Real world data (RWD) in pediatrics.

Unique challenges pertain when studying children, although many research principles are the same as those when studying adult populations. This truism extends to the use of real-world data (RWD). RWD are particularly relevant to pediatrics because they may potentially provide an additional source of data to inform pediatric labeling and practice patterns when clinical trials have not been or cannot be conducted. The purpose of this commentary is to provide a brief overview of the unique issues in using RWD to study the effectiveness or safety of medical therapies in children.

Categorization of COVID-19 severity to determine mortality risk.

PURPOSE: Algorithms for classification of inpatient COVID-19 severity are necessary for confounding control in studies using real-world data. METHODS: Using Healthverity chargemaster and claims data, we selected patients hospitalized with COVID-19 between April 2020 and February 2021, and classified them by severity at admission using an algorithm we developed based on respiratory support requirements (supplemental oxygen or non-invasive ventilation, O2/NIV, invasive mechanical ventilation, IMV, or NEITHER). To evaluate the utility of the algorithm, patients were followed from admission until death, discharge, or a 28-day maximum to report mortality risks and rates overall and by stratified by severity. Trends for heterogeneity in mortality risk and rate across severity classifications were evaluated using Cochran-Armitage and Logrank trend tests, respectively. RESULTS: Among 118 117 patients, the algorithm categorized patients in increasing severity as NEITHER (36.7%), O2/NIV (54.3%), and IMV (9.0%). Associated mortality risk (and 95% CI) was 11.8% (11.6-12.0%) overall and increased with severity [3.4% (3.2-3.5%), 11.5% (11.3-11.8%), 47.3% (46.3-48.2%); p < 0.001]. Mortality rate per 1000 person-days (and 95% CI) was 15.1 (14.9-15.4) overall and increased with severity [5.7 (5.4-6.0), 14.5 (14.2-14.9), 32.7 (31.8-33.6); p < 0.001]. CONCLUSION: As expected, we observed a positive association between the algorithm-defined severity on admission and 28-day mortality risk and rate. Although performance remains to be validated, this provides some assurance that this algorithm may be used for confounding control or stratification in treatment effect studies.

Current needs in pediatric pharmacoepidemiology.

PURPOSE: We report on a needs assessment conducted by the International Society of Pharmacoepidemiology (ISPE) Pediatric Special Interest Group (SIG) to identify critical needs in pediatric pharmacoepidemiology and directions for future activities. METHODS: A mixed methods survey using a structured interview was conducted in the SIG and ISPE membership to elicit information about current activities in pediatric pharmacoepidemiology and identify critical methodologic issues. The interviews were conducted in two phases over 2013 and 2014, beginning with interviews of SIG members and expanding to the wider ISPE membership. Members of the SIG conducted the interviews and summarized the responses. RESULTS: Twenty-nine ISPE members participated in the needs assessment The respondents reported working with a total of 59 distinct databases, with only eight databases used by more than one respondent. Seventeen respondents (57%) reported issues of limited sample sizes, noting that the problem intensifies when studying age sub-groups or specific genetic populations. Missing data elements were a problem in three main areas: lack of detailed medication information, inability to link to parental data, and lack of detailed information about age. Respondents reported the need for data elements not typically required in studies of adults, such as birthweight and current height and weight, as well as school performance and mental health status. CONCLUSIONS: Our needs assessment describes a preliminary picture of the emerging sub-specialty of pediatric pharmacoepidemiology encompassing a range of age sub-groups, disease areas, and medical specialties. The assessment also documents a body of methodologic challenges unique to pharmacoepidemiologic research in children. Copyright © 2016 John Wiley & Sons, Ltd.

A Descriptive Cohort Study of Drug Utilization Patterns Among Patients Hospitalized With Coronavirus Disease 2019 in the United States, January 2021-February 2022.

Background: There is a dearth of drug utilization studies for coronavirus disease 2019 (COVID-19) treatments in 2021 and beyond after the introduction of vaccines and updated guidelines; such studies are needed to contextualize ongoing COVID-19 treatment effectiveness studies during these time periods. This study describes utilization patterns for corticosteroids, interleukin-6 (IL-6) inhibitors, Janus kinase inhibitors, and remdesivir among hospitalized adults with COVID-19, over the entire hospitalization, and within hospitalization periods categorized by respiratory support requirements. Methods: This descriptive cohort study included United States adults hospitalized with COVID-19 admitted from 1 January 2021 through 1 February 2022; data included HealthVerity claims and hospital chargemaster. The number and distribution of patients were reported for the first 3 drug regimen lines initiated. Results: The cohort included 51 066 patients; the most common initial drug regimens were corticosteroids (23.4%), corticosteroids plus remdesivir (25.1%), and remdesivir (4.4%). IL-6 inhibitors and Janus kinase inhibitors were included in later drug regimens and were more commonly administered with both corticosteroids and remdesivir than with corticosteroids alone. IL-6 inhibitors were more commonly administered than Janus kinase inhibitors when patients received high-flow oxygen or ventilation. Conclusions: These findings provide important context for comparative studies of COVID-19 treatments with study periods extending into 2021 and later. While prescribing generally aligned with National Institutes of Health COVID-19 treatment guidelines during this period, these findings suggest that prescribing preference, potential confounding by indication, and confounding by prior/concomitant use of other therapeutics should be considered in the design and interpretation of comparative studies.

Real-world utilization of SARS-CoV-2 serological testing in RNA positive patients across the United States.

BACKGROUND: As diagnostic tests for COVID-19 were broadly deployed under Emergency Use Authorization, there emerged a need to understand the real-world utilization and performance of serological testing across the United States. METHODS: Six health systems contributed electronic health records and/or claims data, jointly developed a master protocol, and used it to execute the analysis in parallel. We used descriptive statistics to examine demographic, clinical, and geographic characteristics of serology testing among patients with RNA positive for SARS-CoV-2. RESULTS: Across datasets, we observed 930,669 individuals with positive RNA for SARS-CoV-2. Of these, 35,806 (4%) were serotested within 90 days; 15% of which occurred <14 days from the RNA positive test. The proportion of people with a history of cardiovascular disease, obesity, chronic lung, or kidney disease; or presenting with shortness of breath or pneumonia appeared higher among those serotested compared to those who were not. Even in a population of people with active infection, race/ethnicity data were largely missing (>30%) in some datasets-limiting our ability to examine differences in serological testing by race. In datasets where race/ethnicity information was available, we observed a greater distribution of White individuals among those serotested; however, the time between RNA and serology tests appeared shorter in Black compared to White individuals. Test manufacturer data was available in half of the datasets contributing to the analysis. CONCLUSION: Our results inform the underlying context of serotesting during the first year of the COVID-19 pandemic and differences observed between claims and EHR data sources-a critical first step to understanding the real-world accuracy of serological tests. Incomplete reporting of race/ethnicity data and a limited ability to link test manufacturer data, lab results, and clinical data challenge the ability to assess the real-world performance of SARS-CoV-2 tests in different contexts and the overall U.S. response to current and future disease pandemics.

Use of analgesic, anesthetic, and sedative medications during pediatric hospitalizations in the United States 2008.

BACKGROUND: The wide need for analgesia, anesthesia, and sedation in children and the lack of pediatric labeling leads to widespread off-label use of medications for pain and sedation in children. Any attempt to address the lack of labeling will require national estimates of the numbers of children using each medication, their ages, and other factors, to understand the overall use of these medications. We describe use of analgesics, anesthetics, and sedatives in pediatric inpatients by result of conducting a statistical analysis of medication data from >800,000 pediatric hospitalizations in the United States. The purpose was to provide national estimates for the percentage of hospitalized children receiving specific analgesics, anesthetics, and sedatives and their use by age group. METHODS: Data from the Premier Database, the largest hospital-based, service-level comparative database in the country, were used. We identified all uses of a given medication, selected the first use for each child, and calculated the prevalence of use of specific medications among hospitalized children in 2008 as the number of hospitalizations in which the drug was used per 100 hospitalizations. Dose and number of doses were not considered in these analyses. RESULTS: The dataset contained records for 877,201 hospitalizations of children younger than 18 years of age at the time of admission. Thirty-three medications and an additional 11 combinations were administered in this population, including nonsteroidal antiinflammatory drugs, local and regional anesthetics, opioids, benzodiazepines, sedative-hypnotics, barbiturates, and others. The 10 most frequently administered analgesic, anesthetic, or sedative medications used in this population were acetaminophen (14.7%), lidocaine (11.0%), fentanyl (6.6%), ibuprofen (6.3%), morphine (6.2%), midazolam (4.5%), propofol (4.1%), lidocaine/prilocaine (2.5%), hydrocodone/acetaminophen (2.1%), and acetaminophen/codeine (2.0%). Use changed with age, and the direction of change (increases and decreases) and the type of change (linear, u-shaped, or other) appeared to be specific to each drug. CONCLUSIONS: A variety of drug classes and individual medications were used to manage pain and sedation in hospitalized children. The variation in patterns of use reflects the heterogeneity of the dataset, comprising a wide range of ages and conditions in which analgesia, anesthesia, and sedation might be required. It was not possible to assess whether use of a specific medication was clinically appropriate, except to note use of medications in age subgroups without pediatric labeling.

Describing characteristics and treatment patterns of patients hospitalized with COVID-19 by race and ethnicity in a national RWD during the early months of the pandemic.

OBJECTIVE: To describe differences by race and ethnicity in treatment patterns among hospitalized COVID-19 patients in the US from March-August 2020. METHODS: Among patients in de-identified Optum electronic health record data hospitalized with COVID-19 (March-August 2020), we estimated odds ratios of receiving COVID-19 treatments of interest (azithromycin, dexamethasone, hydroxychloroquine, remdesivir, and other steroids) at hospital admission, by race and ethnicity, after adjusting for key covariates of interest. RESULTS: After adjusting for key covariates, Black/African American patients were less likely to receive dexamethasone (adj. OR [95% CI]: 0.83 [0.71, 0.96]) and more likely to receive other steroids corticosteroids (adj. OR [95% CI]: 2.13 [1.90, 2.39]), relative to White patients. Hispanic/Latino patients were less likely to receive dexamethasone than Not Hispanic/Latino patients (adj. OR [95% CI]: 0.69 [0.58, 0.82]). CONCLUSIONS: Our findings suggest that COVID-19 treatments patients received in Optum varied by race and ethnicity after adjustment for other possible explanatory factors. In the face of rapidly evolving treatment landscapes, policies are needed to ensure equitable access to novel and repurposed therapeutics to avoid disparities in care by race and ethnicity.

Estimating pediatric inpatient medication use in the United States.

PURPOSE: We demonstrated the feasibility of developing national estimates of pediatric inpatient medication use by analyzing data from a large administrative database. METHODS: Pediatric inpatient data were extracted from Premier Perspective® database to calculate the prevalence of use of specific medications among hospitalized children in 2008. The database was validated by comparing characteristics to the HCUP KID sample of pediatric hospitalizations for 2006. Prevalence was calculated by categorizing patients as ever or never having received a specific drug. RESULTS: The 10 drugs administered in the most pediatric hospitalizations were acetaminophen, lidocaine, ampicillin, gentamicin, fentanyl, ibuprofen, morphine, ondansetron, ceftriaxone, and albuterol. CONCLUSIONS: Although the database is not a probability-based sample, it bears sufficient similarity to a probability-based sample of pediatric hospitalizations (HCUP KID) to serve as a starting point in developing national estimates of inpatient pediatric medication use. Over 500 drug entities were administered to hospitalized children, but most are used by small percentages of hospitalized patients. The small numbers of children using any one drug has implications for efforts to study efficacy and safety, describe off-label use, monitor adverse events, describe practice, and conduct comparative effectiveness research.