Cross-sectional analysis of avoidable emergency department visits before and during the COVID-19 pandemic.

BACKGROUND: COVID-19 had a significant impact on Emergency Departments (ED) with early data suggesting an initial decline in avoidable ED visits. However, the sustained impact over time is unclear. In this study, we analyzed ED discharges over a two-year time period after the COVID-19 pandemic began and compared it with a control time period pre-pandemic to evaluate the difference in ED visit categories, including total, avoidable, and unavoidable visits. METHODS: This was a retrospective, cross-sectional study assessing the distribution of visits with ED discharges from two hospitals within a health system over a three-year time period (1/1/2019-12/31/2021). Visits were categorized using the expanded NYU-EDA algorithm modified to include COVID-19-related visits. Categories included: Emergent - Not Preventable/Avoidable, Emergent - Preventable/Avoidable, Emergent - Primary Care Treatable, Non-Emergent, Mental Health, Alcohol, Substance Abuse, Injury, and COVID-19. Chi-square testing was conducted to investigate differences within the time period before COVID-19 (1/1/2019-12/31/2019) and both initial (1/1/2020-12/31/2020) and delayed (1/1/2021-12/31/2021) COVID-19 time frames and ED visit categories, as well as post hoc testing using Fisher's exact tests with Bonferroni correction. ANOVA with post hoc Bonferroni testing was used to determine differences based on daily census for each ED visit category. RESULTS: A total of 228,010 ED discharges (Hospital #1 = 126,858; Hospital #2 = 101,152) met our inclusion criteria over the three-year period. There was a significant difference in the distribution of NYU-EDA categories between the two time periods (pre-COVID-19 versus during COVID-19) for the combined hospitals (p < 0.001), Hospital #1 (p < 0.001), and Hospital #2 (p < 0.001). When examining daily ED discharges, there was a decline in all categories from 2019 to 2020 except for "Emergent - Not Preventable/Avoidable" which remained stable and "Substance Abuse" which increased. From 2020 to 2021, there were no differences in ED avoidable visits. However, there were increases in discharged visits related to "Injuries", "Alcohol", and "Mental health" and a decrease in "COVID-19". CONCLUSION: Our study identified a sustained decline in discharged avoidable ED visits during the two years following the beginning of the COVID-19 pandemic, which was partially offset by the increase in COVID-19 visits. This work can help inform ED and healthcare systems in resource allocation, hospital staffing, and financial planning during future COVID-19 resurgences and pandemics.

A Standard-Based Citywide Health Information Exchange for Public Health in Response to COVID-19: Development Study.

BACKGROUND: Disease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards. OBJECTIVE: We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources. METHODS: Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems-a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds. RESULTS: Data from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. CONCLUSIONS: We described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.