The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly, but real-world clinical implementation has not yet become a reality. Here we review some of the ...key practical issues surrounding the implementation of AI into existing clinical workflows, including data sharing and privacy, transparency of algorithms, data standardization, and interoperability across multiple platforms, and concern for patient safety. We summarize the current regulatory environment in the United States and highlight comparisons with other regions in the world, notably Europe and China.
The Coronavirus Disease 2019 (COVID-19) pandemic has necessitated a sudden transition to remote learning in medical schools. We aimed to assess perceptions of remote learning among pre-clinical ...medical students and subsequently to identify pros and cons of remote learning, as well as uncover gaps to address in ongoing curricular development.
A survey was distributed to first- and second-year medical students at the University of California San Diego School of Medicine in March 2020. Frequencies of responses to structured multiple-choice questions were compared regarding impacts of remote learning on quality of instruction and ability to participate, value of various remote learning resources, living environment, and preparedness for subsequent stages of training. Responses to open-ended questions about strengths and weaknesses of the remote curriculum and overall reflections were coded for thematic content.
Of 268 students enrolled, 104 responded (53.7% of first-year students and 23.9% of second-year students). Overall, students felt that remote learning had negatively affected the quality of instruction and their ability to participate. Most (64.1%) preferred the flexibility of learning material at their own pace. Only 25.5% of respondents still felt connected to the medical school or classmates, and feelings of anxiety and isolation were noted negatives of remote learning. Most second-year students (56.7%) felt their preparation for the United States Medical Licensing Examination Step 1 exam was negatively affected, and 43.3% felt unprepared to begin clerkships. In narrative responses, most students appreciated the increased flexibility of remote learning, but they also identified several deficits that still need to be addressed, including digital fatigue, decreased ability to participate, and lack of clinical skills, laboratory, and hands-on learning.
Videocasted lectures uploaded in advance, electronic health record and telehealth training for students, and training for teaching faculty to increase technological fluency may be considered to optimize remote learning curricula.
Ability to afford medication is a major determinate of medication adherence among patients.
To determine cost-related barriers to medication adherence by race and ethnicity in a nationwide cohort of ...patients with glaucoma.
This cross-sectional study included patients with glaucoma enrolled in the National Institutes of Health All of Us Research Program, a nationwide longitudinal cohort of US adults, with more than 300 000 currently enrolled. Individuals with a diagnosis of glaucoma based on electronic health record diagnosis codes who participated in the Health Care Access and Utilization survey and had complete data on all covariates were studied. Data were collected from June 2016 to March 2021, and data were analyzed from August to November 2021.
Race and ethnicity defined as non-Hispanic African American, non-Hispanic Asian, Hispanic, and non-Hispanic White.
Logistic regression was used to evaluate the association between reported cost-related barriers to medication adherence (could not afford prescription medication, skipped medication doses to save money, took less medication to save money, delayed filling a prescription to save money, asked for lower-cost medication to save money, bought prescriptions from another country to save money, and used alternative therapies to save money) and race and ethnicity, adjusting multivariable models by age, gender, health insurance status, education, and income. Odds ratios of these barriers were obtained by race and ethnicity, with non-Hispanic White race as the reference group.
Of 3826 included patients with glaucoma, 481 (12.6%) were African American, 119 (3.1%) were non-Hispanic Asian, 351 (9.2%) were Hispanic, and 2875 (75.1%) were non-Hispanic White. The median (IQR) age was 69 (60-75) years, and 2307 (60.3%) were female. After adjusting for confounders, non-Hispanic African American individuals (odds ratio, 1.82; 95% CI, 1.34-2.44) and Hispanic individuals (odds ratio, 1.77; 95% CI, 1.25-2.49) were more likely than non-Hispanic White individuals to report not being able to afford medications. Further, despite having the lowest rate of endorsing difficulty affording medications, non-Hispanic White individuals were equally likely to ask for lower-cost medication from their clinicians as individuals of racial and ethnic minority groups.
In this study, there was significantly higher odds of self-reported difficulty affording medications among non-Hispanic African American and Hispanic individuals compared with non-Hispanic White individuals. Clinicians should be proactive and initiate discussions about costs in an effort to promote medication adherence and health equity among patients.
Data provide an opportunity to discover disparities and inequities that may otherwise be unrecognized. Within the American Academy of Ophthalmology (AAO) Task Force on Disparities in Eye Care, the ...Leveraging Data Sub-task Force was charged with identifying data sources to study health disparities in eye care and to leverage data to advance health equity. We evaluated large data sources to determine their strengths, deficiencies, and relative accessibility in relation to the likelihood of identifying eye care disparities. We highlight the current challenges with these data sources and review key recommendations for improving future sources for studying health disparities in eye care.
Current glaucoma treatments aim to lower intraocular pressure, often with topical ocular hypotensive medications. Unfortunately, the effectiveness of these medications depends on sustained patient ...adherence to regimens which may involve instilling multiple medications several times daily. Patient adherence to glaucoma medications is often low. Recent innovations in digital sensor technologies have been leveraged to confirm eyedrop medication usage in real-time and relay this information back to providers. Some sensors have also been designed to deliver medication reminders and notifications as well as assist with correct eyedrop administration technique. Here, we review recent innovations targeted at improving glaucoma medication adherence and discuss their limitations.
The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning ...framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes.
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•An artificial intelligence system using transfer learning techniques was developed•It effectively classified images for macular degeneration and diabetic retinopathy•It also accurately distinguished bacterial and viral pneumonia on chest X-rays•This has potential for generalized high-impact application in biomedical imaging
Image-based deep learning classifies macular degeneration and diabetic retinopathy using retinal optical coherence tomography images and has potential for generalized applications in biomedical image interpretation and medical decision making.
Inadequacies in healthcare access and utilization substantially impact outcomes for diabetic patients. The All of Us database offers extensive survey data pertaining to social determinants that is ...not routinely available in electronic health records. This study assesses whether social determinants were associated with an increased risk of developing proliferative diabetic retinopathy or related complications (e.g. related diagnoses or procedures).
We identified 729 adult participants in the National Institutes of Health All of Us Research Program data repository with diabetic retinopathy (DR) who answered survey questions pertaining to healthcare access and utilization. Electronic health record data regarding co-morbidities, laboratory values, and procedures were extracted. Multivariable logistic regression with bi-directional stepwise variable selection was performed from a wide range of predictors. Statistical significance was defined as p<0.05.
The mean (standard deviation) age of our cohort was 64.9 (11.4) years. 15.2% identified as Hispanic or Latino, 20.4% identified as Black, 60.6% identified as White, and 19.3% identified as Other. 10-20% of patients endorsed several reasons for avoiding or delaying care, including financial concerns and lack of access to transportation. Additional significant social determinants included race and religion discordance between healthcare provider and patient (odds ratio OR 1.20, 95% confidence interval CI 1.02-1.41, p = 0.03) and caregiver responsibilities toward others (OR 3.14, 95% CI 1.01-9.50, p = 0.04).
Nationwide data demonstrate substantial barriers to healthcare access among DR patients. In addition to financial and social determinants, race and religion discordance between providers and patients may increase the likelihood of PDR and related complications.
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