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Research surrounding tumor boards has focused on patient outcomes and care coordination. Little is known about the patient experience with tumor boards. This survey examined aspects of the patient experience for patients presented at our multidisciplinary endocrine tumor board (ETB). A 15-item survey was distributed via the online patient portal to patients over the age of 18 whose case had been discussed at our ETB over an 18-month period. Descriptive statistics were reported, and a Fisher's exact test was used to examine relationships between variables. A total of 47 patients completed the survey (46%). A majority (72%) report their provider explained what the ETB is, and 77% report being informed their case would be discussed. Most patients were satisfied their case was being discussed (72%). A number of patients did report moderate or severe anxiety knowing their case was being discussed (15%). Sixty-four percent of patients report the ETB recommendations were clearly explained; however, satisfaction with the recommendations was slightly lower (53%). Despite the somewhat low satisfaction with the recommendations, 75% of patients felt more confident in their treatment plan knowing their case was discussed. Finally, if given the chance, 66% responded that they would have been interested in participating in their own ETB discussion. This study provides some insight into the patient experience surrounding tumor board discussions. Overall, patients are satisfied when their case is discussed at ETB. Patients can also experience anxiety about these discussions, and many patients desire to be present for their own discussions.

Severity of fibrosis is the driver of liver-related outcomes in metabolic dysfunction-associated steatotic liver disease (MASLD), and non-invasive testing such as fibrosis-4 (FIB-4) score is utilized for risk stratification. We aimed to determine if primary care patients at risk for MASLD and advanced fibrosis were evaluated with subsequent testing. A secondary aim was to determine if at-risk patients with normal aminotransferases had advanced fibrosis. Primary care patients at increased risk for MASLD with advanced fibrosis (n = 91,914) were identified using previously established criteria. Patients with known alternative/concomitant etiology of liver disease or cirrhosis were excluded. The study cohort included patients with calculated FIB-4 score in 2020 (n = 52,006), and stratified into low, indeterminate, and high likelihood of advanced fibrosis. Among those at indeterminate/high risk, rates of subsequent testing were measured. Risk stratification with FIB-4 characterized 77% (n = 40,026) as low risk, 17% (n = 8847) as indeterminate, and 6% (n = 3133) as high risk. Among indeterminate/high-risk patients (n = 11,980), 78.7% (n = 9433) had aminotransferases within normal limits, 0.95% (n = 114) had elastography, and 8.2% (n = 984) were referred for subspecialty evaluation. In this cohort of primary care patients at risk for MASLD with fibrosis, the FIB-4 score identified a substantial proportion of indeterminate/high-risk patients, the majority of which had normal aminotransferase levels. Low rates of subsequent testing were observed. These data suggest that a majority of patients at increased risk for liver-related outcomes remain unrecognized and highlight opportunities to facilitate their identification.

Literature suggests patients with thyroid cancer have unmet informational needs in many aspects of care. Patients often turn to online resources for their health-related information, and generative artificial intelligence programs such as ChatGPT are an emerging and attractive resource for patients. To assess the quality of ChatGPT's responses to thyroid cancer-related questions. Four endocrinologists and 4 endocrine surgeons, all with expertise in thyroid cancer, evaluated the responses to 20 thyroid cancer-related questions. Responses were scored on a 7-point Likert scale in areas of accuracy, completeness, and overall satisfaction. Comments from the evaluators were aggregated and a qualitative analysis was performed. Overall, only 57%, 56%, and 52% of the responses \"agreed\" or \"strongly agreed\" that ChatGPT's answers were accurate, complete, and satisfactory, respectively. One hundred ninety-eight free-text comments were included in the qualitative analysis. The majority of comments were critical in nature. Several themes emerged, which included overemphasis of diet and iodine intake and its role in thyroid cancer, and incomplete or inaccurate information on risks of both thyroid surgery and radioactive iodine therapy. Our study suggests that ChatGPT is not accurate or reliable enough at this time for unsupervised use as a patient information tool for thyroid cancer.

Background and Aims Severity of fibrosis is the driver of liver-related outcomes in metabolic dysfunction-associated steatotic liver disease (MASLD), and non-invasive testing such as fibrosis-4 (FIB-4) score is utilized for risk stratification. We aimed to determine if primary care patients at risk for MASLD and advanced fibrosis were evaluated with subsequent testing. A secondary aim was to determine if at-risk patients with normal aminotransferases had advanced fibrosis. Methods Primary care patients at increased risk for MASLD with advanced fibrosis ( n  = 91,914) were identified using previously established criteria. Patients with known alternative/concomitant etiology of liver disease or cirrhosis were excluded. The study cohort included patients with calculated FIB-4 score in 2020 ( n  = 52,006), and stratified into low, indeterminate, and high likelihood of advanced fibrosis. Among those at indeterminate/high risk, rates of subsequent testing were measured. Results Risk stratification with FIB-4 characterized 77% ( n  = 40,026) as low risk, 17% ( n  = 8847) as indeterminate, and 6% ( n  = 3133) as high risk. Among indeterminate/high-risk patients ( n  = 11,980), 78.7% ( n  = 9433) had aminotransferases within normal limits, 0.95% ( n  = 114) had elastography, and 8.2% ( n  = 984) were referred for subspecialty evaluation. Conclusion In this cohort of primary care patients at risk for MASLD with fibrosis, the FIB-4 score identified a substantial proportion of indeterminate/high-risk patients, the majority of which had normal aminotransferase levels. Low rates of subsequent testing were observed. These data suggest that a majority of patients at increased risk for liver-related outcomes remain unrecognized and highlight opportunities to facilitate their identification.

Health-related social needs are associated with poor health outcomes, increased acute health care use, and impaired chronic disease management. Given these negative outcomes, an increasing number of national health care organizations have recommended that the health system screen and address unmet health-related social needs as a routine part of clinical care, but there are limited data on how to implement social needs screening in clinical settings to improve the management of chronic diseases such as hypertension. SMS text messaging could be an effective and efficient approach to screen patients; however, there are limited data on the feasibility of using it. We conducted a cross-sectional study of patients with hypertension to determine the feasibility of using SMS text messaging to screen patients for unmet health-related social needs. We randomly selected 200 patients (≥18 years) from 1 academic health system. Patients were included if they were seen at one of 17 primary care clinics that were part of the academic health system and located in Forsyth County, North Carolina. We limited the sample to patients seen in one of these clinics to provide tailored information about local community-based resources. To ensure that the participants were still patients within the clinic, we only included those who had a visit in the previous 3 months. The SMS text message included a link to 6 questions regarding food, housing, and transportation. Patients who screened positive and were interested received a subsequent message with information about local resources. We assessed the proportion of patients who completed the questions. We also evaluated for the differences in the demographics between patients who completed the questions and those who did not using bivariate analyses. Of the 200 patients, the majority were female (n=109, 54.5%), non-Hispanic White (n=114, 57.0%), and received commercial insurance (n=105, 52.5%). There were no significant differences in demographics between the 4446 patients who were eligible and the 200 randomly selected patients. Of the 200 patients included, the SMS text message was unable to be delivered to 9 (4.5%) patients and 17 (8.5%) completed the social needs questionnaire. We did not observe a significant difference in the demographic characteristics of patients who did versus did not complete the questionnaire. Of the 17, a total of 5 (29.4%) reported at least 1 unmet need, but only 2 chose to receive resource information. We found that only 8.5% (n=17) of patients completed a SMS text message-based health-related social needs questionnaire. SMS text messaging may not be feasible as a single modality to screen patients in this population. Future research should evaluate if SMS text message-based social needs screening is feasible in other populations or effective when paired with other screening modalities.

Background Digital health (patient portals, remote monitoring devices, video visits) is a routine part of health care, though the digital divide may affect access. Objectives To test and validate an electronic health record (EHR) screening tool to identify patients at risk of the digital divide. Materials and Methods We conducted a retrospective EHR data extraction and cross-sectional survey of participants within 1 health care system. We identified 4 potential digital divide markers from the EHR: (1) mobile phone number, (2) email address, (3) active patient portal, and (4) >2 patient portal logins in the last year. We mailed surveys to patients at higher risk (missing all 4 markers), intermediate risk (missing 1-3 markers), or lower risk (missing no markers). Combining EHR and survey data, we summarized the markers into risk scores and evaluated its association with patients’ report of lack of Internet access. Then, we assessed the association of EHR markers and eHealth Literacy Scale survey outcomes. Results A total of 249 patients (39.4%) completed the survey (53%>65 years, 51% female, 50% minority race, 55% rural/small town residents, 46% private insurance, 45% Medicare). Individually, the 4 EHR markers had high sensitivity (range 81%-95%) and specificity (range 65%-79%) compared with survey responses. The EHR marker-based score (high risk, intermediate risk, low risk) predicted absence of Internet access (receiver operator characteristics c-statistic=0.77). Mean digital health literacy scores significantly decreased as her marker digital divide risk increased (P  <.001). Discussion Each of the four EHR markers (Cell phone, email address, patient portal active, and patient portal actively used) compared with self-report yielded high levels of sensitivity, specificity, and overall accuracy. Conclusion Using these markers, health care systems could target interventions and implementation strategies to support equitable patient access to digital health. Lay Summary Digital health tools, such as patient portals and video visits, are increasingly important in health care, but not everyone has equal access. This study aimed to validate a screening tool using electronic health record (EHR) data to identify patients at risk of being left behind due to the “digital divide.” Researchers analyzed EHR data and conducted surveys among patients in a health care system, focusing on 4 markers: having a mobile phone number, email address, an active patient portal account, and frequent portal use. Patients were categorized into high, intermediate, or low digital divide risk based on missing markers. Survey results from 249 participants showed the markers accurately predicted lack of Internet access, with good sensitivity and specificity. Additionally, higher digital divide risk was strongly linked to lower digital health literacy scores. These findings suggest that EHR-based markers can help health care systems identify patients who may need additional support, such as digital literacy training or alternative communication methods, to ensure equitable access to digital health services.