Your browser doesn't support javascript.
Creating Surveillance Data Infrastructure Using Laboratory Analytics: Leveraging Visiun and Epic Systems to Support COVID-19 Pandemic Response.
Haghighi, Mehrvash; Adhimoolam, Dayanandan; Kwan, Ricky; Gitman, Melissa; McGuire, Maria; Mendu, Damodara R; Firpo-Betancourt, Adolfo; McBride, Russell B; Cordon-Cardo, Carlos; Craven, Catherine K.
  • Haghighi M; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Adhimoolam D; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Kwan R; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Gitman M; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • McGuire M; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Mendu DR; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Firpo-Betancourt A; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • McBride RB; Department of Pathology, The Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Cordon-Cardo C; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Craven CK; Department of Population Health Sciences, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
J Pathol Inform ; 13: 2, 2022.
Article in English | MEDLINE | ID: covidwho-1675005
ABSTRACT

BACKGROUND:

Pandemics are unpredictable and can rapidly spread. Proper planning and preparation for managing the impact of outbreaks is only achievable through continuous and systematic collection and analysis of health-related data. We describe our experience on how to comply with required reporting and develop a robust platform for surveillance data during an outbreak. MATERIALS AND

METHODS:

At Mount Sinai Health System, New York City, we applied Visiun, a laboratory analytics dashboard, to support main response activities. Epic System Inc.'s SlicerDicer application was used to develop clinical and research reports. We followed World Health Organization (WHO); federal and state guidelines; departmental policies; and expert consultation to create the framework.

RESULTS:

The developed dashboard integrated data from scattered sources are used to seamlessly distribute reports to key stakeholders. The main report categories included federal, state, laboratory, clinical, and research. The first two groups were created to meet government and state reporting requirements. The laboratory group was the most comprehensive category and included operational reports such as performance metrics, technician performance assessment, and analyzer metrics. The close monitoring of testing volumes and lab operational efficiency was essential to manage increasing demands and provide timely and accurate results. The clinical data reports were valuable for proper managing of medical surge requirements, such as healthcare workforce and medical supplies. The reports included in the research category were highly variable and depended on healthcare setting, research priorities, and available funding. We share a few examples of queries that were included in the designed framework for research projects.

CONCLUSION:

We reviewed here the key components of a conceptual surveillance framework required for a robust response to COVID-19 pandemics. We demonstrated leveraging a lab analytics dashboard, Visiun, combined with Epic reporting tools to function as a surveillance system. The framework could be used as a generic template for possible future outbreak events.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials / Systematic review/Meta Analysis Language: English Journal: J Pathol Inform Year: 2022 Document Type: Article Affiliation country: Jpi.jpi_54_21

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials / Systematic review/Meta Analysis Language: English Journal: J Pathol Inform Year: 2022 Document Type: Article Affiliation country: Jpi.jpi_54_21