California Health and Human Services Agency

Introduction: Climate change is associated with increasing frequency and severity of extreme weather events, but little is known about the impact of disaster exposure on people living with dementia (PLWD). PLWD may experience increased confusion, disorientation, anxiety, and paranoia during disasters, potentially leading to the inappropriate use of psychotropic medications as a form of symptom management. This study examined new psychotropic prescription medications or changes to existing prescriptions among US Medicare beneficiaries with a dementia diagnosis following hurricane exposure. Methods: This study used a retrospective cohort design with administrative claims data from Medicare beneficiaries diagnosed with dementia. The study population included 71,401 beneficiaries residing in counties exposed to Hurricanes Harvey, Irma, or Florence between 2017 and 2018. Exposure to major hurricanes (Harvey, Irma, and Florence) was determined based on Federal Emergency Management Agency disaster declarations for affected counties. The primary outcome was the rate of new psychotropic prescriptions or changes to existing prescriptions within 12 months post-hurricane exposure, compared between beneficiaries in exposed versus unexposed counties. Results: PLWD exposed to hurricanes had a 10% higher rate of starting new antipsychotic prescriptions compared to those in unexposed counties (Incidence Rate Ratio [IRR]: 1.10; 95% CI, 1.04-1.17). Exposure to Hurricane Harvey was associated with a 20% higher rate of new antipsychotic prescriptions (IRR: 1.20; 95% CI, 1.07-1.36), while no significant changes were observed following Hurricanes Irma (IRR: 0.99; 95% CI, 0.90-1.08) or Florence (IRR: 0.92; 95% CI, 0.80-1.05). Conclusion: Exposure to Hurricane Harvey was associated with increased rates of new antipsychotic prescriptions among PLWD, suggesting that tailored disaster preparedness and response strategies are needed to address the unique needs of this vulnerable population. Understanding patterns in psychotropic medication prescribing among PLWD before, during, and after disasters is essential to improving disaster readiness and reducing inappropriate medication use.

The authors have no conflicts of interest to disclose.

Spectral correction is commonly applied to CdTe systems while current standard practice assumes the effects are negligible for cSi system energy yield. In this work, we quantify the difference in energy at the inverter level by applying spectral correction using First Solar model for several sites using TMY and timeseries weather data. We demonstrate that on average, a spectral correction application can lead to an energy yield difference of 0.4% at the inverter. We also review the spectral correction uncertainty from the First Solar model against the value calculated from FARMS-NIT spectra and measured quantum efficiency.

BackgroundMedications for opioid use disorder (MOUD), such as methadone and buprenorphine, are the gold standard for opioid use disorder (OUD) treatment. Owing to various barriers, MOUD access and retention are low in the United States. The internet presents a digital solution to mitigate barriers, but a comprehensive and reliable resource is lacking. We present a user-friendly, web-based resource, the MOUD Hub, that provides reliable information on MOUD.ObjectiveThis study aims to assess the safety, acceptability, feasibility of dissemination, and reach of the MOUD Hub using focus groups and advertising on 1 key search engine and 1 social media platform.MethodsThis protocol describes the development of the MOUD Hub and the descriptive observational feasibility study that will be undertaken. The MOUD Hub uses motivational interviewing principles to guide users through the stages of change. The website provides evidence-based information from national health and substance use agencies, harm reduction organizations, and peer-reviewed literature. First, pilot focus groups with 10 graduate students who have lived experience with OUD will be conducted to provide feedback on safety concerns. Then, focus groups with 20-30 potential MOUD Hub users (eg, people with OUD with and without MOUD experience, friends and family, and health care providers) will be conducted to assess safety, acceptability, reach, and usability. Data will be analyzed using inductive thematic analysis. The website will be advertised on Google and MOUD-specific Reddit forums to assess dissemination, reach, and user acceptability based on the total user volume, sociodemographic characteristics, pop-up survey responses, and 1-year engagement patterns. This information will be collected through Google Analytics. Potential differences between users from Google and Reddit will be assessed.ResultsThe MOUD Hub will be launched in January 2025. Data collected from 5 focus groups (approximately 30-40 participants) will be used to improve the website before launching it. There is no target sample size for the second stage of the study as it aims to assess dissemination feasibility and reach. Data will be collected for a year, analyzed every 3 months, and used to improve the website.ConclusionsThe MOUD Hub offers an innovative theory-based approach, tailored to people with OUD and their family and friends, to increase access to and retention in MOUD treatment in the United States and provides broader harm reduction resources for those not currently in a position to receive treatment or those at risk of resuming illicit opioid use. Findings from this feasibility phase will serve to better tailor the MOUD Hub. After modifying the website based on our findings, we will use a randomized controlled trial to assess its efficacy in increasing MOUD access and retention, contributing to growing research on web-based interventions for OUD.International Registered Report Identifier (IRRID)PRR1-10.2196/57065

BackgroundSub-optimal HbA1c control is a driver of disparities in diabetes outcomes among Hispanic patients. Differences in medication adherence may underlie racial/ethnic differences in HbA1c level.ObjectiveTo examine the relationship between medication adherence and disparities in HbA1c level among Hispanic patients, relative to other racial/ethnic groups, obtaining care in the University of California Health System (UC Health).DesignThis study used clinical, administrative, and prescription dispensing data (January–December 2021) derived from the electronic health records of 5 Academic Medical Centers in UC Health, and linear regression models (LRMs) to conduct a cross-sectional analysis of the association between medication adherence, race/ethnicity, and HbA1c level. Adjusted LRMs were run with and without the measure of medication adherence to assess this relationship.ParticipantsPatients with a UC Health primary care physician (PCP), with ≥ 1 PCP visit within the last 3 years, ages 18–75, reporting Asian, Hispanic, or White race/ethnicity, and who had ≥ 2 encounters with an ICD diagnosis of diabetes or had a prescription for a diabetes medication within the last 2 years, as of 12/31/21 (N = 27, 542; Asian = 6253, Hispanic = 7216, White = 14,073).Main MeasuresOur measure of medication adherence was the proportion of days covered (PDC) for diabetes medications in 2021. Our outcome was the most recent HbA1c value.Key ResultsIn the LRM excluding the PDC, Hispanic ethnicity was positively associated with HbA1c level (β = 0.31, p = < 0.001). In the LRM model including PDC, PDC was negatively associated with HbA1c level (β = − 0.18, p = < 0.001). However, the positive relationship between Hispanic ethnicity and HbA1c level did not change (β = 0.31, p = < 0.001).ConclusionsThe findings of this study suggest that the relationship between Hispanic ethnicity, HbA1c level, and factors outside of medication adherence should be explored among primary care patients receiving care in Academic Medical Centers.

This cross-sectional study evaluates the association of a cap on monthly out-of-pocket spending on high-cost drugs with use of these drugs and out-of-pocket spending in California in 2015 and 2016.

Evidence suggests an association between rurality and decreased life expectancy. To determine whether rural hospitals have higher hospital mortality, given that very sick patients may be transferred to regional hospitals. In this ecologic study, we combined Medicare hospital mortality ratings (N = 1267) with US census data, critical access hospital classification, and National Center for Health Statistics urban-rural county classifications. Ratings included mortality for coronary artery bypass grafting, stroke, chronic obstructive pulmonary disease, heart attack, heart failure, and pneumonia across 277 California hospitals between July 2011 and June 2014. We used generalized estimating equations to evaluate the association of urban-rural county classifications on mortality ratings. Unfavorable Medicare hospital mortality rating "worse than the national rate" compared with "better" or "same." Compared with large central "metro" (metropolitan) counties, hospitals in medium-sized metro counties had 6.4 times the odds of rating "worse than the national rate" for hospital mortality (95% confidence interval = 2.8-14.8, p < 0.001). For hospitals in small metro counties, the odds of having such a rating were 3.7 times greater (95% confidence interval = 0.7-23.4, p = 0.12), although not statistically significant. Few ratings were provided for rural counties, and analysis of rural counties was underpowered. Hospitals in medium-sized metro counties are associated with unfavorable Medicare mortality ratings, but current methods to assign mortality ratings may hinder fair comparisons. Patient transfers from rural locations to regional medical centers may contribute to these results, a potential factor that future research should examine.