Trends in non-COVID-19 hospitalizations prior to and during the COVID-19 pandemic period, United States, 2017–2021
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Abstract
COVID-19 pandemic-related shifts in healthcare utilization, in combination with trends in non-COVID-19 disease transmission and non-pharmaceutical intervention use, had clear impacts on rates of hospitalization for infectious and chronic diseases. Using a U.S. national healthcare billing database, we estimated the monthly incidence rate ratio of hospitalizations between March 2020 and June 2021 according to 19 ICD-10 diagnostic chapters and 189 subchapters. The majority of primary diagnoses for hospitalization showed an immediate decline in incidence during March 2020. Hospitalizations for reproductive neoplasms, hypertension, and diabetes returned to pre-pandemic levels during late 2020 and early 2021, while others, like those for infectious respiratory disease, did not return to pre-pandemic levels during this period. Our assessment of subchapter-level primary hospitalization codes offers insight into trends among less frequent causes of hospitalization during the COVID-19 pandemic in the U.S.
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SciScore for 10.1101/2022.04.26.22274301: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Data queries and analyses were run in SQL and R version 4.0.2 using the packages data.table, DBI, dplyr, ggplot2, glue, gridExtra, lubridate, and readr. ggplot2suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The most likely explanation for the fluctuations in neoplasm diagnoses are disruptions to cancer screenings and subsequent diagnoses resulting from …
SciScore for 10.1101/2022.04.26.22274301: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Data queries and analyses were run in SQL and R version 4.0.2 using the packages data.table, DBI, dplyr, ggplot2, glue, gridExtra, lubridate, and readr. ggplot2suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The most likely explanation for the fluctuations in neoplasm diagnoses are disruptions to cancer screenings and subsequent diagnoses resulting from healthcare access limitations during the early pandemic period followed by an influx of patients in need of delayed cancer screenings and referrals [40–43]. Cluster C, as a whole, could be characterized as declining in relative incidence in correspondence with waves of COVID-19 occurring in the US, primarily March and April of 2020 and January 2021. This supports the hypothesis that these hospitalizations are primarily those that could be delayed during peak COVID-19 transmission cycles. Strengths and Limitations: Due to the passive nature of data reporting to the healthcare encounter billing clearinghouse and the differential reporting by the insurance payer, different payers may contribute to relative increases or decreases in disease rates in a manner that might not be reflective of true trends present across the US during the study period. Alternative explanations for the relative increases in disease diagnoses include payer catchment area redefinitions (and sudden inclusions of specialty facilities), reimbursement policies, and primary vs secondary diagnostic field coding practices. Our analysis was limited to primary diagnostic codes, thus the full range of diagnoses made during the study period were not captured and it is possible that IRR trends may vary if the full breadth of secondary codes were included for analysis. Th...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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