Literature DB >> 31340399

Visualizing Infection Surveillance Data for Policymaking Using Open Source Dashboarding.

Monika Maya Wahi1,2, Natasha Dukach2,3.   

Abstract

BACKGROUND: Health care-associated infections, specifically catheter-associated urinary tract infections (CAUTIs), can cause significant mortality and morbidity. However, the process of collecting CAUTI surveillance data, storing it, and visualizing the data to inform health policy has been fraught with challenges.
OBJECTIVES: No standard has been developed, so the objective of this article is to present a prototype solution for dashboarding public health surveillance data based on a real-life use-case for the purposes of enhancing clinical and policy-level decision-making.
METHODS: The solution was developed in open source software R, which allows for the creation of dashboard applications using the integrated development environment developed for R called RStudio, and a package for R called Rshiny. How the surveillance system was designed, why R was chosen, how the dashboard was developed, and how the dashboard features were programmed and function will be described.
RESULTS: The prototype dashboard includes multiple tabs for visualizing data, and allows the user to interact with the data by setting dynamic filters. Controls were used to facilitate the interaction between the user and application. Rshiny is reactive, in that when the user (e.g., clinician or policymaker) changes the parameters on the data, the application automatically updates the visualization as well as parameters available based on current filters.
CONCLUSION: The prototype dashboard has the potential to enhance clinical and policy-level decision-making because it facilitates interaction with the data that provides useful visualizations to provide such guidance. Georg Thieme Verlag KG Stuttgart · New York.

Entities:  

Mesh:

Year:  2019        PMID: 31340399      PMCID: PMC6656571          DOI: 10.1055/s-0039-1693649

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  17 in total

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3.  National surveillance of health care-associated infections in Egypt: Developing a sustainable program in a resource-limited country.

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4.  Secondary Analysis of an Electronic Surveillance System Combined with Multi-focal Interventions for Early Detection of Sepsis.

Authors:  Bonnie L Westra; Sean Landman; Pranjul Yadav; Michael Steinbach
Journal:  Appl Clin Inform       Date:  2017-01-18       Impact factor: 2.342

5.  Implementation of central venous catheter bundle in an intensive care unit in Kuwait: Effect on central line-associated bloodstream infections.

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Authors:  Somayeh Jahani-Sherafat; Maryam Razaghi; Victor D Rosenthal; Elahe Tajeddin; Simasadat Seyedjavadi; Marjan Rashidan; Masoud Alebouyeh; Maryam Rostampour; Arezo Haghi; Masoumeh Sayarbayat; Somayeh Farazmandian; Tahere Yarmohammadi; Fardokht K Arshadi; Nahid Mansouri; Mohammad R Sarbazi; Mariano Vilar; Mohammad R Zali
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7.  Early deaths in bloodstream infections: a population-based case series.

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9.  The World Health Organization STEPwise Approach to Noncommunicable Disease Risk-Factor Surveillance: Methods, Challenges, and Opportunities.

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10.  Hospital-acquired urinary tract infection point prevalence in Turkey: differences in risk factors among patient groups.

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Journal:  Appl Clin Inform       Date:  2020-08-26       Impact factor: 2.342

2.  Developing Dashboards to Address Children's Health Disparities in Ohio.

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3.  Tracking COVID-19 Inequities Across Jurisdictions Represented in the Big Cities Health Coalition (BCHC): The COVID-19 Health Inequities in BCHC Cities Dashboard.

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4.  Visualizing Opportunity Index Data Using a Dashboard Application: A Tool to Communicate Infant Mortality-Based Area Deprivation Index Information.

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Review 5.  U.S. COVID-19 State Government Public Dashboards: An Expert Review.

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6.  Environmental scan of COVID-19 infection dashboards in the Florida public school system.

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7.  CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database.

Authors:  Palash Sharma; Robert N Montgomery; Rasinio S Graves; Kayla Meyer; Suzanne L Hunt; Eric D Vidoni; Jonathan D Mahnken; Russell H Swerdlow; Jeffrey M Burns; Dinesh Pal Mudaranthakam
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  7 in total

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