Abstract
Background:
The COVID-19 pandemic challenged healthcare systems across the United States. It had distinct effects in rapidly growing cities like San Antonio, Texas. San Antonio, one of the fastest-expanding metropolitan areas, faces high rates of uninsured residents and a mix of urban and semi-rural healthcare landscapes. This makes it a valuable case for understanding health system responses to access challenges during public health crises. This qualitative study examined how healthcare system leaders, frontline providers, and policymakers in San Antonio navigated three major challenges during COVID-19: system-level disruptions in healthcare delivery, telehealth access, and health insurance coverage.
Methods:
From February to April 2023, data came from 2 focus groups (n = 20) and 12 key informant interviews. These were analyzed thematically using a grounded theory approach to identify barriers and evidence-based resolutions.
Results:
Participants identified three core challenges: First, disruptions in healthcare delivery due to workforce shortages, reduced preventive care access, and discharge delays. Second, barriers to telehealth access related to the digital divide and health literacy. Third, instability in health insurance coverage following the rollback of pandemic-era Medicaid protections. Participants also shared practice-based recommendations. These included standardized screening for social determinants of health (SDOH) with linked referrals to resources, culturally responsive food assistance programs, and hybrid care models that integrate telehealth with in-person care.
Conclusion:
This project shows that engaging local leadership and coordinating strategies can make systems more resilient. These actions improve healthcare access during public health crises and offer practical lessons for other urban healthcare systems.
Keywords
Introduction
San Antonio, Texas, is one of the fastest-growing metropolitan regions in the United States and provides a unique setting for studying healthcare access and system resilience.1,2 With a population of 1.43 million in 2022 and a high unemployment and uninsurance rate, the city combines rapid urban growth with persistent economic vulnerability.1,3–5 Its urban and semi-rural makeup makes healthcare delivery especially complex, as service availability varies widely across neighborhoods. A substantial share of households lives below the federal poverty level, and the region has a documented history of provider shortages in both primary and mental healthcare.6,7 These factors make San Antonio a key place to study how healthcare systems function across diverse economic and geographic context.
Even before the COVID-19 pandemic, some San Antonio residents faced challenges accessing healthcare. Many hospitals and healthcare facilities were disproportionately located in wealthier northern areas, with fewer facilities on the South and West Sides of the city.4,8 The city’s persistent shortages of primary and mental health providers have been formally recognized through its designation as a Health Professional Shortage Area (HPSA) by the Texas Primary Care Office and HRSA. 9 The onset of the COVID-19 pandemic introduced acute operational and policy challenges for healthcare institutions across the United States. Clinic closures, workforce disruptions, and widespread delays in preventive and emergency care worsened existing inequities in healthcare access.10,11 In 2019, Bexar County had only 4659 direct patient care physicians for more than 2 million residents, roughly 1 physician per 441 people, and each primary care physician served an average of 1359 patients annually.12,13 These service gaps highlight long-standing inequities that have limited the region’s capacity to deliver consistent, accessible care, even before the pandemic intensified existing vulnerabilities.
National studies have documented the pandemic’s impacts on healthcare delivery, telehealth adoption, and insurance coverage, such as clinic closures, widespread delays in preventive and emergency care, and operational disruptions affecting core health services.14–17 However, there has been wide variability in how different areas have responded to the pandemic, and few studies have examined how local healthcare systems in diverse, semi-rural, high-uninsurance metropolitan areas adapted to both long-standing and pandemic-specific access challenges. Addressing this gap is vital for understanding how local community leadership, health system capacity, and policy alignment can influence resilience and improve access to care during public health crises.
This qualitative study explores how the COVID-19 pandemic disrupted system-level access to care in San Antonio, focusing on telehealth, healthcare delivery, and insurance coverage. Drawing on interviews and focus groups with healthcare leaders, community health workers, and policymakers, it examines how local systems responded to these disruptions and the strategies that emerged to support continuity of care. This study synthesizes stakeholder perspectives on these challenges and highlights leadership strategies that can strengthen system preparedness and resilience during future public health emergencies.
Methods
Study design
This qualitative study employed a grounded theory design to explore how the COVID-19 pandemic affected healthcare accessibility and system resilience in San Antonio, Texas. 18 The study aimed to elicit perspectives from healthcare leaders, frontline providers, and policy stakeholders to understand barriers to care and system-level responses during the pandemic, rather than to test pre-existing hypotheses. Data were collected through 2 focus group discussions and 12 key informant interviews with healthcare leaders, frontline providers, and policy stakeholders in San Antonio.
A semi-structured interview guide was developed by the research team at the University of Texas Health Science Center at Houston (UTHealth) School of Public Health and refined through stakeholder feedback to ensure relevance and clarity.
Representative questions included:
“How did the pandemic affect your availability to patients?”
“What are the greatest barriers to accessing preventive or emergency care since the pandemic?”
“To what extent do patients and healthcare workers embrace telehealth?”
This study was reported in accordance with the Standards for Reporting Qualitative Research (SRQR) guidelines recommended by the EQUATOR Network 19 (Appendix 1).
Ethical considerations and informed consent
In accordance with UTHealth criteria, the study was exempt from Institutional Review Board review as it originated from a funded quality improvement initiative with the local health department, the San Antonio Metropolitan Health District (herein referred to as Metro Health). Verbally informed consent was obtained at the beginning of each interview and focus group using a standardized script outlining the study purpose, voluntary participation, and audio-recording procedures. Consent was documented in audio recordings. Written confirmation was subsequently obtained via email prior to publication, with all participants reaffirming their consent for the anonymized inclusion of their perspectives.
Participant selection and recruitment
Participants for individual interviews were recruited by The Health Collaborative (THC), a local non-profit organization in San Antonio. They used a purposive sampling framework to recruit key stakeholders to ensure representation across hospital systems, community health centers, professional medical and dental societies, health insurance programs, community health organizations, and municipal or county policy offices.
Participants for focus groups were also recruited by THC. A convenience sampling method using targeted email and phone invitations via professional networks, was used to reach emergency and primary care providers, nurses, mental health professionals, dentists, EMT staff, and private clinicians. Although invitation counts were not systematically tracked, the estimated response rate was 70%, and most non-participation resulted from scheduling conflicts.
The final sample included 12 key informant interviews with healthcare executives and policy leaders and 2 focus groups comprising 20 healthcare providers (one group of nurses (n = 3) and one group of community health workers (n = 17)). Demographic information for the community health worker focus group was collected via a pre-session intake form. Among those who reported, 81.8% identified as Hispanic, 9.1% as Black/African American, and 9.1% as Asian. Not all participants disclosed demographic details, and comparable data were not systematically collected for the frontline provider focus group or key informant interviews. A summary of these characteristics is presented in Table 1.
Demographic characteristics of community health worker participants (n = 17).
UTHSCSA: university of Texas health science center at San Antonio.
Data collection
The study took place in San Antonio, Texas, a diverse urban–semirural region, between February and April 2023. One-on-one interviews were conducted via Zoom, and focus groups were in person. All interviews and focus groups were audio-recorded and transcribed, then cleaned to remove filler words, anonymized, and stored on limited, shared drives. Filler words and repeated phrases were removed for clarity, and some quotations were lightly edited for length without altering their meaning. Each session was co-facilitated by two interviewers: one public health researcher and one graduate student, both formally trained in qualitative research. One PhD researcher with experience and formal training in qualitative research served as a supervisor.
Data analysis
Data were analyzed using Strauss and Corbin’s (1998) grounded theory procedures of open, axial, and selective coding. 18 A constant comparative method was used to integrate findings across stakeholder groups. Coding was conducted using Atlas.ti software. To enhance inter-coder reliability, initial coding was performed by one coder and reviewed by a second; discrepancies were resolved through discussion until consensus was reached. Data saturation was achieved when no new substantive themes emerged from subsequent interviews or focus groups.
Rigor
Methodological rigor was ensured through multiple strategies. Credibility was supported through member checking, in which participants reviewed summaries of their contributions for accuracy. Dependability was strengthened through the use of consistent data collection protocols and dual facilitation of all sessions. Confirmability was addressed by maintaining an audit trail documenting analytic decisions and code development. Transferability was enhanced by detailed descriptions of participants’ roles and the study context. Data integrity was supported through audio recording, professional transcription, and inter-coder review.
Results
Across focus groups and key stakeholder interviews with healthcare leaders, frontline providers, and policy leaders in San Antonio, three overarching themes emerged that describe barriers to access to care during the COVID-19 pandemic. These themes included: (a) disruptions in healthcare delivery due to staffing shortages and care bottlenecks; (b) health insurance instability, particularly around Medicaid redetermination; and (c) barriers to telehealth access driven by digital inequities and literacy challenges.
Disruptions in healthcare delivery due to staffing shortages and care bottlenecks
Within this theme, participants described increased staffing demands, reliance on temporary labor, patient volume surges, and downstream impacts on care quality.
Participants described how staffing shortages during COVID-19 strained care delivery and forced widespread adaptation. Leaders across hospitals and urgent care centers noted that early protocols required more personnel than were available, leading to heavy reliance on agency and cross-trained staff.
“Early in the pandemic, we implemented multiple safety protocols that demanded more nursing staff than were available.” – healthcare leader, one-on-one interview.
To address staffing shortages, health systems relied heavily on temporary staffing mechanisms, including agency personnel, cross-trained staff, and regional surge-response programs such as the South Texas Regional Advisory Council (STRAC). While these approaches expanded short-term capacity, participants reported that temporary staff unfamiliar with institutional workflows sometimes introduced inefficiencies and inconsistencies in care delivery. Reliance on travel nurses also increased financial strain, as many permanent staff left for higher-paying short-term contracts before being rehired at premium rates.
Front-line providers described severe volume surges in urgent care and emergency departments, which reduced their ability to provide thorough care.
“We started seeing 80 to 100 patients a day—it felt like herding cattle.” – front-line provider, focus group.
Collectively, participants described these disruptions as reflecting structural weaknesses in surge-response planning and workforce retention within the local healthcare system.
Health insurance instability, particularly around Medicaid redetermination
Within this theme, participants described temporary stabilization of coverage during the public health emergency, anticipated disruptions following Medicaid redetermination, limitations of Marketplace insurance alternatives, geographic concentration of insurance vulnerability, and insurance-related barriers affecting discharge and continuity of care.
Participants consistently described how pandemic-era policies, especially the federal continuous Medicaid coverage, initially stabilized access for vulnerable populations. Several healthcare leaders emphasized that automatic renewals during the public health emergency allowed continuous coverage for postpartum women and low-income families who would otherwise have been disenrolled after 90 days.
“During the pandemic, I wasn’t removed from Medicaid rolls even after that time period. That made a huge difference for my patients.” – healthcare leader, one-on-one interview.
As protections ended, participants anticipated widespread disenrollment and administrative backlogs. Front-line providers described challenges related to renewal literacy, limited system capacity, and prolonged response times, which they expected to disproportionately affect patients with limited resources.
“If you come across anybody who needs to renew in the next few months, it’s better to do it now rather than waiting till the last minute. They’re having to wait three to four more months just to get a response.” – front-line provider, focus group.
Healthcare leaders also expected related reductions in safety-net supports, including food assistance benefits, which they viewed as closely intertwined with healthcare access and stability.
“They’re taking a minimum of $95 off of everybody’s food stamp benefits. In the next few months, it’s gonna get a little worse.” – healthcare leader, focus group.
In addition to public coverage instability, policy leaders described barriers in private insurance options, particularly through the Health Insurance Marketplace. Policy leaders noted that Marketplace plans were not a realistic alternative for most low-income families due to high costs and limited coverage options.
“Even with premium tax credits, marketplace coverage is still unaffordable for many. The plans that are affordable provide hardly any coverage, and the ones with better coverage are too expensive. I don’t know of any clients that have successfully gotten insurance from the marketplace.” – policy leader, one-on-one interview.
Insurance instability was described as disproportionately concentrated in San Antonio’s South and West Sides, where preexisting rates of uninsurance were already high. Participants noted that the pandemic deepened these disparities as job losses and reduced work hours left many residents without employer-based coverage.
“Prior to COVID-19, we already had a high percentage of uninsured residents. That issue worsened as people lost jobs and their healthcare coverage, since most healthcare access is tied to employment. Some workers had their hours reduced, which also impacted their ability to maintain coverage.” – policy leader, one-on-one interview.
Finally, participants emphasized that insurance-related discharge delays further complicated patient flow, citing challenges with prior authorizations, limited insurance office hours, and post-acute bed shortages.
“We cannot send them home if home care will not accept them due to a lack of benefits or financial resources. Some patients don’t even have a home to go to.” – healthcare leader, one-on-one interview.
Barriers to telehealth access, driven by digital inequities and literacy challenges
Within this theme, participants described digital literacy and language barriers, technology and connectivity constraints, patient disengagement during rapid telehealth expansion, and the need for culturally responsive hybrid models of care.
Participants reported that digital literacy significantly limited telehealth use during the pandemic, particularly among older adults, non-English-speaking patients, and individuals with limited health literacy. Healthcare leaders noted that language barriers and low reading proficiency complicated patients’ ability to navigate online platforms and understand care instructions.
“Health literacy is already difficult for a lot of residents in my area because many speak Spanish or read at a certain grade level. Even when they receive a diagnosis, it can be difficult to understand their treatment options.” – healthcare leader, one-on-one interview. “Patients often felt rushed or unheard, especially those who already had difficult experiences with other institutions like law enforcement or social services.” – front-line provider, focus group. “The rapid shift to telehealth caused some patients to disengage when in-person visits were suspended.” – healthcare leader, one-on-one interview.
Discussion
This qualitative study examined how the COVID-19 pandemic disrupted healthcare delivery and access for underserved populations in San Antonio, Texas, a city long affected by healthcare access issues and high uninsured rates.4,5 The aim was to understand how healthcare leaders, frontline providers, and policymakers responded to operational, technological, and policy challenges and to identify practical strategies to build a more resilient healthcare system.
Participants described significant workforce shortages as a central driver of care disruption, mirroring national trends observed during COVID.20,21 Heavy reliance on contract and travel staff temporarily expanded capacity but introduced workflow inconsistencies and financial strain. Participants further noted that temporary regulatory flexibilities, while necessary during the emergency phase, complicated post-pandemic efforts to restore consistent practice standards. Together, these findings underscore the need for structured workforce recovery strategies that prioritize retention, competency restoration, and preparedness for future surges, concerns echoed in national hospital workforce analyzes. 22
Insurance instability emerged as another critical barrier. Although the federal continuous-coverage policy temporarily stabilized access, participants anticipated major bureaucratic delays and process backlogs once renewals resumed. Within a month of the study’s focus groups, that prediction materialized in Texas, where Medicaid processing delays and coverage losses increased in early 2023. 23 Participants also highlighted the interconnected nature of healthcare access and social support, noting that reductions in programs such as SNAP further strained low-income households. These findings align with prior evidence demonstrating how administrative complexity and benefit churn disproportionately affect marginalized populations in non-Medicaid-expansion states.24,25
Structural inequities across San Antonio’s South and West Sides further compounded insurance barriers.4,26 Participants described how employment-based coverage models left residents vulnerable to job losses during the pandemic, with refugee and immigrant families facing additional constraints due to limited provider acceptance of resettlement assistance programs.27,28 Participants also questioned the affordability and adequacy of Health Insurance Marketplace plans, reinforcing existing evidence that cost-sharing and limited plan literacy hinder uptake in Texas.29,30
Digital barriers similarly constrained access to care. Participants described how limited digital literacy, language barriers, and inadequate internet access reduced engagement with telehealth, particularly among older adults and non-English-speaking populations. Participants cautioned that without intentional design, virtual care risks widening existing disparities. These findings align with literature emphasizing the importance of culturally responsive communication and alternative access pathways in technology-enabled care. 31
Beyond identifying barriers, participants articulated system-level strategies to strengthen access to care. These included integrating standardized SDOH screening with referral pathways, expanding culturally tailored outreach models, and adopting hybrid care approaches that combine in-person assessment with virtual consultation. Illustrative participant-identified strategies for system-level change are summarized in Appendix 2. Notably, several post-study developments, such as CMS’s adoption of mandatory SDOH reporting measures and local digital inclusion initiatives, reflect movement toward the infrastructure participants described as necessary.32,33 Several San Antonio hospitals have already begun adopting SDOH models by aligning with CMS 2024 regulations to integrate healthcare and social support systems.34,35 Concurrently, the city released its 2023 Digital Inclusion Survey, which documented broadband and device gaps and informed new outreach strategies for digitally disconnected residents. 36
Taken together, these findings highlight the interconnected nature of workforce, insurance, and digital barriers in shaping healthcare access during and beyond the pandemic.
This study provides insights into how healthcare leaders, frontline providers, and policy stakeholders in San Antonio experienced and responded to disruptions in healthcare access during the COVID-19 pandemic. While prior studies have examined workforce shortages, insurance instability, and digital barriers separately,20–22,29–31,37 this study highlights how these challenges interact within a metropolitan health system with high uninsured rates and diverse populations. The findings are likely relevant beyond the pandemic, as workforce constraints, insurance instability, and digital access barriers remain ongoing challenges in San Antonio and similar regions. By synthesizing participant-informed, practice-based recommendations, including hybrid care models, coordinated social needs screening, and targeted outreach strategies, this study identifies actionable approaches to address persistent barriers to care and strengthen healthcare system resilience in both emergency and routine settings.
Despite these contributions, several limitations should be considered. First, the focus group size (n = 17) was determined by scheduling rather than sampling design, which may have limited balanced participation. Quieter participants may have contributed less, and some responses may reflect more dominant voices. Second, the study relied on retrospective accounts of the COVID-19 pandemic, introducing the possibility of recall bias. This was most evident when participants described workforce and training challenges, as few provided detailed examples of specific training gaps or operational difficulties encountered during the pandemic’s peak. Third, demographic data were not consistently collected across all participant groups, limiting the ability to assess variation in perspectives by demographic characteristics. Finally, as the study was conducted within a single metropolitan area, findings may not be generalizable to other settings with different healthcare systems or policy environments.
Overall, this study highlights how COVID-19 exposed and intensified existing vulnerabilities in healthcare delivery, insurance coverage, and digital access within a diverse metropolitan region. By grounding these findings in system- and provider-level perspectives, the study offers practical insights to inform healthcare planning, resource allocation, and access strategies in both future public health emergencies and routine care delivery.
Conclusion
The COVID-19 pandemic exposed and intensified existing challenges in healthcare access across San Antonio, particularly for populations facing economic, linguistic, and age-related barriers. This study identified key system-level challenges, including workforce shortages, insurance coverage instability, and barriers to telehealth access, and highlighted participant-informed, practice-based strategies to address these issues.
Findings underscore the importance of culturally responsive outreach, improved digital access, and integrated approaches to social needs screening with referral pathways. While broader policy factors influence healthcare access, participants emphasized the role of local health systems in implementing practical strategies such as hybrid care delivery, coordinated social needs screening, and targeted outreach to address gaps in access.
As Metro Health San Antonio continues advancing its goals to improve population health in the coming years, these insights remain relevant beyond the pandemic and can inform ongoing efforts to strengthen healthcare delivery, improve access, and enhance system preparedness in both routine and emergency contexts.
Footnotes
Appendix 1
Illustrative participant quotes reflecting recommended system-level strategies.
| Theme | Participant recommendation |
|---|---|
| Disruptions in healthcare delivery due to staffing shortages and care bottlenecks | “Most hospitals collect age, sex, race, and ethnicity but don’t ask about housing insecurity, transportation, or food access. If we want to address these issues, we have to ask patients about them. These questions can be uncomfortable, and if not asked carefully, they can cause harm.” – Healthcare leader Key Informant |
| “You can’t just collect the data and say “thanks.” What are you doing with it? Some health systems are even investing in housing because they realize there aren’t enough resources in the community. “Screening is only useful if it leads to action. In medicine, we always say, ‘Don’t order a test unless you know what you’re going to do with the results.’ The same applies here.” – Healthcare leader Key Informant | |
| Barriers to telehealth access driven by digital inequities and literacy challenges | “We did robocalls and reached out directly to residents via phone to let them know where and how to get a vaccine. Many older adults wouldn’t have been able to access the internet or navigate online forms.” – Policy leader Key Informant |
| “There’s a barrier when there aren’t enough bilingual providers. Caregivers are often forced into a hybrid communication method or left to navigate English-only documentation.” – Healthcare leader Key Informant | |
| “A home nurse could visit, do the exam, and FaceTime or conduct telehealth with the physician. That would be an improvement, but it requires manpower.” – Healthcare leader Key Informant | |
| “We try to teach our clients to scan documents instead of taking blurry pictures, but that does not always get through. If they struggle with that, we need to create platforms that meet them where they are.” – Healthcare Leader Key Informant | |
| “For screening-type visits, it works well. If someone has congestive heart failure, they can send weight and blood pressure readings remotely, and a provider can adjust medications.” – Healthcare leader Key Informant | |
| “We expanded telehealth in the ED, allowing patients to be seen remotely by a provider upon arrival. We also deployed iPads so pulmonologists and hospitalists could conduct telehealth consultations across multiple hospital floors. “Instead of traveling between hospital floors or facilities, physicians could log in from a single location and see more patients.” – Healthcare leader Key Informant | |
| Health insurance instability, particularly around Medicaid redetermination | “When we give property tax abatements, that is less money going into the university healthcare system. If we continue removing funding, it will impact care quality and provider capacity.” – Policy leader Key Informant |
| “We had a focus group with refugee, immigrant, and migrant families, and one issue raised was making exceptions on SNAP benefits for families that require cultural foods. Some policies force families into consuming foods that are not part of their diet, causing more harm than good. There’s a policy mentality that says, ‘Well, we’re giving it to you, and if you’re not using it, it’s your fault.’ That thinking needs to change.” – Healthcare leader focus group |
Appendix 2
Standards for reporting qualitative research (SRQR) checklist.
| No. | Item | Description/expectation | Location in manuscript |
|---|---|---|---|
| 1 | Title | Identifies the study as qualitative; specifies approach or data source. | Title |
| 2 | Abstract | Structured summary of background, purpose, methods, results, and conclusions. | Abstract |
| 3 | Problem formulation | Describes problem significance, relevance, and study rationale. | Introduction |
| 4 | Purpose or research question | States clear study aim or questions. | Introduction |
| 5 | Qualitative approach and research paradigm | Specifies analytic approach (e.g., thematic, grounded theory) and paradigm (e.g., constructivist). | Methods: Study design |
| 6 | Researcher characteristics and reflexivity | Notes researchers’ backgrounds, assumptions, and influence on interpretation. | Methods: Data Collection |
| 7 | Context | Describes study setting and key contextual factors. | Introduction |
| 8 | Sampling strategy | Explains participant selection and justification (e.g., purposive, snowball). | Methods: Participant Selection and Recruitment |
| 9 | Ethical issues | Mentions IRB approval, consent, and confidentiality. | |
| 10 | Data collection methods | Details how data were obtained (interviews, focus groups), by whom, and when. | Methods: Data Collection |
| 11 | Data collection instruments and technologies | Describes interview guides, recorders, or software used. | Methods: Data Collection, Data Analysis |
| 12 | Units of study | Reports participant numbers and key characteristics. | Methods: Participant Selection and Recruitment |
| 13 | Data processing | Explains transcription, data management, and anonymization. | Methods: Data Collection |
| 14 | Data analysis | Describes coding process, whether inductive/deductive, and software (e.g., ATLAS.ti). | Methods: Data Analysis |
| 15 | Techniques to enhance trustworthiness | Explains credibility checks (triangulation, member checking, audit trail). | Methods: Rigor |
| 16 | Synthesis and interpretation | Presents key themes and relationships among concepts. | Results |
| 17 | Links to empirical data | Supports themes with participant quotes or field evidence. | Results |
| 18 | Integration with prior work, implications, transferability, contribution | Compares with existing literature; notes significance and transferability. | Discussion |
| 19 | Limitations | Discusses trustworthiness and methodological boundaries. | Limitations |
| 20 | Conflicts of interest | States any potential bias or conflicts. | Conflict of Interest |
| 21 | Funding | Lists funding sources and role of funders. | Funding |
Source: O’Brien et al. (2014). 19
Acknowledgements
We gratefully acknowledge the San Antonio Metropolitan Health District (Metro Health) for their funding and support of this quality improvement initiative to assess healthcare system resilience during the COVID-19 pandemic. Their commitment to understanding and addressing healthcare access barriers has been invaluable to this work. We also extend our sincere appreciation to the Bexar County Community Health Collaborative for their partnership and assistance in participant recruitment and community engagement throughout the research process. Special thanks to all healthcare leaders, community health workers, and policymakers who generously shared their time and insights for this study.
Ethical considerations
This study was exempt from IRB review by the UTHealth School of Public Health because it originated from a quality improvement (QI) project in partnership with San Antonio Metropolitan Health District.
Consent to participate
All participants provided informed consent prior to participation. No financial incentives were offered for participation in the study; participation was entirely voluntary. Confidentiality was maintained throughout the study in compliance with ethical research standards.
Author contributions
SO: Conceptualization, Methodology, Investigation, Data collection, Formal analysis, Writing - original draft, Writing - review & editing. Led the project and manuscript preparation. AC: Conceptualization, Methodology, Investigation, Data collection, Formal analysis, Writing - original draft, Writing - review & editing. DF: Analysis guidance, Writing - review & editing LM, JT: Supervision, Resources, Project administration, Writing - review & editing, and served as Principal Investigators on the project.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by San Antonio Metropolitan Health District as part of a quality improvement initiative to assess access to care during the COVID-19 pandemic.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data availability statement
This project was conducted as a quality improvement initiative. Full transcripts are not publicly available due to confidentiality protections and the sensitive nature of participant responses.