Abstract
Background:
Latinx populations in the United States bear a disproportionate burden of diabetic eye disease. Teleophthalmology with and without artificial intelligence (AI)-based image interpretation are validated methods for diabetic eye screening, but limited literature exists on patient perspectives. This study aimed at understanding the perspectives of Latinx patients with diabetes on teleophthalmology, AI-based image interpretation, and general virtual care to prevent avoidable blindness in this population.
Methods:
We conducted semi-structured, individual interviews with 20 Latinx patients with diabetes at an urban, federally qualified health center in Madison, WI. Interviews were transcribed verbatim, professionally translated from Spanish to English, and analyzed using both inductive open coding and deductive coding.
Results:
Most participants had no prior experience with teleophthalmology but did have experience with virtual care. Participants expressed a preference for teleophthalmology compared with traditional in-person dilated eye exams but were willing to obtain whichever method of screening was recommended by their primary care clinician. They also strongly preferred having human physician oversight in image review compared with having images interpreted solely using AI. Many participants preferred in-person clinic visits to virtual health care due to the ability to have a more thorough physical exam, as well as for improved non-verbal communication with their clinician.
Discussion:
Leveraging primary care providers' recommendations, human oversight of AI-based image interpretation, and improving communication may enhance acceptance and utilization of teleophthalmology, AI, and virtual care by Latinx patients.
Conclusions:
Understanding Latinx patient perspectives may contribute toward the development of more effective telemedicine interventions to enhance health equity in Latinx communities.
Introduction
Latinx populations bear a disproportionate burden from diabetes and have the highest rates of visual impairment and blindness of any ethnic group in the United States.1–4 Although early detection and treatment decreases the risk of severe vision loss by 90%, most Latinx patients with diabetic retinopathy remain undiagnosed due to a lack of yearly eye screening as recommended by the American Diabetes Association.1,5
As an evidence-based alternative to traditional in-person dilated eye exams, teleophthalmology provides convenient, low-cost screening using retinal photos taken at a primary care clinic.6,7 Primary care is an ideal setting for teleophthalmology because nearly 90% of U.S. adults with diabetes regularly obtain care from a primary care clinician. 8
Teleophthalmology images are usually interpreted remotely by an eye care clinician. More recently, two Food and Drug Administration (FDA)-cleared, autonomous artificial intelligence (AI) algorithms for stand-alone interpretation of images (designed for use without human involvement) have been used to detect diabetic retinopathy from retinal images with high sensitivity and specificity.9,10 However, a few recent studies have noted barriers to patient acceptance of AI-based image interpretation.11,12
Most studies of Latinx patient perceptions of teleophthalmology and AI use in health care have been survey-based rather than qualitative.12–14 The latter provides a richer and more in-depth understanding of complex issues, such as how differences in patient perceptions of new technologies may contribute to health disparities.12,15,16
The only two previous qualitative studies evaluating patient perspectives on the use of AI for teleophthalmology were conducted outside the United States and found that while most participants were receptive to the use of AI, a substantial minority expressed a preference for human image review.15,17 An improved understanding of patient perspectives may facilitate the development of strategies to effectively integrate AI into telemedicine and enhance health equity in the Latinx community. Thus, our study aimed at understanding Latinx patient perspectives on teleophthalmology, AI-based image interpretation, and virtual care.
Methods
Participant recruitment and research setting
Adults (18 years or older) who self-identified as Latinx/Hispanic and diagnosed with type 1 or type 2 diabetes were eligible to participate in semi-structured, individual interviews. A culturally informed recruitment letter and flyer were developed with the following organizations in Dane County, WI: the Latino Health Council of Dane County (a Latinx community stakeholder group), NewBridge Madison (a non-profit organization serving older adults), and Access Community Health Centers (ACHC) (an urban, federally qualified health center).
Of note, this study was conducted before implementing teleophthalmology at ACHC. ACHC staff mailed recruitment letters and flyers to a random sample of their Latinx patients with diabetes (n = 523). Patients could opt-in to participate by calling the research team, and recruitment continued until reaching informational redundancy, in which sample size was sufficient so that no new information could be acquired from subsequent interviews. 18
Interviews
The interview guide (Supplementary Data S1) was adapted from a prior study among predominantly non-Hispanic, white, rural patients. 19 A Spanish-language version was created by professional translators and then edited for accuracy by three Spanish speakers on the research team (including a Venezuelan physician with over 10 years of experience in engaging U.S. Latinx communities in research and two Mexican-American research specialists).
Components from the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework were used to create questions that addressed participants' perspectives on teleophthalmology, AI-based image interpretation, and virtual care. 20 Participants were shown an image of a patient obtaining a traditional dilated eye exam and an image of a patient having their eyes photographed using teleophthalmology (Supplementary Data S2).
Teleophthalmology was described verbally as “a technician uses a special camera to take photos for an eye doctor to look inside your eyes.” To assess their perspectives on AI-based interpretation, participants were asked, “Would you be more comfortable having the eye photo test if the photos were reviewed by an eye doctor or by a computer? Why?”
Demographic information, including age, gender, race and ethnicity, country of heritage or origin, insurance status, diabetes type, duration of diabetes, diabetic eye screening adherence, highest level of education, English fluency, and health literacy using the Single Item Literacy Screener, was collected using a written survey. 21 The Social Vulnerability Index (SVI), which accesses the vulnerability of communities based on social factors (on a scale 0–1.0, 1.0 being the most vulnerable and 0.46 being the median SVI for the United States overall), was calculated based on a patient's home address zip code using U.S. Census data.22,23
From July to November 2022, interviews (45–60 min) were conducted in the participants' preferred language (i.e., either Spanish or English) either virtually or in-person at a community center owned by the University of Wisconsin (UW)-Madison. All interviews were led by a bilingual male Bachelor's-level research specialist (C.P.) with qualitative research training and who self-identifies as Mexican–American. Field notes were taken by the interviewer during the interview. Participants were informed that the interviewer had no specialized medical knowledge of diabetes or diabetic retinopathy and were provided with $30 in compensation for their time and were offered coverage of transportation costs.
Data analysis
Audio recordings of interviews were transcribed verbatim, professionally translated from Spanish to English, and analyzed using QSR NVivo software for Mac Version 1.7 (QSR International, Melbourne, Australia). We performed inductive open coding and deductive coding using the NIMHD Research Framework and the Campbell and Egede Model, which describes challenges experienced by inner-city African-Americans in managing type 2 diabetes.20,24
The research specialist (C.P.) performed independent open coding of the first five transcripts. The research team members, N.J. (a PhD qualitative methodologist), and members of the UW Institute of Clinical and Translational Research-Community Academic Partnership (ICTR-CAP) Qualitative Research Group iteratively reviewed codes and refined the coding framework. The Principal investigator (Y.L.) ensured consistency by dual-coding every fifth transcript.
To enhance rigor, we performed member-checking to review our results with a subset of participants and community stakeholders (i.e., patients [n = 3] and Latinx community members recruited from NewBridge Madison [n = 3]) in two separate 1-h meetings. 25 Members judged our interpretation of the interview data to be accurate and complete and provided more nuanced perspectives. Our report of this study follows the Consolidated Criteria for Reporting Qualitative Research (Supplementary Data S3). 26
Ethics/Institutional Review Board review
The UW-Madison Health Sciences Institutional Review Board (IRB) determined that this interview research met criteria for exemption. Following the guidance of the IRB, the interviewer (C.P.) obtained verbal consent from all participants. All research activities were conducted in accordance with the Declaration of Helsinki.
Results
Participant characteristics
Among the 22 Latinx individuals with diabetes who contacted the research team in response to the recruitment flyer, two did not attend an interview after multiple rescheduling attempts. Interview participants (n = 20) all had a diagnosis of type 2 diabetes and had a mean age of 59.8 years (range: 33–79 years) (Table 1). Most participants were female (60%, n = 12), reported either Mexican origin or heritage (60%, n = 12), were uninsured (60%, n = 12), and had low or moderate health literacy (60%, n = 12).
Demographics of Patient Interview Participants (n = 20)
GED, general educational development; SD, standard deviation; SVI, Social Vulnerability Index.
More than half had an English fluency of “not at all” or “not very well” (55%, n = 11), and most preferred to speak Spanish during their clinic appointments (75%, n = 15). The majority (70%, n = 14) had not received diabetic eye screening within the past year, and only two participants (10%) had eye photos taken in the past. Nearly all had prior experience with virtual care (95%, n = 19). Interviews were primarily conducted in-person (90%, n = 18) and in Spanish (85%, n = 17).
Two participants (10%) were acquainted with the interviewer (C.P.) from his prior work on increasing COVID-19 vaccination rates in the Latinx community in partnership with the Latino Health Council of Dane County.
Teleophthalmology versus traditional in-person dilated eye exam for diabetic eye screening
Many participants reported preferring teleophthalmology over a traditional in-person dilated eye exam, because they believed that teleophthalmology represented more advanced technology that had greater precision and accuracy (Table 2). One participant specifically noted a general perception that electronic equipment (i.e., teleophthalmology) worked better than manual processes, such as an in-person dilated eye exam.
Teleophthalmology Versus Traditional In-Person Dilated Eye Exam for Diabetic Eye Screening
PCP, primary care clinician.
Participants also noted several logistical benefits of teleophthalmology, including that it does not require dilating eye drops that blur their vision and require them to have a driver. Further, most participants felt that offering teleophthalmology for an out-of-pocket cost of $20 (i.e., amount equivalent to standard co-pays for in-person clinic visits, such as for dilated eye exams, among insured patients) would be acceptable and that teleophthalmology would be more time-efficient than an in-person dilated eye exam.
Participants also noted the benefits of having teleophthalmology eye photos as part of their medical records. Some appreciated the opportunity to directly review their results by seeing their eye photo. Another perceived benefit was that teleophthalmology allows for the comparison of eye photos over time to detect changes. In addition, some participants believed that teleophthalmology complements the eye exam performed by a primary care clinician to catch diabetic eye disease that might otherwise be missed.
While most participants were highly receptive to teleophthalmology, a few participants indicated distrust of new technologies and preferred an in-person dilated eye exam. Yet, all participants reported that they would obtain whichever type of diabetic eye screening was recommended to them by their primary care or eye care clinician. Participants expressed their belief that doctors are the most knowledgeable as to which type of screening would be most appropriate for an individual patient and emphasized their trust in the expertise of health care professionals.
AI versus physician-based image interpretation of teleophthalmology
Participants strongly preferred that a human physician be involved in the review and interpretation of their eye photos, rather than relying solely on an AI algorithm (Table 3). Many reported trusting the education and professional experience of a human physician, because they valued the human capacity to learn and reason when encountering unfamiliar scenarios, in contrast to “a machine does what it's already programmed to do, nothing more” (Patient #13).
Artificial Intelligence Versus Physician-Based Diagnostic Interpretation of Teleophthalmology for Diabetic Eye Screening
AI, artificial intelligence.
Further, some participants noted that human physicians are motivated to help patients due to having empathy, as well as to avoid making mistakes that could harm their professional reputation. In addition, participants expressed safety concerns that computers could make serious mistakes, and some noted uncertainty regarding the accuracy of AI.
Most participants reported feeling comfortable with the use of AI as a decision support tool for human physicians. Even when they acknowledged the benefits of AI in providing a fast and accurate analysis that may exceed that of a human physician, many participants still wanted the human physician involved in the final decision-making process because of their greater trust in health care professionals compared with machines.
Experiences with and perspectives on virtual health care
Participants reported that they appreciated the convenience and time efficiency of virtual health care (i.e., not specific to eye care), which removes important barriers to access (Table 4). One participant found virtual appointments over the phone particularly helpful when struggling with depression and having trouble just getting out of bed.
Experiences with and Perspectives on Virtual Health Care
Participants also appreciated the time-saving aspects of virtual care, particularly for shorter appointment types, such as those for medication management that may not require a physical exam. However, most participants preferred in-person visits for their annual physical exams or to evaluate symptoms that could be related to a new diagnosis.
Some participants felt that virtual care is inadequate when they believe a physical exam is needed to fully evaluate their medical problem. In addition, there was a preference for in-person visits when they must go to the clinic to get laboratory tests done, such as for hemoglobin A1c. Likewise, despite having a home blood pressure monitor, another participant reported feeling more confident in blood pressure measurements obtained at a clinic.
Many participants also emphasized the importance of in-person care for establishing an emotional connection with a physician, because they felt that they could detect emotions more clearly. One participant specifically mentioned the importance of having support from human warmth and physical contact with their doctor, particularly during difficult times.
Some participants also expressed concerns about the inability to fully assess a clinician's body language during virtual care encounters that would help them better assess whether to trust that clinician and follow their recommendations. Conversely, one participant noted that a patient's body language can also help clinicians identify additional problems that patients may not verbally express.
Another participant reported feeling uncomfortable with virtual care and had never used it. Some participants suggested that virtual care should be used only when in-person care is not possible.
Discussion
In this qualitative study, most participants perceived teleophthalmology to be superior to in-person dilated eye exams for diabetic eye screening because they felt that it was advanced technology and had better accuracy. In addition, they preferred teleophthalmology because it was offered at an acceptable cost, was more time-efficient, was conveniently located in the primary care clinic, and did not require the use of dilating eye drops. In contrast, a small number of participants expressed a distrust of technology and preferred an in-person eye exam. All participants reported that they would follow their physician's recommendation as to which screening method would be most appropriate for them. Further, most participants preferred to have oversight from a human physician in reviewing their eye photos rather than evaluation solely using AI. While participants regarded virtual health care to be more accessible and efficient, they noted that virtual visits might be inadequate for medical issues that required a physical exam, and that it was more difficult to establish an emotional connection with their clinician compared with an in-person clinic visit.
Our qualitative study builds upon the limited existing literature on perceptions of teleophthalmology in Latinx communities. A focus group study among Latinx and Black patients undergoing teleophthalmology found that many did not understand its purpose, how the program worked, how to receive their results, and what to do after the test. 27 Fear of technology was voiced by some of their participants. Yet, all participants in this prior study had used teleophthalmology despite significant knowledge gaps and concerns, which suggests that factors not described in their study were able to overcome these barriers (possibly a recommendation from their primary care clinician, which was a strong facilitator noted by participants in our study). Another study among predominantly Latinx adults found that 88% would highly recommend teleophthalmology to others and appreciated having the camera conveniently located in a community center. 28
Our results agreed with these previously reported findings in that most Latinx individuals generally held positive views of teleophthalmology and providing the service in a convenient location was highly valued. However, a limitation of the community-center based study was that 85% of the participants did not have a diagnosis of diabetes and thus would not be eligible for teleophthalmology in health care settings. 28 Further, our study identified that the perceived accuracy of teleophthalmology contributes toward positive Latinx attitudes toward this technology.
Prior studies regarding non-Latinx patient perceptions of AI-based interpretation of teleophthalmology found high acceptance of this technology. An Australian study among patients who had experience with both human and AI-based image interpretation for teleophthalmology found that 96% of participants were either satisfied or very satisfied with AI-based interpretation, and 78% preferred AI-based interpretation. 17 A New Zealand study also found that most respondents who were obtaining teleophthalmology screening reported that they were comfortable with the use of AI in their care, but only about half reported trusting AI as much as a human health care professional. 15 Perceived benefits of using AI included faster diagnostic speeds and greater accuracy, but 36% still preferred human image interpretation even though it would take longer to receive their screening results.
In contrast, we found that most of our participants preferred to have humans involved in teleophthalmology image review. Concerns about cybersecurity were also raised in these prior studies but were not mentioned by participants in our study. Notably, neither of these prior studies reported the inclusion of any Latinx patients, whereas our study specifically focused on Latinx patient perspectives.
Patient perspectives on the use of AI in health care have found variability in its acceptance based on race and ethnicity, as well as health care application. A survey study by Tyson et al. found that Latinx patients were more likely to accept the use of AI for skin cancer screening (69%) compared with White (65%) and Black (57%) respondents. 12 In contrast, 40% or fewer of all U.S. adults reported accepting AI for pain management after surgery, AI-based surgical robots, or AI-based mental health chatbots. Our study found that most Latinx patients preferred human oversight in AI-based interpretation for teleophthalmology because they valued physicians' education, experience, empathy, ability to reason in unfamiliar scenarios, and professional accountability.
Our study also expanded the literature on Latinx perspectives regarding virtual care. A prior study found that Latinx participants expressed some concerns about confidentiality, privacy, and the physical absence of the clinician in virtual care interactions, but to a lesser extent than African Americans. 13 In our study, Latinx patients reported the inability to assess body language as an important limitation of virtual care because of their concern that a patient's ability to decide whether to trust a clinician was diminished.
Another study found that Latinx parents significantly preferred in-person rather than virtual visits for their children as compared with non-Latinx parents (61.3% vs. 28.6%). 14 The inability to conduct a thorough physical exam was viewed as a significant limitation of virtual care, particularly for a new or potentially serious diagnosis.
A pre-existing positive relationship with the clinician made the use of virtual care more acceptable. An additional theme noted by Latinx participants in our study included concerns that virtual care limited one's non-verbal communication and emotional connection with a clinician.
Of note, our interview participants may have had virtual care experiences with providers who had limited training in how to strengthen patient-provider relationships in telehealth and/or a few protocols in place due to the need to rapidly adopt virtual care models at the time of the COVID-19 pandemic. If providers had the benefit of such training and protocols, then it is possible that participants may have felt more of an emotional connection with their virtual care providers.
Possible solutions include providing hands-on training to health care providers on conducting a 3-way virtual call with an interpreter, properly orienting the patient to the telehealth visit, making eye contact by looking into the camera, providing a clear view of one's face and body language for gestures, affirmational head nodding and smiling, talking about non-health care-specific subjects to establish a social connection, demonstrating active listening, and the use of a validated checklist such as the Teaching Interpersonal Skills for Telehealth Checklist.29,30
While our study had several strengths, such as recruiting a large proportion of uninsured participants and those non-adherent with screening (populations less likely to participate in research), it also had a few limitations. Our study seeks to assess knowledge, beliefs, and acceptability of teleophthalmology and AI-based image interpretation among Latinx patients, the majority of whom did not have firsthand experience with these technologies.
We acknowledge that patients' perspectives might change if they did have such experiences. For example, patients may find that the advantage of having much more rapid receipt of results at the point-of-care from AI-based image interpretation outweighs their perceived desire for human involvement in image interpretation, as was noted by a few participants in an Australian study of non-Latinx patient populations. 17 In addition, the two current FDA-cleared AI algorithms for teleophthalmology interpretation are specifically designed to be autonomous for stand-alone interpretation of medical images without human involvement. Thus, we investigated in this study how Latinx patients with diabetes perceived the use of this currently available AI technology. It would be interesting in future studies to assess patients' perceptions on varying methods for using AI in conjunction with clinicians in teleophthalmology image interpretation.
Other limitations of our study include that the “opt in” method of recruitment requiring patients to call in to the research team to participate likely selected for a more motivated patient population than a study that used an “opt out” method of recruitment in which researchers may directly contact any patient who did not explicitly “opt out” from contact by researchers. Participants were predominantly Mexican in origin and heritage, consistent with the demographics of Latinx populations in Wisconsin. 31 To assess the generalizability of our findings, future studies could consider using “opt out” recruitment methods, as well as include Latinx patients who have had teleophthalmology imaging, AI-based image interpretation, those living in other regions of the United States, and those with other national origins or heritage.
In summary, we found that Latinx participants preferred teleophthalmology to in-person dilated eye exams, strongly preferred human oversight of AI-based retinal image interpretation, and had concerns about the effectiveness of non-verbal communication in virtual care visits. Our qualitative data allow us to better understand the reasons that underlie Latinx patient perceptions that may contribute to the development of more effective telemedicine interventions to enhance health equity in Latinx communities.
Footnotes
Acknowledgments
The authors acknowledge the Latino Health Council of Dane County, NewBridge Madison, and ACHC, Madison, WI for their partnership in the development and distribution of interview participant recruitment materials, as well in the design, conduct, and analysis of data for this study. They also acknowledge the UW ICTR-CAP Qualitative Research Group for their input on the data analysis and the National Institutes of Health (NIH)/National Eye Institute (NEI) Implementation of Teleophthalmology in Rural Health Systems (I-TRUST) Study Data and Safety Monitoring Committee (DSMC) for their helpful feedback on the article. This study was presented as a poster presentation at the Association for Research in Vision and Ophthalmology Annual Meeting on April 26, 2023, in New Orleans, LA.
Authors' Contributions
C.P.: funding acquisition (supporting), formal analysis (lead), investigation (equal), visualization (lead), and writing—review and editing (supporting). J.H.: formal analysis (equal), investigation (equal), writing—original draft (lead), M.M.P.: conceptualization (supporting), funding acquisition (supporting), methodology (supporting), formal analysis (equal), investigation (equal), supervision (supporting), visualization (supporting), and writing—review and editing (supporting). L.J.L.: investigation (equal), writing—review and editing (supporting). C.F.: investigation (equal), writing—review and editing (supporting). C.L.S.: investigation (equal), writing—review and editing (supporting). N.A.J.: investigation (equal), writing—review and editing (supporting). R.C.: investigation (equal), writing—review and editing (supporting). Y.L.: conceptualization (lead), funding acquisition (lead), methodology (lead), formal analysis (equal); supervision (lead), and writing—review and editing (lead).
Disclaimer
The funders had no influence on the design or results of the study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
This work was supported by NIH/NEI UG1 EY032446-02S1 Diversity Supplement to C. Pelayo (Y.L.), NIH/NEI UG1 EY032446 I-TRUST Study (Y.L.), UW Shapiro Summer Research Program (J.H.), NIH/NIA K99 AG076966-01 (M.M.P.), and NIH/NEI K23 EY030911-04 (R.C.). It was also supported in part by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR002373 and an Unrestricted Grant from Research to Prevent Blindness, Inc., to the UW-Madison Department of Ophthalmology and Visual Sciences.
Abbreviations Used
References
Supplementary Material
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