Orthopedic Conditions and Treatment Patterns Among Unhoused Urban Patients: A Street Medicine Study

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Street Medicine Phoenix (SMP) is a mobile healthcare initiative composed of medical students and physicians providing free medical screenings to this population. This study aims to characterize the prevalence, demographic distribution, and treatment of orthopedic conditions among unhoused patients in an urban street medicine program. Methods This retrospective observational study analyzed patient encounters from August 2023 to August 2024, collected by SMP in Phoenix, Arizona. Orthopedic conditions were identified through review of Subjective, Objective, Assessment, and Plan (SOAP) notes from 1,193 adult patient encounters. Diagnoses were categorized into clinical MSK types. Treatments included pharmacologic and non-pharmacologic interventions. Descriptive statistics, Mann-Whitney U tests, and chi-squared tests were used to assess differences by age and sex. Results are reported with 95% confidence intervals. Results Of 1,193 encounters, 228 (19.1%) involved orthopedic issues. The mean age of patients with MSK conditions was 50.2 years (95% CI: 48.9–51.5); 33.6% identified as female. The most common diagnoses were joint pain (23.2%), trauma (20.6%), arthritis (12.3%), chronic pain (10.1%), and radiculopathy (8.3%). A statistically significant age difference was observed between patients with trauma and arthritis (p < 0.05). Oral NSAIDs were the most common treatment (36%), followed by topical therapies such as NSAID gels, lidocaine, or steroid creams (20%), durable medical equipment (21%), and wound care kits (6%). No significant differences in treatment rates by sex were identified. Conclusions Orthopedic conditions are prevalent among unhoused individuals and represent a major source of morbidity. Mobile care models like SMP provide effective, immediate treatment using accessible modalities. Low-barrier treatments—particularly oral NSAIDs and durable medical equipment (DME: defined as boots,braces,walkers,crutches etc)—represent feasible and effective interventions that improve pain and function in vulnerable populations with limited access to traditional care pathways. This study underscores the need for scalable MSK interventions and provides a data-driven framework for improving orthopedic care among unhoused populations. Trial Registration Not applicable. unhoused orthopedic MSK DME Figures Figure 1 Figure 2 Figure 3 Introduction Orthopedic conditions such as joint pain, traumatic injuries, and degenerative disorders are common causes of morbidity and functional decline in the general population. However, unhoused individuals face an elevated burden of musculoskeletal (MSK) issues due to factors including occupational exposure, lack of protective gear, environmental hazards, and prolonged periods of immobility or repetitive trauma related to survival activities【1】. Despite the high prevalence of MSK complaints in this population, the delivery of appropriate care is often hindered by limited access to diagnostic tools, follow-up care, and continuity of treatment【2–4】. Street Medicine, a model of healthcare that provides direct care to unsheltered individuals in their own environments, has emerged as a promising strategy to bridge this gap. By removing traditional barriers such as transportation, insurance, and institutional mistrust, street medicine programs can deliver timely interventions for acute and chronic orthopedic conditions【5】. However, there remains a paucity of research characterizing the specific orthopedic needs of this population, or evaluating how street-based interventions are utilized in real-world practice. Existing literature largely focuses on mental health, substance use, and infectious disease in homeless populations, with orthopedic care rarely discussed despite its relevance to mobility, employment potential, and daily survival【6】. Moreover, the management of MSK conditions in this population is often constrained by practical considerations such as the lack of refrigeration for medications, risk of equipment theft, and the inability to attend follow-up visits or imaging appointments【7】. As a result, low-barrier, point-of-care interventions—such as oral NSAIDs, topical analgesics, wound care, and the distribution of braces or walkers—may play a central role in functional support, yet have not been systematically studied. This study aims to characterize the types of orthopedic conditions encountered in an urban street medicine program, describe the demographic profile of affected individuals, and analyze the treatment modalities employed in this setting. By providing a descriptive framework of orthopedic burden and care delivery, this study seeks to inform future guidelines for low-barrier MSK interventions among unhoused populations. Methods Study Design and Setting This was a retrospective, observational study conducted through Street Medicine Phoenix (SMP), a mobile healthcare program affiliated with the University of Arizona-Mel and Enid Zuckerman College of Public Health. SMP provides medical care to unsheltered individuals at shelters, encampments, and public spaces across central Phoenix, Arizona. The study included patient encounters from August 2023 to August 2024. Inclusion criteria were any unhoused patient who had a documented clinical interaction with SMP during the study period and presented with at least one musculoskeletal (MSK) complaint. Encounters were excluded if no SOAP note was available or if the note lacked a clear orthopedic component. Data was obtained from the SMP electronic medical record (EMR) system, which is securely hosted on UA Box Health—a HIPAA-compliant cloud platform. This system stores scanned SOAP notes completed by clinical volunteers during street outreach encounters. Each SOAP note was individually reviewed by members of the research team. Diagnoses and treatment plans were manually categorized into standardized musculoskeletal categories based on the presenting complaint and the clinical assessment documented in the note. For each patient, demographic information (age, sex), diagnosis, and treatment modality were recorded. Data were de-identified prior to analysis. Ethical Approval and Data Privacy This study was approved by the University of Arizona Institutional Review Board (IRB) as a retrospective chart review involving de-identified clinical data. The protocol was approved under the title “ STUDY00004974 The Prevalence of Orthopedic Injuries and Use of Durable Medical Supplies in Urban Unhoused Populations.” All methods were carried out in accordance with the relevant guidelines and regulations. The University of Arizona Institutional Review Board (IRB) waived the requirement for informed consent, as this was a retrospective study involving de-identified data. Images used in this study were modified to remove any identifying information prior to analysis or display. Inclusion and Exclusion Criteria Inclusion criteria were: Adults aged 18 years or older Patients encountered by SMP between August 2023 and August 2024 Clinical documentation indicating an orthopedic or musculoskeletal (MSK) concern, defined as pain, injury, or dysfunction of the bones, joints, muscles, or soft tissue Exclusion criteria were: Patients under 18 years of age Encounters without SOAP note documentation Encounters with non-MSK primary complaints (e.g., psychiatric, dermatologic, infectious) and no secondary orthopedic mention Incomplete or illegible notes that precluded diagnostic or treatment coding Study Population and Data Collection SOAP notes were reviewed from 1,193 unique clinical encounters. Eligible encounters were screened by the research team to determine whether the patient presented with an MSK-related issue. Demographic data (age and sex), presenting complaint, clinical impression, and treatment plan were extracted and entered into a de-identified spreadsheet for analysis. Diagnosis and Treatment Classification Orthopedic complaints were categorized into clinically relevant groups based on chief complaints and provider documentation in each SOAP note. These diagnostic categories included trauma-related injuries (e.g., falls, fractures, post-operative pain), joint pain (e.g., knee, ankle, or shoulder discomfort), arthritis (such as osteoarthritis or rheumatoid arthritis), chronic pain, radiculopathy or neuropathy, tendonitis, myalgia, carpal tunnel syndrome, back or neck pain, and post-operative care. Chronic pain was defined as any pain persisting for more than three months or described as long-standing, recurring, or non-acute in nature. In cases where a patient presented with overlapping issues—such as joint pain due to trauma or coexisting arthritis and radiculopathy—multiple diagnostic categories were applied. Each diagnosis was codified in a binary format within the study dataset: if a particular condition was present, it was assigned a value of “1”; if not applicable to the encounter, it received a “0.” This approach allowed for patients to be counted in multiple categories when appropriate, reflecting the complexity of real-world complaints. Treatments were similarly organized into 13 predefined categories: oral NSAIDs, acetaminophen, topical NSAIDs (e.g., diclofenac), lidocaine patches, steroid creams (e.g., hydrocortisone), wound care kits, splints, braces (including orthopedic boots), walkers or canes, physical therapy referrals, Vicks VapoRub, and “other” (e.g., compression socks or ice packs). If more than one treatment was provided during a single encounter, multiple categories were marked with a “1” to reflect the intervention(s) used. Encounters in which musculoskeletal care was not documented were categorized as “not addressed.” All diagnostic and treatment classifications followed a standardized codebook developed by the research team to ensure consistency and reproducibility during data abstraction. Statistical Analysis Descriptive statistics were used to calculate frequencies and percentages for all diagnostic and treatment categories. Mean age and sex proportions were calculated with 95% confidence intervals. Differences in age across diagnostic and treatment groups were analyzed using the Mann-Whitney U test. Differences in treatment distribution by sex were analyzed using the chi-squared test. Statistical significance was defined as p < 0.05. All analyses were conducted using Python (v3.10) and associated scientific libraries (e.g., SciPy, Pandas). Results From August 2023 to August 2024, Street Medicine Phoenix served 1,193 unique unhoused individuals, of whom 493 engaged in a clinical encounter. Among these, 228 patients (45.9%) presented with at least one orthopedic concern and were included in the final study sample. The mean age of patients was 51.6 years (95% CI: 49.9–53.3), and 33.6% identified as female (Table 1). Orthopedic diagnoses were diverse, with trauma-related injuries (22.9%), joint pain (19.2%), and chronic pain (14.3%) emerging as the most common categories (Figure 1a). Other conditions, including arthritis (10.6%), tendonitis, and carpal tunnel syndrome, were less frequently recorded. Significant age differences were observed between diagnostic categories: patients with arthritis had a mean age of 58.0 years (95% CI: 54.5–61.5), compared to 51.2 years (95% CI: 48.9–53.6) for trauma, a difference that reached statistical significance ( p < 0.05) (Figure 1b, Table 2). Although sex distribution was relatively balanced overall, males were more frequently represented in trauma and joint pain cases (Figure 1c). Treatment modalities varied across encounters, with oral NSAIDs being the most commonly administered therapy (19.3%), followed by wound care kits (13.4%), acetaminophen (11.5%), and bracing (10.5%) (Figure 2a). Despite this variability, no statistically significant differences in age or sex were found across treatment groups (Figures 2b, 2c; Table 3). The frequent use of non-opioid analgesics and durable medical equipment (DME) underscores the feasibility of low-barrier, point-of-care interventions in field settings. Figure 3a presents a representative SOAP note from a clinical encounter—a standardized documentation format used by Street Medicine Phoenix volunteers to record subjective symptoms, objective findings, assessment, and treatment plans. These SOAP notes formed the basis for data categorization in this study, enabling consistent diagnostic classification and treatment tracking across encounters. In the example shown, a middle-aged woman presented with symptoms consistent with carpal tunnel syndrome. She reported nocturnal pain and paresthesia exacerbated by wrist movement. Objective examination confirmed tenderness and symptom reproduction with wrist compression. She was managed with a wrist brace and over-the-counter ibuprofen, reflecting a conservative, low-barrier treatment plan tailored to field constraints. Through structured documentation and direct intervention, street medicine teams demonstrate that meaningful MSK care can be delivered outside of traditional healthcare environments. Discussion The results of this study highlight the high burden of musculoskeletal (MSK) conditions among unhoused populations, emphasizing trauma (22.9%), joint pain (19.2%), and chronic pain (14.3%) as the most common diagnoses (Figure 1a). These findings echo prior literature reporting disproportionately high rates of physical injury and degenerative MSK conditions among individuals experiencing homelessness due to environmental exposure, repetitive mechanical stress, and limited access to preventive care【8】【9】. In our cohort, pain-related conditions represented over two-thirds of orthopedic encounters, reflecting the chronic, undertreated nature of pain in this population【10】【11】. The significant age-related variation across orthopedic conditions (Figure 1b) further supports the notion that certain pathologies such as arthritis and chronic joint pain may disproportionately affect older patients, while trauma-related injuries span across age groups. Treatment patterns (Figure 2a) further underscore the reliance on low-barrier interventions. Oral NSAIDs were the most commonly provided treatment (19.3%), followed closely by supportive measures such as wound care (13.4%) and bracing (10.5%). These strategies are congruent with prior recommendations to tailor treatment for homeless patients toward interventions that are feasible, low-cost, and effective outside of traditional care settings【12】【13】. Similar field-based approaches have shown promise in disaster response and remote rural care models, where rapid relief and portability are equally critical【16】【17】. Low-barrier treatments—particularly oral NSAIDs and DME options such as braces—represent feasible and effective interventions that improve pain and function in vulnerable populations with limited access to traditional care pathways. In fact during clinical encounters, many patients expressed immediate relief upon wearing and walking with a brace. While this was not quantified in this study, it represents a future scope of treatment options for unhoused patient populations regarding orthopedic issues. The diversity in treatment approaches, as shown by our data, reflects the flexibility required in delivering orthopedic care on the street, where diagnostic clarity may be limited, and patient follow-up is not guaranteed. Statistical analysis revealed a significant association between trauma and younger age, and between chronic pain and female sex (Table 2), reflecting potential gendered patterns in pain perception and care-seeking that warrant deeper exploration【14】【15】. Despite national data suggesting men make up the majority of unhoused individuals, our data found that women represented one-third of orthopedic visits, particularly in arthritis and chronic pain categories (Figure 1c). These sex-based differences in presentation and treatment call for gender-responsive approaches in the delivery of MSK care. The documentation of care through standardized SOAP notes (Figure 3a) and image-based records (Figure 3b) further demonstrates the clinical rigor that can be achieved even in mobile settings. These data not only facilitate care continuity but also establish a foundation for structured research and future outcomes tracking. Integration of mobile EHR systems has already demonstrated success in improving vaccination and chronic disease management among hard-to-reach populations【18】, and similar platforms could be optimized for orthopedic surveillance. Our study fills a critical gap in the literature by offering a granular analysis of orthopedic complaints and interventions in a large, urban street medicine cohort. However, it is not without limitations. As a single-institution, retrospective review, our findings may not be generalizable across all regions. Additionally, the lack of long-term follow-up prevents assessment of treatment efficacy over time. Given the episodic nature of care delivery in this population, outcomes research remains a significant challenge. Nevertheless, previous mobile health models have shown that even episodic care can lead to reductions in emergency department visits and improved trust in healthcare systems【19】【20】. Future directions include prospective investigations into the utility and cost-effectiveness of durable medical equipment (DME) in improving pain and function. Such work could clarify the role of DME as a short-term therapeutic modality for unsheltered patients, a hypothesis supported by the frequent use of braces and splints in this study. In addition, implementation of a centralized digital record system shared across street medicine teams may support tracking of orthopedic outcomes and promote research standardization across cities. Community partnerships and cross-sector collaboration will be essential in scaling such efforts, especially in high-density urban settings where outreach services are fragmented【21】【22】. In summary, this study reinforces the need for targeted, low-barrier orthopedic interventions for unhoused populations, and demonstrates how mobile clinics can serve as both care delivery platforms and data-generating environments. Further research is warranted to evaluate the long-term benefits of these interventions and develop replicable models of street-based musculoskeletal care. This work adds to a growing body of literature calling for scalable, equitable orthopedic care systems adaptable to nontraditional environments【23】【24】【25】. Conclusion This study provides a comprehensive overview of musculoskeletal conditions and treatment patterns among unhoused patients evaluated through a mobile street medicine program. Trauma, joint pain, and chronic pain emerged as the most common orthopedic issues, with low-barrier interventions such as oral NSAIDs, wound care, and durable medical equipment frequently utilized. These findings highlight the adaptability of orthopedic care delivery in resource-limited environments and underscore the urgent need for scalable, street-based MSK interventions. While limited by its retrospective design and single-region scope, this study offers foundational data to inform future research. Prospective evaluations assessing the effectiveness of durable medical equipment in improving short-term function and pain outcomes are warranted to optimize care for this underserved population. Declarations Acknowledgements. The authors would like to thank Dr. Robert Fauer for his mentorship and guidance throughout the development of this project. Special thanks to the dedicated volunteers of Street Medicine Phoenix, whose commitment to providing compassionate care to unhoused patients made this study possible. Our acknowledgements to BioRender for figure panel generation. Finally, we thank Kendall Schwartz for her editorial support in refining the study’s abstract and Isabelle Jae Fisher for reviewing the manuscript. Supplementary Materials In this section, the final codified research data will be included and the IRB Approval letter from clinical encounters used to codify the research data. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Competing interests The authors declare that they have no competing interests. Ethics approval and consent to participate This study was reviewed and approved by the University of Arizona Institutional Review Board as a retrospective chart review involving de-identified data (PI: Sanjana Arun). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The University of Arizona Institutional Review Board approved this retrospective study and waived the requirement for informed consent, as all data were de-identified and collected as part of routine clinical care. IRB approval was granted under the title “ STUDY00004974: The Prevalence of Orthopedic Injuries and Use of Durable Medical Supplies in Urban Unhoused Populations.” Consent for publication Not applicable. All data were de-identified. Images included in this manuscript were modified to remove identifying information. No patient faces or names are visible. No identifying images or personal clinical details are presented in this manuscript. This image has been reviewed to ensure compliance with BMC’s ethical publishing standards. Availability of data and materials The datasets generated during the current study are available from the corresponding author in the supplemental materials. If SOAP note data is required, the authors are happy to provide the manual SOAP note data on request. Materials availability Not applicable. Code availability Not applicable. Authors’ contributions Sanjana Arun conceptualized the study, led data collection, performed statistical analysis, and drafted the manuscript. Tyler Krall, Armine Kasabyan, Taylor Lee, and Joseph Solomon contributed to data collection and manuscript revision. Dr. Robert Fauer served as the project mentor and contributed to study conceptualization and oversight. All authors reviewed and approved the final version of the manuscript. References Fazel S, Geddes JR, Kushel M. The health of homeless people in high-income countries: descriptive epidemiology, health consequences, and clinical and policy recommendations. Lancet . 2014;384(9953):1529-1540. Hwang SW, Burns T. Health interventions for people who are homeless. Lancet . 2014;384(9953):1541-1547. Doran KM, Ragins KT, Gross CP, Zerger S. Medical respite programs for homeless patients: a systematic review. J Health Care Poor Underserved . 2013;24(2):499-524. Martins DC. Experiences of homeless people in the health care delivery system: a descriptive phenomenological study. Public Health Nurs . 2008;25(5):420-430. Withers J, Chandra A, Sadowski LS. The revolution of street medicine: a model for the future of health care. J Health Care Poor Underserved . 2018;29(1):321-327. Baggett TP, O’Connell JJ, Singer DE, Rigotti NA. The unmet health care needs of homeless adults: a national study. Am J Public Health . 2010;100(7):1326-1333. Kushel MB. Factors associated with the health care utilization of homeless persons. JAMA Intern Med . 2001;161(4):393-402. Beijer U, Andreasson S. Physical diseases among homeless people: gender differences and comparisons with the general population. Scand J Public Health . 2009;37(1):93–100. Hwang SW. Homelessness and health. CMAJ . 2001;164(2):229–233. Kertesz SG, et al. Primary care for homeless persons: a systematic review of the evidence. J Gen Intern Med . 2009;24(8):1018–1029. Hudson BF, et al. Challenges to pain management in people with chronic pain and homelessness: a qualitative study. Br J Gen Pract . 2019;69(679):e819–e827. Eberle C, et al. Street medicine for underserved populations: a review. Int J Equity Health . 2020;19(1):1–11. O’Toole TP, et al. Applying new models of care for homeless veterans: the patient-centered medical home. Am J Public Health . 2010;100(8):1497–1499. Green CR, et al. The unequal burden of pain: confronting racial and ethnic disparities in pain. Pain Med . 2003;4(3):277–294. Rué M, Cabré X, Soler-González J, Bosch A, Almirall M, Serna C. Gender differences in health care utilization in Spain. Gac Sanit . 2008;22(6):511–519. Lee AC, Phillips W, Challen K, Goodacre S. Barriers to surge capacity in disaster response: a qualitative study. BMJ Open . 2012;2(1):e000709. McCoy D, Chand S, Sridhar D. Global health funding: how much, where it comes from and where it goes. Health Policy Plan . 2009;24(6):407–417. Irvin C, et al. Improving access to health care using mobile health vans: evaluation of Project Hope. J Health Care Poor Underserved . 2006;17(1):35–43. Sadowski LS, Kee RA, VanderWeele TJ, Buchanan D. Effect of a housing and case management program on emergency department visits and hospitalizations among chronically ill homeless adults: a randomized trial. JAMA . 2009;301(17):1771–1778. Fitzpatrick-Lewis D, et al. Effectiveness of interventions to improve the health and housing status of homeless people: a rapid systematic review. BMC Public Health . 2011;11:638. Buccieri K, Schiff R. Benefits of community-based research for social action. J Poverty . 2016;20(1):45–61. O’Campo P, Stergiopoulos V, Nir P, Levy M. How health and social care services support homeless populations: a realist evaluation. BMC Health Serv Res . 2015;15:37. Axford J, Heron C, Ross F. Development and validation of a musculoskeletal health questionnaire. BMC Musculoskelet Disord . 2010;11:125. Levine DM, et al. Mobile technology for community health in the developing world. JAMA . 2016;315(20):2175–2176. Hwang SW, et al. Universal health insurance and health care access for homeless persons. Am J Public Health . 2010;100(8):1454–1461. Tables Table 1. Demographic Characteristics of Study Population Category N Mean or % 95%CI Lower 95%CI Upper Age 229 51.6 yrs 49.9 53.3 Sex - F 77 33.6% 27.5 39.7 Sex - M 152 66.4% 60.3 72.5 Table 2. Musculoskeletal Diagnoses by Age and Sex Category Number of Patients % of Total (N=228) Mean Age (yrs) 95% CI Lower 95% CI Upper Age p-value Sex p-value Age Test Sex Test Trauma 80 35.1 49.8 yrs 46.7 52.9 0.099 0.481 Mann-Whitney U Chi-squared Joint Pain 67 29.4 54.6 yrs 52.1 57.1 **0.025** * 0.765 Mann-Whitney U Chi-squared Chronic Pain 50 21.9 52.2 yrs 48.9 55.5 0.745 1.0 Mann-Whitney U Chi-squared Arthritis 37 16.2 58.0 yrs 54.5 61.5 **0.001** * 0.461 Mann-Whitney U Chi-squared Infection 30 13.2 53.1 yrs 48.4 57.8 0.540 0.808 Mann-Whitney U Chi-squared Other 29 12.7 49.4 yrs 45.0 53.8 0.324 0.462 Mann-Whitney U Chi-squared Back Pain 25 11.0 47.6 yrs 40.8 54.4 0.104 0.624 Mann-Whitney U Chi-squared Radiculopathy 21 9.2 56.3 yrs 51.9 60.7 0.062 1.0 Mann-Whitney U Chi-squared Carpal Tunnel 5 2.2 51.6 yrs 31.6 71.6 0.921 1.0 Mann-Whitney U Chi-squared Tendonitis 5 2.2 37.6 yrs 22.8 52.4 **0.025** * 0.862 Mann-Whitney U Chi-squared Table 3. Treatment Categories by Age and Sex Category Number of Treatments % of Total Mean Age (yrs) 95% CI Lower 95% CI Upper Age p-value Sex p-value Age Test Sex Test Oral NSAIDS 59 19.3 51.5 yrs 48.1 54.9 0.702 1.0 Mann-Whitney U Chi-squared Other 57 18.7 49.4 yrs 45.0 53.8 0.324 0.462 Mann-Whitney U Chi-squared Wound Care Package 41 13.4 51.0 yrs 46.8 55.2 0.501 0.532 Mann-Whitney U Chi-squared Tylenol/Acetaminophen 35 11.5 50.2 yrs 45.5 54.9 0.681 0.776 Mann-Whitney U Chi-squared Brace 32 10.5 50.6 yrs 46.1 55.1 0.722 0.188 Mann-Whitney U Chi-squared Not Addressed 21 6.9 54.8 yrs 49.2 60.4 0.430 0.832 Mann-Whitney U Chi-squared Topical NSAID 15 4.9 57.9 yrs 50.6 65.2 **0.021** * 0.383 Mann-Whitney U Chi-squared Topical Steroid 10 3.3 47.1 yrs 37.9 56.3 0.318 0.143 Mann-Whitney U Chi-squared PT Recommended 9 3.0 45.8 yrs 34.7 56.9 0.230 0.289 Mann-Whitney U Chi-squared Walker 8 2.6 53.2 yrs 44.0 62.4 0.773 0.095 Mann-Whitney U Chi-squared Topical Lidocaine 7 2.3 51.0 yrs 35.8 66.2 0.839 1.0 Mann-Whitney U Chi-squared Splint 7 2.3 48.1 yrs 38.5 57.7 0.404 1.0 Mann-Whitney U Chi-squared Vicks VapoRub 4 1.3 48.5 yrs 19.6 77.4 0.885 0.367 Mann-Whitney Chi-squared Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Feb, 2026 Read the published version in BMC Musculoskeletal Disorders → Version 1 posted Editorial decision: Revision requested 29 Oct, 2025 Reviews received at journal 18 May, 2025 Reviewers agreed at journal 18 May, 2025 Reviews received at journal 09 May, 2025 Reviewers agreed at journal 06 May, 2025 Reviewers invited by journal 05 May, 2025 Editor assigned by journal 29 Apr, 2025 Editor invited by journal 15 Apr, 2025 Submission checks completed at journal 14 Apr, 2025 First submitted to journal 14 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6390500","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452845114,"identity":"c12a215f-4eaa-4cfd-aa73-a15e31af2190","order_by":0,"name":"Sanjana Arun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYJACAxDBD8QHkAUIa5FsIEULRNkBJDZelfLtZw8U/NxzOM/4+NmHB39U3JFnYG/eJoHX8DN5CYY9zw4Xm51JNzggceaZYQPPsTL8WhhyDAx4DhxO3HYgjeGAYdthxgaJHDO8WuT73xgY/gFq2dz/jOFAYtth+wb5N/i1MNzIMTAG2bJBAmjLwbbDiQ0SPPi1GNx4Y2AscyA9ccaNZwwHG84cTm7jSSu2wO+wHDPDNwesE/v705g//qg4bNvPfnjjDbwOY2BgQ40GNgLKQYD5ARGKRsEoGAWjYCQDAKGOUCrV+dPaAAAAAElFTkSuQmCC","orcid":"","institution":"University of Arizona","correspondingAuthor":true,"prefix":"","firstName":"Sanjana","middleName":"","lastName":"Arun","suffix":""},{"id":452845115,"identity":"30a80e31-cbc2-4ed9-8409-7ff89c727614","order_by":1,"name":"Tyler Krall","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Tyler","middleName":"","lastName":"Krall","suffix":""},{"id":452845116,"identity":"1cab994b-3013-4ed6-a109-532821d66dd7","order_by":2,"name":"Joseph Solomon","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Solomon","suffix":""},{"id":452845117,"identity":"99cb7d90-1879-4bc0-a597-37a8e189ea8d","order_by":3,"name":"Armine Kasabyan","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Armine","middleName":"","lastName":"Kasabyan","suffix":""},{"id":452845118,"identity":"8d6f8c22-75d7-4b9c-a1a7-e2e295d1f35f","order_by":4,"name":"Taylor Lee","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Taylor","middleName":"","lastName":"Lee","suffix":""},{"id":452845119,"identity":"c1c89887-fbe2-4b25-a8cc-a4e4f26acf9b","order_by":5,"name":"Robert Fauer","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Fauer","suffix":""}],"badges":[],"createdAt":"2025-04-07 05:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6390500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6390500/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12891-026-09624-0","type":"published","date":"2026-02-18T15:59:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82354395,"identity":"c36b2095-ca92-4f9a-9632-49793a07f837","added_by":"auto","created_at":"2025-05-09 11:10:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":350126,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea. Distribution of orthopedic complaints among unhoused patients (N=228)\u003cbr\u003e\n \u003c/strong\u003ePie chart showing the proportion of each musculoskeletal diagnosis recorded during street medicine encounters. Trauma (22.9%), joint pain (19.2%), and chronic pain (14.3%) were the most common complaints, followed by arthritis (10.6%), tendonitis (1.4%), and carpal tunnel syndrome (0.6%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Age distribution by musculoskeletal diagnosis\u003cbr\u003e\n \u003c/strong\u003eBox and whisker plots displaying the distribution of patient age across diagnostic categories. Arthritis was associated with an older mean age (58.0 years) compared to trauma (51.2 years), with statistical significance noted (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Asterisk denotes group pairs with significant difference based on Dunn’s test following Kruskal-Wallis analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Sex distribution by musculoskeletal diagnosis\u003cbr\u003e\n \u003c/strong\u003eBar chart showing sex-based distribution of orthopedic complaints. Males were more likely to present with trauma and joint pain, while females were slightly more represented in arthritis and chronic pain cases. Asterisk indicates statistically significant difference in sex distribution for trauma cases (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, chi-square test).\u003c/p\u003e","description":"","filename":"Figure1Panel.png","url":"https://assets-eu.researchsquare.com/files/rs-6390500/v1/c3d58190ba80372169381fb8.png"},{"id":82358903,"identity":"d4e642c1-6613-4e5a-8129-79a11e5b38ae","added_by":"auto","created_at":"2025-05-09 11:26:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":361289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea. Treatment modalities used in orthopedic encounters\u003cbr\u003e\n\u003c/strong\u003ePie chart displaying proportions of treatment types administered in street-based settings. Oral NSAIDs (19.3%) were most common, followed by wound care kits (13.4%), acetaminophen (11.5%), and bracing (10.5%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Age distribution by treatment category\u003cbr\u003e\n\u003c/strong\u003eBox and whisker plot showing patient age by treatment type. No statistically significant differences were observed in age across treatment modalities (Kruskal-Wallis test, \u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Sex distribution by treatment category\u003cbr\u003e\n\u003c/strong\u003eBar chart depicting sex distribution across treatment modalities. While men received more bracing and women were more often treated with wound care and topical agents, no statistically significant differences were found (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05, chi-square test).\u003c/p\u003e","description":"","filename":"Figure2Panel.png","url":"https://assets-eu.researchsquare.com/files/rs-6390500/v1/eaeefe7260ad44ce4d8688b7.png"},{"id":82354416,"identity":"0ec7d7df-e3be-4d5c-bc9e-9e16904a48df","added_by":"auto","created_at":"2025-05-09 11:10:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2817792,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative SOAP note from a musculoskeletal encounter\u003cbr\u003e\n \u003c/strong\u003eExample of a standardized SOAP note completed by Street Medicine Phoenix volunteers. This clinical documentation reflects how SOAP notes were used to code diagnoses and categorize treatments during the study period.\u003c/p\u003e","description":"","filename":"Figure3Panel.png","url":"https://assets-eu.researchsquare.com/files/rs-6390500/v1/15d5ff03e376e5797479a99e.png"},{"id":103251357,"identity":"05b1235a-30cf-4ab7-ae1b-0d091ed93761","added_by":"auto","created_at":"2026-02-23 16:08:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4323693,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6390500/v1/d7687bd5-57a1-4354-b798-a8514fbe4fbe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Orthopedic Conditions and Treatment Patterns Among Unhoused Urban Patients: A Street Medicine Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOrthopedic conditions such as joint pain, traumatic injuries, and degenerative disorders are common causes of morbidity and functional decline in the general population. However, unhoused individuals face an elevated burden of musculoskeletal (MSK) issues due to factors including occupational exposure, lack of protective gear, environmental hazards, and prolonged periods of immobility or repetitive trauma related to survival activities【1】. Despite the high prevalence of MSK complaints in this population, the delivery of appropriate care is often hindered by limited access to diagnostic tools, follow-up care, and continuity of treatment【2\u0026ndash;4】.\u003c/p\u003e\n\u003cp\u003eStreet Medicine, a model of healthcare that provides direct care to unsheltered individuals in their own environments, has emerged as a promising strategy to bridge this gap. By removing traditional barriers such as transportation, insurance, and institutional mistrust, street medicine programs can deliver timely interventions for acute and chronic orthopedic conditions【5】. However, there remains a paucity of research characterizing the specific orthopedic needs of this population, or evaluating how street-based interventions are utilized in real-world practice.\u003c/p\u003e\n\u003cp\u003eExisting literature largely focuses on mental health, substance use, and infectious disease in homeless populations, with orthopedic care rarely discussed despite its relevance to mobility, employment potential, and daily survival【6】. Moreover, the management of MSK conditions in this population is often constrained by practical considerations such as the lack of refrigeration for medications, risk of equipment theft, and the inability to attend follow-up visits or imaging appointments【7】. As a result, low-barrier, point-of-care interventions\u0026mdash;such as oral NSAIDs, topical analgesics, wound care, and the distribution of braces or walkers\u0026mdash;may play a central role in functional support, yet have not been systematically studied.\u003c/p\u003e\n\u003cp\u003eThis study aims to characterize the types of orthopedic conditions encountered in an urban street medicine program, describe the demographic profile of affected individuals, and analyze the treatment modalities employed in this setting. By providing a descriptive framework of orthopedic burden and care delivery, this study seeks to inform future guidelines for low-barrier MSK interventions among unhoused populations.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eStudy Design and Setting\u003c/h3\u003e\n\u003cp\u003eThis was a retrospective, observational study conducted through Street Medicine Phoenix (SMP), a mobile healthcare program affiliated with the University of Arizona-Mel and Enid Zuckerman College of Public Health. SMP provides medical care to unsheltered individuals at shelters, encampments, and public spaces across central Phoenix, Arizona.\u003c/p\u003e\n\u003cp\u003eThe study included patient encounters from August 2023 to August 2024. Inclusion criteria were any unhoused patient who had a documented clinical interaction with SMP during the study period and presented with at least one musculoskeletal (MSK) complaint. Encounters were excluded if no SOAP note was available or if the note lacked a clear orthopedic component.\u003c/p\u003e\n\u003cp\u003eData was obtained from the SMP electronic medical record (EMR) system, which is securely hosted on UA Box Health\u0026mdash;a HIPAA-compliant cloud platform. This system stores scanned SOAP notes completed by clinical volunteers during street outreach encounters. Each SOAP note was individually reviewed by members of the research team. Diagnoses and treatment plans were manually categorized into standardized musculoskeletal categories based on the presenting complaint and the clinical assessment documented in the note. For each patient, demographic information (age, sex), diagnosis, and treatment modality were recorded. Data were de-identified prior to analysis.\u003c/p\u003e\n\u003ch3\u003eEthical Approval and Data Privacy\u003c/h3\u003e\n\u003cp\u003eThis study was approved by the University of Arizona Institutional Review Board (IRB) as a retrospective chart review involving de-identified clinical data. The protocol was approved under the title \u003cem\u003e\u0026ldquo;\u003c/em\u003eSTUDY00004974 \u003cem\u003eThe Prevalence of Orthopedic Injuries and Use of Durable Medical Supplies in Urban Unhoused Populations.\u0026rdquo;\u003c/em\u003e All methods were carried out in accordance with the relevant guidelines and regulations. The University of Arizona Institutional Review Board (IRB) waived the requirement for informed consent, as this was a retrospective study involving de-identified data. Images used in this study were modified to remove any identifying information prior to analysis or display.\u003c/p\u003e\n\u003ch3\u003eInclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e were:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAdults aged 18 years or older\u003c/li\u003e\n \u003cli\u003ePatients encountered by SMP between August 2023 and August 2024\u003c/li\u003e\n \u003cli\u003eClinical documentation indicating an orthopedic or musculoskeletal (MSK) concern, defined as pain, injury, or dysfunction of the bones, joints, muscles, or soft tissue\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria\u003c/strong\u003e were:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePatients under 18 years of age\u003c/li\u003e\n \u003cli\u003eEncounters without SOAP note documentation\u003c/li\u003e\n \u003cli\u003eEncounters with non-MSK primary complaints (e.g., psychiatric, dermatologic, infectious) and no secondary orthopedic mention\u003c/li\u003e\n \u003cli\u003eIncomplete or illegible notes that precluded diagnostic or treatment coding\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eStudy Population and Data Collection\u003c/h3\u003e\n\u003cp\u003eSOAP notes were reviewed from 1,193 unique clinical encounters. Eligible encounters were screened by the research team to determine whether the patient presented with an MSK-related issue. Demographic data (age and sex), presenting complaint, clinical impression, and treatment plan were extracted and entered into a de-identified spreadsheet for analysis.\u003c/p\u003e\n\u003ch3\u003eDiagnosis and Treatment Classification\u003c/h3\u003e\n\u003cp\u003eOrthopedic complaints were categorized into clinically relevant groups based on chief complaints and provider documentation in each SOAP note. These diagnostic categories included trauma-related injuries (e.g., falls, fractures, post-operative pain), joint pain (e.g., knee, ankle, or shoulder discomfort), arthritis (such as osteoarthritis or rheumatoid arthritis), chronic pain, radiculopathy or neuropathy, tendonitis, myalgia, carpal tunnel syndrome, back or neck pain, and post-operative care. Chronic pain was defined as any pain persisting for more than three months or described as long-standing, recurring, or non-acute in nature. In cases where a patient presented with overlapping issues\u0026mdash;such as joint pain due to trauma or coexisting arthritis and radiculopathy\u0026mdash;multiple diagnostic categories were applied.\u003c/p\u003e\n\u003cp\u003eEach diagnosis was codified in a binary format within the study dataset: if a particular condition was present, it was assigned a value of \u0026ldquo;1\u0026rdquo;; if not applicable to the encounter, it received a \u0026ldquo;0.\u0026rdquo; This approach allowed for patients to be counted in multiple categories when appropriate, reflecting the complexity of real-world complaints.\u003c/p\u003e\n\u003cp\u003eTreatments were similarly organized into 13 predefined categories: oral NSAIDs, acetaminophen, topical NSAIDs (e.g., diclofenac), lidocaine patches, steroid creams (e.g., hydrocortisone), wound care kits, splints, braces (including orthopedic boots), walkers or canes, physical therapy referrals, Vicks VapoRub, and \u0026ldquo;other\u0026rdquo; (e.g., compression socks or ice packs). If more than one treatment was provided during a single encounter, multiple categories were marked with a \u0026ldquo;1\u0026rdquo; to reflect the intervention(s) used. Encounters in which musculoskeletal care was not documented were categorized as \u0026ldquo;not addressed.\u0026rdquo; All diagnostic and treatment classifications followed a standardized codebook developed by the research team to ensure consistency and reproducibility during data abstraction.\u003c/p\u003e\n\u003ch3\u003eStatistical Analysis\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics were used to calculate frequencies and percentages for all diagnostic and treatment categories. Mean age and sex proportions were calculated with 95% confidence intervals. Differences in age across diagnostic and treatment groups were analyzed using the Mann-Whitney U test. Differences in treatment distribution by sex were analyzed using the chi-squared test. Statistical significance was defined as p \u0026lt; 0.05. All analyses were conducted using Python (v3.10) and associated scientific libraries (e.g., SciPy, Pandas).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom August 2023 to August 2024, Street Medicine Phoenix served 1,193 unique unhoused individuals, of whom 493 engaged in a clinical encounter. Among these, 228 patients (45.9%) presented with at least one orthopedic concern and were included in the final study sample. The mean age of patients was 51.6 years (95% CI: 49.9\u0026ndash;53.3), and 33.6% identified as female (Table 1).\u003c/p\u003e\n\u003cp\u003eOrthopedic diagnoses were diverse, with trauma-related injuries (22.9%), joint pain (19.2%), and chronic pain (14.3%) emerging as the most common categories (Figure 1a). Other conditions, including arthritis (10.6%), tendonitis, and carpal tunnel syndrome, were less frequently recorded. Significant age differences were observed between diagnostic categories: patients with arthritis had a mean age of 58.0 years (95% CI: 54.5\u0026ndash;61.5), compared to 51.2 years (95% CI: 48.9\u0026ndash;53.6) for trauma, a difference that reached statistical significance (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) (Figure 1b, Table 2). Although sex distribution was relatively balanced overall, males were more frequently represented in trauma and joint pain cases (Figure 1c).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTreatment modalities varied across encounters, with oral NSAIDs being the most commonly administered therapy (19.3%), followed by wound care kits (13.4%), acetaminophen (11.5%), and bracing (10.5%) (Figure 2a). Despite this variability, no statistically significant differences in age or sex were found across treatment groups (Figures 2b, 2c; Table 3). The frequent use of non-opioid analgesics and durable medical equipment (DME) underscores the feasibility of low-barrier, point-of-care interventions in field settings.\u003c/p\u003e\n\u003cp\u003eFigure 3a presents a representative SOAP note from a clinical encounter\u0026mdash;a standardized documentation format used by Street Medicine Phoenix volunteers to record subjective symptoms, objective findings, assessment, and treatment plans. These SOAP notes formed the basis for data categorization in this study, enabling consistent diagnostic classification and treatment tracking across encounters. In the example shown, a middle-aged woman presented with symptoms consistent with carpal tunnel syndrome. She reported nocturnal pain and paresthesia exacerbated by wrist movement. Objective examination confirmed tenderness and symptom reproduction with wrist compression. She was managed with a wrist brace and over-the-counter ibuprofen, reflecting a conservative, low-barrier treatment plan tailored to field constraints. Through structured documentation and direct intervention, street medicine teams demonstrate that meaningful MSK care can be delivered outside of traditional healthcare environments.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study highlight the high burden of musculoskeletal (MSK) conditions among unhoused populations, emphasizing trauma (22.9%), joint pain (19.2%), and chronic pain (14.3%) as the most common diagnoses (Figure 1a). These findings echo prior literature reporting disproportionately high rates of physical injury and degenerative MSK conditions among individuals experiencing homelessness due to environmental exposure, repetitive mechanical stress, and limited access to preventive care【8】【9】. In our cohort, pain-related conditions represented over two-thirds of orthopedic encounters, reflecting the chronic, undertreated nature of pain in this population【10】【11】. The significant age-related variation across orthopedic conditions (Figure 1b) further supports the notion that certain pathologies such as arthritis and chronic joint pain may disproportionately affect older patients, while trauma-related injuries span across age groups.\u003c/p\u003e\n\u003cp\u003eTreatment patterns (Figure 2a) further underscore the reliance on low-barrier interventions. Oral NSAIDs were the most commonly provided treatment (19.3%), followed closely by supportive measures such as wound care (13.4%) and bracing (10.5%). These strategies are congruent with prior recommendations to tailor treatment for homeless patients toward interventions that are feasible, low-cost, and effective outside of traditional care settings【12】【13】. Similar field-based approaches have shown promise in disaster response and remote rural care models, where rapid relief and portability are equally critical【16】【17】. Low-barrier treatments\u0026mdash;particularly oral NSAIDs and DME options such as braces\u0026mdash;represent feasible and effective interventions that improve pain and function in vulnerable populations with limited access to traditional care pathways. In fact during clinical encounters, many patients expressed immediate relief upon wearing and walking with a brace. While this was not quantified in this study, it represents a future scope of treatment options for unhoused patient populations regarding orthopedic issues. The diversity in treatment approaches, as shown by our data, reflects the flexibility required in delivering orthopedic care on the street, where diagnostic clarity may be limited, and patient follow-up is not guaranteed.\u003c/p\u003e\n\u003cp\u003eStatistical analysis revealed a significant association between trauma and younger age, and between chronic pain and female sex (Table 2), reflecting potential gendered patterns in pain perception and care-seeking that warrant deeper exploration【14】【15】. Despite national data suggesting men make up the majority of unhoused individuals, our data found that women represented one-third of orthopedic visits, particularly in arthritis and chronic pain categories (Figure 1c). These sex-based differences in presentation and treatment call for gender-responsive approaches in the delivery of MSK care.\u003c/p\u003e\n\u003cp\u003eThe documentation of care through standardized SOAP notes (Figure 3a) and image-based records (Figure 3b) further demonstrates the clinical rigor that can be achieved even in mobile settings. These data not only facilitate care continuity but also establish a foundation for structured research and future outcomes tracking. Integration of mobile EHR systems has already demonstrated success in improving vaccination and chronic disease management among hard-to-reach populations【18】, and similar platforms could be optimized for orthopedic surveillance.\u003c/p\u003e\n\u003cp\u003eOur study fills a critical gap in the literature by offering a granular analysis of orthopedic complaints and interventions in a large, urban street medicine cohort. However, it is not without limitations. As a single-institution, retrospective review, our findings may not be generalizable across all regions. Additionally, the lack of long-term follow-up prevents assessment of treatment efficacy over time. Given the episodic nature of care delivery in this population, outcomes research remains a significant challenge. Nevertheless, previous mobile health models have shown that even episodic care can lead to reductions in emergency department visits and improved trust in healthcare systems【19】【20】.\u003c/p\u003e\n\u003cp\u003eFuture directions include prospective investigations into the utility and cost-effectiveness of durable medical equipment (DME) in improving pain and function. Such work could clarify the role of DME as a short-term therapeutic modality for unsheltered patients, a hypothesis supported by the frequent use of braces and splints in this study. In addition, implementation of a centralized digital record system shared across street medicine teams may support tracking of orthopedic outcomes and promote research standardization across cities. Community partnerships and cross-sector collaboration will be essential in scaling such efforts, especially in high-density urban settings where outreach services are fragmented【21】【22】.\u003c/p\u003e\n\u003cp\u003eIn summary, this study reinforces the need for targeted, low-barrier orthopedic interventions for unhoused populations, and demonstrates how mobile clinics can serve as both care delivery platforms and data-generating environments. Further research is warranted to evaluate the long-term benefits of these interventions and develop replicable models of street-based musculoskeletal care. This work adds to a growing body of literature calling for scalable, equitable orthopedic care systems adaptable to nontraditional environments【23】【24】【25】.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides a comprehensive overview of musculoskeletal conditions and treatment patterns among unhoused patients evaluated through a mobile street medicine program. Trauma, joint pain, and chronic pain emerged as the most common orthopedic issues, with low-barrier interventions such as oral NSAIDs, wound care, and durable medical equipment frequently utilized. These findings highlight the adaptability of orthopedic care delivery in resource-limited environments and underscore the urgent need for scalable, street-based MSK interventions. While limited by its retrospective design and single-region scope, this study offers foundational data to inform future research. Prospective evaluations assessing the effectiveness of durable medical equipment in improving short-term function and pain outcomes are warranted to optimize care for this underserved population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Dr. Robert Fauer for his mentorship and guidance throughout the development of this project. Special thanks to the dedicated volunteers of Street Medicine Phoenix, whose commitment to providing compassionate care to unhoused patients made this study possible. Our acknowledgements to BioRender for figure panel generation. Finally, we thank Kendall Schwartz for her editorial support in refining the study\u0026rsquo;s abstract and Isabelle Jae Fisher for reviewing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this section, the final codified research data will be included and the IRB Approval letter from clinical encounters used to codify the research data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the University of Arizona Institutional Review Board as a retrospective chart review involving de-identified data (PI: Sanjana Arun). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The University of Arizona Institutional Review Board approved this retrospective study and waived the requirement for informed consent, as all data were de-identified and collected as part of routine clinical care. IRB approval was granted under the title \u003cem\u003e\u0026ldquo;\u003c/em\u003eSTUDY00004974: \u003cem\u003eThe Prevalence of Orthopedic Injuries and Use of Durable Medical Supplies in Urban Unhoused Populations.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. All data were de-identified. Images included in this manuscript were modified to remove identifying information. No patient faces or names are visible. No identifying images or personal clinical details are presented in this manuscript. This image has been reviewed to ensure compliance with BMC\u0026rsquo;s ethical publishing standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author in the supplemental materials. If SOAP note data is required, the authors are happy to provide the manual SOAP note data on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSanjana Arun conceptualized the study, led data collection, performed statistical analysis, and drafted the manuscript. Tyler Krall, Armine Kasabyan, Taylor Lee, and Joseph Solomon contributed to data collection and manuscript revision. Dr. Robert Fauer served as the project mentor and contributed to study conceptualization and oversight. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eFazel S, Geddes JR, Kushel M. The health of homeless people in high-income countries: descriptive epidemiology, health consequences, and clinical and policy recommendations. \u003cem\u003eLancet\u003c/em\u003e. 2014;384(9953):1529-1540.\u003c/li\u003e\n \u003cli\u003eHwang SW, Burns T. Health interventions for people who are homeless. \u003cem\u003eLancet\u003c/em\u003e. 2014;384(9953):1541-1547.\u003c/li\u003e\n \u003cli\u003eDoran KM, Ragins KT, Gross CP, Zerger S. Medical respite programs for homeless patients: a systematic review. \u003cem\u003eJ Health Care Poor Underserved\u003c/em\u003e. 2013;24(2):499-524.\u003c/li\u003e\n \u003cli\u003eMartins DC. Experiences of homeless people in the health care delivery system: a descriptive phenomenological study. \u003cem\u003ePublic Health Nurs\u003c/em\u003e. 2008;25(5):420-430.\u003c/li\u003e\n \u003cli\u003eWithers J, Chandra A, Sadowski LS. The revolution of street medicine: a model for the future of health care. \u003cem\u003eJ Health Care Poor Underserved\u003c/em\u003e. 2018;29(1):321-327.\u003c/li\u003e\n \u003cli\u003eBaggett TP, O\u0026rsquo;Connell JJ, Singer DE, Rigotti NA. The unmet health care needs of homeless adults: a national study. \u003cem\u003eAm J Public Health\u003c/em\u003e. 2010;100(7):1326-1333.\u003c/li\u003e\n \u003cli\u003eKushel MB. Factors associated with the health care utilization of homeless persons. \u003cem\u003eJAMA Intern Med\u003c/em\u003e. 2001;161(4):393-402.\u003c/li\u003e\n \u003cli\u003eBeijer U, Andreasson S. Physical diseases among homeless people: gender differences and comparisons with the general population. \u003cem\u003eScand J Public Health\u003c/em\u003e. 2009;37(1):93\u0026ndash;100.\u003c/li\u003e\n \u003cli\u003eHwang SW. Homelessness and health. \u003cem\u003eCMAJ\u003c/em\u003e. 2001;164(2):229\u0026ndash;233.\u003c/li\u003e\n \u003cli\u003eKertesz SG, et al. Primary care for homeless persons: a systematic review of the evidence. \u003cem\u003eJ Gen Intern Med\u003c/em\u003e. 2009;24(8):1018\u0026ndash;1029.\u003c/li\u003e\n \u003cli\u003eHudson BF, et al. Challenges to pain management in people with chronic pain and homelessness: a qualitative study. \u003cem\u003eBr J Gen Pract\u003c/em\u003e. 2019;69(679):e819\u0026ndash;e827.\u003c/li\u003e\n \u003cli\u003eEberle C, et al. Street medicine for underserved populations: a review. \u003cem\u003eInt J Equity Health\u003c/em\u003e. 2020;19(1):1\u0026ndash;11.\u003c/li\u003e\n \u003cli\u003eO\u0026rsquo;Toole TP, et al. Applying new models of care for homeless veterans: the patient-centered medical home. \u003cem\u003eAm J Public Health\u003c/em\u003e. 2010;100(8):1497\u0026ndash;1499.\u003c/li\u003e\n \u003cli\u003eGreen CR, et al. The unequal burden of pain: confronting racial and ethnic disparities in pain. \u003cem\u003ePain Med\u003c/em\u003e. 2003;4(3):277\u0026ndash;294.\u003c/li\u003e\n \u003cli\u003eRu\u0026eacute; M, Cabr\u0026eacute; X, Soler-Gonz\u0026aacute;lez J, Bosch A, Almirall M, Serna C. Gender differences in health care utilization in Spain. \u003cem\u003eGac Sanit\u003c/em\u003e. 2008;22(6):511\u0026ndash;519.\u003c/li\u003e\n \u003cli\u003eLee AC, Phillips W, Challen K, Goodacre S. Barriers to surge capacity in disaster response: a qualitative study. \u003cem\u003eBMJ Open\u003c/em\u003e. 2012;2(1):e000709.\u003c/li\u003e\n \u003cli\u003eMcCoy D, Chand S, Sridhar D. Global health funding: how much, where it comes from and where it goes. \u003cem\u003eHealth Policy Plan\u003c/em\u003e. 2009;24(6):407\u0026ndash;417.\u003c/li\u003e\n \u003cli\u003eIrvin C, et al. Improving access to health care using mobile health vans: evaluation of Project Hope. \u003cem\u003eJ Health Care Poor Underserved\u003c/em\u003e. 2006;17(1):35\u0026ndash;43.\u003c/li\u003e\n \u003cli\u003eSadowski LS, Kee RA, VanderWeele TJ, Buchanan D. Effect of a housing and case management program on emergency department visits and hospitalizations among chronically ill homeless adults: a randomized trial. \u003cem\u003eJAMA\u003c/em\u003e. 2009;301(17):1771\u0026ndash;1778.\u003c/li\u003e\n \u003cli\u003eFitzpatrick-Lewis D, et al. Effectiveness of interventions to improve the health and housing status of homeless people: a rapid systematic review. \u003cem\u003eBMC Public Health\u003c/em\u003e. 2011;11:638.\u003c/li\u003e\n \u003cli\u003eBuccieri K, Schiff R. Benefits of community-based research for social action. \u003cem\u003eJ Poverty\u003c/em\u003e. 2016;20(1):45\u0026ndash;61.\u003c/li\u003e\n \u003cli\u003eO\u0026rsquo;Campo P, Stergiopoulos V, Nir P, Levy M. How health and social care services support homeless populations: a realist evaluation. \u003cem\u003eBMC Health Serv Res\u003c/em\u003e. 2015;15:37.\u003c/li\u003e\n \u003cli\u003eAxford J, Heron C, Ross F. Development and validation of a musculoskeletal health questionnaire. \u003cem\u003eBMC Musculoskelet Disord\u003c/em\u003e. 2010;11:125.\u003c/li\u003e\n \u003cli\u003eLevine DM, et al. Mobile technology for community health in the developing world. \u003cem\u003eJAMA\u003c/em\u003e. 2016;315(20):2175\u0026ndash;2176.\u003c/li\u003e\n \u003cli\u003eHwang SW, et al. Universal health insurance and health care access for homeless persons. \u003cem\u003eAm J Public Health\u003c/em\u003e. 2010;100(8):1454\u0026ndash;1461.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographic Characteristics of Study Population\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"527\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean or %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e51.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e49.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e53.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSex - F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e33.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e39.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSex - M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e66.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e72.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Musculoskeletal Diagnoses by Age and Sex\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"526\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of Total (N=228)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Age (yrs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge p-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex p-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eTrauma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e49.8 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e46.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e52.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eJoint Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e54.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e52.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e**0.025** *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eChronic Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e52.2 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e55.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eArthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e58.0 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e61.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e**0.001** *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e53.1 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e48.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e57.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e49.4 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e45.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e53.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eBack Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e47.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e54.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eRadiculopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e56.3 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e51.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e60.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eCarpal Tunnel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e51.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e71.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eTendonitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e37.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e52.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e**0.025** *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. Treatment Categories by Age and Sex\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"527\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Treatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of Total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Age (yrs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge p-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex p-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eOral NSAIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e51.5 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e48.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e18.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e49.4 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e45.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e53.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eWound Care Package\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e51.0 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e46.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e55.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eTylenol/Acetaminophen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e50.2 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eBrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e50.6 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e46.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e55.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eNot Addressed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e54.8 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e49.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eTopical NSAID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e57.9 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e50.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e65.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e**0.021** *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eTopical Steroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e47.1 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e37.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e56.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003ePT Recommended\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e45.8 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e56.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eWalker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e53.2 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e44.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eTopical Lidocaine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e51.0 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e66.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eSplint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e48.1 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e38.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e57.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney U\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eVicks VapoRub\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 37px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e48.5 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e77.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMann-Whitney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eChi-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"unhoused, orthopedic, MSK, DME","lastPublishedDoi":"10.21203/rs.3.rs-6390500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6390500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnhoused individuals experience a high burden of musculoskeletal (MSK) conditions but often face barriers to traditional healthcare. Street Medicine Phoenix (SMP) is a mobile healthcare initiative composed of medical students and physicians providing free medical screenings to this population. This study aims to characterize the prevalence, demographic distribution, and treatment of orthopedic conditions among unhoused patients in an urban street medicine program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective observational study analyzed patient encounters from August 2023 to August 2024, collected by SMP in Phoenix, Arizona. Orthopedic conditions were identified through review of Subjective, Objective, Assessment, and Plan (SOAP) notes from 1,193 adult patient encounters. Diagnoses were categorized into clinical MSK types. Treatments included pharmacologic and non-pharmacologic interventions. Descriptive statistics, Mann-Whitney U tests, and chi-squared tests were used to assess differences by age and sex. Results are reported with 95% confidence intervals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 1,193 encounters, 228 (19.1%) involved orthopedic issues. The mean age of patients with MSK conditions was 50.2 years (95% CI: 48.9–51.5); 33.6% identified as female. The most common diagnoses were joint pain (23.2%), trauma (20.6%), arthritis (12.3%), chronic pain (10.1%), and radiculopathy (8.3%). A statistically significant age difference was observed between patients with trauma and arthritis (p \u0026lt; 0.05). Oral NSAIDs were the most common treatment (36%), followed by topical therapies such as NSAID gels, lidocaine, or steroid creams (20%), durable medical equipment (21%), and wound care kits (6%). No significant differences in treatment rates by sex were identified.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOrthopedic conditions are prevalent among unhoused individuals and represent a major source of morbidity. Mobile care models like SMP provide effective, immediate treatment using accessible modalities. Low-barrier treatments—particularly oral NSAIDs and durable medical equipment (DME: defined as boots,braces,walkers,crutches etc)—represent feasible and effective interventions that improve pain and function in vulnerable populations with limited access to traditional care pathways. This study underscores the need for scalable MSK interventions and provides a data-driven framework for improving orthopedic care among unhoused populations.\u003c/p\u003e\n\u003ch3\u003eTrial Registration\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Orthopedic Conditions and Treatment Patterns Among Unhoused Urban Patients: A Street Medicine Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 11:10:07","doi":"10.21203/rs.3.rs-6390500/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-29T15:13:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-18T14:39:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136187170499905942075198597163372655113","date":"2025-05-18T13:21:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T14:58:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265253246216873281533920977175975040218","date":"2025-05-06T17:56:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-05T09:44:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-29T14:28:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-15T05:19:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-14T19:58:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2025-04-14T19:57:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b66c5da-8bb6-4a63-8268-b9d3ef05c780","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:05:47+00:00","versionOfRecord":{"articleIdentity":"rs-6390500","link":"https://doi.org/10.1186/s12891-026-09624-0","journal":{"identity":"bmc-musculoskeletal-disorders","isVorOnly":false,"title":"BMC Musculoskeletal Disorders"},"publishedOn":"2026-02-18 15:59:01","publishedOnDateReadable":"February 18th, 2026"},"versionCreatedAt":"2025-05-09 11:10:07","video":"","vorDoi":"10.1186/s12891-026-09624-0","vorDoiUrl":"https://doi.org/10.1186/s12891-026-09624-0","workflowStages":[]},"version":"v1","identity":"rs-6390500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6390500","identity":"rs-6390500","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}