Regional responsibility and coordination of appropriate inpatient care capacities for patients with COVID-19 - the German DISPENSE model

PLoS One. 2022 Jan 27;17(1):e0262491. doi: 10.1371/journal.pone.0262491. eCollection 2022.

Abstract

As of late 2019, the COVID-19 pandemic has been a challenge to health care systems worldwide. Rapidly rising local COVID-19 incidence rates, result in demand for high hospital and intensive care bed capacities on short notice. A detailed up-to-date regional surveillance of the dynamics of the pandemic, precise prediction of required inpatient capacities of care as well as a centralized coordination of the distribution of regional patient fluxes is needed to ensure optimal patient care. In March 2020, the German federal state of Saxony established three COVID-19 coordination centers located at each of its maximum care hospitals, namely the University Hospitals Dresden and Leipzig and the hospital Chemnitz. Each center has coordinated inpatient care facilities for the three regions East, Northwest and Southwest Saxony with 36, 18 and 29 hospital sites, respectively. Fed by daily data flows from local public health authorities capturing the dynamics of the pandemic as well as daily reports on regional inpatient care capacities, we established the information and prognosis tool DISPENSE. It provides a regional overview of the current pandemic situation combined with daily prognoses for up to seven days as well as outlooks for up to 14 days of bed requirements. The prognosis precision varies from 21% and 38% to 12% and 15% relative errors in normal ward and ICU bed demand, respectively, depending on the considered time period. The deployment of DISPENSE has had a major positive impact to stay alert for the second wave of the COVID-19 pandemic and to allocate resources as needed. The application of a mathematical model to forecast required bed capacities enabled concerted actions for patient allocation and strategic planning. The ad-hoc implementation of these tools substantiates the need of a detailed data basis that enables appropriate responses, both on regional scales in terms of clinic resource planning and on larger scales concerning political reactions to pandemic situations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19 / epidemiology
  • Critical Care
  • Delivery of Health Care
  • Forecasting / methods*
  • Germany / epidemiology
  • Hospitalization / statistics & numerical data
  • Hospitalization / trends*
  • Humans
  • Inpatients
  • Intensive Care Units
  • Models, Theoretical
  • Pandemics / statistics & numerical data
  • Patient Acceptance of Health Care / statistics & numerical data*
  • SARS-CoV-2 / pathogenicity

Grants and funding

The study was funded by the Saxon Ministry for Social Affairs. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Open Access Funding by the Publication Fund of the TU Dresden.