Exploring racial and secondary substance use differences in route of administration of opioid drugs: Analysis of the 2015-2019 treatment admission data.

INTRODUCTION: The opioid crisis continues to evolve with increasing opioid-related overdose deaths among under-represented minorities. A better understanding of substance use differences in the route of administration for people using heroin and other opioids can lead to targeted strategies and interventions. METHODS: Using the 2015-2019 Treatment Episode Data Set - Admissions (TEDS-A), a multinomial logistic regression model examined the relationship between race/ethnicity and secondary substance use with route of administration in a subset of 591,078 admissions. RESULTS: For individuals reporting heroin as their primary substance, minoritized clients were both more likely to smoke (NH Blacks RR: 2.28, 95 % CI 2.16-2.41; Hispanic RR: 1.80, 95 % CI: 1.74, 1.87; Other RR: 2.09, 95 % CI: 2.00, 2.20) or inhale heroin (Hispanic RR: 1.82, 95 % CI 1.78-1.85; Other RR: 1.30, 95 % CI 1.25, 1.34) compared to non-Hispanic (NH) Whites. NH Black clients were nearly seven and a half times more likely to report inhaling (RR: 7.45, 95 % CI 7.28, 7.62) heroin over injecting it. Clients were more likely to smoke heroin compared to injection if they reported secondary drug use of methamphetamines (RR: 2.28, 95 % CI 2.21, 2.35) and other opioids (RR: 1.21, 95 % CI 1.15, 1.28). For clients reporting other opioids as their primary substance, Hispanic (RR: 1.33, 95 % CI 1.19, 1.47) and other racial/ethnic minority clients (RR: 2.50, 95 % CI 2.23, 2.79) were more likely to smoke opioids vs take it orally compared to their NH White counterparts. Individuals who reported methamphetamine use as a secondary substance were significantly more than three times as likely to smoke (RR: 3.07, 95 % CI 2.74, 3.45) or inject (RR: 3.36, 95 % CI 3.17, 3.57) compared to orally ingesting opioids, while those who reported cocaine or crack cocaine use were more than twice as likely to inject (RR: 2.22, 95 % CI 2.09-2.36) opioids than taking them orally. CONCLUSION: Findings demonstrate significant racial and ethnic differences in the route of administration. This work expands on the understanding of the complex nature of polysubstance use in the evolving opioid crisis and the secondary substance use of clients on routes of administration of opioids and heroin, highlighting the need for tailored interventions to address the treatment needs of under-represented minorities.

ChatGPT's Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study.

BACKGROUND: ChatGPT is the most advanced large language model to date, with prior iterations having passed medical licensing examinations, providing clinical decision support, and improved diagnostics. Although limited, past studies of ChatGPT's performance found that artificial intelligence could pass the American Heart Association's advanced cardiovascular life support (ACLS) examinations with modifications. ChatGPT's accuracy has not been studied in more complex clinical scenarios. As heart disease and cardiac arrest remain leading causes of morbidity and mortality in the United States, finding technologies that help increase adherence to ACLS algorithms, which improves survival outcomes, is critical. OBJECTIVE: This study aims to examine the accuracy of ChatGPT in following ACLS guidelines for bradycardia and cardiac arrest. METHODS: We evaluated the accuracy of ChatGPT's responses to 2 simulations based on the 2020 American Heart Association ACLS guidelines with 3 primary outcomes of interest: the mean individual step accuracy, the accuracy score per simulation attempt, and the accuracy score for each algorithm. For each simulation step, ChatGPT was scored for correctness (1 point) or incorrectness (0 points). Each simulation was conducted 20 times. RESULTS: ChatGPT's median accuracy for each step was 85% (IQR 40%-100%) for cardiac arrest and 30% (IQR 13%-81%) for bradycardia. ChatGPT's median accuracy over 20 simulation attempts for cardiac arrest was 69% (IQR 67%-74%) and for bradycardia was 42% (IQR 33%-50%). We found that ChatGPT's outputs varied despite consistent input, the same actions were persistently missed, repetitive overemphasis hindered guidance, and erroneous medication information was presented. CONCLUSIONS: This study highlights the need for consistent and reliable guidance to prevent potential medical errors and optimize the application of ChatGPT to enhance its reliability and effectiveness in clinical practice.

Access to technology, internet usage, and online health information-seeking behaviors in a racially diverse, lower-income population.

Background: This study examined access to technology, internet usage, and online health information-seeking behaviors, in a racially diverse, lower-income population. Methods: Data were obtained via a cross-sectional survey of low-income communities in Houston, Los Angeles, and New York between April and August 2023. Binary responses to the following online health information-seeking behaviors, internet and technology access, were examined: using the internet to (i) understand a medical diagnosis, (ii) fill a prescription, (iii) schedule a healthcare appointment, (iv) email communication with a healthcare provider, and (v) access electronic health records and medical notes. Results: 41% of survey respondents identified as non-Hispanic Black individuals, 33% as non-Hispanic White individuals, and 22% as Hispanic individuals. 69% reported a pre-tax annual household income of less than $35,000. 97% reported ownership/access to a smart device; 97% reported access to reliable internet. In the past year, only 59% reported using the internet to better understand their medical diagnosis, 36% reported filling a prescription online, 47% scheduled a medical appointment online, 47% viewed electronic health records online, and 56% emailed healthcare providers. Female sex, higher incomes, and having at least a bachelor's degree were significantly associated with all five online health information-seeking attributes. Conclusion: Despite high technology adoption rates, we observed suboptimal online health information-seeking behaviors. This underutilization has potential adverse implications for healthcare access and use given the documented advantage of HIT. Efforts to increase health information-seeking behaviors should explore the identification of HIT barriers, and patient education to increase familiarity and usage in this population.

Prevalence of youth experiencing homelessness and its association with suicidal thoughts and behaviors: Findings from a population-based study.

Although various studies have examined factors associated with suicidal behaviors among youth, few studies have investigated the association between youth experiencing homelessness (YEH) and suicidal thoughts and behaviors (STBs) using a large nationally representative sample. The objectives of this study were to investigate prevalence of YEH and its association with STBs. Data for this study came from the 2021 Youth Risk Behavior Survey. An analytic sample of 17,033 youth aged 14-18 (51.7 % male) was analyzed using binary logistic regression. Of the 17,033 youth examined, 3 % experienced homelessness during the past 30 days, 21.3 % experienced suicidal ideation, 17.3 % made a suicide plan, and 10.9 % attempted suicide during the past 12 months. Controlling for demographic characteristics and feeling sad or hopeless, YEH was associated with 2.48 times higher odds of experiencing suicidal ideation (AOR=2.48, p<.001), 2.46 times higher odds of making a suicide plan (AOR=2.46, p<.001), and 4.38 times higher odds of making a suicide attempt (AOR=4.38, p<.001). The findings of this study highlight the importance of identifying youth who are at risk of experiencing homelessness to ensure early interventions are put in place to prevent suicidal behaviors.

Proxy use of patient portals on behalf of children: Federally Qualified Health Centers as a case study.

Objective: This study examined the proxy use of patient portals for children in a large Federally Qualified Health Centers (FQHC) network in Texas. Methods: We used de-identified individual-level data of patients, 0-18 years, who had 1+ visits between December 2018 and November 2020. Logistic regression was used to examine patient-, clinic-, and geographic-level factors associated with portal usage by an assumed proxy (i.e. parent or guardian). Results: The proxy portal usage rate increased from 28% in the pre-pandemic months (November 2018-February 2020) to 34% in the pandemic months (March-Nov 2020). Compared to patients 0-5 years, patients aged 6 to 18 years had lower odds of portal usage (6-10 OR: 0.77, p < 0.001; 11-14 OR: 0.62, p < 0.001; 15-18 OR: 0.51, p < 0.001). Minoritized groups had significantly lower odds of portal usage when compared to their non-Hispanic White counterparts (non-Hispanic Black OR: 0.78, p < 0.001; Hispanic OR 0.63, p < 0.001; Asian OR: 0.69, p < 0.001). Having one chronic condition was associated with portal usage (OR: 1.57, p < 0.001); however, there were no significant differences in portal usage between those with none or multiple chronic conditions. Portal usage also varied by service lines, with obstetrics and gynecology (OR: 1.84, p < 0.001) and behavioral health (OR 1.82, p < 0.001) having the highest odds of usage when compared to pediatrics. Having a telemedicine visit was the strongest predictor of portal usage (OR: 2.30, p < 0.001), while residence in zip codes with poor broadband internet access was associated with lower odds of portal usage (OR: 0.97, p < 0.001). Conclusion: While others have reported portal usage rates as high as 64% in pediatric settings, our analysis suggests proxy portal usage rates of 30% in pediatric FQHC settings, with race/ethnicity, age group, and chronic disease status being significant drivers of portal non-usage. These findings highlight the need for appropriate and responsive health information technology approaches for vulnerable populations receiving care in low-resource settings.

Racial and ethnic differences in predictors of participation in an intergenerational social connectedness intervention for older adults.

BACKGROUND: Social connectedness is a key determinant of health and interventions have been developed to prevent social isolation in older adults. However, these interventions have historically had a low participation rate amongst minority populations. Given the sustained isolation caused by the COVID-19 pandemic, it is even more important to understand what factors are associated with an individual's decision to participate in a social intervention. To achieve this, we used machine learning techniques to model the racial and ethnic differences in participation in social connectedness interventions. METHODS: Data were obtained from a social connectedness intervention that paired college students with Houston-area community-dwelling older adults (> 65 yo) enrolled in Medicare Advantage plans. Eligible participants were contacted telephonically and asked to complete the 3-item UCLA Loneliness Scale. We used the following machine-learning methods to identify significant predictors of participation in the program: k-nearest neighbors, logistic regression, decision tree, gradient-boosted decision tree, and random forest. RESULTS: The gradient-boosted decision tree models yielded the best parameters for all race/ethnicity groups (96.1% test accuracy, 0.739 AUROC). Among non-Hispanic White older adults, key features of the predictive model included Functional Comorbidity Index (FCI) score, Medicare prescription risk score, Medicare risk score, and depression and anxiety indicators within the FCI. Among non-Hispanic Black older adults, key features included disability, Medicare prescription risk score, FCI and Medicare risk scores. Among Hispanic older adults, key features included depression, FCI and Medicare risk scores. CONCLUSIONS: These findings offer a substantial opportunity for the design of interventions that maximize engagement among minority groups at greater risk for adverse health outcomes.

Evaluating Predictors of Participation in Telephone-Based Social-Connectedness Interventions for Older Adults: A Dual Machine-Learning and Regression Approach.

Social isolation is a well-documented contributor to poor mental and physical health, and interventions promoting social connectedness have been associated with various health benefits. This study examined predictors of participation in a telephone-based social connectedness intervention for socially isolated older adults. Data were obtained from a social-connectedness intervention that paired college students with Houston-area, community-dwelling adults aged 65 years and older and enrolled in Medicare Advantage plans. We combined machine learning and regression techniques to identify significant predictors of program participation. The following machine-learning methods were implemented: (1) k-nearest neighbors, (2) decision tree and ensembles of decision trees, (3) gradient-boosted decision tree, and (4) random forest. The primary outcome was a binary flag indicating participation in the telephone-based social-connectedness intervention. The most predictive variables in the ML models, with scores corresponding to the 90th percentile or greater, were included in the regression analysis. The predictive ability of each model showed high discriminative power, with test accuracies greater than 95%. Our findings suggest that telephone-based social-connectedness interventions appeal to individuals with disabilities, depression, arthritis, and higher risk scores. scores. Recognizing features that predict participation in social-connectedness programs is the first step to increasing reach and fostering patient engagement.

Population-based assessment of the burden of COVID-19 infection in African countries: a first-year report card and public health implications.

Background: The COVID-19 pandemic constitutes a global health threat and poses a major burden on the African continent. We assessed the real-world burden of COVID-19 infection in African Union (AU) member states to determine the distributional patterns of epidemiological measures during the first 1 year of the pandemic. Methods: This retrospective cross-sectional study utilized COVID-19 data from publicly available data repositories of the African Center for Disease Control and Prevention and Our World in Data for the period February 2020 to January 2021. AU member states were classified into low, medium, and high burdens based on COVID-19 morbidity. We conducted descriptive and inferential analyses of COVID-19-reported cases, deaths, recoveries, active cases, COVID-19 tests, and epidemiological measures that included morbidity and mortality rates, case fatality rate (CFR), and case ratios. Results: A total of 3.21 million cases were reported during the 1-year period, with 2.6 million recoveries, 536,784 cases remaining active, and 77,486 deaths. Most countries (49.1%, n = 26) in AU experienced a low burden of COVID-19 infection compared to 28.3% (n = 15) with medium burden and 22.6% (n = 12) with high burden. AU nations with a high burden of the disease were mainly in the northern and southern regions. South Africa recorded the highest number of cases (1.31 million), followed by Morocco with 457,625 and Tunisia with 175,065 cases. Correspondently, death tolls for these countries were 36,467, 7888, and 5528 deaths, respectively. Of the total COVID-19 tests performed (83.8 million) during the first 1 year, 62.43% were from high-burden countries. The least testing occurred in the medium-burden (18.42%) countries. The overall CFR of AU was 2.21%. A morbidity rate of 327.52/105 population and mortality rate of 5.96/105 population were recorded during the first 1-year period with significant variations (p < 0.0001) across burden levels. Continental morbidity and mortality rates of 17,359/105 and 315.933/105 populations were recorded with significant correlation (r = 0.863, p < 0.0001) between them and variations across selected epidemiological measures by COVID-19 burden levels. Conclusion: Understanding the true burden of the disease in AU countries is important for establishing the impact of the pandemic in the African continent and for intervention planning, preparedness, and deployment of resources during COVID-19 surges and future pandemics.

The Effects of COVID-19 Lockdown on Social Connectedness and Psychological Distress in U.S. Adults with Chronic Diseases.

Lockdown measures enacted in 2020 to control the spread of COVID-19 led to increases in the prevalence of mental health problems. Due to their high-risk status, individuals with chronic diseases may be at increased risk and disproportionately adversely affected by the COVID-19 pandemic. The investigators examined associations between having a high-risk chronic condition, social connectedness, and general distress and COVID-19-specific distress among U.S. adults during the COVID-19 lockdown. Baseline measures of a longitudinal survey collected at the beginning of the pandemic (April to June 2020) were analyzed to identify factors associated with loss of social connectedness from pre- to post-lockdown. The associations between social connectedness and both general and COVID-19-specific psychological distress were adjusted for certain high-risk chronic illnesses and interaction effects. The sample available for analysis included 1354 subjects (262 high-risk chronic diseases and 1092 without chronic illness). Those reporting the loss of social connectedness were younger (median = 39 vs. 42) and more likely to be unemployed because of the pandemic (19.4% vs. 11.0%). Adjustment for interaction demonstrated a stronger negative association between social connectedness change and the psychosocial impact of COVID-19 for those with high-risk illness(es) (change in connectedness*chronic illness OR = 0.88, 95%CI: 0.79-0.98, p = 0.020). These findings inform our understanding of the distribution and intersection of responses to public health lockdown orders in the U.S. and build further evidence of the importance of social connectedness on psychological distress.

Rethinking access to care: A spatial-economic analysis of the potential impact of pharmacy closures in the United States.

Data chronicling the geo-locations of all 61,589 pharmacies in the U.S. (from the Homeland Infrastructure Foundation-Level Data (HIFLD) Open Data interface, updated on April 2018) across 215,836 census block groups were combined with Medically Underserved Areas (MUAs) information, and the Centers for Disease Control and Prevention's Social Vulnerability Index (CDC-SVI). Geospatial techniques were applied to calculate the distance between the center of each census block and the nearest pharmacy. We then modeled the expected additional travel distance if the nearest pharmacy to the center of a census block closed and estimated additional travel costs, CO2 emissions, and lost labor productivity costs associated with the additional travel. Our findings revealed that MUA residents have almost two times greater travel distances to pharmacies than non-MUAs (4,269 m (2.65 mi) vs. 2,388 m (1.48 mi)), and this disparity is exaggerated with pharmacy closures (107% increase in travel distance in MUAs vs. 75% increase in travel distance in non-MUAs). Similarly, individuals living in MUAs experience significantly greater average annual economic costs than non-MUAs ($34,834 ± $668 vs. $22,720 ± $326). Our findings suggest the need for additional regulations to ensure populations are not disproportionately affected by these closures and that there is a significant throughput with community stakeholders before any pharmacy decides to close.

Comparing In-Person Only, Telemedicine Only, and Hybrid Health Care Visits Among Older Adults in Safety-Net Clinics.

Introduction: Older adults face challenges in seeking health care. This study examined factors associated with in-person only versus telemedicine only versus hybrid health care visits among adults 65+ in safety-net clinics. Methods: Data were obtained from a large Texas-based Federally Qualified Health Center (FQHC) network. The dataset included 12,279 appointments for 3914 unique older adults between March and November 2020. The outcome of interest was a 3-level indicator of telemedicine visits: in-person visits only, telemedicine visits only, and hybrid (in person + telemedicine) visits during the study period. We used a multinomial logit model adjusting for patient level characteristics to assess the strength of the relationships. Results: Compared to their white counterparts, black and Hispanic older adults were significantly likely to have telemedicine only visits versus in-person only visits (black RRR: 0.59, 95% confidence interval [CI]: 0.41-0.86; Hispanic RRR: 0.46, 95% CI: 0.36-0.60). However, there were no significant racial and ethnic differences in hybrid utilization (black RRR: 0.91, 95% CI: 0.67-1.23; Hispanic RRR: 0.86, 95% CI: 0.70-1.07). Discussion: Our findings suggest that hybrid opportunities may bridge racial and ethnic disparities in access to care. Clinics should consider building capacity for both in-person and telemedicine opportunities as complementary strategies.

Trends in Mental Health Utilization Before and During the COVID-19 Pandemic: Federally Qualified Health Centers As a Case Study.

This study examined differential mental health utilization patterns before and during the COVID-19 pandemic. Data were obtained from 12 Federally Qualified Health Center (FQHC)-behavioral health clinics and included 65,561 visits between February 2019 and November 2020 for adults aged 18-64 years. To allow for a year-over-year comparison, the pre-COVID-19 period was flagged as visits between February 2019 and November 2019 and the peri-COVID-19 period as visits between February 2020 and November 2020. A difference-in-difference model with Poisson regression was used to predict racial/ethnic differences in the number of visits between the pre- and peri-COVID-19 periods. Overall, the average number of visits per patient increased from 5.45 visits in the pre-COVID period to 5.78 visits in the peri-COVID-19 period. Hispanics had +0.6 visits, Blacks had +0.3 visits, and other racial groups had +0.9 visits during the peri-COVID-19 period than the pre-COVID-19 period. In contrast, Whites (-0.6 visits) and Asians (-1.7 visits) were less likely to use mental health services in these FQHC clinics in the peri-COVID-19 period as compared with the pre-COVID-19 period. Peri-COVID-19 utilization rates were significantly higher for virtual visits (incident-rate ratio [IRR] = 1.15, P < 0.01) and residence in a metropolitan area (IRR = 1.14, P < 0.01), but lower for persons aged 55+ years (IRR = 0.92, P < 0.01) and males (IRR = 0.87, P < 0.01). Racial/ethnic minority patients, except Asians, were more likely to use mental health services during the COVID-19 pandemic than in the preceding year. This may be attributable to policy changes such as the CARES Act, which expanded health care access options to include telemedicine.

Measuring Historic and Longitudinal Social Vulnerability in Disaster-Prone Communities: A Modification to the Centers for Disease Control and Prevention Social Vulnerability Index (CDC-SVI).

OBJECTIVE: Researchers have developed numerous indices to identify vulnerable sub-populations. The Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) is the most common and highly serviceable, but it has some temporal limitations considering that some variables used in calculating the CDC-SVI were not available before 1980. Changes in societal composition over time can impact social vulnerability. This study defines an alternate, but similar, index that could serve as a surrogate for the CDC-SVI without the temporal limitations. METHODS: An inventory analysis of the historical census data (1960-2018) was used to develop a Modified SVI that allows for historic analyses. To consider the chronic effect of social vulnerabilities, a longitudinal SVI was introduced to elucidate how a community's multidimensional experiences exacerbate vulnerability to disaster events, such as the COVID-19 pandemic. We use Harris County, Texas, in this case study to examine how the Modified SVI performs against the original CDC-SVI. RESULTS: This Modified SVI was used to generate historical maps, find temporal patterns, and inform a longitudinal SVI measure. The results showed a good agreement among the developed indices and the CDC-SVI. We also observed satisfactory performance in identifying the areas that are most vulnerable to the COVID-19 pandemic. CONCLUSIONS: The Modified SVI overcomes temporal limitations associated with the CDC-SVI, and the longitudinal SVI captures a community's multidimensional experiences that exacerbate a community's vulnerability to disaster events over time.

Coping With Disasters and Pandemics Through Experience and Community: How African American Older Adults Navigate Disaster Planning, Response, and Recovery.

OBJECTIVE: Studies have reported that minorities are disproportionately impacted by the COVID-19 pandemic. Few studies have elucidated the lived experiences of African American older adults, and the resiliency displayed in combatting the COVID-19 pandemic and other disasters. METHODS: This study used 4 recorded focus groups with 26 African American older adults who have spent most of their lives living in Houston, Texas to assess safety, economic, and health concerns related to the pandemic and similarities or differences with other types of disasters that are specific to Houston/ the Gulf Region of Texas, such as Hurricane Harvey. RESULTS: Key themes emerged from the thematic analysis: 1) previous disasters provided important coping and preparation skills, although each occurrence was still a major stressor, 2) while telehealth was a significant benefit, regular health maintenance and chronic disease management were not completed during the COVID-19 pandemic, 3) information from the federal and state authorities were inconsistent and spurred fear and anxiety, 4) participants experienced few to no disruptions to their income but were heavily called on to support family members, and 5) participants experienced anxiety and isolation, but many used existing social connections to cope. CONCLUSIONS: These findings demonstrate how African American older adults navigate disaster response and recovery through experience and community. Providing unambiguous information to older adults could prove useful in preparing for future disaster events and coping with disasters.

Examining Black and Hispanic physicians and other healthcare providers' attitudes toward the COVID-19 vaccine.

OBJECTIVES: Recognizing that the voice delivering the message is as important as the information being shared, we examined vaccine perceptions and willingness to encourage patients to obtain COVID-19 vaccinations among Black and Hispanic healthcare providers. METHODS: We conducted a cross-sectional, online survey of Black and Hispanic healthcare providers who were members of the National Medical Association (NMA), National Hispanic Medical Association (NHMA), and National Pharmaceutical Association (NPhA) between January 11 - March 3, 2021, shortly after emergency use authorization (EUA) for the Pfizer and Moderna COVID-19 vaccines. Three multivariable logistic regression models were used to determine factors associated with the willingness to encourage COVID-19 vaccination. RESULTS: The analytic sample consisted of 542 fully completed surveys. Pharmacists reported intent to take the vaccine (75.0% "as soon as you can" vs 91.4% for MD/DOs; p<0.001) and encouraged patients to get vaccinated (78.6% vs 91.0% for MD/DOs; p = 0.01). Providers in a suburban practice location were less likely to recommend vaccines to patients (OR=0.43, 95%CI: 0.22-0.87) and personal family (OR=0.45, 95%CI: 0.22-0.92) compared to those practicing in urban areas. Providers over age 45 were also more likely to report intent to take the vaccine themselves as soon as it was available (OR=3.72, 95%CI: 1.30-10.64). CONCLUSIONS: This is likely the first cross-sectional study in the United States demonstrating the substantial vaccine confidence among Black and Hispanic healthcare providers who serve minoritized communities that have borne the greatest risk of adverse COVID-related outcomes.

Self-perceived disaster preparedness in minority older adults: A cross-sectional study.

OBJECTIVE: Evidence suggests that people of color, especially African Americans and non-White Hispanics, residing in low-income communities are the most vulnerable to natural disasters. This study assessed individual level of self-perceived disaster preparedness, disaster response actions, and sociodemographic predictors of disaster preparedness among older minority adults in Houston, Texas. METHOD: Working with Houston-area community-based organizations and senior-living centers, a cross-sectional survey, available in English and Spanish, was disseminated between November 2020 and January 2021. PARTICIPANTS: Five hundred and twenty-two older minority adults aged 55+ completed the electronic survey. MAIN OUTCOME MEASURE(S): The main outcome measure was the level of self-perceived preparedness regarding emergencies and disastersie, prepared vs not prepared-among the study participants. RESULTS: Overall, about 58 percent of older minority adults did not perceive themselves to be prepared. Compared to individuals reporting annual incomes below $25,000, individuals reporting annual incomes between $25,000 and $74,999 were more likely to report being prepared [odds ratio (OR) = 2.28, 95 percent confidence interval (CI) = 1.29, 4.05]. Individuals who tested positive or had a close family member test positive for COVID-19 experienced 2.16 times higher odds of having self-perceived disaster preparedness than those who did not [OR = 2.16, 95 percent CI = 1.37, 3.42]. None of the other covariates were statistically significant. CONCLUSIONS: While we observed no differences in self-perceived disaster preparedness between African American and Hispanic older adults, our findings suggest the importance of prior experience/exposure to previous disasters and the role of socioeconomic status in self-perceived disaster preparedness in minority older adults.

Assessment of Unmet Health-Related Social Needs Among Patients With Mental Illness Enrolled in Medicare Advantage.

Importance: A large body of literature has found associations between unmet health-related social needs (HRSNs) and adverse mental health outcomes. A comparative analysis of the risks associated with HRSNs among patients with varying severity of mental illness and an assessment of how these risks compare with those of individuals without mental illness are needed. Objective: To examine the prevalence and risks of HRSNs among patients with serious and persistent mental illness (SPMI), patients with mental health diagnoses but no serious and persistent mental illness (non-SPMI), and patients with both SPMI and non-SPMI compared with individuals without mental illness. Design, Setting, and Participants: This retrospective cohort study used data from the Accountable Health Communities HRSN Screening Tool surveys, which target a nationally representative sample of Medicare Advantage members of a large payer (Humana Inc). The surveys were conducted between October 16, 2019, and February 29, 2020. Of the initial 329 008 eligible Medicare Advantage enrollees, 70 273 responded to the survey (21.4% response rate). Of those, 56 081 respondents (79.8%) had complete survey responses and were included in the final analytic sample. Main Outcomes and Measures: Outcomes of interest included 7 HRSNs (financial strain, food insecurity, housing instability, housing quality, severe loneliness, transportation problems, and utility affordability) based on responses to the survey. The major independent variable was the presence of mental illness up to 12 months preceding the date of survey completion. Codes indicating mental illness listed as the primary, principal, or secondary diagnoses of a patient's inpatient or outpatient medical claims data were identified, and participants were grouped into 4 cohorts: SPMI, non-SPMI, SPMI plus non-SPMI, and no mental illness. Results: Among 56 081 older adults, the mean (SD) age was 71.31 (8.59) years; 32 717 participants (58.3%) were female, and 43 498 (77.6%) were White. A total of 21 644 participants (38.6%) had at least 1 mental illness diagnosis in the past year, 30 262 (54.0%) had an HRSN, and 14 163 (25.3%) had both mental illness and an HRSN. Across all specific HRSNs, the odds of experiencing the respective HRSN was most substantial for those with SPMI plus non-SPMI vs those with only non-SPMI or SPMI. The HRSN with the largest risk differences among the study cohorts was severe loneliness; compared with the cohort without mental illness, the non-SPMI cohort had 2.07 times higher odds (95% CI, 1.84-2.32; P < .001), the SPMI cohort had 3.35 times higher odds (95% CI, 3.03-3.71; P < .001), and the SPMI plus non-SPMI cohort had 5.13 times higher odds (95% CI, 4.68-5.61; P < .001) of severe loneliness. Conclusions and Relevance: In this study, the increased risk of having HRSNs associated with SPMI, alone or in combination with non-SPMI, emphasizes the need for more targeted interventions to address social needs in this vulnerable population.

Increased Revenue From Averted Missed Appointments Following Telemedicine Adoption at a Large Federally Qualified Health Center.

This study examined savings from averted missed appointments following telemedicine adoption. Data were obtained from a large Federally Qualified Health Center in Texas during the early pandemic months. Patient encounters fell into one of three categories: (1) in-person visit, (2) telemedicine alone with no support team engagement, and (3) telemedicine with previsit support team engagement for device and connectivity testing. Our findings revealed that in-person visits had a 21% missed appointment rate compared to 19% for telemedicine alone and 15% for telemedicine with previsit support. Translating the reductions following both telemedicine encounters into net reimbursement, telemedicine alone saved the Federally Qualified Health Center $16 444 per month, while telemedicine + support team reduced missed appointments and saved the clinic an additional $29 134. The revenue from averted missed appointments totaled $45 578 per month. In conclusion, telemedicine reduced missed appointments, and these averted missed appointments translated into cost-savings. Savings were more pronounced with the implementation of a support team that conducted previsit device and connectivity testing.