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.

Maternal Tdap and influenza vaccination uptake 2017-2021 in the United States: Implications for maternal RSV vaccine uptake in the future

BACKGROUND

Assessment of maternal vaccine coverage is important for understanding and quantifying the impact of currently recommended vaccines as well as modeling the potential impact of future vaccines. However, existing data lack detail regarding uptake according to week of gestational age (wGA). Such granularity is valuable for more accurate estimation of vaccine impact.

OBJECTIVE

To summarize contemporary maternal Tdap vaccination uptake, overall, yearly, and by wGA, and maternal influenza vaccination uptake, overall, by influenza observation year, immunization month, and delivery month, in the US.

METHODS

Female patients 18-49 years of age with a pregnancy resulting in a live born infant (i.e., delivery) between 2017 and 2021 were selected from the Optum electronic health records (EHRs) database. Recently published gestational age algorithms were utilized to estimate wGA.

RESULTS

Of 1,021,260 deliveries among 886,660 women between 2017-2021, 55.1% had Tdap vaccination during pregnancy; vaccine coverage varied slightly by year (2017: 56.6%; 2018: 55.2%; 2019: 55.2%; 2020: 54.7%; 2021: 52.1%). Most (64.4%) maternal Tdap vaccinations occurred 27-32 wGA; 79.5% occurred during the entire 10-week recommended vaccination window (27-36 wGA). In the evaluation of influenza vaccination uptake (n=798,113 deliveries; 714,841 women), 33.5% of deliveries had influenza vaccination during influenza observation years 2017-2021, most (73.0%) of which occurred during influenza peak activity months (October-January) with approximately one-quarter (27.0%) of vaccinations having occurred during the off-peak months, mostly in September.

CONCLUSIONS

In this large contemporary analysis of EHR data, uptake of Tdap vaccination during pregnancy was consistent with previously published estimates; notably, most vaccination occurred early in the recommended 27-36 wGA window. Maternal influenza vaccination uptake largely correlated with peak influenza activity months and not gestational age. These study findings may have important implications for estimating the potential uptake and impact of future maternal vaccines.

106. High Maternal Tdap Vaccine Uptake During Early Part of Vaccination Window: Implications for Future Maternal Vaccines

Background

Maternal vaccines to prevent respiratory syncytial virus (RSV) among infants are in development. Uptake of existing maternal vaccines can be used to predict uptake of future maternal RSV vaccines and may be used to inform vaccine policy decisions. Previous reports of maternal vaccination rates do not estimate vaccine uptake by gestational week (wGA) of pregnancy, which is needed for precise estimation of vaccine impact. This study estimated the uptake of maternal Tdap vaccination overall and by wGA in a large electronic health records (EHR) database representing both privately and publicly insured patients over a recent 5-year period.

Methods

We identified pregnant women aged 15 – 44 years who had a live birth delivery between 01/01/2017 – 9/29/2021 in the Optum EHR database. Continuous activity for 6 months pre-conception through 1 day after delivery were required. Patients with >1 type of pregnancy outcome within 7 days and/or unidentifiable wGA were excluded. We utilized recently published gestational age algorithms to estimate the uptake of maternal Tdap vaccination overall and by wGA of pregnancy. Results were reported by year.

Results

The population included 1,056,488 live births among 919,510 pregnant women during the study period. The average age at delivery was 29.7 years (SD: 5.6), 72% were white, 82% were non-Hispanic; 58% had private insurance, and 38% had Medicaid. Overall, 56% of the pregnancies included a Tdap vaccine during their pregnancy. Among vaccinated pregnancies, the majority (68%) of Tdap vaccines were administered during the first 6 weeks of the recommended 10-week vaccination window (CDC recommends Tdap vaccination from 27-36 wGA) (Table). Table.

396. Incidence and Attributable Mortality of Clostridioides difficile Infection Among US Adults 18-64 Years of Age

Background

Studies characterizing the burden of Clostridioides difficile infection (CDI) have largely focused on older adults, with limited data among those < 65 years of age insured under commercial plans.

Methods

This retrospective cohort study from 2012–2020 used Optum’s de-identified Clinformatics® Data Mart of about 42 million commercially insured persons. CDI was defined by ICD9/ICD10 diagnosis codes or a combination of CDI diagnosis/testing with antibiotic receipt; cases occurring ≤60 days after prior CDI occurrences were excluded. Annual CDI incidence was evaluated among individuals who were 18–64 years old and enrolled in an Optum commercial plan by January 1 of the corresponding year. Mortality was evaluated in persons with CDI from 2016–2018 who were continuously enrolled in the database for ≥12 months prior; follow-up occurred through the earliest of 12 months, disenrollment, or death. To assess CDI-attributable mortality, CDI+ cases were matched 1:1 to CDI– controls by the propensity score for CDI. Mortality was stratified by age group, acquisition type, and hospitalization status.

Results

CDI incidence was generally stable from 2012–2016 (217–220 and 112–118 episodes per 100,000 person-years (PY) in the 50–64- and 18–49-year age groups, respectively) before decreasing gradually between 2016 and 2020 to 139 episodes per 100,000 PY (50–64-year age group) and to 66 episodes per 100,000 PY (18–49-year age group) (Figure 1). In the 50–64-year age group, CDI-attributable mortality increased to 2.2% at 12 months (CDI+, 4.2%; CDI−, 2.0%), with larger attributable differences observed among hospitalized (healthcare associated [HA], 18.1%; community associated [CA], 7.0%) vs nonhospitalized (HA, 3.3%; CA, −0.1%) patients (Figure 2). The CDI-attributable mortality rate of 0.6% at 12 months among the 18–49-year age group was lower than that in the 50–64-year age group but trended similarly (CDI+, 1.2%; CDI−, 0.6%).

Conclusion

As reported previously, both CDI incidence and attributable mortality among US individuals 18–64 years increased with age. Identifying high-risk groups among non-elderly adults is warranted to develop better strategies for effective prevention.

Funded by Pfizer Inc.

Disclosures

Holly Yu, MSPH, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Tamuno Alfred, PhD, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Jingying Zhou, MA, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Jennifer Judy, MS, PhD, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Margaret A A. Olsen, PhD, MPH, Pfizer Inc: Advisor/Consultant|Pfizer Inc: Grant/Research Support.

393. Healthcare and Out-of-Pocket Costs Associated With Clostridioides difficile Infection Among US Adults 18–64 Years of Age

Background

Limited data are available on healthcare costs associated with Clostridioides difficile infection (CDI) among adults &lt; 65 years of age.

Methods

This retrospective cohort study used Optum’s de-identified Clinformatics® Data Mart to identify first CDI episodes from 2016–2019 among individuals 18–64 years of age insured under commercial plans. CDI was defined by ICD9/ICD10 diagnosis codes or a combination of CDI diagnosis/testing with antibiotic treatment. Healthcare costs were evaluated among CDI+ cases and 1:1 propensity score-matched CDI− controls. Both CDI+ cases and controls had continuous database enrollment for ≥12 months prior; follow-up continued through the earliest of death, disenrollment or 12 months post-index. Costs were analyzed by age group, acquisition type, and hospitalization status within 2 months of the CDI index date.

Results

We identified 13,820 CDI+ cases and 4,027,386 potential controls; 12,999 cases (18–49 y, n=6667; 50–64 y, n=6332) were matched to a control. In the 50–64-year matched groups, mean total healthcare costs at 2 months post-index were $18,453 (CDI+) and $6819 (CDI−); $11,634 in excess costs were attributable to CDI (Figure 1A). Mean attributable costs were higher for hospitalized healthcare-associated ($68,745) and hospitalized community-associated ($37,646) cases than non-hospitalized healthcare- or community-associated cases ($8333 and $2953, respectively). The mean attributable out-of-pocket (OOP) cost in the 50–64-year age group was $573 and was higher for community-associated vs healthcare-associated cases (Figure 1B). Overall CDI-attributable costs in the 18–49-year age group trended similarly but were mostly lower for total healthcare costs ($7826 [CDI+, $12,019; CDI−, $4193]; Figure 2A) and slightly higher for OOP healthcare costs ($642 [CDI+, $954; CDI–, $311]; Figure 2B).

Conclusion

CDI-attributable healthcare costs among US individuals 18–64 years of age are substantial, particularly for those hospitalized for CDI. Effective prevention in younger adults may significantly reduce healthcare resource utilization and costs to both the healthcare system and patients.

Funded by Pfizer Inc.

Disclosures

Holly Yu, MSPH, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Tamuno Alfred, PhD, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Jingying Zhou, MA, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Jennifer Judy, MS, PhD, Pfizer Inc: Employee|Pfizer Inc: Stocks/Bonds Margaret A A. Olsen, PhD, MPH, Pfizer Inc: Advisor/Consultant|Pfizer Inc: Grant/Research Support.

COVID-19 vaccine effectiveness among immunocompromised populations: a targeted literature review of real-world studies

Introduction

From July through October of 2021, several countries issued recommendations for increased COVID-19 vaccine protection for individuals with one or more immunocompromised (IC) conditions. It is critically important to understand the vaccine effectiveness (VE) of COVID-19 vaccines among IC populations as recommendations are updated over time in response to the evolving COVID-19 pandemic.

Areas covered

A targeted literature review was conducted to identify real-world studies that assessed COVID-19 VE in IC populations between December 2020 and September 2021. A total of 10 studies from four countries were identified and summarized in this review.

Expert opinion

VE of the widely available COVID-19 vaccines, including BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), Ad26.COV2.S (Janssen), and ChAdOx1 nCoV-19 (Oxford/AstraZeneca), ranged from 64% to 90% against SARS-CoV-2 infection, 73% to 84% against symptomatic illness, 70% to 100% against severe illness, and 63% to 100% against COVID-19-related hospitalization among the fully vaccinated IC populations included in the studies. COVID-19 VE for most outcomes in the IC populations included in these studies were lower than in the general populations. These findings provide preliminary evidence that the IC population requires greater protective measures to prevent COVID-19 infection and associated illness, hence should be prioritized while implementing recommendations of additional COVID-19 vaccine doses.

A retrospective study of in-hospital mortality in patients with idiopathic pulmonary fibrosis between 2015 and 2018

Hospitalizations are common in patients with idiopathic pulmonary fibrosis (IPF) and are associated with high mortality. We used data from the Premier Healthcare Database to determine in-hospital mortality rates and the factors associated with in-hospital mortality in patients with IPF in the era of approved antifibrotic drugs.The Premier Healthcare Database is a detailed and broadly representative database of hospital admissions and discharges in the US. Patients with IPF who were hospitalized between 1 January 2015 and 28 February 2018 were identified using a diagnostic algorithm comprising International Classification of Diseases -9 and International Classification of Diseases -10 diagnostic codes and billing data. Associations between patient-, hospital- and treatment-related factors and a composite outcome of death during the index visit, lung transplant during the index visit but >1 day after admission, or death during a readmission within 90 days of the index visit were analyzed using logistic regression.The cohort comprised 9667 hospitalized patients with IPF. In total, 1414 patients (14.6%) met the composite outcome: 1036 (10.7%) died during the index visit, 371 (3.8%) died during a readmission within 90 days; 7 (0.1%) underwent lung transplant >1 day after admission. Factors significantly associated with a higher risk of the composite outcome included mechanical ventilation (odds ratio 6.41 [95% CI: 5.24, 7.84]), admission to the intensive care unit (1.73 [1.49, 2.00]), attendance by a critical care physician (2.12 [1.33, 3.38]), older age (1.20 [1.12, 1.28] per 10-year increase), and use of intravenous steroids (1.16 [1.00, 1.34]), intravenous antibiotics (1.49 [1.22, 1.83]) and opioids (3.41 [2.95, 3.93]). Factors significantly associated with a lower risk of the composite outcome included female sex (0.70 [0.61, 0.80]), comorbid chronic obstructive pulmonary disease (0.69 [0.60, 0.78]), attendance by a family medicine physician (0.67 [0.48, 0.94]) or internal medicine physician (0.59 [0.46, 0.75]), and use of oral steroids (0.62 [0.51, 0.77]), statins (0.76 [0.67, 0.87]) and proton pump inhibitors (0.80 [0.70, 0.92]).In conclusion, patients with IPF are at risk of mortality during a hospital stay or readmission within 90 days, particularly those who receive mechanical ventilation.

In-Hospital Mortality in Patients with Idiopathic Pulmonary Fibrosis: A US Cohort Study

Purpose

In patients with idiopathic pulmonary fibrosis (IPF), hospitalizations are associated with high mortality. We sought to determine in-hospital mortality rates and factors associated with in-hospital mortality in patients with IPF.

Methods

Patients with IPF were identified from the Premier Healthcare Database, a representative administrative dataset that includes > 20% of hospital discharges in the US, using an algorithm based on diagnostic codes and billing data. We used logistic regression to analyze associations between patient-, hospital-, and treatment-related characteristics and a composite primary outcome of death during the index visit, lung transplant during the index visit and > 1 day after admission, or death during a readmission within 90 days.

Results

The cohort comprised 6665 patients with IPF hospitalized between October 2011 and October 2014. A total of 963 (14.4%) met the primary outcome. Factors significantly associated with a higher risk of the primary outcome included mechanical ventilation [odds ratio 4.65 (95% CI 3.73, 5.80)], admission to the intensive care unit [1.83 (1.52, 2.21)], treatment with opioids (3.06 [2.57, 3.65]), and a diagnosis of pneumonia [1.44 (1.21, 1.71)]. Factors significantly associated with a lower risk included concurrent chronic obstructive pulmonary disease [0.65 (0.55, 0.77)] and female sex [0.67 (0.57, 0.79)].

Conclusions

Patients with IPF, particularly those receiving mechanical ventilation or intensive care, are at substantial risk of death or lung transplant during hospitalization or death during a readmission within 90 days.

Electronic supplementary material

The online version of this article (10.1007/s00408-019-00270-z) contains supplementary material, which is available to authorized users.

Replication of Epigenetic Postpartum Depression Biomarkers and Variation with Hormone Levels

DNA methylation variation at HP1BP3 and TTC9B is modified by estrogen exposure in the rodent hippocampus and was previously shown to be prospectively predictive of postpartum depression (PPD) when modeled in antenatal blood. The objective of this study was to replicate the predictive efficacy of the previously established model in women with and without a previous psychiatric diagnosis and to understand the effects of changing hormone levels on PPD biomarker loci. Using a statistical model trained on DNA methylation data from N=51 high-risk women, we prospectively predicted PPD status in an independent N=51 women using first trimester antenatal gene expression levels of HP1BP3 and TTC9B, with an area under the receiver operator characteristic curve (AUC) of 0.81 (95% CI: 0.69-0.92, p<5 × 10(-4)). Modeling DNA methylation of these genes in N=240 women without a previous psychiatric diagnosis resulted in a cross-sectional prediction of PPD status with an AUC of 0.81 (95% CI: 0.68-0.93, p=0.01). TTC9B and HP1BP3 DNA methylation at early antenatal time points showed moderate evidence for association to the change in estradiol and allopregnanolone over the course of pregnancy, suggesting that epigenetic variation at these loci may be important for mediating hormonal sensitivity. In addition both loci showed PPD-specific trajectories with age, possibly mediated by age-associated hormonal changes. The data add to the growing body of evidence suggesting that PPD is mediated by differential gene expression and epigenetic sensitivity to pregnancy hormones and that modeling proxies of this sensitivity enable accurate prediction of PPD.

Meta-analysis of genetic association studies on bipolar disorder

Numerous candidate gene association studies of bipolar disorder (BP) have been carried out, but the results have been inconsistent. Individual studies are typically underpowered to detect associations with genes of small effect sizes. We conducted a meta-analysis of published candidate gene studies to evaluate the cumulative evidence. We systematically searched for all published candidate gene association studies of BP. We then carried out a random-effects meta-analysis on all polymorphisms that were reported on by three or more case-control studies. The results from meta-analyses of these genes were compared with the findings from a recent mega-analysis of eleven genome-wide association studies (GWAS) in BP performed by the Psychiatric GWAS Consortium (PGC). A total of 487 articles were included in our review. Among these, 33 polymorphisms in 18 genes were reported on by three or more case-control studies and included in the random-effects meta-analysis. Polymorphisms in BDNF, DRD4, DAOA, and TPH1, were found to be nominally significant with a P-value < 0.05. However, none of the findings were significant after correction for multiple testing. Moreover, none of these polymorphisms were nominally significant in the PGC-BP GWAS. A number of plausible candidate genes have been previously associated with BP. However, the lack of robust findings in our review of these candidate genes highlights the need for more atheoretical approaches to study the genetics of BP afforded by GWAS. The results of this meta-analysis and from other on-going genomic experiments in BP are available online at Metamoodics (http://metamoodics.igm.jhmi.edu).

Data mining approaches for genome-wide association of mood disorders

BACKGROUND

Mood disorders are highly heritable forms of major mental illness. A major breakthrough in elucidating the genetic architecture of mood disorders was anticipated with the advent of genome-wide association studies (GWAS). However, to date few susceptibility loci have been conclusively identified. The genetic etiology of mood disorders appears to be quite complex, and as a result, alternative approaches for analyzing GWAS data are needed. Recently, a polygenic scoring approach that captures the effects of alleles across multiple loci was successfully applied to the analysis of GWAS data in schizophrenia and bipolar disorder (BP). However, this method may be overly simplistic in its approach to the complexity of genetic effects. Data mining methods are available that may be applied to analyze the high dimensional data generated by GWAS of complex psychiatric disorders.

RESULTS

We sought to compare the performance of five data mining methods, namely, Bayesian networks, support vector machine, random forest, radial basis function network, and logistic regression, against the polygenic scoring approach in the analysis of GWAS data on BP. The different classification methods were trained on GWAS datasets from the Bipolar Genome Study (2191 cases with BP and 1434 controls) and their ability to accurately classify case/control status was tested on a GWAS dataset from the Wellcome Trust Case Control Consortium.

CONCLUSION

The performance of the classifiers in the test dataset was evaluated by comparing area under the receiver operating characteristic curves. Bayesian networks performed the best of all the data mining classifiers, but none of these did significantly better than the polygenic score approach. We further examined a subset of single-nucleotide polymorphisms (SNPs) in genes that are expressed in the brain, under the hypothesis that these might be most relevant to BP susceptibility, but all the classifiers performed worse with this reduced set of SNPs. The discriminative accuracy of all of these methods is unlikely to be of diagnostic or clinical utility at the present time. Further research is needed to develop strategies for selecting sets of SNPs likely to be relevant to disease susceptibility and to determine if other data mining classifiers that utilize other algorithms for inferring relationships among the sets of SNPs may perform better.