Excess prevalence of preexisting chronic conditions in older adults with incident epilepsy.

OBJECTIVE: Prior studies have examined chronic conditions in older adults with prevalent epilepsy, but rarely among those with incident epilepsy. Identifying the chronic conditions with which older adults present at epilepsy incidence assists with the evaluation of disease burden in this patient population and informs coordinated care development. The aim of this study was to identify preexisting chronic conditions with excess prevalence in older adults with incident epilepsy compared to those without. METHODS: Using a random sample of 4 999 999 fee-for-service Medicare beneficiaries aged >65 years, we conducted a retrospective cohort study of epilepsy incidence in 2019. Non-Hispanic Black and Hispanic beneficiaries were oversampled. We identified preexisting chronic conditions from the 2016-2018 Medicare Beneficiary Summary Files and compared chronic condition prevalence between Medicare beneficiaries with and without incident epilepsy in 2019. We characterized variations in preexisting excess chronic condition prevalence by age, sex, and race/ethnicity, adjusting for the racial/ethnic oversampling. RESULTS: We observed excess prevalence of most preexisting chronic conditions in beneficiaries with incident epilepsy (n = 20 545, weighted n = 19 631). For stroke, for example, the adjusted prevalence rate ratio (APRR) was 4.82 (99% CI:4.60, 5.04), meaning that, compared to those without epilepsy, beneficiaries with incident epilepsy in 2019 had 4.82 times the stroke prevalence. Similarly, beneficiaries with incident epilepsy had a higher prevalence rate for preexisting neurological conditions (APRR = 3.17, 99% CI = 3.08-3.27), substance use disorders (APRR = 3.00, 99% CI = 2.81-3.19), and psychiatric disorders (APRR = 1.98, 99% CI = 1.94-2.01). For most documented chronic conditions, excess prevalence among beneficiaries with incident epilepsy in 2019 was larger for younger age groups compared to older age groups, and for Hispanic beneficiaries compared to both non-Hispanic White and non-Hispanic Black beneficiaries. SIGNIFICANCE: Compared to epilepsy-free Medicare beneficiaries, those with incident epilepsy in 2019 had a higher prevalence of most preexisting chronic conditions. Our findings highlight the importance of health promotion and prevention, multidisciplinary care, and elucidating shared pathophysiology to identify opportunities for prevention.

Functional Status is Key to Long-term Survival in Emergency General Surgery Conditions.

INTRODUCTION: Emergency General Surgery (EGS) conditions in older patients constitutes a substantial public health burden due to high morbidity and mortality. We sought to utilize a supervised machine learning method to determine combinations of factors with the greatest influence on long-term survival in older EGS patients. METHODS: We identified community dwelling participants admitted for EGS conditions from the Medicare Current Beneficiary Survey linked with claims (1992-2013). We categorized three binary domains of multimorbidity: chronic conditions, functional limitations, and geriatric syndromes (such as vision or hearing impairment, falls, incontinence). We also collected EGS disease type, age, and sex. We created a classification and regression tree (CART) model to identify groups of variables associated with our outcome of interest, three-year survival. We then performed Cox proportional hazards analysis to determine hazard ratios for each group with the lowest risk group as reference. RESULTS: We identified 1960 patients (median age 79 [interquartile range [IQR]: 73, 85], 59.5% female). The CART model identified the presence of functional limitations as the primary splitting variable. The lowest risk group were patient aged ≤81 y with biliopancreatic disease and without functional limitations. The highest risk group was men aged ≥75 y with functional limitations (hazard ratio [HR] 11.09 (95% confidence interval [CI] 5.91-20.83)). Notably absent from the CART model were chronic conditions and geriatric syndromes. CONCLUSIONS: More than the presence of chronic conditions or geriatric syndromes, functional limitations are an important predictor of long-term survival and must be included in presurgical assessment.

Palliative care and aggressive interventions after falling: A Nationwide Inpatient Sample analysis.

OBJECTIVE: The purpose of this study is to identify whether there is an opportunity for improvement to provide palliative care services after a serious fall. We hypothesized that (1) palliative care services would be utilized in less than 10% of patients over the age of 65 who fall and (2) more than 20% of patients would receive aggressive life-sustaining treatments (LSTs) prior to death. METHODS: Using the 2017 Nationwide Inpatient Sample, we identified patients who were admitted to the hospital with a fall (ICD-10 W00-W19) and were hospitalized at least two days with valid discharge data. Palliative care services (Z51.5) or LSTs (cardiopulmonary resuscitation, ventilation, reintubation, tracheostomy, feeding tube placement, vasopressors, transfusion, total parenteral nutrition, and hemodialysis) were identified with ICD-10 codes. We examined the use of palliative care or LSTs by discharge destination (home, facility, and death). Logistic regression was used to identify factors associated with palliative care. RESULTS: In total, 155,241 patients were identified (median 82 years old, interquartile range 74-88); 2.5% died in hospital, and 69.4% were transferred to a facility. Palliative care occurred in 4.5% of patients, and LST occurred in 15.1%. Patients who died were significantly more likely to have had palliative care (50.1% vs. 3.4% of home or facility discharges) and were more likely to have an LST [53.0% vs. 9.8% (home) vs. 15.9% (facility)]. Palliative care was associated with both death [adjusted odds ratio (AOR) 19.84, 95% confidence interval (CI) 18.39-21.41, p < 0.001] and LST (AOR 1.36, 95% CI 1.27-1.46, p < 0.001). SIGNIFICANCE OF RESULTS: Palliative care is associated with both death and LST, suggesting that physicians use palliative care as a last resort after aggressive measures have been exhausted. Patients who fall would likely benefit from the early use of palliative care to align future goals of care.

Markers of Quality Care for Newly Diagnosed People With Epilepsy on Medicaid.

BACKGROUND: For newly diagnosed people with epilepsy (PWE), proper treatment is important to improve outcomes, yet limited data exist on markers of quality care. OBJECTIVE: Examine markers of quality care for newly diagnosed PWE. METHODS: Using Medicaid claims data (2010-2014) for 15 states we identified adults 18-64 years of age diagnosed with incident epilepsy in 2012 or 2013. We built 5 sequential logistic regression models to evaluate: (1) seeing a neurologist; (2) diagnostic evaluation; (3) antiepileptic medication adherence; (4) serum drug levels checked; and (5) being in the top quartile of number of negative health events (NHEs). We adjusted for demographics, comorbidities, county-level factors, and the outcomes from all prior models. RESULTS: Of 25,663 PWE, 37.3% saw a neurologist, with decreased odds for those of older age, those residing in counties with low-density of neurologists, and certain race/ethnicities; about 57% of PWE received at least 1 diagnostic test; and nearly 62% of PWE were adherent to their medication. The most common comorbidities were hypertension (37.1%) and psychoses (26.9%). PWE with comorbidities had higher odds of seeing a neurologist and to have NHEs. Substance use disorders were negatively associated with medication adherence and positively associated with high NHEs. CONCLUSIONS: There are notable differences in demographics among people with incident epilepsy who do or do not see a neurologist. Differences in NHEs persist, even after controlling for neurologist care and diagnostic evaluation. Continued attention to these disparities and comorbidities is needed in the evaluation of newly diagnosed PWE.

Health-Related Social Needs and Increased Readmission Rates: Findings from the Nationwide Readmissions Database.

BACKGROUND: While health-related social needs (HRSN) are known to compromise health, work to date has not clearly demonstrated the relationship between clinically acknowledged social needs, via ICD-10 Z-codes, and readmission. OBJECTIVE: Assess the rate of 30-, 60-, and 90-day readmission by the level of ICD-10-identified social need. In addition, we examined the associations between demographics, social need, hospital characteristics, and comorbidities on 30-day readmission. DESIGN: Retrospective study using the 2017 Nationwide Readmission Database PARTICIPANTS: We identified 5 domains of HRSN from ICD-10 diagnosis codes including employment, family, housing, psychosocial, and socioeconomic status (SES) and identified how many and which an individual was coded with during the year. MAIN MEASURES: The proportion of patients with 30-, 60-, and 90-day readmission stratified by the number of HRSN domains with a multivariable logistic regression to examine the relationship between the number/type of and readmission adjusting for sex, age, payer, hospital characteristics, functional limitations, and comorbidities. KEY RESULTS: From 13,217,506 patients, only 2.4% had at least one HRSN diagnosis. Among patients without HRSN, 11.5% had a 30-day readmission, compared to 27.0% of those with 1 domain, increasing to 63.5% for patients with codes in 5 domains. Similar trends were observed for 60- and 90-day readmission; 78.7% of patients with documented HRSN in all 5 domains were hospitalized again within 90 days. The adjusted odds ratio for readmission for individuals with all 5 domains was 12.55 (95% CI: 9.04, 17.43). Housing and employment emerged as two of the most commonly documented HRSN, as well as having the largest adjusted odds ratio. CONCLUSIONS: There is a dose-response relationship between the number of HRSN diagnoses and hospital readmission. This work calls attention to the need to develop interventions to reduce readmissions for those at social risk and demonstrates the significance of ICD-10 Z-codes in health outcomes studies.

Trends in Pulmonary Critical Care Fellowship Applications and Match Rates before and after the Onset of the COVID-19 Pandemic.

Background: Because of the coronavirus disease (COVID-19) pandemic, fellowship interviews for pulmonary disease and critical care medicine (PCCM) switched from an in-person to virtual interview format. Objective: This study aimed to examine the changes that resulted from this switch (appointment year 2021 and beyond) for both the individual applicants and the match process as a whole. Methods: This cross-sectional study used longitudinal data from the Electronic Residency Application Service and the National Resident Matching Program from appointment years 2017 to 2022. Data from the Electronic Residency Application Service included the number of programs applicants applied to, and National Resident Matching Program data included the number of fellowship positions available, number entering the match, match rate, and the number of applicants who matched within the same region/program as their core residency training program. Descriptive and summary statistics and unadjusted linear models were used to identify if trends appeared in post-COVID-19 appointment years (2021 and beyond). Results: The number of PCCM positions increased by 33 (95% confidence interval, 26.2, 39.8) yearly between 2017 and 2022, with almost twice as many applicants (62.6; 95% CI confidence interval, 37.8, 87.4) entering the PCCM fellowship match during that same period. There was a decrease in the percentage of applicants matched each year, a trend unchanged before and after COVID-19, by an average of -2.15%. Comparing before and after COVID-19 appointment years, there was no significant change in same-region or same-program matches. Conclusion: Our analysis shows steadily rising interest in application rates for PCCM fellowships through the onset of the pandemic. However, a lack of proportionate increase in fellowship positions led to a decrease in overall match rates for applicants. To mitigate this, an increase in PCCM fellowship positions should be considered, and surveillance of these trends should continue.

Mortality burden from variation in provision of surgical care in emergency general surgery: a cohort study using the National Inpatient Sample.

Background: The decision to undertake a surgical intervention for an emergency general surgery (EGS) condition (appendicitis, diverticulitis, cholecystitis, hernia, peptic ulcer, bowel obstruction, ischemic bowel) involves a complex consideration of factors, particularly in older adults. We hypothesized that identifying variability in the application of operative management could highlight a potential pathway to improve patient survival and outcomes. Methods: We included adults aged 65+ years with an EGS condition from the 2016-2017 National Inpatient Sample. Operative management was determined from procedure codes. Each patient was assigned a propensity score (PS) for the likelihood of undergoing an operation, modeled from patient and hospital factors: EGS diagnosis, age, gender, race, presence of shock, comorbidities, and hospital EGS volumes. Low and high probability for surgery was defined using a PS cut-off of 0.5. We identified two model-concordant groups (no surgery-low probability, surgery-high probability) and two model-discordant groups (no surgery-high probability, surgery-low probability). Logistic regression estimated the adjusted OR (AOR) of in-hospital mortality for each group. Results: Of 375 546 admissions, 21.2% underwent surgery. Model-discordant care occurred in 14.6%; 5.9% had no surgery despite a high PS and 8.7% received surgery with low PS. In the adjusted regression, model-discordant care was associated with significantly increased mortality: no surgery-high probability AOR 2.06 (1.86 to 2.27), surgery-low probability AOR 1.57 (1.49 to 1.65). Model-concordant care showed a protective effect against mortality (AOR 0.83, 0.74 to 0.92). Conclusions: Nearly one in seven EGS patients received model-discordant care, which was associated with higher mortality. Our study suggests that streamlined treatment protocols can be applied in EGS patients as a means to save lives. Level of evidence: III.

The Impact of Gardening on Dietary Inflammation: Mixed-Effect Models and Propensity Score Analyses.

Introduction: Gardening has been found to increase vegetable intake and reduce BMI; this suggests that it may improve diets by lowering inflammatory content. The goal of this study goal was to evaluate the effect of gardening on Dietary Inflammatory Index scores. Methods: Longitudinal data were collected annually between 2015 and 2018 from adults in low-income, urban neighborhoods of Cleveland and Columbus, Ohio. The authors measured the association between gardening and Dietary Inflammatory Index in the full data set using multivariable mixed-effect models with a random intercept for participant (Model 1; n=409). To further explore potential causation, the author used propensity score analyses in a subset of the data by building a 1-to-1 matched model (Model 2; n=339). Results: Of 409 adults, 30.3% were gardeners with Dietary Inflammatory Index scores ranging from -6.228 to +6.225. Participating in gardening was associated with lower Dietary Inflammatory Index scores in the mixed-effects model (-0.45; 95% CI= -0.85, -0.04; Model 1) and the 1-to-1 matched model (-0.77; 95% CI= -1.40, -0.14; Model 2). Conclusions: The analyses indicate that gardeners had lower Dietary Inflammatory Index scores than nongardeners, implying lower diet-driven inflammation. These findings highlight the potential for a causal relationship between gardening and Dietary Inflammatory Index, which should be confirmed in future studies. If this relationship is validated, strategies to increase gardening may be worth testing as primary prevention tools for diet-driven chronic disease.

Comparing the use of aggressive end-of life care among frail and non-frail patients with cancer using a claims-based frailty index.

INTRODUCTION: Despite mounting consensus that end-of-life (EOL) care for patients with cancer should focus on improving quality of life, many patients continue to receive aggressive, disease-oriented treatment until death. Within this group, patients with increased frailty may be at higher risk of adverse treatment-related outcomes. We therefore examined the relationship between degree of frailty and receipt of aggressive EOL care among Medicare-insured patients with cancer in Ohio. MATERIALS AND METHODS: From the Ohio Cancer Incidence Surveillance System (OCISS) linked with Medicare claims, we identified patients diagnosed with breast, colorectal, lung, or prostate cancer who died between 2012 and 2016. Frailty was operationalized using a validated claims-based frailty index. Six quality indicators reflecting receipt of aggressive EOL care were identified from claims: (1) any cancer-directed treatment, (2) >1 emergency department (ED) visit, (3) >1 hospital admission, (4) any intensive care unit (ICU) admission in the last 30 days of life, (5) entry to hospice in the last three days of life, and (6) in-hospital mortality. Multivariable logistic regression analysis was performed to control for demographic factors, Medicare and Medicaid dual enrollment, and cancer type and stage in the relationship between frailty and aggressive EOL care. RESULTS: Overall, 31,465 patients met selection criteria. Patients with moderate/severe frailty were less likely than non-/pre-frail patients to receive any aggressive EOL care (adjusted odds ratio [aOR] 0.92 [95% confidence interval 0.86-0.99]). This group was also less likely to undergo cancer-directed treatment in their last 30 days or to enter hospice in their last three days. Increasing frailty was associated with lower odds of admission to the ICU in the last 30 days of life (mild frailty: aOR 0.88 [0.83-0.94]; moderate/severe frailty: aOR 0.85 [0.78-0.92]) or of dying in-hospital (mild frailty: 0.85 [0.79-0.91]; moderate/severe frailty: aOR 0.74 [0.67-0.82]), but higher odds of having >1 ED visit in the last 30 days of life (mild frailty: aOR 1.43 [1.32-1.53]; moderate/severe frailty: aOR 1.61 [1.47-1.77]). DISCUSSION: These findings suggest the need for more explicit discussion of emergency care seeking for patients with cancer at the end of life.

Care Delivery in Community Health Centers Before, During, and After the COVID-19 Pandemic (2019-2022).

INTRODUCTION: Health centers provide primary and behavioral health care to the nation's safety net population. Many health centers served on the frontlines of the COVID-19 pandemic, which brought major changes to health center care delivery. OBJECTIVE: To elucidate primary care and behavioral health service delivery patterns in health centers before and during the COVID-19 public health emergency (PHE). METHODS: We compared annual and monthly patients from 2019 to 2022 for new and established patients by visit type (primary care, behavioral health) and encounter visits by modality (in-person, telehealth) across 218 health centers in 13 states. RESULTS: There were 1581,744 unique patients in the sample, most from health disparate populations. Review of primary care data over 4 years show that health centers served fewer pediatric patients over time, while retaining the capacity to provide to patients 65+. Monthly data on encounters highlights that the initial shift in March/April 2020 to telehealth was not sustained and that in-person visits rose steadily after November/December 2020 to return as the predominant care delivery mode. With regards to behavioral health, health centers continued to provide care to established patients throughout the PHE, while serving fewer new patients over time. In contrast to primary care, after initial uptake of telehealth in March/April 2020, telehealth encounters remained the predominant care delivery mode through 2022. CONCLUSION: Four years of data demonstrate how COVID-19 impacted delivery of primary care and behavioral health care for patients, highlighting gaps in pediatric care delivery and trends in telehealth over time.

Capturing the care of complex community-based health center patients: A comparison of multimorbidity indices and clinical classification software.

OBJECTIVE: To compare morbidity burden captured from multimorbidity indices and aggregated measures of clinically meaningful categories captured in primary care community-based health center (CBHC) patients. DATA SOURCES AND STUDY SETTING: Electronic health records of patients seen in 2019 in OCHIN's national network of CBHCs serving patients in rural and underserved communities. STUDY DESIGN: Age-stratified analyses comparing the most common conditions captured by the Charlson, Elixhauser, and Multimorbidity Weighted (MWI) indices, and Classification Software Refined (CCSR) and Chronic Condition Indicator (CCI) algorithms. DATA COLLECTION/EXTRACTION METHODS: Active ICD-10 conditions on patients' problem list in 2019. PRINCIPAL FINDINGS: Approximately 35%-56% of patients with at least one condition are not captured by the Charlson, Elixhauser, and MWI indices. When stratified by age, this range broadens to 9%-90% with higher percentages in younger patients. The CCSR and CCI reflect a broader range of acute and chronic conditions prevalent among CBHC patients. CONCLUSION: Three commonly used indices to capture morbidity burden reflect conditions most prevalent among older adults, but do not capture those on problem lists for younger CBHC patients. An index with an expanded range of care conditions is needed to understand the complex care provided to primary care populations across the lifespan.

Variation in multimorbidity by sociodemographics and social drivers of health among patients seen at community-based health centers.

Purpose: Understanding variation in multimorbidity across sociodemographics and social drivers of health is critical to reducing health inequities. Methods: From the multi-state OCHIN network of community-based health centers (CBHCs), we identified a cross-sectional cohort of adult (> 25 years old) patients who had a visit between 2019-2021. We used generalized linear models to examine the relationship between the Multimorbidity Weighted Index (MWI) and sociodemographics and social drivers of health (Area Deprivation Index [ADI] and social risks [e.g., food insecurity]). Each model included an interaction term between the primary predictor and age to examine if certain groups had a higher MWI at younger ages. Results: Among 642,730 patients, 28.2% were Hispanic/Latino, 42.8% were male, and the median age was 48. The median MWI was 2.05 (IQR: 0.34, 4.87) and was higher for adults over the age of 40 and American Indians and Alaska Natives. The regression model revealed a higher MWI at younger ages for patients living in areas of higher deprivation. Additionally, patients with social risks had a higher MWI (3.16; IQR: 1.33, 6.65) than those without (2.13; IQR: 0.34, 4.89) and the interaction between age and social risk suggested a higher MWI at younger ages. Conclusions: Greater multimorbidity at younger ages and among those with social risks and living in areas of deprivation shows possible mechanisms for the premature aging and disability often seen in community-based health centers and highlights the need for comprehensive approaches to improving the health of vulnerable populations.

Care Quality and Equity in Health Centers During and After the COVID-19 Pandemic.

INTRODUCTION: Federally Qualified Community Health Centers (FQHCs) are on the frontline of efforts to improve healthcare equity and reduce disparities exacerbated by the COVID-19 pandemic. This study assesses the provision and equity of preventive care and chronic disease management by FQHCs before, during, and after the pandemic. METHODS: Using electronic health record data from 210 FQHCs nationwide and employing segmented regression in an interrupted time series design, preventive screening and chronic disease management were assessed for 939,053 patients from 2019 to 2022. Care measures included cancer screenings, blood pressure control, diabetes control, and childhood immunizations; patient-level factors including race and ethnicity, language preference, and multimorbidity status were analyzed for equitable care provision. Analyses were conducted in 2023-2024. RESULTS: Cancer screening rates and blood pressure control initially declined after the onset of the pandemic but later rebounded, while diabetes control showed a slight increase, later stabilizing. Racial and ethnic disparities persisted, with Asian individuals having a higher prevalence of screenings and blood pressure control, and Black/African American individuals facing a lower prevalence for most screenings but a higher prevalence for cervical cancer screening. Hispanic/Latino individuals had a higher prevalence of various screenings and diabetes control. Disparities persisted for Native Hawaiian/Other Pacific Islander and American Indian/Alaska Native individuals and were observed based on language and multimorbidity status. CONCLUSIONS: While preventive screening and chronic disease management in FQHCs have largely rebounded to pre-pandemic levels following an initial decline, persistent disparities highlight the need for targeted interventions to support FQHCs in addressing healthcare inequities.

An Increase in the Use of ICD-10 Z-Codes for Social Risks and Social Needs: 2015 to 2019.

Attention to 10th Revision of the International Classification of Disease (ICD-10)-CM Z-codes as a mechanism for capturing social risk has grown over the years. However, it remains unclear whether the use of Z-codes has changed over time. This study sought to examine the trends in Z-code use between their introduction in 2015 and the end of 2019 across 2 markedly different states. Using the Healthcare Cost and Utilization Project, all emergency department visits or hospitalizations at short-term general hospitals in Florida and Maryland from 2015 Q4 through 2019 were identified. This study focused on a subset of the Z-codes that are intended to capture social risk to identify the percentage of encounters with a Z-code, percentage of facilities using Z-codes, and facility median of number of encounters with a Z-code per 1000 encounters across quarters, states, and care settings. In total, 495,212 (0.84%) of 58,993,625 encounters had a Z-code. Despite Florida's higher area deprivation, Z-codes were less frequently used and increasing more slowly than when compared with those in Maryland. There were 2.1 times the use of Z-codes in Maryland than in Florida at the encounter level. This difference was also seen when evaluating the median number of encounters with a Z-code, per 1000 encounters (12.1 vs. 3.4). Z-codes were more commonly used at major teaching facilities, and for patients who were uninsured or on Medicaid. The use of ICD-10-CM Z-codes has increased over time, with this increase occurring at nearly all short-term general hospitals. Their use was higher in Maryland than in Florida and among major teaching facilities.

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening.

Introduction: Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers. Methods: Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated. Results: Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs. Conclusion: Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

Ibrutinib Is Associated With Increased Cardiovascular Events and Major Bleeding in Older CLL Patients.

Background: Early ibrutinib trials showed an association between ibrutinib use and risk of bleeding and atrial fibrillation (AF) in younger chronic lymphocytic leukemia (CLL) patients. Little is known about these adverse events in older CLL patients and whether increased AF rates are associated with increased stroke risk. Objectives: To compare the incidence of stroke, AF, myocardial infarction, and bleeding in CLL patients treated with ibrutinib with those who were treated without ibrutinib in a linked SEER-Medicare database. Methods: The incidence rate of each adverse event for treated and untreated patients was calculated. Among those treated, inverse probability weighted Cox proportional hazards regression models were used to calculate HRs and 95% CIs for the association between ibrutinib treatment and each adverse event. Results: Among 4,958 CLL patients, 50% were treated without ibrutinib and 6% received ibrutinib. The median age at first treatment was 77 (IQR: 73-83) years. Compared with those treated without ibrutinib, those treated with ibrutinib had a 1.91-fold increased risk of stroke (95% CI: 1.06-3.45), 3.65-fold increased risk of AF (95% CI: 2.42-5.49), a 4.92-fold increased risk of bleeding (95% CI: 3.46-7.01) and a 7.49-fold increased risk of major bleeding (95% CI: 4.32-12.99). Conclusions: In patients a decade older than those in the initial clinical trials, treatment with ibrutinib was associated with an increased risk of stroke, AF, and bleeding. The risk of major bleeding is higher than previously reported and underscores the importance of surveillance registries to identify new safety signals.

Disparities in adherence and emergency department utilization among people with epilepsy: A machine learning approach.

PURPOSE: We used a machine learning approach to identify the combinations of factors that contribute to lower adherence and high emergency department (ED) utilization. METHODS: Using Medicaid claims, we identified adherence to anti-seizure medications and the number of ED visits for people with epilepsy in a 2-year follow up period. We used three years of baseline data to identify demographics, disease severity and management, comorbidities, and county-level social factors. Using Classification and Regression Tree (CART) and random forest analyses we identified combinations of baseline factors that predicted lower adherence and ED visits. We further stratified these models by race and ethnicity. RESULTS: From 52,175 people with epilepsy, the CART model identified developmental disabilities, age, race and ethnicity, and utilization as top predictors of adherence. When stratified by race and ethnicity, there was variation in the combinations of comorbidities including developmental disabilities, hypertension, and psychiatric comorbidities. Our CART model for ED utilization included a primary split among those with previous injuries, followed by anxiety and mood disorders, headache, back problems, and urinary tract infections. When stratified by race and ethnicity we saw that for Black individuals headache was a top predictor of future ED utilization although this did not appear in other racial and ethnic groups. CONCLUSIONS: ASM adherence differed by race and ethnicity, with different combinations of comorbidities predicting lower adherence across racial and ethnic groups. While there were not differences in ED use across races and ethnicity, we observed different combinations of comorbidities that predicted high ED utilization.

Racial and Ethnic Differences in Antiseizure Medications Among People With Epilepsy on Medicaid: A Case of Potential Inequities.

Background and Objectives: Being on a newer, second-, and third-generation antiseizure medication (ASM) may represent an important marker of quality of care for people with epilepsy. We sought to examine whether there were racial/ethnic differences in their use. Methods: Using Medicaid claims data, we identified the type and number of ASMs, as well as the adherence, for people with epilepsy over a 5-year period (2010-2014). We used multilevel logistic regression models to examine the association between newer-generation ASMs and adherence. We then examined whether there were racial/ethnic differences in ASM use in models adjusted for demographics, utilization, year, and comorbidities. Results: Among 78,534 adults with epilepsy, 17,729 were Black, and 9,376 were Hispanic. Overall, 25.6% were on older ASMs, and being solely on second-generation ASMs during the study period was associated with better adherence (adjusted odds ratio: 1.17, 95% confidence interval [CI]: 1.11-1.23). Those who saw a neurologist (3.26, 95% CI: 3.13-3.41) or who were newly diagnosed (1.29, 95% CI: 1.16-1.42) had higher odds of being on newer ASMs. Importantly, Black (0.71, 95% CI: 0.68-0.75), Hispanic (0.93, 95% CI: 0.88-0.99), and Native Hawaiian and Other Pacific Island individuals (0.77, 95% CI: 0.67-0.88) had lower odds of being on newer ASMs when compared with White individuals. Discussion: Generally, racial and ethnic minoritized people with epilepsy have lower odds of being on newer-generation ASMs. Greater adherence by people who were only on newer ASMs, their greater use among people seeing a neurologist, and the opportunity of a new diagnosis point to actionable leverage points for reducing inequities in epilepsy care.

ICD-10 Z-Code Health-Related Social Needs and Increased Healthcare Utilization.

INTRODUCTION: Health-related social needs are known drivers of health and health outcomes, yet work to date to examine health-related social needs using ICD-10 Z-codes remains limited. This study seeks to evaluate the differences in the prevalence of conditions as well as utilization and cost between patients with and without health-related social needs. METHODS: Using the 2017 Florida State Emergency Department and State Inpatient Databases, this study identified patients with documented health-related social needs using ICD-10 Z-codes. The prevalence ratio was calculated for 14 conditions that are the leading causes of mortality and economic costs. In addition, ratios for the median total number of negative health events and total annual costs between patients with health-related social needs and those without health-related social needs across these conditions were calculated. Data analysis was conducted in 2021. RESULTS: Of 4,477,772 patients, 46,081 (1.0%) had documented health-related social needs and had 4 times the negative health events and 9.3 times the total annual costs. Trends of increased negative health events and costs were seen across all examined conditions; patients with health-related social needs had 2.5-3.5 times the negative health events and 2-18 times greater total costs. The biggest difference in negative health events was seen in patients with unintentional injuries and depression and psychoses (3.5 times for patients with health-related social needs), whereas the biggest difference in total costs was for unintentional injuries (18.4 times for patients with health-related social needs). CONCLUSIONS: This study shows the increased prevalence of numerous high-priority conditions as well as increased utilization and costs among patients with documented health-related social needs.