound care with a voice at the national level, particularly in an era of value-based care. Wound care clinicians will be able to advocate for specialty-specific quality metrics and avoid potential penalization for not meeting quality metrics that are irrelevant to wound care.

Often disguised as comorbid conditions, nonhealing and chronic wounds have emerged as a silent epidemic that affects about 6.5 million Americans.^1-3 In 2023, estimated US wound care costs were $126.86 billion.⁴ About 1% to 2% of individuals worldwide will experience a chronic wound in their lifetime. The Veterans Health Administration reported 277,000 inpatient and outpatient encounters for ulcers in 2011, including chronic ulcers of the lower extremity due to diabetes, venous disease, or arterial disease.⁵ Associated costs of chronic wounds are expected to increase as the populations of developed countries age.⁶ Effective treatment of chronic wounds requires a nuanced understanding of complex wound pathophysiology, best practices in interdisciplinary and multidisciplinary wound care, and advanced wound care technologies.^7,8

The typical 4-year medical school curriculum, followed by residency, offers little in the way of formal didactic training in wound care.^9,10 Without specialized and advanced fellowship training dedicated to wound care, health care will lack specialists prepared to manage complex wounds. As a result, wound care-related difficulties may be exacerbated by prolonged recovery time, increased costs, productivity loss, and increased mortality risk.⁸ Wound care is a growing field of study and practice, and there is a critical need for rigorous training, research, and quality improvement efforts to enhance outcomes for patients with nonhealing wounds.⁵

One of the most direct ways to address the need for more physicians with specialty training in wound medicine is to implement a comprehensive training curriculum for advanced wound care practice. Although specialized advanced wound care fellowships are available, the curricula primarily detail rotation names and areas for practice without accompanying competencies, milestones, or entrustable professional activities.¹¹ Furthermore, wound care is not recognized as a subspecialty by the Accreditation Council for Graduate Medical Education (ACGME).

This article synthesized the literature and integrated innovative, evidence-based practices into a curriculum for a formal advanced fellowship training program. To our knowledge, no comprehensive wound care curriculum is publicly available that includes rotations, competencies, milestones, entrustable professional activities, and 360-degree evaluation forms.

Program Development

The advanced wound care fellowship program started in January 2014 at the Michael E. DeBakey Veterans Affairs Medical Center in affiliation with the Baylor College of Medicine. The fellowship program was originally designed for geriatrics fellows to extend the 1-year fellowship for an additional year to learn wound care. It has been adjusted to address formal program goals and objectives, competencies, milestones, entrustable professional activities, and evaluations, with the goal of developing an example curriculum for wound care fellowships across specialties. Although the ACGME does not recognize a wound care subspecialty, this curriculum complies with the ACGME 1-year fellowship common program requirements.^12,13

Scoping Review

A scoping literature review of Google Scholar and PubMed was performed using the medical subject heading terms “wound care + curriculum” and “wound + care + curriculum” to find advanced wound care medical training, fellowship programs, boards, and related ACGME-accredited specialty curricula. The local wound care fellowship program was initially implemented based on an informal literature review by faculty and their respective contributions to curriculum (ie, process establishing wound care-specific competency domains in accordance with ACGME accreditation competency requirements of 1-year fellowships). ^12,13 Standing program practice-based competencies and activities were examined and determined to align with best practices. This scoping review considered additional competencies, competency domains, and entrustable professional activities of reputable wound care fellowship training programs (eg, University of Chicago at Illinois and Wake Forest School of Medicine),^8,11,14 a specialty wound care board (American Board of Wound Medicine and Surgery),¹⁵ an international wound specialist professional society (European Union of Medical Specialists), ¹⁶ and recommended curriculum guidelines for wound care residency programs.¹⁷ ACGME-accredited specialty and subspecialty milestones professional activities were examined, including vascular surgery,¹⁸ plastic surgery,¹⁹ dermatology, ²⁰ foot and ankle,²¹ orthopedic surgery,²² spinal cord injury,²³ and geriatric medicine.²⁴

The competencies, milestones, and entrustable professional activities were compiled and redundancies were eliminated. Wound care specialists from geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy examined the findings and suggested eliminating redundancies, irrelevant content, and content that fell below the minimal expected level of competence for an advanced medical specialist in wound care. An expert consensus meeting further refined items presented to the panel before unanimous consensus resulted in the final set of curriculum competencies, milestones, and entrustable professional activities.

Training Program Feedback

We developed a comprehensive wound care curriculum for an advanced physician fellowship training program based on the streamlined competencies, milestones, and entrustable professional activities (Appendix). Multiple wound care experts from various interdisciplinary backgrounds reached consensus to establish this fellowship curriculum as adaptable for use across training settings. The training program is 12 core rotations and 2 elective rotations (Table 1). Additionally, we developed wound care evaluation forms for faculty-, peer-, and self-assessment of trainees which were adapted from an evidence-based 360-degree evaluation template.²⁵ Suggestions for structured, advanced didactics are in Table 2.

Seventeen fellows have successfully matriculated through the wound care training program. Although wound care certification is not required to work as a wound care specialist, after completion of this fellowship, graduates are able to sit for a wound care certification examination. The American Board of Wound Medicine and Surgery (ABWMS) and the American Board of Wound Management (ABWM) allow physicians to take a certification examination after 1 year of a dedicated wound fellowship program, instead of the typical wound care practice experience ≥ 3 years.

The Clinical Wound Care Fellowship Program collected data for program improvement, and 15 alumni responded (response rate, 88%) to a survey using a 5-point Likert scale. Respondents indicated high mean scores for overall satisfaction (4.7), instructional methods (4.7), program enjoyment (4.7), teaching materials (4.6), and relevance (4.6). All respondents indicated that the fellowship prepared them for a career in wound care as well as their current employment, and 13 of 15 (87%) reported they obtained immediate relevant postfellowship wound care positions and stated that the fellowship prepared them for their current roles. Nine respondents (69%) reported that they were engaged in wound care ≥ 26% of work time. Six respondents (46%) worked in private practice, 3 (23%) at academic medical centers, and 2 (15%) at government- funded hospitals. Four respondents indicated they were board certified in wound care. Program alumni are currently involved in scholarly activities, including 8 in quality improvement and 3 in research.

Discussion

An easily accessible, comprehensive wound care fellowship curriculum has not been previously developed or published. This limited the sources that informed this curriculum. However, the developmental process for this curriculum was robust, as the authors reviewed previously published materials related to wound care, including: 1) descriptive overviews of wound care fellowships; 2) details of month-long rotations for medical students and residents; and 3) practices of the specific environment in which this curriculum was created. Confidence in the practical nature of the curriculum can be assumed, as the experts involved in the development process represented diverse physician specializations, including geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy.

Most wound care clinicians have not completed a formal comprehensive fellowship program. Instead, due to the lack of a comprehensive training curriculum, clinicians have had to use various continuing medical education programs and practice in a wound care setting for ≥ 3 years to be eligible for certification in the specialty. This curriculum will help academic medical centers develop their own fellowship programs, enabling new wound care clinicians to attain certifications more efficiently. As more fellowship programs develop, the goal would be to obtain recognition as an ACGME specialty and standardize the training and competencies for graduates of wound care fellowships.

Conclusions

As new wound care fellowships develop, wound care may become formally acknowledged as its own specialty within medicine and surgery. This will provide wound care with a voice at the national level, particularly in an era of value-based care. Wound care clinicians will be able to advocate for specialty-specific quality metrics and avoid potential penalization for not meeting quality metrics that are irrelevant to wound care.

Often disguised as comorbid conditions, nonhealing and chronic wounds have emerged as a silent epidemic that affects about 6.5 million Americans.^1-3 In 2023, estimated US wound care costs were $126.86 billion.⁴ About 1% to 2% of individuals worldwide will experience a chronic wound in their lifetime. The Veterans Health Administration reported 277,000 inpatient and outpatient encounters for ulcers in 2011, including chronic ulcers of the lower extremity due to diabetes, venous disease, or arterial disease.⁵ Associated costs of chronic wounds are expected to increase as the populations of developed countries age.⁶ Effective treatment of chronic wounds requires a nuanced understanding of complex wound pathophysiology, best practices in interdisciplinary and multidisciplinary wound care, and advanced wound care technologies.^7,8

The typical 4-year medical school curriculum, followed by residency, offers little in the way of formal didactic training in wound care.^9,10 Without specialized and advanced fellowship training dedicated to wound care, health care will lack specialists prepared to manage complex wounds. As a result, wound care-related difficulties may be exacerbated by prolonged recovery time, increased costs, productivity loss, and increased mortality risk.⁸ Wound care is a growing field of study and practice, and there is a critical need for rigorous training, research, and quality improvement efforts to enhance outcomes for patients with nonhealing wounds.⁵

One of the most direct ways to address the need for more physicians with specialty training in wound medicine is to implement a comprehensive training curriculum for advanced wound care practice. Although specialized advanced wound care fellowships are available, the curricula primarily detail rotation names and areas for practice without accompanying competencies, milestones, or entrustable professional activities.¹¹ Furthermore, wound care is not recognized as a subspecialty by the Accreditation Council for Graduate Medical Education (ACGME).

This article synthesized the literature and integrated innovative, evidence-based practices into a curriculum for a formal advanced fellowship training program. To our knowledge, no comprehensive wound care curriculum is publicly available that includes rotations, competencies, milestones, entrustable professional activities, and 360-degree evaluation forms.

Program Development

The advanced wound care fellowship program started in January 2014 at the Michael E. DeBakey Veterans Affairs Medical Center in affiliation with the Baylor College of Medicine. The fellowship program was originally designed for geriatrics fellows to extend the 1-year fellowship for an additional year to learn wound care. It has been adjusted to address formal program goals and objectives, competencies, milestones, entrustable professional activities, and evaluations, with the goal of developing an example curriculum for wound care fellowships across specialties. Although the ACGME does not recognize a wound care subspecialty, this curriculum complies with the ACGME 1-year fellowship common program requirements.^12,13

Scoping Review

A scoping literature review of Google Scholar and PubMed was performed using the medical subject heading terms “wound care + curriculum” and “wound + care + curriculum” to find advanced wound care medical training, fellowship programs, boards, and related ACGME-accredited specialty curricula. The local wound care fellowship program was initially implemented based on an informal literature review by faculty and their respective contributions to curriculum (ie, process establishing wound care-specific competency domains in accordance with ACGME accreditation competency requirements of 1-year fellowships). ^12,13 Standing program practice-based competencies and activities were examined and determined to align with best practices. This scoping review considered additional competencies, competency domains, and entrustable professional activities of reputable wound care fellowship training programs (eg, University of Chicago at Illinois and Wake Forest School of Medicine),^8,11,14 a specialty wound care board (American Board of Wound Medicine and Surgery),¹⁵ an international wound specialist professional society (European Union of Medical Specialists), ¹⁶ and recommended curriculum guidelines for wound care residency programs.¹⁷ ACGME-accredited specialty and subspecialty milestones professional activities were examined, including vascular surgery,¹⁸ plastic surgery,¹⁹ dermatology, ²⁰ foot and ankle,²¹ orthopedic surgery,²² spinal cord injury,²³ and geriatric medicine.²⁴

The competencies, milestones, and entrustable professional activities were compiled and redundancies were eliminated. Wound care specialists from geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy examined the findings and suggested eliminating redundancies, irrelevant content, and content that fell below the minimal expected level of competence for an advanced medical specialist in wound care. An expert consensus meeting further refined items presented to the panel before unanimous consensus resulted in the final set of curriculum competencies, milestones, and entrustable professional activities.

Training Program Feedback

We developed a comprehensive wound care curriculum for an advanced physician fellowship training program based on the streamlined competencies, milestones, and entrustable professional activities (Appendix). Multiple wound care experts from various interdisciplinary backgrounds reached consensus to establish this fellowship curriculum as adaptable for use across training settings. The training program is 12 core rotations and 2 elective rotations (Table 1). Additionally, we developed wound care evaluation forms for faculty-, peer-, and self-assessment of trainees which were adapted from an evidence-based 360-degree evaluation template.²⁵ Suggestions for structured, advanced didactics are in Table 2.

Seventeen fellows have successfully matriculated through the wound care training program. Although wound care certification is not required to work as a wound care specialist, after completion of this fellowship, graduates are able to sit for a wound care certification examination. The American Board of Wound Medicine and Surgery (ABWMS) and the American Board of Wound Management (ABWM) allow physicians to take a certification examination after 1 year of a dedicated wound fellowship program, instead of the typical wound care practice experience ≥ 3 years.

The Clinical Wound Care Fellowship Program collected data for program improvement, and 15 alumni responded (response rate, 88%) to a survey using a 5-point Likert scale. Respondents indicated high mean scores for overall satisfaction (4.7), instructional methods (4.7), program enjoyment (4.7), teaching materials (4.6), and relevance (4.6). All respondents indicated that the fellowship prepared them for a career in wound care as well as their current employment, and 13 of 15 (87%) reported they obtained immediate relevant postfellowship wound care positions and stated that the fellowship prepared them for their current roles. Nine respondents (69%) reported that they were engaged in wound care ≥ 26% of work time. Six respondents (46%) worked in private practice, 3 (23%) at academic medical centers, and 2 (15%) at government- funded hospitals. Four respondents indicated they were board certified in wound care. Program alumni are currently involved in scholarly activities, including 8 in quality improvement and 3 in research.

Discussion

An easily accessible, comprehensive wound care fellowship curriculum has not been previously developed or published. This limited the sources that informed this curriculum. However, the developmental process for this curriculum was robust, as the authors reviewed previously published materials related to wound care, including: 1) descriptive overviews of wound care fellowships; 2) details of month-long rotations for medical students and residents; and 3) practices of the specific environment in which this curriculum was created. Confidence in the practical nature of the curriculum can be assumed, as the experts involved in the development process represented diverse physician specializations, including geriatrics, family medicine, internal medicine, undersea and hyperbaric medicine, general surgery, podiatry, and physical therapy.

Most wound care clinicians have not completed a formal comprehensive fellowship program. Instead, due to the lack of a comprehensive training curriculum, clinicians have had to use various continuing medical education programs and practice in a wound care setting for ≥ 3 years to be eligible for certification in the specialty. This curriculum will help academic medical centers develop their own fellowship programs, enabling new wound care clinicians to attain certifications more efficiently. As more fellowship programs develop, the goal would be to obtain recognition as an ACGME specialty and standardize the training and competencies for graduates of wound care fellowships.

Conclusions

As new wound care fellowships develop, wound care may become formally acknowledged as its own specialty within medicine and surgery. This will provide wound care with a voice at the national level, particularly in an era of value-based care. Wound care clinicians will be able to advocate for specialty-specific quality metrics and avoid potential penalization for not meeting quality metrics that are irrelevant to wound care.

The US Department of Veterans Affairs (VA) Home Loan Program, administered by the Veterans Benefits Administration (VBA), is a unique benefit for veterans, active-duty service members, National Guard and Reserve members, and eligible surviving spouses. Established in 1944, the program aims to help these individuals achieve homeownership by leveraging a third-party guarantee, typically from a government agency, to enhance access to credit and improve loan terms for borrowers who may not meet conventional loan qualifications.¹ Since its inception, the VA has guaranteed > 28.5 million loans, enabling millions of veterans to buy, build, repair, retain, or adapt homes for personal occupancy.² The program is designed to support veterans and eligible individuals to become homeowners, recognizing homeownership as a pathway to financial stability and community integration. VA home loans are provided by private lenders (eg, banks, mortgage companies) with a portion guaranteed by the VA, which reduces the risk for lenders and enables them to offer competitive terms, such as no down payment and lower interest rates, making homeownership more accessible to veterans.²

Eligibility criteria for the VA Home Loan Program include military service criteria such as active-duty service members with ≥ 90 continuous days of service; veterans with an honorable discharge meeting minimum service requirements; individuals who served in the National Guard/Reserve for ≥ 90 days of active service or 6 years of service with an honorable discharge; and surviving spouses of veterans who died in service or from a service-connected disability, were designated as missing in action/ prisoner of war, and the spouse is receiving Dependency and Indemnity Compensation. Financial criteria also apply: borrowers must meet lender requirements for credit and income (although VA loans are more flexible than conventional loans) and the home must be for personal occupancy rather than an investment property.³

A June 2025 PubMed literature search did not reveal any prior research on the VA Home Loan Program, although a limited number of studies tackled a wide range of issues related to federal and private home loans.^4-12 To our knowledge, there is no prior published examination of the VA Home Loan Program. Understanding VA Home Loan Program usage among Veterans Health Administration (VHA) users can inform the future direction of the program. The VHA operates the largest integrated US health care system, serving > 9 million enrolled veterans annually at 1321 facilities, including 172 medical centers and 1138 outpatient clinics, providing primary and specialized health care, and related medical and social support services for enrolled veterans, including those who are experiencing housing instability or homelessness.¹³ Specialized VHA programs for homeless veterans include housing, employment, health care, justice, and re-entryrelated services in collaboration with federal and community partners.¹⁴ Housing instability has been defined as the state of being at risk of losing housing due to challenges such as difficulties paying rent, overcrowding, frequent relocation, and a substantial proportion of income spent on housing.^15,16 Homelessness is a severe manifestation of housing instability that has been defined as the lack of stable, safe, and functioning housing.^17,18

Health care and social services, including those that address housing instability and homelessness, are major priorities for the VHA and VBA.¹⁹ The VA Home Loan Program may represent an important resource to help veterans achieve long-term housing stability through home ownership. There has been wide public concern about housing affordability and the ability of many Americans, including veterans, to achieve home ownership.²⁰ Homeownership is considered an important part of developing financial assets and achieving financial stability. Lowincome veterans, in particular, may benefit from this program as a national study found that 8.0% of low-income veterans and 13.9% of veterans with a history of homelessness have previously experienced a home foreclosure. ²¹ A greater understanding of who applies for and receives assistance from the VA Home Loan Program would inform homelessness prevention services and future planning for this program.

We conducted a quality improvement (QI) project on behalf of the VHA Homeless Programs Office and in partnership with the VBA. Our goals were to: (1) describe the annual number of applicants and recipients of the VA Home Loan Program by age group, sex, race/ethnicity, presence of any diagnosed substance use and/or mental health disorder, and history of homelessness; and (2) compare demographic, clinical, and homelessness characteristics among individuals who apply and are granted a loan through this program, individuals who apply and are denied a loan through this program, and individuals who do not apply for a loan through this program.

Methods

This project involved linked VA administrative national databases and was undertaken by the VHA Homeless Programs Office in partnership with the VBA. Specifically, VHA and VBA databases were linked together using veteran identifiers and all data were managed and analyzed on secure VA servers. The project followed VA’s Program Guide 1200.21 for nonresearch activities and institutional review board approval was waived through sponsorship by the VA Homeless Programs Office. The VHA Corporate Data Warehouse (CDW) was accessed to obtain data from the Homeless Operations Management and Evaluation System (HOMES) and other clinical data systems used by VHA clinicians and administrators that capture diagnoses, workload, and other health care data.^22,23 HOMES collects intake, progress, and outcome data on homeless veterans within its care system that enables the VA to assess the effectiveness of programs and strategically allocate resources to prevent homelessness.^24,25

A list of veterans who filed disability compensation and pension claims was obtained from the VBA Office of Performance Analysis and Integrity, including Social Security number, name, city and state, date of claim submission, grant or increase in benefits, homeless status, VA home loan approval, and homeless aid for dependent children from fiscal year (FY) 2022 through FY 2024. VBA data were linked to VHA CDW electronic health record data from veterans who sought VA health care services and HOMES data on veteran participation in homeless programs who were also experiencing homelessness. VHA data included demographic characteristics (eg, sex, age, race, marital status, combat service) at an index date (earliest visit to the VHA between October 1, 2021, and September 30, 2024); military sexual trauma; clinical characteristics within 12 months prior to the index date (VHA disability rating, substance use disorder [SUD] diagnosis, mental health disorder diagnosis, Charlson Comorbidity Index [CCI] score), and homelessness experience ≤ 5 years prior to the index date.

History of homelessness ≤ 5 years prior to the index date was determined using an operational definition of homelessness based on multiple indicators, including International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic code Z59.0; clinic stop codes or HOMES records indicating VA homeless programs clinical encounters; or a positive screen on an annual homelessness screener.¹⁶ US Department of Housing and Urban Development-VA Supportive Housing enrollees were excluded because they are considered to no longer be experiencing homelessness, and Veterans Justice Program enrollees were excluded because the program primarily focuses on serving criminal justice-involved veterans. The CCI predicts the risk of death ≤ 1 year by assessing the number and severity of a patient’s coexisting health conditions and is a valuable tool for understanding a patient’s overall health burden, aiding in clinical decision-making and evaluation research studies.^26-29 Diagnoses based on ICD-10-CM codes were used to determine SUDs, mental health disorders, and CCI score, using methods that have been described in other publications.³⁰

Population

The VBA cohort of veterans requesting benefits was further restricted to those who met the following eligibility criteria: (1) requested VA benefits FYs 2022 to 2024; (2) sought VHA services ≥ 1 time between FY 2022 and 2024; (3) had matching VBA/VHA records; (4) had no missing data on claim status and/ or demographic, clinical, and homelessness characteristics; and (5) had known home loan status FYs 2022 to 2024. The original VBA dataset consisted of 4,219,755 records and the original VHA dataset consisted of 7,170,199 records (Figure 1). The final linked VBA/VHA dataset after excluding 29 records with missing data on sex, 7 with missing data on age, 6 with missing data on marital status, and an additional 143,444 with unknown VBA claim status, consisted of 3,089,295 records corresponding to 2,260,851 unique veterans. Specifically, 251,796 records corresponded to veterans who had applied and received a loan, 84,751 to veterans who had applied and were nonrecipients of a loan, and 2,752,748 to veterans who did not apply for a loan.

Statistical Analysis

All statistical analyses were performed using SAS Enterprise Guide, an application that provides a point-and-click interface for data access, analysis, and management, accommodating both code-based and visual programming. ³¹ First, we relied on the final analytic sample to calculate the annual proportions of veterans who applied for and/or received a loan through the VA Home Loan Program. We also generated descriptive statistics stratified by age group, sex, race/ethnicity, SUD, mental health disorder, and homelessness, overall and within each FY. Pearson χ² and Cochran-Armitage trend tests were applied to examine differences in application and receipt of a home loan by baseline characteristics and FY, respectively. Second, we conducted bivariate and multivariable analyses to compare demographic, clinical, and homelessness characteristics between 3 groups of veterans as they pertain to the VA Home Loan Program. Veterans who applied and were nonrecipients of a loan (group 1), veterans who applied and were recipients of a loan (group 2), and veterans who did not apply for a loan (group 3). Similar analyses compared VA Home Loan Program applicants who were recipients of a home loan vs VA Home Loan Program applicants who were nonrecipients of a home loan. Multinomial and binary logistic regression models were constructed to estimate the relative risk ratio (RR) and odds ratio (OR) with 95% CIs for comparisons between these distinct groups on demographic, clinical, and homelessness characteristics. Two-sided statistical tests were evaluated at α = 0.05.

Results

Tables 1 and 2 present the number of VBA applicants, including those who applied for and received benefits through the VA Home Loan Program, by age group, sex, race/ethnicity, as well as histories of SUDs, mental health disorders, and homelessness, overall, and by FY. As shown in Figure 2, 336,547 of 3,089,295 VBA applications (10.9%) pertained to the VA Home Loan Program, with a statistically significant decline in application rates, from 12.2% in FY 2022 to 9.9% in FY 2024 (P < .001 for trend). Among 336,547 veterans who applied for the VA Home Loan Program, 251,796 (74.8%) received a home loan during FYs 2022 to 2024, ranging between 73.8% for FY 2024 and 75.5% for FY 2023 (P < .001 for trend).

Multinomial logistic regression models for demographic, clinical, and homelessness characteristics as predictors of VA Home Loan Program status are provided in Appendix 1. Based on the fully adjusted model, compared with veterans who did not apply to the VA Home Loan Program, those who applied for a home loan were less likely to be aged ≥ 50 years, unmarried, Hispanic ethnicity, mixed race, or other race, diagnosed with a SUD, or history of homelessness. Veterans with higher VA service-connected disability ratings were more frequently recipients of VA home loans, whereas those who self-identified as non-Hispanic Black and those with higher CCI scores were less frequently recipients of VA home loans. Finally, those with mental health disorders were more likely than their counterparts to be applicants (recipients or nonrecipients) of VA home loans.

Binary logistic regression models for demographic, clinical, and homelessness characteristics as predictors of receipt status among applicants to the VA Home Loan Program are provided in Appendix 2. Among applicants, those who were granted a VA home loan were less likely to be aged ≥ 50 years; have a CCI score > 0; have experienced combat service and/or military sexual trauma; be diagnosed with a SUD and/or mental health disorder; or to have a history of homelessness compared with those denied a VA home loan. Applicants granted a VA home loan were also more likely to be female, non-Hispanic White, single or never married, and/or have a VA service-connected disability ratings > 0%.

Discussion

The VA Home Loan Program is a unique benefit and resource for eligible veterans that may be increasingly important in a time of growing concern about the affordability of housing for many Americans. Research on other federally-supported home loan programs as well as private home mortgage programs has been mostly conducted in the economic realm, and studies focused on understanding these programs from a health care system perspective have been sparse.^32,33 However, there is a large body of literature documenting the importance of stable, safe, and secure housing on health and well-being.^34-37 This study did not focus on evaluating the effects of the VA Home Loan Program, because we wanted to first examine the characteristics of veterans who benefited from the program and how they differed from veterans who did not apply or did apply but had a denied application.

Our findings suggest that several thousands of veterans benefit from the VA Home Loan Program each year. For historical context, the time period examined was one of economic downturn with rising costs of living, including housing, and steady increases in homelessness as reported in the annual point-in-time count of sheltered and unsheltered people experiencing homelessness on a single night as mandated by the US Department of Housing and Urban Development.^38-40 The Sergeant First Class Heath Robinson Honoring Our Promise to Address Comprehensive Toxics (PACT) Act of 2022 expanded health care and benefits for veterans exposed to burn pits, Agent Orange, and other toxic substances, resulting in more VA disability benefit claims, including large retroactive payments.^41-43 Anecdotally, the VBA has noted that the PACT Act helped some homeless veterans with funds and stability to exit homelessness and enroll in the VA Home Loan Program.

Our analysis suggests that beneficiaries of the VA Home Loan Program were frequently aged < 50 years, female, of non-Hispanic White race, and did not have histories of psychiatric disorders or homelessness. Most of these demographic and clinical characteristics were not surprising given the composition of the veteran population, although in-depth analyses are needed to examine sex differences that may have led to more females than males benefiting from the VA Home Loan Program. In addition, it was notable that many younger and non-Hispanic Black veterans had applied. While relatively few veterans with SUDs benefited from the VA Home Loan Program, few had applied. Research is warranted into why veterans with SUDs are less likely to apply for home loans. Quite surprisingly, a sizable proportion of veterans with histories of homelessness reported they had applied to the VA Home Loan Program, although they were less likely than veterans who had not experienced homelessness to be granted a loan.

The examination of differences between veterans who did not apply, were granted, and denied a loan through the VA Home Loan Program revealed several key predictors of application outcomes in multivariable models. Specifically, veterans who applied for home loans were less likely to be aged ≥ 50 years, unmarried, of Hispanic, mixed, or other race/ethnicity, diagnosed with an SUD, or have a history of homelessness. Veterans with higher disability ratings were less frequently denied and more frequently approved, while non-Hispanic Black veterans and those with higher CCI scores were more frequently denied and less frequently approved. VBA applicants with mental health disorders were also more likely to apply for a home loan. Conversely, those granted a home loan were more likely than those denied a home loan to be female, non-Hispanic White, single/unmarried, or to have > 0% VA service-connected disability rating, but less likely to be aged ≥ 50 years, have CCI score > 0, be diagnosed with psychiatric disorders, or have a history of homelessness.

Limitations

This analysis was restricted to a subset of FY 2022 to FY 2024 linked VBA/VHA databases (ie, to veterans who had both VBA and VHA records and met prespecified eligibility criteria). Despite the large number of linked records, a small percentage of these records corresponded to veterans who were applicants or recipients of the VA Home Loan Program. Future studies should expand the time frame to examine variations in application outcomes over time and by background characteristics of veterans enrolled in VHA care who applied for VBA benefits. In addition, we relied on data and ICD-10-CM diagnostic codes from existing electronic health records and claims data to define histories of homelessness, comorbidities, SUDs, and mental health disorders. Given the time-varying nature of these conditions, the temporal sequence of events was difficult to ascertain. Third, it is worth noting that these findings can only be generalized to veterans who applied for VBA benefits and met eligibility criteria, and that these veterans may differ in terms of their demographic and clinical characteristics from those who did not apply for these benefits.

Conclusions

This study analyzed data from 251,796 individuals who applied for and received a VA home loan, 84,751 who were denied a VA home loan, and 2,752,748 veterans who did not apply for a VA home loan from FY 2022 to FY 2024. Accordingly, 11% of applications pertained to the VA Home Loan Program, and 75% of VA Home Loan Program applicants received a home loan. Distinct demographic and clinical characteristics were observed for applicants and recipients of the VA Home Loan Program, which can set the stage for future planning and evaluation of the program. Despite the broad accessibility of veterans to the VA Home Loan Program, there were differences in approval rates among applicants based on sociodemographic and clinical characteristics. Further evaluation, perhaps using qualitative methods, is needed to better understand opportunities and challenges to achieving a VA home loan, especially among underserved veteran populations. Investigation and research can guide future recommendations for any development or corrective actions that can help increase access to veterans who can benefit from the program. Future analyses are also needed to compare veterans enrolled and not enrolled in the VA Home Loan Program on health care-related outcomes.

The US Department of Veterans Affairs (VA) Home Loan Program, administered by the Veterans Benefits Administration (VBA), is a unique benefit for veterans, active-duty service members, National Guard and Reserve members, and eligible surviving spouses. Established in 1944, the program aims to help these individuals achieve homeownership by leveraging a third-party guarantee, typically from a government agency, to enhance access to credit and improve loan terms for borrowers who may not meet conventional loan qualifications.¹ Since its inception, the VA has guaranteed > 28.5 million loans, enabling millions of veterans to buy, build, repair, retain, or adapt homes for personal occupancy.² The program is designed to support veterans and eligible individuals to become homeowners, recognizing homeownership as a pathway to financial stability and community integration. VA home loans are provided by private lenders (eg, banks, mortgage companies) with a portion guaranteed by the VA, which reduces the risk for lenders and enables them to offer competitive terms, such as no down payment and lower interest rates, making homeownership more accessible to veterans.²

Eligibility criteria for the VA Home Loan Program include military service criteria such as active-duty service members with ≥ 90 continuous days of service; veterans with an honorable discharge meeting minimum service requirements; individuals who served in the National Guard/Reserve for ≥ 90 days of active service or 6 years of service with an honorable discharge; and surviving spouses of veterans who died in service or from a service-connected disability, were designated as missing in action/ prisoner of war, and the spouse is receiving Dependency and Indemnity Compensation. Financial criteria also apply: borrowers must meet lender requirements for credit and income (although VA loans are more flexible than conventional loans) and the home must be for personal occupancy rather than an investment property.³

A June 2025 PubMed literature search did not reveal any prior research on the VA Home Loan Program, although a limited number of studies tackled a wide range of issues related to federal and private home loans.^4-12 To our knowledge, there is no prior published examination of the VA Home Loan Program. Understanding VA Home Loan Program usage among Veterans Health Administration (VHA) users can inform the future direction of the program. The VHA operates the largest integrated US health care system, serving > 9 million enrolled veterans annually at 1321 facilities, including 172 medical centers and 1138 outpatient clinics, providing primary and specialized health care, and related medical and social support services for enrolled veterans, including those who are experiencing housing instability or homelessness.¹³ Specialized VHA programs for homeless veterans include housing, employment, health care, justice, and re-entryrelated services in collaboration with federal and community partners.¹⁴ Housing instability has been defined as the state of being at risk of losing housing due to challenges such as difficulties paying rent, overcrowding, frequent relocation, and a substantial proportion of income spent on housing.^15,16 Homelessness is a severe manifestation of housing instability that has been defined as the lack of stable, safe, and functioning housing.^17,18

Health care and social services, including those that address housing instability and homelessness, are major priorities for the VHA and VBA.¹⁹ The VA Home Loan Program may represent an important resource to help veterans achieve long-term housing stability through home ownership. There has been wide public concern about housing affordability and the ability of many Americans, including veterans, to achieve home ownership.²⁰ Homeownership is considered an important part of developing financial assets and achieving financial stability. Lowincome veterans, in particular, may benefit from this program as a national study found that 8.0% of low-income veterans and 13.9% of veterans with a history of homelessness have previously experienced a home foreclosure. ²¹ A greater understanding of who applies for and receives assistance from the VA Home Loan Program would inform homelessness prevention services and future planning for this program.

We conducted a quality improvement (QI) project on behalf of the VHA Homeless Programs Office and in partnership with the VBA. Our goals were to: (1) describe the annual number of applicants and recipients of the VA Home Loan Program by age group, sex, race/ethnicity, presence of any diagnosed substance use and/or mental health disorder, and history of homelessness; and (2) compare demographic, clinical, and homelessness characteristics among individuals who apply and are granted a loan through this program, individuals who apply and are denied a loan through this program, and individuals who do not apply for a loan through this program.

Methods

This project involved linked VA administrative national databases and was undertaken by the VHA Homeless Programs Office in partnership with the VBA. Specifically, VHA and VBA databases were linked together using veteran identifiers and all data were managed and analyzed on secure VA servers. The project followed VA’s Program Guide 1200.21 for nonresearch activities and institutional review board approval was waived through sponsorship by the VA Homeless Programs Office. The VHA Corporate Data Warehouse (CDW) was accessed to obtain data from the Homeless Operations Management and Evaluation System (HOMES) and other clinical data systems used by VHA clinicians and administrators that capture diagnoses, workload, and other health care data.^22,23 HOMES collects intake, progress, and outcome data on homeless veterans within its care system that enables the VA to assess the effectiveness of programs and strategically allocate resources to prevent homelessness.^24,25

A list of veterans who filed disability compensation and pension claims was obtained from the VBA Office of Performance Analysis and Integrity, including Social Security number, name, city and state, date of claim submission, grant or increase in benefits, homeless status, VA home loan approval, and homeless aid for dependent children from fiscal year (FY) 2022 through FY 2024. VBA data were linked to VHA CDW electronic health record data from veterans who sought VA health care services and HOMES data on veteran participation in homeless programs who were also experiencing homelessness. VHA data included demographic characteristics (eg, sex, age, race, marital status, combat service) at an index date (earliest visit to the VHA between October 1, 2021, and September 30, 2024); military sexual trauma; clinical characteristics within 12 months prior to the index date (VHA disability rating, substance use disorder [SUD] diagnosis, mental health disorder diagnosis, Charlson Comorbidity Index [CCI] score), and homelessness experience ≤ 5 years prior to the index date.

History of homelessness ≤ 5 years prior to the index date was determined using an operational definition of homelessness based on multiple indicators, including International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic code Z59.0; clinic stop codes or HOMES records indicating VA homeless programs clinical encounters; or a positive screen on an annual homelessness screener.¹⁶ US Department of Housing and Urban Development-VA Supportive Housing enrollees were excluded because they are considered to no longer be experiencing homelessness, and Veterans Justice Program enrollees were excluded because the program primarily focuses on serving criminal justice-involved veterans. The CCI predicts the risk of death ≤ 1 year by assessing the number and severity of a patient’s coexisting health conditions and is a valuable tool for understanding a patient’s overall health burden, aiding in clinical decision-making and evaluation research studies.^26-29 Diagnoses based on ICD-10-CM codes were used to determine SUDs, mental health disorders, and CCI score, using methods that have been described in other publications.³⁰

Population

The VBA cohort of veterans requesting benefits was further restricted to those who met the following eligibility criteria: (1) requested VA benefits FYs 2022 to 2024; (2) sought VHA services ≥ 1 time between FY 2022 and 2024; (3) had matching VBA/VHA records; (4) had no missing data on claim status and/ or demographic, clinical, and homelessness characteristics; and (5) had known home loan status FYs 2022 to 2024. The original VBA dataset consisted of 4,219,755 records and the original VHA dataset consisted of 7,170,199 records (Figure 1). The final linked VBA/VHA dataset after excluding 29 records with missing data on sex, 7 with missing data on age, 6 with missing data on marital status, and an additional 143,444 with unknown VBA claim status, consisted of 3,089,295 records corresponding to 2,260,851 unique veterans. Specifically, 251,796 records corresponded to veterans who had applied and received a loan, 84,751 to veterans who had applied and were nonrecipients of a loan, and 2,752,748 to veterans who did not apply for a loan.

Statistical Analysis

All statistical analyses were performed using SAS Enterprise Guide, an application that provides a point-and-click interface for data access, analysis, and management, accommodating both code-based and visual programming. ³¹ First, we relied on the final analytic sample to calculate the annual proportions of veterans who applied for and/or received a loan through the VA Home Loan Program. We also generated descriptive statistics stratified by age group, sex, race/ethnicity, SUD, mental health disorder, and homelessness, overall and within each FY. Pearson χ² and Cochran-Armitage trend tests were applied to examine differences in application and receipt of a home loan by baseline characteristics and FY, respectively. Second, we conducted bivariate and multivariable analyses to compare demographic, clinical, and homelessness characteristics between 3 groups of veterans as they pertain to the VA Home Loan Program. Veterans who applied and were nonrecipients of a loan (group 1), veterans who applied and were recipients of a loan (group 2), and veterans who did not apply for a loan (group 3). Similar analyses compared VA Home Loan Program applicants who were recipients of a home loan vs VA Home Loan Program applicants who were nonrecipients of a home loan. Multinomial and binary logistic regression models were constructed to estimate the relative risk ratio (RR) and odds ratio (OR) with 95% CIs for comparisons between these distinct groups on demographic, clinical, and homelessness characteristics. Two-sided statistical tests were evaluated at α = 0.05.

Results

Tables 1 and 2 present the number of VBA applicants, including those who applied for and received benefits through the VA Home Loan Program, by age group, sex, race/ethnicity, as well as histories of SUDs, mental health disorders, and homelessness, overall, and by FY. As shown in Figure 2, 336,547 of 3,089,295 VBA applications (10.9%) pertained to the VA Home Loan Program, with a statistically significant decline in application rates, from 12.2% in FY 2022 to 9.9% in FY 2024 (P < .001 for trend). Among 336,547 veterans who applied for the VA Home Loan Program, 251,796 (74.8%) received a home loan during FYs 2022 to 2024, ranging between 73.8% for FY 2024 and 75.5% for FY 2023 (P < .001 for trend).

Multinomial logistic regression models for demographic, clinical, and homelessness characteristics as predictors of VA Home Loan Program status are provided in Appendix 1. Based on the fully adjusted model, compared with veterans who did not apply to the VA Home Loan Program, those who applied for a home loan were less likely to be aged ≥ 50 years, unmarried, Hispanic ethnicity, mixed race, or other race, diagnosed with a SUD, or history of homelessness. Veterans with higher VA service-connected disability ratings were more frequently recipients of VA home loans, whereas those who self-identified as non-Hispanic Black and those with higher CCI scores were less frequently recipients of VA home loans. Finally, those with mental health disorders were more likely than their counterparts to be applicants (recipients or nonrecipients) of VA home loans.

Binary logistic regression models for demographic, clinical, and homelessness characteristics as predictors of receipt status among applicants to the VA Home Loan Program are provided in Appendix 2. Among applicants, those who were granted a VA home loan were less likely to be aged ≥ 50 years; have a CCI score > 0; have experienced combat service and/or military sexual trauma; be diagnosed with a SUD and/or mental health disorder; or to have a history of homelessness compared with those denied a VA home loan. Applicants granted a VA home loan were also more likely to be female, non-Hispanic White, single or never married, and/or have a VA service-connected disability ratings > 0%.

Discussion

The VA Home Loan Program is a unique benefit and resource for eligible veterans that may be increasingly important in a time of growing concern about the affordability of housing for many Americans. Research on other federally-supported home loan programs as well as private home mortgage programs has been mostly conducted in the economic realm, and studies focused on understanding these programs from a health care system perspective have been sparse.^32,33 However, there is a large body of literature documenting the importance of stable, safe, and secure housing on health and well-being.^34-37 This study did not focus on evaluating the effects of the VA Home Loan Program, because we wanted to first examine the characteristics of veterans who benefited from the program and how they differed from veterans who did not apply or did apply but had a denied application.

Our findings suggest that several thousands of veterans benefit from the VA Home Loan Program each year. For historical context, the time period examined was one of economic downturn with rising costs of living, including housing, and steady increases in homelessness as reported in the annual point-in-time count of sheltered and unsheltered people experiencing homelessness on a single night as mandated by the US Department of Housing and Urban Development.^38-40 The Sergeant First Class Heath Robinson Honoring Our Promise to Address Comprehensive Toxics (PACT) Act of 2022 expanded health care and benefits for veterans exposed to burn pits, Agent Orange, and other toxic substances, resulting in more VA disability benefit claims, including large retroactive payments.^41-43 Anecdotally, the VBA has noted that the PACT Act helped some homeless veterans with funds and stability to exit homelessness and enroll in the VA Home Loan Program.

Our analysis suggests that beneficiaries of the VA Home Loan Program were frequently aged < 50 years, female, of non-Hispanic White race, and did not have histories of psychiatric disorders or homelessness. Most of these demographic and clinical characteristics were not surprising given the composition of the veteran population, although in-depth analyses are needed to examine sex differences that may have led to more females than males benefiting from the VA Home Loan Program. In addition, it was notable that many younger and non-Hispanic Black veterans had applied. While relatively few veterans with SUDs benefited from the VA Home Loan Program, few had applied. Research is warranted into why veterans with SUDs are less likely to apply for home loans. Quite surprisingly, a sizable proportion of veterans with histories of homelessness reported they had applied to the VA Home Loan Program, although they were less likely than veterans who had not experienced homelessness to be granted a loan.

The examination of differences between veterans who did not apply, were granted, and denied a loan through the VA Home Loan Program revealed several key predictors of application outcomes in multivariable models. Specifically, veterans who applied for home loans were less likely to be aged ≥ 50 years, unmarried, of Hispanic, mixed, or other race/ethnicity, diagnosed with an SUD, or have a history of homelessness. Veterans with higher disability ratings were less frequently denied and more frequently approved, while non-Hispanic Black veterans and those with higher CCI scores were more frequently denied and less frequently approved. VBA applicants with mental health disorders were also more likely to apply for a home loan. Conversely, those granted a home loan were more likely than those denied a home loan to be female, non-Hispanic White, single/unmarried, or to have > 0% VA service-connected disability rating, but less likely to be aged ≥ 50 years, have CCI score > 0, be diagnosed with psychiatric disorders, or have a history of homelessness.

Limitations

This analysis was restricted to a subset of FY 2022 to FY 2024 linked VBA/VHA databases (ie, to veterans who had both VBA and VHA records and met prespecified eligibility criteria). Despite the large number of linked records, a small percentage of these records corresponded to veterans who were applicants or recipients of the VA Home Loan Program. Future studies should expand the time frame to examine variations in application outcomes over time and by background characteristics of veterans enrolled in VHA care who applied for VBA benefits. In addition, we relied on data and ICD-10-CM diagnostic codes from existing electronic health records and claims data to define histories of homelessness, comorbidities, SUDs, and mental health disorders. Given the time-varying nature of these conditions, the temporal sequence of events was difficult to ascertain. Third, it is worth noting that these findings can only be generalized to veterans who applied for VBA benefits and met eligibility criteria, and that these veterans may differ in terms of their demographic and clinical characteristics from those who did not apply for these benefits.

Conclusions

This study analyzed data from 251,796 individuals who applied for and received a VA home loan, 84,751 who were denied a VA home loan, and 2,752,748 veterans who did not apply for a VA home loan from FY 2022 to FY 2024. Accordingly, 11% of applications pertained to the VA Home Loan Program, and 75% of VA Home Loan Program applicants received a home loan. Distinct demographic and clinical characteristics were observed for applicants and recipients of the VA Home Loan Program, which can set the stage for future planning and evaluation of the program. Despite the broad accessibility of veterans to the VA Home Loan Program, there were differences in approval rates among applicants based on sociodemographic and clinical characteristics. Further evaluation, perhaps using qualitative methods, is needed to better understand opportunities and challenges to achieving a VA home loan, especially among underserved veteran populations. Investigation and research can guide future recommendations for any development or corrective actions that can help increase access to veterans who can benefit from the program. Future analyses are also needed to compare veterans enrolled and not enrolled in the VA Home Loan Program on health care-related outcomes.

The US Department of Veterans Affairs (VA) Home Loan Program, administered by the Veterans Benefits Administration (VBA), is a unique benefit for veterans, active-duty service members, National Guard and Reserve members, and eligible surviving spouses. Established in 1944, the program aims to help these individuals achieve homeownership by leveraging a third-party guarantee, typically from a government agency, to enhance access to credit and improve loan terms for borrowers who may not meet conventional loan qualifications.¹ Since its inception, the VA has guaranteed > 28.5 million loans, enabling millions of veterans to buy, build, repair, retain, or adapt homes for personal occupancy.² The program is designed to support veterans and eligible individuals to become homeowners, recognizing homeownership as a pathway to financial stability and community integration. VA home loans are provided by private lenders (eg, banks, mortgage companies) with a portion guaranteed by the VA, which reduces the risk for lenders and enables them to offer competitive terms, such as no down payment and lower interest rates, making homeownership more accessible to veterans.²

Eligibility criteria for the VA Home Loan Program include military service criteria such as active-duty service members with ≥ 90 continuous days of service; veterans with an honorable discharge meeting minimum service requirements; individuals who served in the National Guard/Reserve for ≥ 90 days of active service or 6 years of service with an honorable discharge; and surviving spouses of veterans who died in service or from a service-connected disability, were designated as missing in action/ prisoner of war, and the spouse is receiving Dependency and Indemnity Compensation. Financial criteria also apply: borrowers must meet lender requirements for credit and income (although VA loans are more flexible than conventional loans) and the home must be for personal occupancy rather than an investment property.³

A June 2025 PubMed literature search did not reveal any prior research on the VA Home Loan Program, although a limited number of studies tackled a wide range of issues related to federal and private home loans.^4-12 To our knowledge, there is no prior published examination of the VA Home Loan Program. Understanding VA Home Loan Program usage among Veterans Health Administration (VHA) users can inform the future direction of the program. The VHA operates the largest integrated US health care system, serving > 9 million enrolled veterans annually at 1321 facilities, including 172 medical centers and 1138 outpatient clinics, providing primary and specialized health care, and related medical and social support services for enrolled veterans, including those who are experiencing housing instability or homelessness.¹³ Specialized VHA programs for homeless veterans include housing, employment, health care, justice, and re-entryrelated services in collaboration with federal and community partners.¹⁴ Housing instability has been defined as the state of being at risk of losing housing due to challenges such as difficulties paying rent, overcrowding, frequent relocation, and a substantial proportion of income spent on housing.^15,16 Homelessness is a severe manifestation of housing instability that has been defined as the lack of stable, safe, and functioning housing.^17,18

Health care and social services, including those that address housing instability and homelessness, are major priorities for the VHA and VBA.¹⁹ The VA Home Loan Program may represent an important resource to help veterans achieve long-term housing stability through home ownership. There has been wide public concern about housing affordability and the ability of many Americans, including veterans, to achieve home ownership.²⁰ Homeownership is considered an important part of developing financial assets and achieving financial stability. Lowincome veterans, in particular, may benefit from this program as a national study found that 8.0% of low-income veterans and 13.9% of veterans with a history of homelessness have previously experienced a home foreclosure. ²¹ A greater understanding of who applies for and receives assistance from the VA Home Loan Program would inform homelessness prevention services and future planning for this program.

We conducted a quality improvement (QI) project on behalf of the VHA Homeless Programs Office and in partnership with the VBA. Our goals were to: (1) describe the annual number of applicants and recipients of the VA Home Loan Program by age group, sex, race/ethnicity, presence of any diagnosed substance use and/or mental health disorder, and history of homelessness; and (2) compare demographic, clinical, and homelessness characteristics among individuals who apply and are granted a loan through this program, individuals who apply and are denied a loan through this program, and individuals who do not apply for a loan through this program.

Methods

This project involved linked VA administrative national databases and was undertaken by the VHA Homeless Programs Office in partnership with the VBA. Specifically, VHA and VBA databases were linked together using veteran identifiers and all data were managed and analyzed on secure VA servers. The project followed VA’s Program Guide 1200.21 for nonresearch activities and institutional review board approval was waived through sponsorship by the VA Homeless Programs Office. The VHA Corporate Data Warehouse (CDW) was accessed to obtain data from the Homeless Operations Management and Evaluation System (HOMES) and other clinical data systems used by VHA clinicians and administrators that capture diagnoses, workload, and other health care data.^22,23 HOMES collects intake, progress, and outcome data on homeless veterans within its care system that enables the VA to assess the effectiveness of programs and strategically allocate resources to prevent homelessness.^24,25

A list of veterans who filed disability compensation and pension claims was obtained from the VBA Office of Performance Analysis and Integrity, including Social Security number, name, city and state, date of claim submission, grant or increase in benefits, homeless status, VA home loan approval, and homeless aid for dependent children from fiscal year (FY) 2022 through FY 2024. VBA data were linked to VHA CDW electronic health record data from veterans who sought VA health care services and HOMES data on veteran participation in homeless programs who were also experiencing homelessness. VHA data included demographic characteristics (eg, sex, age, race, marital status, combat service) at an index date (earliest visit to the VHA between October 1, 2021, and September 30, 2024); military sexual trauma; clinical characteristics within 12 months prior to the index date (VHA disability rating, substance use disorder [SUD] diagnosis, mental health disorder diagnosis, Charlson Comorbidity Index [CCI] score), and homelessness experience ≤ 5 years prior to the index date.

History of homelessness ≤ 5 years prior to the index date was determined using an operational definition of homelessness based on multiple indicators, including International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic code Z59.0; clinic stop codes or HOMES records indicating VA homeless programs clinical encounters; or a positive screen on an annual homelessness screener.¹⁶ US Department of Housing and Urban Development-VA Supportive Housing enrollees were excluded because they are considered to no longer be experiencing homelessness, and Veterans Justice Program enrollees were excluded because the program primarily focuses on serving criminal justice-involved veterans. The CCI predicts the risk of death ≤ 1 year by assessing the number and severity of a patient’s coexisting health conditions and is a valuable tool for understanding a patient’s overall health burden, aiding in clinical decision-making and evaluation research studies.^26-29 Diagnoses based on ICD-10-CM codes were used to determine SUDs, mental health disorders, and CCI score, using methods that have been described in other publications.³⁰

Population

The VBA cohort of veterans requesting benefits was further restricted to those who met the following eligibility criteria: (1) requested VA benefits FYs 2022 to 2024; (2) sought VHA services ≥ 1 time between FY 2022 and 2024; (3) had matching VBA/VHA records; (4) had no missing data on claim status and/ or demographic, clinical, and homelessness characteristics; and (5) had known home loan status FYs 2022 to 2024. The original VBA dataset consisted of 4,219,755 records and the original VHA dataset consisted of 7,170,199 records (Figure 1). The final linked VBA/VHA dataset after excluding 29 records with missing data on sex, 7 with missing data on age, 6 with missing data on marital status, and an additional 143,444 with unknown VBA claim status, consisted of 3,089,295 records corresponding to 2,260,851 unique veterans. Specifically, 251,796 records corresponded to veterans who had applied and received a loan, 84,751 to veterans who had applied and were nonrecipients of a loan, and 2,752,748 to veterans who did not apply for a loan.

Statistical Analysis

All statistical analyses were performed using SAS Enterprise Guide, an application that provides a point-and-click interface for data access, analysis, and management, accommodating both code-based and visual programming. ³¹ First, we relied on the final analytic sample to calculate the annual proportions of veterans who applied for and/or received a loan through the VA Home Loan Program. We also generated descriptive statistics stratified by age group, sex, race/ethnicity, SUD, mental health disorder, and homelessness, overall and within each FY. Pearson χ² and Cochran-Armitage trend tests were applied to examine differences in application and receipt of a home loan by baseline characteristics and FY, respectively. Second, we conducted bivariate and multivariable analyses to compare demographic, clinical, and homelessness characteristics between 3 groups of veterans as they pertain to the VA Home Loan Program. Veterans who applied and were nonrecipients of a loan (group 1), veterans who applied and were recipients of a loan (group 2), and veterans who did not apply for a loan (group 3). Similar analyses compared VA Home Loan Program applicants who were recipients of a home loan vs VA Home Loan Program applicants who were nonrecipients of a home loan. Multinomial and binary logistic regression models were constructed to estimate the relative risk ratio (RR) and odds ratio (OR) with 95% CIs for comparisons between these distinct groups on demographic, clinical, and homelessness characteristics. Two-sided statistical tests were evaluated at α = 0.05.

Results

Tables 1 and 2 present the number of VBA applicants, including those who applied for and received benefits through the VA Home Loan Program, by age group, sex, race/ethnicity, as well as histories of SUDs, mental health disorders, and homelessness, overall, and by FY. As shown in Figure 2, 336,547 of 3,089,295 VBA applications (10.9%) pertained to the VA Home Loan Program, with a statistically significant decline in application rates, from 12.2% in FY 2022 to 9.9% in FY 2024 (P < .001 for trend). Among 336,547 veterans who applied for the VA Home Loan Program, 251,796 (74.8%) received a home loan during FYs 2022 to 2024, ranging between 73.8% for FY 2024 and 75.5% for FY 2023 (P < .001 for trend).

Multinomial logistic regression models for demographic, clinical, and homelessness characteristics as predictors of VA Home Loan Program status are provided in Appendix 1. Based on the fully adjusted model, compared with veterans who did not apply to the VA Home Loan Program, those who applied for a home loan were less likely to be aged ≥ 50 years, unmarried, Hispanic ethnicity, mixed race, or other race, diagnosed with a SUD, or history of homelessness. Veterans with higher VA service-connected disability ratings were more frequently recipients of VA home loans, whereas those who self-identified as non-Hispanic Black and those with higher CCI scores were less frequently recipients of VA home loans. Finally, those with mental health disorders were more likely than their counterparts to be applicants (recipients or nonrecipients) of VA home loans.

Binary logistic regression models for demographic, clinical, and homelessness characteristics as predictors of receipt status among applicants to the VA Home Loan Program are provided in Appendix 2. Among applicants, those who were granted a VA home loan were less likely to be aged ≥ 50 years; have a CCI score > 0; have experienced combat service and/or military sexual trauma; be diagnosed with a SUD and/or mental health disorder; or to have a history of homelessness compared with those denied a VA home loan. Applicants granted a VA home loan were also more likely to be female, non-Hispanic White, single or never married, and/or have a VA service-connected disability ratings > 0%.

Discussion

The VA Home Loan Program is a unique benefit and resource for eligible veterans that may be increasingly important in a time of growing concern about the affordability of housing for many Americans. Research on other federally-supported home loan programs as well as private home mortgage programs has been mostly conducted in the economic realm, and studies focused on understanding these programs from a health care system perspective have been sparse.^32,33 However, there is a large body of literature documenting the importance of stable, safe, and secure housing on health and well-being.^34-37 This study did not focus on evaluating the effects of the VA Home Loan Program, because we wanted to first examine the characteristics of veterans who benefited from the program and how they differed from veterans who did not apply or did apply but had a denied application.

Our findings suggest that several thousands of veterans benefit from the VA Home Loan Program each year. For historical context, the time period examined was one of economic downturn with rising costs of living, including housing, and steady increases in homelessness as reported in the annual point-in-time count of sheltered and unsheltered people experiencing homelessness on a single night as mandated by the US Department of Housing and Urban Development.^38-40 The Sergeant First Class Heath Robinson Honoring Our Promise to Address Comprehensive Toxics (PACT) Act of 2022 expanded health care and benefits for veterans exposed to burn pits, Agent Orange, and other toxic substances, resulting in more VA disability benefit claims, including large retroactive payments.^41-43 Anecdotally, the VBA has noted that the PACT Act helped some homeless veterans with funds and stability to exit homelessness and enroll in the VA Home Loan Program.

Our analysis suggests that beneficiaries of the VA Home Loan Program were frequently aged < 50 years, female, of non-Hispanic White race, and did not have histories of psychiatric disorders or homelessness. Most of these demographic and clinical characteristics were not surprising given the composition of the veteran population, although in-depth analyses are needed to examine sex differences that may have led to more females than males benefiting from the VA Home Loan Program. In addition, it was notable that many younger and non-Hispanic Black veterans had applied. While relatively few veterans with SUDs benefited from the VA Home Loan Program, few had applied. Research is warranted into why veterans with SUDs are less likely to apply for home loans. Quite surprisingly, a sizable proportion of veterans with histories of homelessness reported they had applied to the VA Home Loan Program, although they were less likely than veterans who had not experienced homelessness to be granted a loan.

The examination of differences between veterans who did not apply, were granted, and denied a loan through the VA Home Loan Program revealed several key predictors of application outcomes in multivariable models. Specifically, veterans who applied for home loans were less likely to be aged ≥ 50 years, unmarried, of Hispanic, mixed, or other race/ethnicity, diagnosed with an SUD, or have a history of homelessness. Veterans with higher disability ratings were less frequently denied and more frequently approved, while non-Hispanic Black veterans and those with higher CCI scores were more frequently denied and less frequently approved. VBA applicants with mental health disorders were also more likely to apply for a home loan. Conversely, those granted a home loan were more likely than those denied a home loan to be female, non-Hispanic White, single/unmarried, or to have > 0% VA service-connected disability rating, but less likely to be aged ≥ 50 years, have CCI score > 0, be diagnosed with psychiatric disorders, or have a history of homelessness.

Limitations

This analysis was restricted to a subset of FY 2022 to FY 2024 linked VBA/VHA databases (ie, to veterans who had both VBA and VHA records and met prespecified eligibility criteria). Despite the large number of linked records, a small percentage of these records corresponded to veterans who were applicants or recipients of the VA Home Loan Program. Future studies should expand the time frame to examine variations in application outcomes over time and by background characteristics of veterans enrolled in VHA care who applied for VBA benefits. In addition, we relied on data and ICD-10-CM diagnostic codes from existing electronic health records and claims data to define histories of homelessness, comorbidities, SUDs, and mental health disorders. Given the time-varying nature of these conditions, the temporal sequence of events was difficult to ascertain. Third, it is worth noting that these findings can only be generalized to veterans who applied for VBA benefits and met eligibility criteria, and that these veterans may differ in terms of their demographic and clinical characteristics from those who did not apply for these benefits.

Conclusions

This study analyzed data from 251,796 individuals who applied for and received a VA home loan, 84,751 who were denied a VA home loan, and 2,752,748 veterans who did not apply for a VA home loan from FY 2022 to FY 2024. Accordingly, 11% of applications pertained to the VA Home Loan Program, and 75% of VA Home Loan Program applicants received a home loan. Distinct demographic and clinical characteristics were observed for applicants and recipients of the VA Home Loan Program, which can set the stage for future planning and evaluation of the program. Despite the broad accessibility of veterans to the VA Home Loan Program, there were differences in approval rates among applicants based on sociodemographic and clinical characteristics. Further evaluation, perhaps using qualitative methods, is needed to better understand opportunities and challenges to achieving a VA home loan, especially among underserved veteran populations. Investigation and research can guide future recommendations for any development or corrective actions that can help increase access to veterans who can benefit from the program. Future analyses are also needed to compare veterans enrolled and not enrolled in the VA Home Loan Program on health care-related outcomes.

Traumatic brain injury (TBI) is the signature injury of post-9/11 military operations, impacting > 441,000 combat veterans from 2001 to 2021 and 87% diagnosed with mild TBI (mTBI).^1,2 The most common cause of mTBI during these operations was blast exposures stemming from improvised explosive devices, rocket-propelled grenades, or land mines. mTBI was once thought to be self-limiting, lasting hours or days postinjury, but is now recognized as a complex focal and diffuse injury causing a cascade of molecular and biochemical responses with significant physiologic effects lasting for a longer duration. A significant number of combat veterans with mTBI (23%-48%) experience long-standing postconcussive symptoms (PCSs) for many years postinjury.^3-5

Developing and implementing strategies to reduce persistent symptoms associated with mTBI is of critical importance. Veterans diagnosed with mTBI and experiencing PCSs present ongoing treatment challenges to the health care system due to limited or suboptimal treatment options.^6,7 According to the 2021 US Department of Veterans Affairs (VA) and US Department of Defense (DoD) clinical guidelines for postacute mTBI, treatment for PCSs should be symptom focused. ^8,9 For instance, veterans with migraine headaches associated with mTBIs are often treated with abortive agents (eg, triptans) and preventive medications (eg, anticonvulsants and tricyclics).¹⁰ Cognitive dysfunction and insomnia are treated with cognitive rehabilitation programs, cognitive behavioral therapy, occupational therapy, and medications (eg, hypnotics for insomnia).^11,12 The 2021 VA/DoD guidelines note that veteran and military focus groups described greater success with nonpharmacologic treatments than with pharmacologic treatments.⁸ The VA launched an enterprise-wide Whole Health Service program with the requirement that complementary and integrative health approaches must be available to veterans.¹³ As a nonpharmacologic, integrative, and noninvasive modality, neurofeedback (NFB) supports the VA Whole Health initiative and veterans’ preferences for integrative treatments.¹⁴

Neurofeedback

Rather than a symptom management approach, Defina et al described the possibilities of brain repair in TBI by treatments to enhance neuroplasticity, thereby establishing a more normalized or stable brain environment and enabling the brain to reorganize itself and function more normally.¹⁵ NFB has been shown to influence neuroplasticity,¹⁶ as evident in microstructural changes in white and gray matter¹⁷ and its ability to contribute to functional rehabilitation by restoring connectivity in specific areas of the brain that may have been impaired.¹⁸ The benefits of neuroenhancement strategies include potentially reduced pain for patients with mTBI and improved quality of life (QOL).¹⁹

NFB assists individuals by helping them become more aware of and self-regulate their physiology.^20,21 Because there are several types of NFB (eg, quantitative electroencephalography, Z-scored, α-θ) that differ in terms of equipment, mechanism of action, focus, and patient and clinician procedures, it is important to note that this study used a novel technologically advanced form of NFB, referred to as infra-low frequency (ILF) NFB. It works by reflecting a person’s brain wave activity via conventional electroencephalography back to the person through the visual cortex, thus providing relevant information to which the brain responds to improve core state regulation.²²

In 2006, ILF NFB developers sought to extend NFB capability into the slow cortical potential domain (< 0.1 Hz) and then gradually extended to lower frequencies on the basis of favorable clinical responses.^22,23 In 2017, the technology reached an ILF capacity that appeared to be helpful for several clinical issues. These developments depended on instrumentation capable of low noise signal detection down to the lowest frequency of interest. Instrumentation was developed for the purpose (eg, Bee Medic Cygnet NFB).

Although mTBI has been a clinical focus in NFB since the 1980s, there are few published studies demonstrating the efficacy of ILF NFB relating to the PCSs of interest in this study, and 2 suggested ILF NFB positively affected change in PCS severity.^24,25 Other studies found that ILF NFB decreased incidence of migraines and tension type headaches.^26,27 However, the findings of these studies had limited generalizability due to methodologic limitations, such as selection bias and small sample sizes.^24-27 Of importance to this article, there are also several publications on the efficacy of ILF NFB in clinical settings.^28-33

This article presents the second analysis of data from veterans who completed ILF NFB intervention and control group procedures during a 5-year randomized controlled trial (RCT). The RCT included veterans who experienced an mTBI while participating in post-9/11 military operations to evaluate the impact of ILF NFB on chronic PCSs, including headache, insomnia, and attention dysfunction. Initial results of this trial demonstrated significant differences between the intervention and control groups with strong effect sizes on all outcome measures at the end of treatment.³⁴

Methods

Participants included male and nonpregnant female veterans with a diagnosed mTBI during post-9/11 military operations; aged 18 to 65 years; reports of persistent (ie, > 3 months in duration) headaches, insomnia, and attention difficulties; and able to read and write English, comprehend what is read, and follow directions. mTBI diagnosis was verified for each veteran via the electronic health record. Patients were excluded if they had a severe TBI diagnosis or impaired decision-making capacity; were unable to comply with study visit schedule; or endorsed active suicidal intent on the Columbia-Suicide Severity Rating Scale.³⁵

Recruitment efforts included: (1) letters sent to eligible veterans with mTBI who were identified by clinical informatics data after waiver of Health Insurance Portability and Accountability Act was obtained; veterans could contact the research team directly or the research team would call the veteran 2 weeks after the letter was sent; (2) veterans could be referred by a clinician; and (3) veterans could self-refer based on flyers and other study marketing materials.

The study was conducted from 2019 to 2024 at Spark M. Matsunaga VA Medical Center, in Honolulu, Hawaii. Four private research spaces in compliance with human research standards were used for consent, treatment, and assessment.

Consenting Procedure and Randomization

The privacy rights of potential participants were observed, and interested veterans who met the eligibility criteria underwent an informed consent procedure and were administered the Columbia-Suicide Severity Rating Scale.³⁵ Those veterans not indicating active suicidal intent were randomized into the intervention or control group. Once randomized, the participant was enrolled and scheduled for baseline assessment.

All procedures of this study were performed in adherence with relevant laws and institutional guidelines. The study was reviewed and approved by the VA Pacific Islands Health Care System Institutional Review Board (#2019-06-JC/Promise 0003).

Outcome Measures

The outcome measures were administered at baseline, midpoint (3-7 weeks), end of treatment (6-12 weeks), and at a 2-month follow-up appointment with the research assistant or project coordinator.

The primary outcome measures included the Headache Impact Test (HIT-6), TBIQOL Headache Pain item short form, Insomnia Severity Index (ISI), Quality of Life in Neurological Disorders (Neuro-QOL) Sleep Disturbance short form, and attention measure: QIKtest Continuous Performance Test (QIKtest) (Table 1).^36-44

Secondary outcome measures included QOL After Brain Injury (QOLIBRI), Neuro- QOL Satisfaction With Roles/Activities short form (Neuro-QOL Satisfaction), Neuro-QOL Ability to Participate in Roles/Activities short form (Neuro-QOL Participate), Depression Anxiety Stress Scales (DASS-21), Patient Health Questionnaire-9 (PHQ-9), Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5), and the General Symptom Inventory (eAppendix 1).^39,42,45-52

Sample

Seventy-two participants (36 in each group) were needed to have adequate statistical power for the analysis. Presuming attrition, the goal was to recruit 100 veterans. Literature on NFB studies of patients with mTBI have reported dropout rates ranging from 10% to 30%.^53,54 Assuming a dropout rate of 28% and a moderate autocorrelation of 0.6 among repeated measures, this sample size ensured the detection of an average difference of at least 0.49 SDs with a power of 80% in the NFB intervention group compared with the control group using a 2-tailed significance level of 0.05.

Control Group

Following baseline assessment, control group participants received 8 phone calls (1 call/wk) from 1 of 4 clinical investigators over 8 to 10 weeks. During each 15-minute call, 1 of the following health topics was discussed: sleep hygiene, basic nutritional concepts, beverage choices, positive thinking, thought reframing, fitness, daily calming activity, and enhancement of focus strategies. A script for each topic was used to guide each call.

Intervention Group

Following baseline assessment, intervention group participants completed 20 half-hour ILF NFB sessions, typically receiving 3 sessions per week over an 8- to 10-week period. ILF NFB treatments were administered by 1 of 4 licensed health care employees who had received substantial ILF NFB training and achieved a skill reliability index score of 0.95, ensuring the skill level of the ILF NFB providers was equal. A script was used by the ILF NFB providers during the ILF NFB sessions to keep the interaction approach consistent with all participants.

All procedures were explained in advance to participants and voluntary participation affirmed. At the first session, participants filled out a clinical symptom checklist of 5 symptoms (eAppendix 1).^39,42,45-49 The initial rating on the symptom checklist was reflective of their experience over the past month, while in each subsequent session, participants indicated their experience of those symptoms that day. ILF NFB providers were never privy to participants’ primary or secondary outcome measures data during the study, so these recurring clinical symptom checklist ratings, as well as other feedback provided by participants on their experience within and between sessions, were the clinical data used to make decisions about ILF NFB treatment protocol.

The Othmer Optimal Response Frequency (ORF) protocol was used for participants in this study.⁵⁵ Through an iterative process, ORF protocol establishes the specific frequency point along the 0.000001 mHz to 0.1 Hz continuum, which is optimal to diminish symptoms experienced in real-time during the session (eg, tension or pain in shoulders; racing thoughts).

During each ILF NFB session, participants were seated comfortably and encouraged to look at the feedback screen. The moving images on the game screen provided almost instantaneous feedback (within 500 ms) to participants about their brain functioning, as ascertained by electrodes placed on the scalp as dictated by study protocol.⁵⁶ A standardized protocol for site placement was used beginning with T3-T4, followed by the weekly addition of a site as tolerated in the following sequence: T4-P4, FP2-T4, and FP1-T4. More information about the ILF NFB procedures are outlined in the report of the pilot study and RCT initial results.^22,34

Statistical Analysis

Eighty-seven participants were randomized, with 43 assigned to the intervention group and 44 to the control group to achieve the enrollment goal of ≥ 36 participants in each group. This report is the second analysis of data from this RCT that employed a per-protocol approach, analyzing a subset of participants who fully adhered to the study protocol and completed all study procedures. Outcome scores at baseline, midpoint, end of treatment, and 2-month follow-up were summarized as means with corresponding 95% CIs. Group comparisons at the end of treatment and 2-month follow-up time points were conducted using 2-sample t tests. All statistical tests were 2-sided with a significance level of .05 (Type I error rate). SAS software version 9.4 Maintenance 8 was used for statistical analysis. Cohen d analyses were used for effect sizes.

Results

Seventy-four participants fully adhered to the study protocol and were included in the present analyses, with 38 in the control group and 36 in the intervention group. eAppendix 2 depicts the flow of participants through this study. There were no adverse events related to treatment, and the 13 participants who withdrew typically reported difficulty with scheduling or transportation as the primary reason. This study also took place during the COVID-19 pandemic, which likely had some impact on enrollment; participants were differentially impacted by changes in employment and moves to the continental US.

Participants were aged 30 to 60 years (mean [SD], 45.4 [8.0]). Most participants (90.5%) were male, and multiracial and White were the most common racial identities (Table 2). Participant characteristics were largely balanced across randomized groups. Similarly, test scores on the primary variables of interest in this study and secondary clinical variables assessed were comparable across participants (Table 3).

Primary Variables of Interest Analyses

This study’s hypothesis was that those who completed ILF NFB treatment per protocol would demonstrate statistically significant improvement in symptoms related to headaches, sleep disturbance, and difficulty with attention when compared with veterans in the control group. This hypothesis was partially supported. A 2-sample t test showed that veterans in the intervention group demonstrated significant improvement in headache symptoms compared with veterans in the control group on the HIT-6 at the end-of-treatment (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 1.14). This pattern also was consistent with the TBI-QOL Headache Pain item short form, with veterans in the intervention group showing improvement beyond those in the control group at the end-of-treatment (P < .001, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.83). Two-sample t tests also demonstrated significant improvement in subjective reports of sleep; those in the intervention group had significantly lower scores on the ISI at the end-of-study (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 0.97). This pattern also held true for the Neuro-QOL Sleep Disturbance short form subtest, which demonstrated significantly more improvement in the intervention group compared with the control group at the end-of-study (P < .001, d = 0.97) and 2-month follow- up assessment (P < .001, d = 0.92). improvement in attention was not supported by the present results. A 2-sample t test found no significant difference between performance on the QIKtest for veterans in the intervention group vs the control group at the end-of-study (P = .40, d = 0.19) or the 2-month follow-up (P = .43, d = 0.20) (eAppendix 3).

Secondary Variables of Interest Analysis

Secondary variables examined differences in QOL, PTSD, depressive symptoms, and general symptoms reported between veterans in the intervention and control groups. Results demonstrated that veterans in the intervention group showed improvement above and beyond those in the control group on all measures. In regard to QOL, veterans in the intervention group had significantly higher scores on the Neuro-QOL Participate subtest than those in the control group at the end-of-study (P = .01, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.62). A similar pattern was found for the Neuro-QOL Satisfaction subtest, with veterans in the intervention group showing significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.95) and 2-month follow-up assessment (P < .001, d = 0.62). This also held true on the QOLIBRI, with veterans in the intervention group demonstrating significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.92) and 2-month follow-up assessment (P < .001, d = 0.66).

Veterans in the intervention group had significantly lower scores on the PCL-5 than those in the control group at the end-of- study (P = .003, d = 0.78) and 2-month follow-up assessment (P = .001, d = 0.72). Veterans in the intervention group also had significantly lower scores on the PHQ-9 than those in the control group at the end-of-study (P < .001, d = 0.98) and 2-month follow-up assessment (P < .001, d = 0.83). Veterans in the intervention group had significantly lower scores on the DASS- 21 than those in the control group at the end-of-study (P = .002, d = 0.80) and 2-month follow-up assessment (P = .001, d = 0.77). They also had significantly lower scores on the General Symptom Inventory than those in the control group at the end-of-study (P = .02, d = 0.75) and 2-month follow-up assessment (P = .002, d = 0.57). A clinically significant shift of score occurred for each of the measures except DASS-21 (eAppendix 3). eAppendix 4 depicts the change in scores for the intervention group at the end of treatment and the clinically significant shift score of each measure.

Discussion

The results of this RCT revealed a promising impact of ILF NFB on the commonly experienced persistent PCSs of headaches and disrupted sleep. Veterans in the intervention group demonstrated statistically significant improvement in headache symptoms compared with veterans in the control group when assessed at the end of treatment and during a 2-month follow-up. The statistical significance of these improvements was also supported by large or very large effect sizes. In addition to these primary variables of interest, veterans in the intervention group notably demonstrated significant improvement compared with those in the control group in a number of secondary clinical measures, including QOL, traumatic stress-related symptoms, depressive symptoms, and general symptom report. The clinical impact was further supported by the clinically relevant shift in scores in the intervention group.

The data did not support the hypothesis that attention concerns would show significant improvement following ILF NFB. Performance on an attention measure did not differ significantly between groups at either the end-of-treatment or 2-month follow up assessment. The QIKtest, a continuous performance test used to measure attention, was a go/no-go task and calculated based on a combination of various types of errors and outlier responses. The stimulus for this task is a series of computerized, blinking lights, for which participants are tasked with discriminating targets and nontargets under time pressure. However, the order of the stimuli are consistent across administrations, rather than being randomized, introducing a potential confound of practice effects on this task since patients were administered the QIKtest 3 times in a 2-month period and again 2 months later. Veterans in the control group notably improved in their average performance of this task from baseline to the endpoint of their treatment participation and demonstrated further improvement at the 2-month follow-up assessment; this pattern would be consistent with potential practice effects and warrants caution in its interpretation for both groups.

Previously published ILF NFB clinical studies that used the QIKtest and found positive results were mostly conducted among children and teen populations across longer treatment periods. This research may indicate the QIKtest is not an appropriate measure to assess adults who have specialized training in responding to stimuli (ie, trained military personnel). This suggests the concept of attention dysfunction experienced by veterans and the best method to measure it may need to be explored further. This construct may not be related to the focus and skill in prolonged attention needed in selecting go/ no-go tasks, but rather related to a broader conceptual basis involving memory, recall, clarity of rational thought, and decision making impacted by the mTBI. For instance, a study among combat veterans with mTBI and PTSD found that performance on objective cognitive measures did not significantly correlate with their subjective reports of cognitive difficulties.⁵⁷ This reflects the pattern of the present study, in which subjective reports of attention improved over time on the clinical symptom checklist filled out by participants at each session, but the objective measure did not. The mean attention dysfunction score was 6 at session 1 and 1 to 2 at session 20 (lower scores are better on a 10-point scale).

Strengths and Limitations

This study presents results stemming from the first RCT examining clinical effectiveness of ILF NFB in a VA setting for veterans with diagnoses of mTBI. The study design shows promising external validity. Veterans were able to participate in a treatment consisting of 20 sessions over a period of typically 8 to 10 weeks, entailing 2 to 3 sessions per week, with an attrition of only 18% over the course of the study. Notably, attrition rates may have been impacted by the time course of the study, which was recruiting and running participants throughout the COVID-19 pandemic (March 2020 to May 2023). No attrition was due to the intervention itself, and no adverse reactions to ILF NFB were reported during the course of the study. Other strengths of the study include the ethnically and racially diverse participants, representative of the population of veterans in Hawaii. Additionally, all ILF NFB providers underwent supervised ILF NFB training and achieved a skill reliability index score of 0.95 prior to providing ILF NFB to the intervention group.

This study was not blinded. Neither veterans nor ILF NFB clinicians were blinded and were therefore aware of the randomly assigned groups. Research assistants administering the periodic assessments were meant to be blinded to condition by design; however, as the study progressed, a research assistant became unintentionally aware of each study participant's condition based on required documentation in the veteran’s health records; more notes were present for those in the intervention group (20 specialist notes) than the control group (8 notes). While the presence of a control group represents a strength relative to much of the existing ILF NFB literature, the control group in this case did not account for the total time spent with the researchers. Participants in the intervention group met with researchers for 20 total sessions as opposed to 8 telephone calls. Therefore, the study design cannot fully rule out the differential impact of demand characteristics between the 2 groups, nor can it fully address or rule out the impact of differential motivation and expectations between groups. There is also evidence that technological innovation can influence the expectations of research participants, meaning that the intervention group may have been unduly influenced by the novelty of the ILF NFB technology, to which the control group did not have exposure.⁵⁸

A second attention measure for this study would have been beneficial, perhaps in identifying true change in attention ability or providing more insight into finding better methods to assess attention among veterans with mTBI. ILF NFB demonstrated significant impact across multiple outcome measures of clinical relevance for veterans diagnosed with mTBI, including the primary outcome variables of headache and sleep. The strength of the improvements seen in these areas, supported by large practical effects as well as veterans’ subjective reports, indicates much promise. Follow-up studies may also focus on the potential effectiveness of ILF NFB as a treatment of the secondary concerns measured in this study, including traumatic stress-related and depressive symptoms, and may explore the added benefit, if any, of ILF NFB alongside other evidence-based treatments for traumatic stress-related and mood disorders (eg, cognitive behavioral therapy). Using functional magnetic resonance imaging before and after assessments to determine actual brain enhancement with ILF NFB for certain disorders in which a brain signature exists (ie, migraine) should be explored. Further examination of ILF NFB as an intervention for attention may also be warranted, using more effective measures of attention in the population of veterans with mTBI, given the concerns noted earlier. Future research on this topic will need to clearly define attention in relation to the veteran experience and use relevant measures.

Conclusions

This study supports ILF NFB as a safe, noninvasive, nonpharmacologic treatment that may be effective in addressing the complex clinical concerns of veterans diagnosed with mTBI, a population for whom effective treatments have been difficult to identify. This intervention can provide veterans with a desirable and effective nonpharmacologic alternative in their care.