Development of an Index to Assess COVID-19 Hospital Care Installed Capacity in the 450 Brazilian Health Regions

  1. Claudia Cristina de Aguiar Pereira
  2. Fernando Ramalho Gameleira Soares
  3. Carla Jorge Machado
  4. Gustavo Saraiva Frio
  5. Layana Costa Alves
  6. Fernando José Herkrath
  7. Rodrigo Tobias de Sousa Lima
  8. Ivana Cristina de Holanda Cunha Barreto
  9. Everton Nunes da Silva
  10. Anny Beatriz Costa Antony de Andrade
  11. Leonor Maria Pacheco Santos

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Abstract

Objective:

The article seeks to assess the Brazilian health system ability to respond to the challenges imposed by the coronavirus disease 2019 (COVID-19) pandemic by measuring the capacity of Brazilian hospitals to care for COVID-19 cases in the 450 Health Regions of the country during the year 2020. Hospital capacity refers to the availability of hospital beds, equipment, and human resources.

Methods:

We used longitudinal data from the National Register of Health Facilities (CNES) regarding the availability of resources necessary to care for patients with COVID-19 in inpatient facilities (public or private) from January to December 2020. Among the assessed resources are health professionals (certified nursing assistants, nurses, physical therapists, and doctors), hospital beds (clinical, intermediate care, and intensive care units), and medical equipment (computed tomography scanners, defibrillators, electrocardiograph monitors, ventilators, and resuscitators). In addition to conducting a descriptive analysis of absolute and relative data (per 10,000 users), a synthetic indicator named Installed Capacity Index (ICI) was calculated using the multivariate principal component analysis technique to assess hospital capacity. The indicator was further stratified into value ranges to understand its evolution.

Results:

There was an increase in all selected indicators between January and December 2020. It was possible to observe differences between the Northeast and North regions and the other regions of the country; most Health Regions presented low ICI. The ICI increased between the beginning and the end of 2020, but this evolution differed among Health Regions. The average increase in the ICI was more evident in the groups that already had considerably high baseline capacity in January 2020.

Conclusions:

It was possible to identify inequalities in the hospital capacity to care for patients affected by COVID -19 in the Health Regions of Brazil, with a concentration of low index values in the Northeast and North of the country. As the indicator increased throughout the year 2020, inequalities were also observed. The information here provided may be used by health authorities, providers, and managers in planning and adjusting for future COVID-19 care and in dimensioning the adequate supply of hospital beds, health-care professionals, and devices in Health Regions to reduce associated morbidity and mortality. We recommend that the ICI continue to be calculated in the coming months of the pandemic to monitor the capacity in the country’s Health Regions.

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  1. Version published to 10.1017/dmp.2022.214
  2. ScreenIT

    SciScore for 10.1101/2021.06.17.21259121: (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
    SentencesResources
    The statistical software used was SPSS 26.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results 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:
    It is vital to present some limitations identified in the present work. Despite the positive aspects of CNES as a data source, this system depends on self-completion and updating by the facilities, and for this reason, it can lead to errors or inaccuracies. Therefore, the study is limited to aspects of the reported supply of resources, and it does not reach the dimension of the demand for the use of these resources in the different Health Regions of the country. However, these difficulties sought to be overcome, given that the study used a relative measure to allow comparability of installed capacity between Health Regions.

    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.

    About SciScore

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  3. Version published to 10.1101/2021.06.17.21259121v1 on medRxiv