Economic burden of COVID-19 for employers and employees in the United States.

OBJECTIVE: Describe the economic burden of COVID-19 on employers and employees in the United States (US). METHODS: A targeted literature review was conducted to evaluate the impact of COVID-19 on US-based employers and employees in terms of healthcare resource utilization (HCRU), medical costs, and costs associated with work-loss. Searches were conducted in MEDLINE, Embase, and EconLit using a combination of disease terms, populations, and outcomes to identify articles published from January 2021 to November 4, 2022. As data from the employer perspective were lacking, additional literature related to influenza were included to contextualize the impact of COVID-19, as it shifts into an endemic state, within the existing respiratory illness landscape. RESULTS: A total of 41 articles were included in the literature review. Employer and employee perspectives were not well represented in the literature, and very few articles overlapped on any given outcome. HCRU, costs, and work impairment vary by community transmission levels, industry type, population demographics, telework ability, mitigation implementation measures, and company policies. Work-loss among COVID-19 cases were higher among the unvaccinated and in the week following diagnosis and for some, these continued for 6 months. HCRU is increased in those with COVID-19 and COVID-19-related HCRU can also continue for 6 months. CONCLUSIONS: COVID-19 continues to be a considerable burden to employers. The majority of COVID-19 cases impact working age adults. HCRU is mainly driven by outpatient visits, while direct costs are driven by hospitalization. Productivity loss is higher for unvaccinated individuals. An increased focus to support mitigation measures may minimize hospitalizations and work-loss. A data-driven approach to implementation of workplace policies, targeted communications, and access to timely and appropriate therapies for prevention and treatment may reduce health-related work-loss and associated cost burden.

In January 2020, the US government declared COVID-19 a public health emergency. This lasted until May 2023. To fight this health emergency, the US government provided free testing, vaccination, and treatment. Although the US government has declared the emergency over, COVID-19 continues to infect people. For people with private health insurance, costs associated with COVID-19 patient healthcare have now been transferred from the government to employers. In this study, we collected information from published scientific articles about the costs of COVID-19 for employers and workers in the US. We found that people who were not vaccinated against COVID-19 required more medical care and cost more than people who were vaccinated. In some cases, this trend lasted for as long as 6 months. This was mostly because of workers missing work, not working effectively while sick, and needing to be hospitalized. People who could work from home, whose companies had policies to prevent infections, and who took steps to avoid getting infected needed less medical care and missed work less often. This information may be used to help develop policies, communications, and guidance to prevent COVID-19 and limit its impact on employers and workers.

Survival outcomes for patients with multiple myeloma in France: A retrospective cohort study using the Système National des Données de Santé national healthcare database.

OBJECTIVE: Evaluate the overall survival (OS) of patients with multiple myeloma (MM) at different treatment stages in France. METHODS: This retrospective observational cohort study used data from the French National Health Insurance database to study patients with MM (diagnosis 2013-2019). Patient outcomes included OS (all-cause mortality), time-to-next treatment (TTNT), and duration of therapy (DoT) from initial diagnosis, the start of different lines of therapy (LOTs), triple-class exposure (TCE), and subsequent treatment following TCE. The Kaplan-Meier method analyzed "time-to-event" data. RESULTS: From diagnosis, death rates increased from 1% at 1 month to 24% at 2 years; median OS was 63.8 months (N = 14 309). Median OS from the start of LOTs declined from 61.0 months (LOT1) to 14.8 months (LOT4). Median OS from TCE start was 14.7 months. There was a large variation in TTNT within LOTs (e.g., LOT1: bortezomib + lenalidomide: TTNT = 26.4 months, OS = 61.7 months; lenalidomide: TTNT = 20.0 months, OS = 39.6 months); DoT was similar for LOT1 and LOT2, then progressively declined at LOT4. Patients with stem cell transplant, younger age, and less comorbidity had better survival outcomes. CONCLUSIONS: Patients with MM face a poor prognosis after relapse to multiple LOTs and TCE, demonstrating a worsening of survival outcomes. Access to novel therapies may improve outcomes.

Medicaid Coverage Disruptions Among Children Enrolled in North Carolina Medicaid From 2016 to 2018.

Importance: Brief disruptions in insurance coverage among eligible participants are associated with poorer health outcomes for children. Objective: To describe factors associated with coverage disruptions among children enrolled in North Carolina Medicaid from 2016 to 2018 and estimate the outcome of preventing such disruptions on medical expenditures. Design Setting and Participants: This was a retrospective cohort study using North Carolina Medicaid claims data. All enrolled individuals were aged 1 to 20 years on January 1, 2016, and with 30 days of prior continuous enrollment. Children were observed from January 1, 2016, until December 31, 2018. Analyses were conducted from June 2020 through December 2020. Main Outcomes and Measures: Risk of Medicaid coverage disruptions of 1 to less than 12 months was assessed. Among children who disenrolled from Medicaid for 30 or more days, the risk of reenrollment within 1 to 6 months and 7 to 11 months was assessed. An inverse probability of censoring weights method was then used to estimate the outcome of an intervention to reduce coverage disruptions through preventing disenrollment on per member per month (PMPM) cost. Results: The study population included 831 173 Medicaid beneficiaries aged 1 to 5 years (23%), 6 to 17 years (68%), and 18 to 20 years (9%); 35% were Black, 44% were White, and 14% were Hispanic/Latinx. Among those with a first disenrollment (n = 214 401, 26%), the risk of reenrollment within 6 months and 7 to 11 months was 19% and 7%, respectively. Risk of coverage disruption was higher for Black children (hazard ratio [HR], 1.21; 95% CI, 1.18-1.24), children of other races (Asian, American Indian, Hawaiian or Pacific Islander, multiple races, or unreported; HR, 1.37; 95% CI, 1.33-1.40), and Latinx children (HR, 1.65; 95% CI, 1.60-1.70) compared with White children. Risk of coverage disruption was also higher for children with higher medical complexity (HR, 1.15; 95% CI, 1.12-1.19). The risk of coverage disruption was lower for children living in counties with the highest unemployment rates (HR, 0.89; 95% CI, 0.85-0.94), and comparisons between county-level measures of child poverty and graduation rates showed little or no difference. The estimated PMPM cost for the full population under a scenario in which all medical costs were included was $125.73. Estimated PMPM cost for the full cohort in a counterfactual scenario in which disenrollment was prevented was slightly lower ($122.14). Across all subgroups, estimated PMPM costs were modestly lower ($2-$8) in the scenario in which disenrollment was prevented. Conclusions and Relevance: In this cohort study, the risk of Medicaid coverage disruption was high, with many eligible children in historically marginalized communities continuing to experience unstable enrollment. In addition to improving health outcomes, preventing coverage gaps through policies that decrease disenrollment may also reduce Medicaid costs.

Who are we missing? Underrepresentation of data sources used for pharmacoepidemiology research in the United States.

PURPOSE: Research using healthcare databases often includes patients frequently excluded from clinical trials; yet it is not known whether commonly used data represents the overall population or specific sub-populations of interest. We aimed to examine population representativeness from data sources in recent research studies in the United States (US). METHODS: We identified data sources from abstracts accepted to the 34th International Conference on Pharmacoepidemiology & Therapeutic Risk Management. The final sample included research studies using ≥1 data source from the US. We classified data sources broadly as claims, linkage, electronic health records (EHR), survey, distributed data network, and other. Studies using claims and EHRs were further classified into more specific categories, including special populations of interest (eg, children). RESULTS: We identified 356 abstracts. The majority used claims data (n = 201, 56.5%), followed by data linkages (n = 46, 12.9%), and EHR data (n = 39, 11.0%). Among EHR studies, most (n = 16, 41.0%) came from network data sources (eg, Kaiser Permanente). Almost half (49.4%) of claims-based studies used commercial claims data sources, followed by Medicare (22.1%), Medicaid (11.3%), and Medicare Supplemental (6.1%). Only 15% of studies included children in the study population (n = 53), with 8% focused on a pediatric topic (n = 27). CONCLUSIONS: We find that certain populations in the US are under-represented in pharmacoepidemiology, particularly Medicaid enrollees and children. Researchers should strive to utilize data sources that may be more representative of the US population, particularly vulnerable populations.

Comparative effectiveness of metformin versus insulin for gestational diabetes in New Zealand.

PURPOSE: To measure the comparative effectiveness of metformin versus insulin for initial pharmacological management of gestational diabetes mellitus (GDM). METHODS: We conducted a population-based retrospective cohort study using administrative claims, maternity care, and laboratory result data from New Zealand. We followed pregnant women aged 15 to 45 from GDM diagnosis through delivery and assessed outcomes using maternity care and hospitalization data. We adjusted for covariates using inverse probability of treatment weights and multiple imputation for missing covariate information. We estimated unadjusted and adjusted risk ratios (RRs), risk differences (RDs) per 100, and 95% confidence intervals (CIs). Linear regression was used to estimate the association of treatment with birthweight. We stratified analyses by ethnicity and infant sex in prespecified sensitivity analyses. RESULTS: We compared 3818 metformin-treated pregnancies with 3450 insulin-treated pregnancies. We observed differences in treatment initiation by ethnicity, socioeconomic status, region, and calendar year. Treatment groups were similar in age, body mass index (BMI), and timing of diagnosis/treatment initiation. After adjustment, metformin was associated with reduced absolute risk of planned elective c-section (RD = -2.3, 95% CI, -4.3 to -0.3), large for gestational age (RD = -3.7, 95% CI, -5.5 to -1.8), and neonatal hypoglycemia (RD = -5.0, 95% CI, -6.9 to -3.2) compared with insulin. There were no clinically meaningful differences in average birthweight between metformin- and insulin-treated pregnancies. We observed variation in estimates by ethnicity and infant sex for some neonatal outcomes. CONCLUSION: Metformin appears to be an effective treatment for women with GDM and may reduce risk of some adverse neonatal outcomes when compared with insulin.

Association of Long-term Child Growth and Developmental Outcomes With Metformin vs Insulin Treatment for Gestational Diabetes.

Importance: Metformin is an emerging option for treating gestational diabetes (GDM). However, because metformin crosses the placenta, patients and clinicians are concerned with its long-term effect on child health. Objective: To estimate the association of treating GDM with metformin vs insulin with child growth and development. Design, Setting, and Participants: Population-based cohort study of New Zealand women treated with metformin or insulin for GDM from 2005 to 2012 and their children. This study linked national health care data to create a cohort of mothers and their children, including data from maternity care, pharmaceutical dispensing, hospitalizations, demographic records, and the B4 School Check (B4SC) preschool health assessment. Women treated pharmacologically with metformin or insulin during pregnancy were included. We excluded pregnancies with evidence of diabetes and deliveries prior to 2013. Liveborn infants were linked to their B4SC results. Data were analyzed between January 2017 and May 2018. Exposures: Pharmacologic treatment for GDM with metformin or insulin, measured using pharmaceutical claims data. Main Outcomes and Measures: Child growth (weight and height) and Strengths and Difficulties Questionnaire (SDQ) scores for behavioral development. All outcomes were derived from the B4SC screening program. Linear and log-binomial regression with inverse probability of treatment weighting was used to estimate the association of child growth and psychosocial outcomes with metformin vs insulin treatment for GDM. Results: In both treatment groups, the mean (SD) maternal age was 32 (5) years. A large proportion of mothers who were treated with insulin identified as New Zealand European (867 [44.9%]) while 576 mothers who were treated with metformin (28.9%) identified as New Zealand European. Approximately one-third of mothers who were treated with metformin (n = 639) identified as Asian. We identified 3928 pregnancies treated with metformin (n = 1996) or insulin (n = 1932). After adjustment, we observed no meaningful difference in weight for height z scores between children exposed to metformin compared with insulin (mean difference, -0.10; 95% CI, -0.20 to 0.01). Risk of being 85th percentile or greater for weight for height was similar between treatment groups (adjusted risk ratio, 0.92; 95% CI, 0.83-1.02). Mean SDQ scores were not meaningfully different between the treatment groups, Children of metformin-treated mothers were not significantly more likely to have parent-reported SDQ scores of 14 or more (adjusted risk ratio, 1.13; 95% CI, 0.88-1.46) than those of insulin-treated mothers. Conclusions and Relevance: Our study compares long-term outcomes among school-aged children following maternal use of metformin vs insulin treatment for GDM. Children of metformin-treated mothers were indistinguishable on growth and developmental assessments from those of insulin-treated mothers. These results will help inform future GDM treatment guidelines.

Bias from restricting to live births when estimating effects of prescription drug use on pregnancy complications: A simulation.

PURPOSE: Administrative claim databases are increasingly being used to study the safety of medication exposures during pregnancy. These studies are restricted to live births due to a reliance on algorithms for estimating gestational age that are based on codes associated with live delivery. Conditioning on live birth may induce selection bias when studying the effect of a drug on a pregnancy complication if fetal death is a competing risk for the complication or is caused by the complication. METHODS: We simulated a population of 100,000 pregnancies and estimated the impact of selection bias on relative estimates for the effect of antidepressant exposure on the outcome of preeclampsia. We assumed that the exposure, outcome, and covariates increased the risk of fetal loss. RESULTS: A downward bias in the risk ratio was consistently observed when conditioning on live births. When an unmeasured covariate was assumed to be a common cause of fetal death, antidepressant use, and preeclampsia, the direction of bias varied depending on the strength of the confounding relationship coupled with the selection bias. Despite the very low prevalence of stillbirth, the strength of the relationship between antidepressant use and stillbirth had a substantial impact on bias. CONCLUSIONS: Conditioning on live birth can be problematic when studying pregnancy complications. Simple quantitative selection bias analysis in populations restricted to live births may not fully account for selection bias.

No Increase in Risk of Acute Myocardial Infarction in Privately Insured Adults Prescribed Proton Pump Inhibitors vs Histamine-2 Receptor Antagonists (2002-2014).

BACKGROUND & AIMS: Proton pump inhibitors (PPIs) are commonly used medications. Recent studies reported an increased risk of acute myocardial infarction (MI) in PPI users vs non-users. We evaluated MI risk associated with PPIs compared with histamine-2 receptor antagonists (H2RAs) in privately insured adults in the United States. METHODS: Using administrative claims from commercial and Medicare Supplemental plans (2001-2014), we compared risk of MI in patients who started a new prescription for PPIs vs H2RAs. Enrollees were followed from their first prescription until MI, medication discontinuation, plan disenrollment, or December 31, 2014. MI was defined using hospital diagnosis codes. Risk differences (RD), risk ratios, and 95% confidence intervals (CIs) were estimated using Kaplan-Meier methods at 3, 12, and 36 months after treatment initiation. Standardized morbidity ratio weights were used to control measured confounding. Analyses were stratified by plan type (commercial vs Medicare Supplemental). RESULTS: We identified more than 5 million new users of prescription PPIs and H2RAs. Median follow-up time was 60 days for patients with commercial insurance and 96 days in patients with Medicare Supplemental insurance. The 12-month weighted risk of MI was low overall (approximately 2 cases per 1000 among patients in commercial plans; 8 per 1000 among patients in Medicare Supplemental plans). In the RD analysis, we found no significant differences in MI risk between patients who started PPIs vs H2RAs for the first 12 months, either in the commercial population (weighted RD per 1000, -0.08; 95% CI, -0.51 to 0.36) or the Medicare Supplemental population (weighted RD per 1000, -0.45; 95% CI, -1.53 to 0.58). CONCLUSION: In an analysis of administrative claims from commercial and Medicare Supplemental plans, we found no evidence that prescription PPIs increase risk of MI compared with prescription H2RAs. Physicians and patients should not avoid starting a PPI because of concerns related to MI risk.

Endocrine therapy and urogenital outcomes among women with a breast cancer diagnosis.

PURPOSE: Endocrine therapy for breast cancer can exacerbate menopausal symptoms. The association between endocrine therapy and common pelvic floor disorders including urinary incontinence has rarely been evaluated. We examined urogenital and sexual side effects among women with a breast cancer diagnosis, comparing endocrine therapy users to nonusers. METHODS: Urogenital and sexual symptoms were self-reported during the enrollment interview within the University of North Carolina Cancer Survivorship Cohort. Tumor characteristics and endocrine therapy use were collected from medical and prescription records. We calculated multivariable prevalence ratios (PR) and 95 % confidence intervals (CI) for the association of endocrine therapy (versus no endocrine therapy) and urinary incontinence, overall and by therapy type (tamoxifen or aromatase inhibitors). PROMIS Sexual Function and Satisfaction domain scores were compared across endocrine therapy groups. RESULTS: Among the 548 women with a breast cancer diagnosis, 49 % received endocrine therapy. Overall, 18 % of women reported urinary incontinence symptoms. We observed no association between urinary incontinence and endocrine therapy use overall (PR = 0.97; 95 % CI 0.67, 1.43), tamoxifen (PR = 1.20; 95 % CI 0.74, 1.96), or aromatase inhibitors (PR = 0.89; 95 % CI 0.55, 1.42), compared to no use. Approximately 55 % of women were sexually active. Sexual function scores did not vary according to endocrine therapy use, although urinary incontinence was associated with lower satisfaction scores (p = 0.05). CONCLUSIONS: Our findings demonstrate a high prevalence of urinary incontinence after breast cancer diagnosis similar to the overall prevalence in older U.S. women, and this did not vary strongly according to use of endocrine therapy.

Misclassification in administrative claims data: quantifying the impact on treatment effect estimates.

Misclassification is present in nearly every epidemiologic study, yet is rarely quantified in analysis in favor of a focus on random error. In this review, we discuss past and present wisdom on misclassification and what measures should be taken to quantify this influential bias, with a focus on bias in pharmacoepidemiologic studies. To date, pharmacoepidemiology primarily utilizes data obtained from administrative claims, a rich source of prescription data but susceptible to bias from unobservable factors including medication sample use, medications filled but not taken, health conditions that are not reported in the administrative billing data, and inadequate capture of confounders. Due to the increasing focus on comparative effectiveness research, we provide a discussion of misclassification in the context of an active comparator, including a demonstration of treatment effects biased away from the null in the presence of nondifferential misclassification. Finally, we highlight recently developed methods to quantify bias and offer these methods as potential options for strengthening the validity and quantifying uncertainty of results obtained from pharmacoepidemiologic research.

Receipt of the human papillomavirus vaccine among female college students in the United States, 2009.

OBJECTIVE: To determine receipt of the human papillomavirus (HPV) vaccine among female college students by demographic/descriptive characteristics and sexual behaviors. METHODS: A secondary analysis of the Spring 2009 National College Health Assessment-II was conducted with 40,610 female college students (aged 18 to 24 years) attending 4-year institutions in the United States. RESULTS: Less than half (45.0%) the respondents had received the HPV vaccine. Students who were younger, white, noninternational, and sorority members, had health insurance, attended a college/university in the northeastern United States, did not have or did not live with a partner, participated in sports, ever had vaginal intercourse, had male sex partner(s) (past year), and had a gynecological examination (past year) were more likely to have received the vaccine. CONCLUSIONS: To allow for appropriate intervention, additional research should investigate why certain female college students have not obtained the HPV vaccine. Efforts should be made to link college women without health insurance to no- or low-cost HPV vaccine.