Exploring Large Community- and Clinically-Generated Datasets to Understand Resilience Before and During the COVID-19 Pandemic

Karen A. Monsen, Robin R. Austin, Bhavana Goparaju, Robert Clarence Jones, Michelle A. Mathiason, Anna Pirsch, Milton Eder

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: To explore resilience in the context of whole-person health and the social determinants of health at the individual and community levels using large, standardized nursing datasets. Design: A retrospective, observational, correlational study of existing deidentified Health Insurance Portability and Accountability Act (HIPAA)-compliant data using the Omaha System and its equivalent, Simplified Omaha System Terms. Methods: We used three samples to explore for patterns of resilience: pre-COVID-19 community-generated data (N = 383), pre-COVID-19 clinical documentation data (N = 50,509), and during-COVID-19 community-generated data (N = 102). Community participants used the My Strengths + My Health (MSMH) app to generate the two community datasets. The clinical data were obtained from the Omaha System Data Collaborative. We operationalized resilience as Omaha System Status scores of 4 (minimal signs or symptoms) or 5 (no signs or symptoms) as a discrete strengths measure for each of 42 Omaha System problem concepts. We used visualization techniques and standard descriptive and inferential statistics for analysis. Findings: It was feasible to examine resilience, operationalized as strengths by problem concept, within existing Omaha System or Simplified Omaha System Terms (MSMH) data. We identified several patterns indicating strengths and resilience that were consistent with literature related to community connectedness for community participants, and sleep for individuals in the clinical data. Conclusions: When used consistently, the Omaha System within MSMH enabled robust data collection for a comprehensive, holistic assessment, resulting in better whole-person data including strengths, and enabled us to discover a potentially useful approach for defining resilience in new ways using standardized nursing data. Clinical Relevance: The notion that how we assess individuals and communities (i.e., the completeness of our assessments in relation to whole-person health) determines what we can know about resilience is seemingly in opposition to the critical need to decrease documentation burden, despite the potential to shift from a problem deficit-based assessment to one of strengths and resilience. However, a patient-facing comprehensive assessment that includes resilience and the social determinants of health can provide a transformative, whole-person platform for strengths-based care and population management.

Original languageEnglish (US)
Pages (from-to)262-269
Number of pages8
JournalJournal of Nursing Scholarship
Volume53
Issue number3
Early online dateApr 3 2021
DOIs
StatePublished - May 2021

Bibliographical note

Funding Information:
This study was supported by University of Minnesota Clinical Translational Sciences Institute COVID‐19 Seed Grant Award UL1 TR002494. Clinical Resources

Publisher Copyright:
© 2021 Sigma Theta Tau International

Keywords

  • Big data
  • COVID-19
  • Omaha system
  • community
  • resilience
  • social determinants of health
  • strengths

PubMed: MeSH publication types

  • Journal Article
  • Observational Study
  • Research Support, N.I.H., Extramural

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