Optum (United States)

Patients immunosuppressed because of disease and/or therapy are at increased risk of developing herpes zoster (HZ) and related complications. However, HZ risk due to immunosuppressive medication remains underexplored across a broad spectrum of medication classes and conditions. To estimate HZ risk among US adults initiating immunosuppressive therapy, across underlying conditions. This retrospective study used administrative claims from the Optum Research Database (October 1, 2015, to December 31, 2022) to identify incident HZ diagnoses and the proportion of HZ with complications. Included patients were aged 18years or older and had at least a 12-month baseline period of continuous enrollment with medical and pharmacy benefits. Analyses produced incidence rates (IRs) of HZ during periods of immunosuppression and nonimmunosuppression and compared patients initiating immunosuppressive therapy (immunosuppressed subcohort) vs matched controls who did not (nonimmunosuppressed subcohort). Cox regression analyses compared HZ hazards and a logistic regression model compared the difference in the occurrence of postherpetic neuralgia (PHN) following HZ diagnosis. In patients initiating immunosuppressive medications (N = 528,283), the overall HZ IR was 18.2 (95% CI = 17.9-18.4) per 1,000 person-years. Patients with the highest IRs were those treated with Janus kinase inhibitors (30.5 [95% CI = 25.0-36.9] per 1,000 person-years), rituximab (27.8 [95% CI = 25.2-30.6] per 1,000 person-years), or cyclophosphamide (27.5 [95% CI = 19.3-38.1] per 1,000 person-years). Patients had a higher HZ risk when using immunosuppressive medications (adjusted hazard ratio 2.86 [95% CI = 2.76-2.95]) and with increasing numbers of immunosuppressive medication classes (one vs none: 2.45 [95% CI = 2.37-2.54]; at least 2 vs none: 4.04 [95% CI = 3.87-4.21]). The immunosuppressed subcohort had a higher HZ hazard (adjusted hazard ratio: 1.39 [95% CI = 1.35-1.43]), higher frequency of HZ complications (21.4% vs 18.8% of HZ cases developed PHN, P < 0.001), and increased odds of PHN (adjusted odds ratio: 1.22 [95% CI = 1.14-1.31]) compared with the nonimmunosuppressed subcohort. Immunosuppressive medication use was associated with a higher risk of HZ and HZ-related complications. Measures to prevent HZ before immunosuppressive treatment initiation should be considered according to Advisory Committee on Immunization Practices recommendations and other professional organizations.

Despite broad recommendations in older adults, uptake for the 2-dose recombinant zoster vaccine (RZV), which protects against herpes zoster (ie, shingles), has historically been low in the United States among those aged 50years and older. By recommending RZV, health care providers play a critical role in encouraging shingles prevention among older adults. A vaccine prescription may reinforce a recommendation, but understanding the extent and associated characteristics of uptake following prescription is needed. To describe RZV uptake following an RZV prescription among US adults aged 50years and older. RZV uptake following a prescription among adults aged 50years and older in the United States was assessed from 2017 to 2023 using administrative claims data linked with electronic health records. Patient demographic and clinical characteristics, provider characteristics, and health system factors were presented descriptively and compared between those with and without RZV administration following a prescription. A Cox proportional hazards model assessed associations between patient, provider, and health system factors and RZV administration following an RZV prescription. Of the 8,715 patients with an RZV prescription included, vaccine uptake following prescription was generally high: 71% of patients received at least 1 RZV dose following prescription, of which 82% were administered in a pharmacy setting. Among prescriptions with a known provider specialty source, 91% were written by primary care physicians or internal medicine providers. Factors such as Medicare Advantage with Part D coverage (vs commercial insurance), household income of at least $75,000 (vs <$40,000), and having an immunocompromising or autoimmune condition were associated with higher rates of RZV administration following a prescription. Receipt of RZV is likely following a healthcare provider's recommendation, as shown by the high uptake observed among adults who received RZV prescriptions in this study. Additional efforts are needed to ensure full adherence with provider recommendations for herpes zoster prevention.

BackgroundThe recent developments in Alzheimer’s disease (AD) treatments have elucidated the importance of the timely and accurate diagnosis of AD. As clinical guidelines for the diagnosis of AD are further developed, biomarker testing and neuroimaging will become increasingly important. The purpose of this study was to explore the rates of diagnostic testing in patients newly diagnosed with AD.MethodThis retrospective observational study used de‐identified administrative claims and electronic health records (EHR) from the Optum Market Clarity™ Integrated Clinical + Claims Database to identify US adult commercial and Medicare Advantage enrollees with ≥1 claims for AD (first claim=index date) between 01/01/2020 and 09/30/2024. This dataset was further enhanced by the Optum Alzheimer’s Disease Enriched Clinical Database which leverages validated natural language processing (NLP) methods to extract relevant AD data including cognitive test results (Mini‐Mental State Examination [MMSE] or Montreal Cognitive Assessment [MoCA]). All enrollees had ≥360 days of baseline enrollment. Demographics, AD stage (from cognitive assessments), and biomarker/imaging were captured during the baseline period.Result4,306 patients met all inclusion criteria: baseline enrollment, cognitive assessment before AD diagnosis, and no AD diagnosis during baseline. Twenty‐three percent of patients had “normal” cognitive test results, 40% had “mild,” 30% had “moderate,” and 8% had “severe.” African American patients were more likely to be diagnosed in the moderate (41%) or severe (11%) stages compared to Caucasian patients (27% moderate, 7% severe). Additionally, Hispanic patients were more likely to be diagnosed in the moderate (41%) and severe (16%) stages compared to non‐Hispanic patients (29% moderate, 7% severe). Finally, a low number of patients received biomarker testing (1% overall) or neuroimaging (3% overall) prior to their AD diagnosis regardless of AD stage.ConclusionEnriching claims data with NLP‐derived clinical values added important depth to this retrospective analysis. By identifying cognitive test results, we found racial and ethnic disparities in AD staging preceding a new AD diagnosis. We also found a suboptimal number of patients that received imaging to confirm their AD diagnosis regardless of stage. Future research is needed to better assess the impacts of suboptimal diagnostic testing.

BackgroundAs novel testing and treatments for Alzheimer's disease (AD) become more widely available, understanding the patient journey to diagnosis in real‐world settings is critical to adoption. This study aimed to identify a cohort of newly diagnosed AD patients and describe the clinical and health care characteristics leading up to diagnosis.MethodsDe‐identified administrative claims data from the Optum Labs Data Warehouse were used to identify US adult commercial and Medicare Advantage enrollees 01/01/22‐03/31/24 with ≥1 claim for an AD diagnosis code (earliest claim = index date) and baseline enrollment ≥360 days. To identify newly diagnosed patients, those with evidence of AD in the 360‐day baseline period were excluded. Demographics, AD diagnosis type, and top provider specialties were captured on index. Comorbidities, top diagnoses, health care resource utilization and costs were captured in baseline.ResultOf 99,093 individuals newly diagnosed with AD, 97.6% were age ≥65, 64% were female, and 97.6% had Medicare Advantage insurance (Table 1). On index, provider specialty was most commonly primary care (35.0%) followed by hospital, neurology, psychology, and laboratory. AD diagnosis type was unspecified for the majority (66.5%) of patients, while 27.7% were diagnosed with late‐onset AD and 5.8% with early‐onset AD.In the 360‐day baseline, top diagnosis codes included known AD risk factors (primary hypertension, type 2 diabetes) and more general conditions (Table 2). Nearly one‐third (29.7%) of patients had ≥1 inpatient hospitalization, with a mean stay of 18.4 days (standard deviation [SD] 26.8 days; Table 3). The majority (89.4%) of patients had ≥1 office visit, with an average of 13.8 visits (SD 14.9). Total health care costs were on average $20,005.18 (SD $32,544.13), primarily driven by inpatient hospitalization costs (mean $7,545.09, SD $21,414.60).ConclusionIn this claims‐based study, new AD diagnoses were most frequently associated with primary care providers and the AD type (early‐ vs. late‐onset) was unspecified. In the year before diagnosis, patients were seen for known AD risk factors as well as more general conditions, with extended inpatient hospital stays and frequent office visits. Future research is needed to assess evidence of biomarker testing and treatment post‐diagnosis.

Abstract Background/Introduction Within the broad spectrum of heart failure (HF) with preserved ejection fraction (HFpEF), obesity-related HFpEF displays a distinct phenotype, yet is oftentimes underdiagnosed and undertreated. With the increasing prevalence of HFpEF and obesity, it is critical to have a comprehensive understanding of quality of life (QoL) and symptom burden among those with HFpEF and Obesity. Purpose To describe HF related QoL, symptom severity, and physical limitations among adults diagnosed with HFpEF and stratified by BMI category. Methods This observational cross-sectional survey study identified participants in July 2024 from a large claims dataset. The target population included patients aged ≥ 18 years, with ≥ 6 months of continuous enrollment prior to 07/01/2024, and diagnosed with HFpEF between 10/01/2018 – 05/31/2024. A complex sample of 6,000 patients was taken from the target population. Patients were stratified on claims-recorded body mass index (BMI) categories (normal, overweight, class 1, 2 and 3 obesity), race (White and non-White), and HFpEF visit type. The strata within each BMI category contained a combined 1,200 patients; non-White patients were over sampled and patients with an outpatient without cardiologist visit type were under-sampled. The patient self-administered survey included the Kansas City Cardiomyopathy Questionnaire (KCCQ), a 23-item self-reported HF related health status measure that generates scores related to several domains including symptom burden, physical limitations and QoL ranging from 1 to 100 where higher score represents better health status. Descriptive analyses for the overall respondents and by patient-reported BMI categories were conducted, with analytic weighting applied to account for unequal probabilities of selection and nonresponse. Results A total of 815 patients returned complete, eligible surveys, yielding an overall response rate of 17.5%. Of the 815 respondents, 16%, 30%, 21%, 18%, 15% patients were in normal, overweight, class 1, 2, and 3 obesity categories respectively (unweighted). Respondents and non-respondents were not significantly different on age, sex, and insurance type. Respondents had a mean (SD) age of 77 (9) years, 60% (95% CI hereafter: 56-65%) were female, 78% (75-81%) White. Most respondents reported being diagnosed with HF &amp;gt;5 years ago (42%; 37-46%). The mean KCCQ clinical and overall summary scores ranged from 51-68 and 53-67 respectively, with lowest score in the class 3 obesity category and highest in the normal weight category. Across the majority of KCCQ domains and the two summary scores, the means were numerically lower with increasing patient-reported BMI categories. Conclusion(s) Lower quality of life, higher HF symptom burden, and more physical limitations were observed among survey participants with HFpEF who were in higher BMI categories compared to those who were in lower BMI categories.Figure 1 Figure 2