Development of an interactive open source software application (RadaR) for infection management / antimicrobial stewardship

AbstractObjectivesAnalysing process and outcome measures for patients suspected of or having an infection in an entire hospital requires processing large datasets and accounting for numerous patient parameters and treatment guidelines. Rapid, reproducible and adaptable analyses usually need substantial technical expertise but can yield valuable insight for infection management and antimicrobial stewardship (AMS) teams. We describe a software application (RadaR - Rapid analysis of diagnostic and antimicrobial patterns in R) for infection management allowing user-friendly, intuitive and interactive analysis of large datasets without prior in-depth statistical or software knowledge.Methods and ResultsRadaR was built in R, an open source programming language, making it free to use and adaptable to different settings. Shiny, an additional open source package to implement web-application frameworks in R, was used to develop the application. RadaR was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions.RadaR visualizes analytical graphs and statistical summaries in an interactive manner within seconds. Users can filter large patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results, and outcome in length of stay. Results can easily be stratified and grouped to compare individually defined patient groups. Finally, datasets of identified patients / groups can be downloaded for further analyses.ConclusionRadaR facilitates understanding and communication of trends in antimicrobial use, diagnostic use and patient outcome by linking and aggregating individual patient data in one user-friendly application. RadaR can produce aggregated data analysis while preserving patients’ features in the data to adjust and stratify results in detail. AMS teams can use RadaR to identify areas, both for diagnostic and therapeutic procedures, within their institutions that might benefit from increased support and to target their interventions.

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Rapid Analysis of Diagnostic and Antimicrobial Patterns in R (RadaR): Interactive Open-Source Software App for Infection Management and Antimicrobial Stewardship (Preprint)

10.2196/preprints.12843 ◽

2018 ◽

Author(s):

Christian Friedemann Luz ◽

Matthijs S Berends ◽

Jan-Willem H Dik ◽

Mariëtte Lokate ◽

Céline Pulcini ◽

...

Keyword(s):

Open Source ◽

Antimicrobial Stewardship ◽

Rapid Analysis ◽

Large Datasets ◽

Design Development ◽

Tertiary Referral Hospital ◽

Targeted Interventions ◽

Infection Management ◽

Patient Groups ◽

Programming Knowledge

BACKGROUND Analyzing process and outcome measures for all patients diagnosed with an infection in a hospital, including those suspected of having an infection, requires not only processing of large datasets but also accounting for numerous patient parameters and guidelines. Substantial technical expertise is required to conduct such rapid, reproducible, and adaptable analyses; however, such analyses can yield valuable insights for infection management and antimicrobial stewardship (AMS) teams. OBJECTIVE The aim of this study was to present the design, development, and testing of RadaR (Rapid analysis of diagnostic and antimicrobial patterns in R), a software app for infection management, and to ascertain whether RadaR can facilitate user-friendly, intuitive, and interactive analyses of large datasets in the absence of prior in-depth software or programming knowledge. METHODS RadaR was built in the open-source programming language R, using Shiny, an additional package to implement Web-app frameworks in R. It was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions. RESULTS RadaR enabled visualization of analytical graphs and statistical summaries in a rapid and interactive manner. It allowed users to filter patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results including antimicrobial resistance, and outcome in length of stay. Furthermore, with RadaR, results can be stratified and grouped to compare defined patient groups on the basis of individual patient features. CONCLUSIONS AMS teams can use RadaR to identify areas within their institutions that might benefit from increased support and targeted interventions. It can be used for the assessment of diagnostic and therapeutic procedures and for visualizing and communicating analyses. RadaR demonstrated the feasibility of developing software tools for use in infection management and for AMS teams in an open-source approach, thus making it free to use and adaptable to different settings.

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Rapid Analysis of Diagnostic and Antimicrobial Patterns in R (RadaR): Interactive Open-Source Software App for Infection Management and Antimicrobial Stewardship

Journal of Medical Internet Research ◽

10.2196/12843 ◽

2019 ◽

Vol 21 (6) ◽

pp. e12843 ◽

Cited By ~ 4

Author(s):

Christian Friedemann Luz ◽

Matthijs S Berends ◽

Jan-Willem H Dik ◽

Mariëtte Lokate ◽

Céline Pulcini ◽

...

Keyword(s):

Open Source ◽

Antimicrobial Stewardship ◽

Open Source Software ◽

Rapid Analysis ◽

Infection Management

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Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqaa025 ◽

2020 ◽

Vol 2 (2) ◽

Cited By ~ 1

Author(s):

Frédéric Pont ◽

Marie Tosolini ◽

Qing Gao ◽

Marion Perrier ◽

Miguel Madrid-Mencía ◽

...

Keyword(s):

Flow Cytometry ◽

Single Cell ◽

Open Source ◽

Open Source Software ◽

Healthy Donor ◽

Large Datasets ◽

Integrated Analysis ◽

Functional Maturation ◽

User Friendly ◽

Cell Data

Abstract The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.

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Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

10.1101/843946 ◽

2019 ◽

Author(s):

Frédéric Pont ◽

Marie Tosolini ◽

Qing Gao ◽

Marion Perrier ◽

Miguel Madrid-Mencía ◽

...

Keyword(s):

Flow Cytometry ◽

Single Cell ◽

Open Source ◽

Open Source Software ◽

Healthy Donor ◽

Large Datasets ◽

Integrated Analysis ◽

Functional Maturation ◽

Healthy Donors ◽

User Friendly

ABSTRACTThe development of single cell transcriptomic technologies yields large datasets comprising multimodal informations such as transcriptomes and immunophenotypes. Currently however, there is no software to easily and simultaneously analyze both types of data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and phenotypes of functional maturation in peripheral T lymphocytes from healthy donors. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.

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mmpdb: An Open Source Matched Molecular Pair Platform for Large Multi-Property Datasets

10.26434/chemrxiv.5999375 ◽

2018 ◽

Author(s):

Andrew Dalke ◽

Jerome Hert ◽

Christian Kramer

Keyword(s):

Open Source ◽

Large Datasets ◽

Molecular Pair ◽

New Algorithms

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.

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MackDroid - An Android based Application to monitor devices

Journal of Communications Technology Electronics and Computer Science ◽

10.22385/jctecs.v9i0.130 ◽

2016 ◽

Vol 9 ◽

pp. 1

Author(s):

Maaz Sirkhot ◽

Ekta Sirwani ◽

Aishwarya Kourani ◽

Akshit Batheja ◽

Kajal Jethanand Jewani

Keyword(s):

Operating System ◽

Open Source ◽

Vital Role ◽

Mobile Users ◽

Android Application ◽

Web Page ◽

Technological World ◽

Monitoring Service ◽

User Friendly

In this technological world, smartphones can be considered as one of the most far-reaching inventions. It plays a vital role in connecting people socially. The number of mobile users using an Android based smartphone has increased rapidly since last few years resulting in organizations, cyber cell departments, government authorities feeling the need to monitor the activities on certain targeted devices in order to maintain proper functionality of their respective jobs. Also with the advent of smartphones, Android became one of the most popular and widely used Operating System. Its highlighting features are that it is user friendly, smartly designed, flexible, highly customizable and supports latest technologies like IoT. One of the features that makes it exclusive is that it is based on Linux and is Open Source for all the developers. This is the reason why our project Mackdroid is an Android based application that collects data from the remote device, stores it and displays on a PHP based web page. It is primarily a monitoring service that analyzes the contents and distributes it in various categories like Call Logs, Chats, Key logs, etc. Our project aims at developing an Android application that can be used to track, monitor, store and grab data from the device and store it on a server which can be accessed by the handler of the application.

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Faculty and Resident Physicians' Attitudes, Perceptions, and Knowledge about Antimicrobial Use and Resistance

Infection Control and Hospital Epidemiology ◽

10.1086/660761 ◽

2011 ◽

Vol 32 (7) ◽

pp. 714-718 ◽

Cited By ~ 50

Author(s):

Lilian Abbo ◽

Ronda Sinkowitz-Cochran ◽

Laura Smith ◽

Ella Ariza-Heredia ◽

Orlando Gómez-Marín ◽

...

Keyword(s):

Antimicrobial Stewardship ◽

Antimicrobial Use ◽

Inappropriate Use ◽

Resident Physicians

We surveyed faculty and residents to assess attitudes, perceptions, and knowledge about antimicrobial use and resistance. Most respondents were concerned about resistance when prescribing antibiotics and agreed that antibiotics are overused, that inappropriate use is professionally unethical, and that others, but not themselves, overprescribe antibiotics. Antimicrobial stewardship programs should capitalize on these perceptions.

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Increasing Voluntary Public Health Reporting to the NHSN Antimicrobial Use Option

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.877 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s296-s297

Author(s):

Heather Dubendris ◽

Amy Webb ◽

Melinda Neuhauser ◽

Arjun Srinivasan ◽

Wendy Wise ◽

...

Keyword(s):

Public Health ◽

Antimicrobial Stewardship ◽

Self Report ◽

Antimicrobial Use ◽

Health Departments ◽

Public Health Reporting ◽

Use Stage ◽

Education And Development ◽

Health Registry ◽

Over Time

Background: The CDC NHSN launched the Antimicrobial Use Option in 2011. The Antimicrobial Use Option allows users to implement risk-adjusted antimicrobial use benchmarking within- and between- facilities using the standardized antimicrobial administration ratio (SAAR) and to evaluate use over time. The SAAR can be used for public health surveillance and to guide an organization’s stewardship or quality improvement efforts. Methods: Antimicrobial Use Option enrollment grew through partner engagement, targeted education, and development of data benchmarking. We analyze enrollment over time and discuss key drivers of participation. Results: Initial 2011 Antimicrobial Use Option enrollment efforts awarded grant Funding: to 4 health departments. These health departments partnered with hospitals, which encouraged vendors to build infrastructure for electronic antimicrobial use reporting. CDC supported vendors through outreach and education. In 2012, with CDC support, Veterans’ Affairs (VA) Informatics, Decision-Enhancement, and Analytic Sciences Center and partners began implementation of Antimicrobial Use Option reporting and validation of submitted data. These early efforts led to enrollment of 64 facilities by 2014 (Fig. 1). As awareness of the antimicrobial use option grew, we focused on facility engagement and development of benchmark metrics. A second round of grant Funding: in 2015 supported submission to the Antimicrobial Use Option from additional facilities by Funding: a vendor, a healthcare system, and an antimicrobial stewardship network. In 2015, CMS recognized the Antimicrobial Use Option as a choice for public health registry reporting under Meaningful Use Stage 3, resulting in an increase in participating hospitals. Antimicrobial Use Option enrollment increased in 2015 (n = 120), coinciding with national prioritization of antimicrobial stewardship. In 2016, the SAAR, was released in NHSN. We leveraged the SAAR to encourage participation from additional facilities and began quarterly calls to encourage continued participation from existing users. In 2016, the Department of Defense began submitting data to the Antimicrobial Use Option, resulting in 207 facilities enrolled in 2016, which grew to 616 in 2017. As of November 2019, 12 vendors self-report submission capabilities and 1,470 facilities, of ~6,800 active NHSN participants, are enrolled in the Antimicrobial Use Option. Two states have passed requirements regulating Antimicrobial Use Option reporting with Tennessee’s requirement going into effect in 2021. Conclusions: The Antimicrobial Use Option offers evidence that collaboration with partners, and leveraging of benchmarking metrics available to a national surveillance system can lead to increased voluntary participation in surveillance of high-priority public health data. Moving forward, we will continue expanding analytic capabilities and partner engagement.Funding: NoneDisclosures: None

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mixl: An open-source R package for estimating complex choice models on large datasets

Journal of Choice Modelling ◽

10.1016/j.jocm.2021.100284 ◽

2021 ◽

Vol 39 ◽

pp. 100284

Author(s):

Joseph Molloy ◽

Felix Becker ◽

Basil Schmid ◽

Kay W. Axhausen

Keyword(s):

Open Source ◽

R Package ◽

Choice Models ◽

Large Datasets

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152. Applying A Difference-in-Difference Analysis to Assess Effect of Antimicrobial Stewardship Strategies on Changes in Antimicrobial Use

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.197 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S86-S86

Author(s):

Ann F Chou ◽

Yue Zhang ◽

Makoto M Jones ◽

Christopher J Graber ◽

Matthew B Goetz ◽

...

Keyword(s):

Antimicrobial Stewardship ◽

Clinical Pharmacist ◽

Antibiotic Use ◽

Feedback Mechanism ◽

Health Care Facilities ◽

Antimicrobial Use ◽

Time Points ◽

The Difference ◽

The Impact ◽

Over Time

Abstract Background About 30–50% of inpatient antimicrobial therapy is sub-optimal. Health care facilities have utilized various antimicrobial stewardship (AS) strategies to optimize appropriate antimicrobial use, improve health outcomes, and promote patient safety. However, little evidence exists to assess relationships between AS strategies and antimicrobial use. This study examined the impact of changes in AS strategies on antimicrobial use over time. Methods This study used data from the Veterans Affairs (VA) Healthcare Analysis & Informatics Group (HAIG) AS survey, administered at 130 VA facilities in 2012 and 2015, and antimicrobial utilization from VA Corporate Data Warehouse. Four AS strategies were examined: having an AS team, feedback mechanism on antimicrobial use, infectious diseases (ID) attending physicians, and clinical pharmacist on wards. Change in AS strategies were computed by taking the difference in the presence of a given strategy in a facility between 2012–2015. The outcome was the difference between antimicrobial use per 1000 patient days in 2012–2013 and 2015–2016. Employing multiple regression analysis, changes in antimicrobial use was estimated as a function of changes in AS strategies, controlling for ID human resources in and organizational complexity. Results Of the 4 strategies, only change in availability of AS teams had an impact on antimicrobial use. Compared to facilities with no AS teams at both time points, antibiotic use decreased by 63.9 uses per 1000 patient days in facilities that did not have a AS team in 2012 but implemented one in 2015 (p=0.0183). Facilities that had an AS team at both time points decreased use by 62.2 per 1000 patient days (p=0.0324). Conclusion The findings showed that AS teams reduced inpatient antibiotic use over time. While changes in having feedback on antimicrobial use and clinical pharmacist on wards showed reduced antimicrobial use between 2012–2015, the differences were not statistically significant. These strategies may already be a part of a comprehensive AS program and employed by AS teams. In further development of stewardship programs within healthcare organizations, the association between AS teams and antibiotic use should inform program design and implementation. Disclosures All Authors: No reported disclosures

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