Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries

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Abstract

Background

Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel.

Objective

This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly.

Methods

An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People’s Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam.

Results

We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.website/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository.

Conclusions

The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.

Related collections

Most cited references 38

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Will 10 Million People Die a Year due to Antimicrobial Resistance by 2050?

Marlieke E. A. de Kraker, Andrew Stewardson, Stephan Harbarth (2016)

Marlieke de Kraker and colleagues reflect on the need for better global estimates for the burden of antimicrobial resistance.

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A systematic review of barriers to data sharing in public health

Willem G. van Panhuis, Proma Paul, Claudia Emerson … (2014)

Background In the current information age, the use of data has become essential for decision making in public health at the local, national, and global level. Despite a global commitment to the use and sharing of public health data, this can be challenging in reality. No systematic framework or global operational guidelines have been created for data sharing in public health. Barriers at different levels have limited data sharing but have only been anecdotally discussed or in the context of specific case studies. Incomplete systematic evidence on the scope and variety of these barriers has limited opportunities to maximize the value and use of public health data for science and policy. Methods We conducted a systematic literature review of potential barriers to public health data sharing. Documents that described barriers to sharing of routinely collected public health data were eligible for inclusion and reviewed independently by a team of experts. We grouped identified barriers in a taxonomy for a focused international dialogue on solutions. Results Twenty potential barriers were identified and classified in six categories: technical, motivational, economic, political, legal and ethical. The first three categories are deeply rooted in well-known challenges of health information systems for which structural solutions have yet to be found; the last three have solutions that lie in an international dialogue aimed at generating consensus on policies and instruments for data sharing. Conclusions The simultaneous effect of multiple interacting barriers ranging from technical to intangible issues has greatly complicated advances in public health data sharing. A systematic framework of barriers to data sharing in public health will be essential to accelerate the use of valuable information for the global good. Electronic supplementary material The online version of this article (doi:10.1186/1471-2458-14-1144) contains supplementary material, which is available to authorized users.

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Data Sharing by Scientists: Practices and Perceptions

Carol Tenopir, Suzie Allard, Kimberly Douglass … (2011)

Background Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers – data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results. Methodology/Principal Findings A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing. Scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding. Most respondents are satisfied with their current processes for the initial and short-term parts of the data or research lifecycle (collecting their research data; searching for, describing or cataloging, analyzing, and short-term storage of their data) but are not satisfied with long-term data preservation. Many organizations do not provide support to their researchers for data management both in the short- and long-term. If certain conditions are met (such as formal citation and sharing reprints) respondents agree they are willing to share their data. There are also significant differences and approaches in data management practices based on primary funding agency, subject discipline, age, work focus, and world region. Conclusions/Significance Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves. New mandates for data management plans from NSF and other federal agencies and world-wide attention to the need to share and preserve data could lead to changes. Large scale programs, such as the NSF-sponsored DataNET (including projects like DataONE) will both bring attention and resources to the issue and make it easier for scientists to apply sound data management principles.

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Author and article information

Contributors

Cherry Lim:

ORCID: https://orcid.org/0000-0003-2555-6980

Mahidol Oxford Tropical Medicine Research UnitFaculty of Tropical MedicineMahidol University3rd Floor, 60th Anniversary Chalermprakiat Building420/6 Ratchawithi Rd, Ratchathewi DistrictBangkok, 10400Thailand66 2 203 6333 ext 7352cherry@tropmedres.ac

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J Med Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: October 2020

Publication date (Electronic): 2 October 2020

Volume: 22

Issue: 10

Electronic Location Identifier: e19762

Affiliations

[1 ] Mahidol Oxford Tropical Medicine Research Unit Faculty of Tropical Medicine Mahidol University Bangkok Thailand

[2 ] Nuffield Department of Medicine Centre for Tropical Medicine and Global Health University of Oxford Oxford United Kingdom

[3 ] Cambodia-Oxford Medical Research Unit Angkor Hospital for Children Siem Reap Cambodia

[4 ] Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit Mahosot Hospital Vientiane Lao People's Democratic Republic

[5 ] North Okkalapa General and Teaching Hospital Yangon Myanmar

[6 ] Patan Hospital Kathmandu Nepal

[7 ] Oxford University Clinical Research Unit Patan Hospital Kathmandu Nepal

[8 ] Sunpasitthiprasong Hospital Ubon Ratchathani Thailand

[9 ] Department of Infectious Diseases Centre for Clinical Infection and Diagnostic Research King's College London & Guy's and St Thomas' NHS Foundation Trust London United Kingdom

[10 ] Hospital for Tropical Diseases Ho Chi Minh City Vietnam

[11 ] Brigham and Women's Hospital and Harvard Medical School Boston, MA United States

[12 ] Myanmar Oxford Clinical Research Unit Yangon Myanmar

[13 ] Oxford University Clinical Research Unit Ho Chi Minh City Vietnam

[14 ] Shoklo Malaria Research Unit and Mahidol Oxford Tropical Medicine Research Unit Faculty of Tropical Medicine Mahidol University Mae Sot Thailand

[15 ] Department of Disease Control Bureau of Epidemiology Ministry of Public Health Nonthaburi Thailand

[16 ] Department of Disease Control Office of International Cooperation Ministry of Public Health Nonthaburi Thailand

[17 ] Division of Communicable Diseases Department of Disease Control Ministry of Public Health Nonthaburi Thailand

[18 ] Institute of Research and Education Development University of Health Sciences Vientiane Lao People's Democratic Republic

[19 ] Department of Medicine University of Cambridge Cambridge United Kingdom

Author notes

Corresponding Author: Cherry Lim cherry@ 123456tropmedres.ac

Author information

Cherry Lim https://orcid.org/0000-0003-2555-6980

Thyl Miliya https://orcid.org/0000-0002-7551-6189

Vilada Chansamouth https://orcid.org/0000-0003-3049-784X

Myint Thazin Aung https://orcid.org/0000-0001-7234-1427

Abhilasha Karkey https://orcid.org/0000-0002-5179-650X

Prapit Teparrukkul https://orcid.org/0000-0002-1075-4135

Batra Rahul https://orcid.org/0000-0003-0866-6571

Nguyen Phu Huong Lan https://orcid.org/0000-0002-9551-2302

John Stelling https://orcid.org/0000-0001-5719-7754

Paul Turner https://orcid.org/0000-0002-1013-7815

Elizabeth Ashley https://orcid.org/0000-0002-7620-4822

H Rogier van Doorn https://orcid.org/0000-0002-9807-1821

Htet Naing Lin https://orcid.org/0000-0002-5628-647X

Clare Ling https://orcid.org/0000-0002-5188-0349

Soawapak Hinjoy https://orcid.org/0000-0001-6127-2665

Sopon Iamsirithaworn https://orcid.org/0000-0002-6109-5002

Susanna Dunachie https://orcid.org/0000-0001-5665-6293

Tri Wangrangsimakul https://orcid.org/0000-0003-0430-5699

Viriya Hantrakun https://orcid.org/0000-0002-6727-3404

William Schilling https://orcid.org/0000-0002-6328-8748

Lam Minh Yen https://orcid.org/0000-0002-5126-110X

Le Van Tan https://orcid.org/0000-0002-1791-3901

Htay Htay Hlaing https://orcid.org/0000-0002-9317-8144

Mayfong Mayxay https://orcid.org/0000-0002-6056-4516

Manivanh Vongsouvath https://orcid.org/0000-0002-2249-7367

Buddha Basnyat https://orcid.org/0000-0002-1125-2743

Jonathan Edgeworth https://orcid.org/0000-0002-0881-2703

Sharon J Peacock https://orcid.org/0000-0002-1718-2782

Guy Thwaites https://orcid.org/0000-0002-2858-2087

Nicholas PJ Day https://orcid.org/0000-0003-2309-1171

Ben S Cooper https://orcid.org/0000-0002-9445-7217

Direk Limmathurotsakul https://orcid.org/0000-0001-7240-5320

Article

Publisher ID: v22i10e19762

DOI: 10.2196/19762

PMC ID: 7568216

PubMed ID: 33006570

SO-VID: fd430e76-94ee-49ca-ac7e-c97256ccb7d9

Copyright © ©Cherry Lim, Thyl Miliya, Vilada Chansamouth, Myint Thazin Aung, Abhilasha Karkey, Prapit Teparrukkul, Batra Rahul, Nguyen Phu Huong Lan, John Stelling, Paul Turner, Elizabeth Ashley, H Rogier van Doorn, Htet Naing Lin, Clare Ling, Soawapak Hinjoy, Sopon Iamsirithaworn, Susanna Dunachie, Tri Wangrangsimakul, Viriya Hantrakun, William Schilling, Lam Minh Yen, Le Van Tan, Htay Htay Hlaing, Mayfong Mayxay, Manivanh Vongsouvath, Buddha Basnyat, Jonathan Edgeworth, Sharon J Peacock, Guy Thwaites, Nicholas PJ Day, Ben S Cooper, Direk Limmathurotsakul. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.10.2020.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 3 May 2020

Date revision requested : 10 July 2020

Date revision received : 22 July 2020

Date accepted : 26 July 2020

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