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Figure.  Weekly Hospitalization Rates for 20 Most Common Diagnosis Groups in the Baseline Time Period
Weekly Hospitalization Rates for 20 Most Common Diagnosis Groups in the Baseline Time Period

COVID-19 indicates coronavirus disease 2019.

Table.  Weekly Hospitalization Rates Over Time Categorized by AHRQ Clinical Classifications Software Refined (CCSR) Tool
Weekly Hospitalization Rates Over Time Categorized by AHRQ Clinical Classifications Software Refined (CCSR) Tool
1.
Kansagra  AP, Goyal  MS, Hamilton  S, Albers  GW.  Collateral effect of Covid-19 on stroke evaluation in the United States.   N Engl J Med. 2020;383(4):400-401. doi:10.1056/NEJMc2014816PubMedGoogle ScholarCrossref
2.
Garcia  S, Albaghdadi  MS, Meraj  PM,  et al.  Reduction in ST-segment elevation cardiac catheterization laboratory activations in the United States during COVID-19 pandemic.   J Am Coll Cardiol. 2020;75(22):2871-2872. doi:10.1016/j.jacc.2020.04.011PubMedGoogle ScholarCrossref
3.
Baum  A, Schwartz  MD.  Admissions to Veterans Affairs hospitals for emergency conditions during the COVID-19 pandemic.   JAMA. 2020;324(1):96-99. doi:10.1001/jama.2020.9972PubMedGoogle ScholarCrossref
4.
Petrilli  CM, Jones  SA, Yang  J,  et al.  Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.   BMJ. 2020;369:m1966. doi:10.1136/bmj.m1966PubMedGoogle ScholarCrossref
5.
Healthcare Cost and Utilization Project. Clinical Classifications Software Refined (CCSR) for ICD-10-CM diagnoses. Accessed May 26, 2020. https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp
6.
Woolhandler  S, Himmelstein  DU.  Intersecting US epidemics: COVID-19 and lack of health insurance.   Ann Intern Med. 2020;173(1):63-64. doi:10.7326/M20-1491PubMedGoogle ScholarCrossref
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    EXPAND ALL
    Why is Care for Serious Non-COVID-19 Conditions Seemingly Deferred?
    Michael McAleer, PhD(Econometrics),Queen's | Asia University, Taiwan
    The observed significant deferral of care patterns, as evidenced in non-COVID-19 hospitalizations for chronic disease and acute conditions in 4 hospitals in the NYU Langone Health system from 1 March 1 to 9 May for each of the years 2018, 2019, and 2020, is explained by one or more of the following seven alternative explanations:

    (1) lost health insurance;

    (2) increased threshold for hospitalization by clinicians;

    (3) changes in patient lifestyle; 

    (4) self-management in the context of social distancing'

    (5) prior overuse of hospitalization;

    (6) improved self-management;

    (7) imperfect capture of COVID-19 and other
    diagnoses.

    Additional reasons include:

    (8) lack of trust in the healthcare system with the onset of COVID-19;

    (9) negative social media pronouncements regarding hospitalization and surgery;

    (10) increased threshold for hospitalization by patients;

    (11) increased health insurance costs;

    (12) changes in coverage for pre-existing conditions.
    CONFLICT OF INTEREST: None Reported
    READ MORE
    Research Letter
    October 26, 2020

    Hospitalizations for Chronic Disease and Acute Conditions in the Time of COVID-19

    Author Affiliations
    • 1Division of Healthcare Delivery Science, Department of Population Health, NYU Grossman School of Medicine, New York, New York
    • 2Division of General Internal Medicine and Clinical Innovation, Department of Medicine, NYU Grossman School of Medicine, New York, New York
    • 3Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
    • 4Division of Gastroenterology, Department of Medicine, NYU Grossman School of Medicine, New York, New York
    JAMA Intern Med. Published online October 26, 2020. doi:10.1001/jamainternmed.2020.3978

    Concurrent with surges in hospitalizations for coronavirus disease 2019 (COVID-19), there has been evidence of decreased presentation for acute conditions, including myocardial infarction and stroke.1-3 We examined the frequency of hospitalization for all non–COVID-19-related conditions in a health system at an epicenter of the COVID-19 pandemic.4

    Methods

    We performed a retrospective study of admissions to 4 hospitals in the NYU Langone Health system between March 1 and May 9 in years 2018, 2019, and 2020. We excluded hospitalizations for COVID-19 using discharge diagnosis codes and hospitalizations with a discharge date after May 24 in each year. Weekly admission rates were examined for 4 time periods defined by the volume of COVID-19 hospitalizations: pre–COVID-19 (March 1 to May 9, 2018, and March 1 to May 9, 2019), early COVID-19 (March 1 to March 21, 2020), peak COVID-19 (March 22 to April 11, 2020), and late COVID-19 (April 12 to May 9, 2020). We categorized each hospitalization into both system-level (eg, digestive diseases) and diagnosis-level (eg, appendicitis) classifications using principal discharge diagnoses and software from the Agency for Healthcare Research and Quality.5 We examined weekly hospitalization rates for each time period for each system-level category and for the 20 most frequent diagnoses during the pre–COVID-19 period. We used incidence rate ratios to test for differences in hospitalization rates between periods and considered significance at P = .001, using the Šidák correction for multiple comparisons. Analyses were performed using R, version 4.0.1 (The R Foundation). The study was approved by the NYU Grossman School of Medicine Institutional Review Board, which approved a waiver of consent based on federal regulation 45 CFR §46.

    Results

    Between March 1 and May 9, 2020, there were 3657 non–COVID-19 hospitalizations, compared with 5368 and 6411 hospitalizations during the same period in 2018 and 2019, respectively. Hospitalization rates in the early COVID-19 period were similar to baseline (604.3 vs 584.5 per week; P = .19), decreased during the peak COVID-19 period (247.0 per week; P < .001), and slightly increased in the late COVID-19 period (309.3 per week; P < .001 vs peak COVID-19). Hospitalization rates decreased across all system categories during the peak COVID-19 period (Table). Similarly, we found a significant decline (all P < .001) in hospitalizations during the peak COVID-19 period for the following common diagnoses: septicemia (25.3 vs 51.1 per week), heart failure (9.0 vs 25.6), myocardial infarction (4.0 vs 16.3), cerebral infarction (7.0 vs 14.7), biliary tract disease (3.0 vs 11.7), epilepsy (3.7 vs 11.5), skin infections (2.7 vs 11.5), complications of care (3.7 vs 10.7), cardiac dysrhythmias (2.3 vs 10.6), appendicitis (2.7 vs 8.6), and chronic obstructive pulmonary disease (COPD; 2.3 vs 8.6) (Figure). In the late COVID-19 period, hospitalizations for myocardial infarction, biliary tract disease, and appendicitis began to recover—though not at a level of significance when accounting for multiple comparisons—while hospitalizations for septicemia, diabetes, and COPD did not (Figure).

    Discussion

    We found a substantial decrease in the number of non–COVID-19 hospitalizations across a range of diagnoses during the peak COVID-19 period. The decrease was observed for exacerbations of chronic conditions (heart failure, COPD), acute medical events that typically require inpatient management (myocardial infarction, appendicitis), and injuries. Given the breadth of these diagnoses, the causes for the decrease are likely multifactorial and include patient avoidance of emergency care for fear of COVID-192 or because of lost health insurance,6 increased threshold for hospitalization by clinicians, and changes in patient lifestyle and self-management in the context of social distancing. Notably, while hospitalizations for acute events began recovering in the late COVID-19 period, many of those related to chronic diseases generally did not. The implications of the decreases in hospitalizations for chronic disease are concerning for the possibility that sick patients are not obtaining necessary hospital care; alternatively, this trend could suggest prior overuse of hospitalization or improved self-management.

    Study limitations include use of a single health system and reliance on diagnostic codes, which have imperfect capture of both COVID-19 and other diagnoses. However, we used a standard approach for classifying diagnoses.5

    In an epicenter of COVID-19, we found that the pandemic was associated with substantial changes in hospitalization patterns for non–COVID-19 conditions. The long-term effects of hospitalization reductions on both patient outcomes and the health care system remain to be seen.

    Back to top
    Article Information

    Accepted for Publication: July 2, 2020.

    Published Online: October 26, 2020. doi:10.1001/jamainternmed.2020.3978

    Corresponding Author: Saul Blecker, MD, MHS, Division of Healthcare Delivery Science, Department of Population Health, NYU Grossman School of Medicine, 227 E 30th St, 6th Floor, New York, NY 10016 (saul.blecker@nyulangone.org).

    Author Contributions: Drs Blecker and Petrilli had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Study concept and design: Blecker, Jones, Petrilli, Admon, Francois, Horwitz.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Blecker, Jones, Petrilli, Francois.

    Critical revision of the manuscript for important intellectual content: Jones, Petrilli, Admon, Weerahandi, Francois, Horwitz.

    Statistical analysis: Jones, Petrilli, Admon, Horwitz.

    Administrative, technical, or material support: Blecker, Petrilli, Admon, Weerahandi, Francois, Horwitz.

    Study supervision: Francois, Horwitz.

    Conflict of Interest Disclosures: Dr Admon reported receiving grants from the National Heart, Lung, and Blood Institute during the conduct of the study. Dr Weerahandi reported receiving grants from the National Institutes of Health/National Heart, Lung, and Blood Institute outside the submitted work. No other disclosures were reported.

    Additional Contributions: We thank Harish Rajagopalan, MS, NYU Langone Health, New York, New York, for assistance with data extraction. No additional compensation was provided for this contribution.

    References
    1.
    Kansagra  AP, Goyal  MS, Hamilton  S, Albers  GW.  Collateral effect of Covid-19 on stroke evaluation in the United States.   N Engl J Med. 2020;383(4):400-401. doi:10.1056/NEJMc2014816PubMedGoogle ScholarCrossref
    2.
    Garcia  S, Albaghdadi  MS, Meraj  PM,  et al.  Reduction in ST-segment elevation cardiac catheterization laboratory activations in the United States during COVID-19 pandemic.   J Am Coll Cardiol. 2020;75(22):2871-2872. doi:10.1016/j.jacc.2020.04.011PubMedGoogle ScholarCrossref
    3.
    Baum  A, Schwartz  MD.  Admissions to Veterans Affairs hospitals for emergency conditions during the COVID-19 pandemic.   JAMA. 2020;324(1):96-99. doi:10.1001/jama.2020.9972PubMedGoogle ScholarCrossref
    4.
    Petrilli  CM, Jones  SA, Yang  J,  et al.  Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.   BMJ. 2020;369:m1966. doi:10.1136/bmj.m1966PubMedGoogle ScholarCrossref
    5.
    Healthcare Cost and Utilization Project. Clinical Classifications Software Refined (CCSR) for ICD-10-CM diagnoses. Accessed May 26, 2020. https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp
    6.
    Woolhandler  S, Himmelstein  DU.  Intersecting US epidemics: COVID-19 and lack of health insurance.   Ann Intern Med. 2020;173(1):63-64. doi:10.7326/M20-1491PubMedGoogle ScholarCrossref
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