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Tan L, Ganapathy SS, Lim KK, Ahmad NA. Development and Utility of an Interactive Online Dashboard for Monitoring Data Collection and Data Processing During a School-Based Health Survey. JOURNAL OF PUBLIC HEALTH MANAGEMENT AND PRACTICE 2024; 30:605-609. [PMID: 38870377 DOI: 10.1097/phh.0000000000001906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2024]
Abstract
We built an interactive online dashboard using Google Looker Studio to monitor data collection and data processing activities during the Adolescent Health Survey (AHS) 2022, a large-scale nationwide survey conducted among school-going adolescents in Malaysia. Through user testing and training, refinements were made to the initial dashboard, resulting in a more streamlined and concise dashboard design. The dashboard comprised 2 pages that provided key metrics on the progress of data collection and data processing, respectively. The introduction of the dashboard enhanced the quality and ease of weekly progress reporting during meetings of the survey's central coordinating team, while its drill-down and filtering functionalities helped us detect arising issues early and supported collaborative problem-solving. Research teams coordinating comparable school-based health surveys are invited to duplicate the dashboard using Looker Studio's built-in "Make a copy" function and customize it further based on their country- or survey-specific requirements.
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Affiliation(s)
- LeeAnn Tan
- Author Affiliations: Institute for Public Health, National Institutes of Health, and Ministry of Health Malaysia, Setia Alam, Selangor, Malaysia
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Kazazian L, Silver R, Rao CY, Park M, Ciuba C, Farron M, Henao OL. A toolkit for planning and implementing acute febrile illness (AFI) surveillance. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003115. [PMID: 38635502 PMCID: PMC11025857 DOI: 10.1371/journal.pgph.0003115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/06/2024] [Indexed: 04/20/2024]
Abstract
Acute febrile illness (AFI) is a broad clinical syndrome with a wide range of potential infectious etiologies. The lack of accessible, standardized approaches to conducting AFI etiologic investigations has contributed to significant global gaps in data on the epidemiology of AFI. Based on lessons learned from years of supporting AFI sentinel surveillance worldwide, the U.S. Centers for Disease Control and Prevention developed the toolkit for planning and implementing AFI surveillance, described here. This toolkit provides a comprehensive yet flexible framework to guide researchers, public health officials, and other implementers in developing a strategy to identify and/or monitor the potential causes of AFI. The toolkit comprises a cohesive set of planning aids and supporting materials, including an implementation framework, generic protocol, several generic forms (including screening, case report, specimen collection and testing, and informed consent and assent), and a generic data dictionary. These materials incorporate key elements intended to harmonize approaches for AFI surveillance, as well as setting-specific components and considerations for adaptation based on local surveillance objectives and limitations. Appropriate adaptation and implementation of this toolkit may generate data that expand the global AFI knowledge base, strengthen countries' surveillance and laboratory capacity, and enhance outbreak detection and response efforts.
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Affiliation(s)
- Lilit Kazazian
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Rachel Silver
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Carol Y. Rao
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Michael Park
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Chandler Ciuba
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Madeline Farron
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Olga L. Henao
- Global Epidemiology, Laboratory, and Surveillance Branch, Division of Global Health Protection, Global Health Center, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Rabiei R, Bastani P, Ahmadi H, Dehghan S, Almasi S. Developing public health surveillance dashboards: a scoping review on the design principles. BMC Public Health 2024; 24:392. [PMID: 38321469 PMCID: PMC10848508 DOI: 10.1186/s12889-024-17841-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 01/22/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards. METHODOLOGY This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted. RESULTS Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure. CONCLUSION Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development.
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Affiliation(s)
- Reza Rabiei
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Peivand Bastani
- College of Business, Government and Law, Flinders University, Adelaide, SA, 5042, Australia
| | - Hossein Ahmadi
- Centre for Health Technology, Faculty of Health, University of Plymouth, Plymouth, PL4 8AA, UK
| | - Shirin Dehghan
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sohrab Almasi
- Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Schulze A, Brand F, Geppert J, Böl GF. Digital dashboards visualizing public health data: a systematic review. Front Public Health 2023; 11:999958. [PMID: 37213621 PMCID: PMC10192578 DOI: 10.3389/fpubh.2023.999958] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 04/05/2023] [Indexed: 05/23/2023] Open
Abstract
Introduction Public health is not only threatened by diseases, pandemics, or epidemics. It is also challenged by deficits in the communication of health information. The current COVID-19 pandemic demonstrates that impressively. One way to deliver scientific data such as epidemiological findings and forecasts on disease spread are dashboards. Considering the current relevance of dashboards for public risk and crisis communication, this systematic review examines the state of research on dashboards in the context of public health risks and diseases. Method Nine electronic databases where searched for peer-reviewed journal articles and conference proceedings. Included articles (n = 65) were screened and assessed by three independent reviewers. Through a methodological informed differentiation between descriptive studies and user studies, the review also assessed the quality of included user studies (n = 18) by use of the Mixed Methods Appraisal Tool (MMAT). Results 65 articles were assessed in regards to the public health issues addressed by the respective dashboards, as well as the data sources, functions and information visualizations employed by the different dashboards. Furthermore, the literature review sheds light on public health challenges and objectives and analyzes the extent to which user needs play a role in the development and evaluation of a dashboard. Overall, the literature review shows that studies that do not only describe the construction of a specific dashboard, but also evaluate its content in terms of different risk communication models or constructs (e.g., risk perception or health literacy) are comparatively rare. Furthermore, while some of the studies evaluate usability and corresponding metrics from the perspective of potential users, many of the studies are limited to a purely functionalistic evaluation of the dashboard by the respective development teams. Conclusion The results suggest that applied research on public health intervention tools like dashboards would gain in complexity through a theory-based integration of user-specific risk information needs. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=200178, identifier: CRD42020200178.
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Etiology of acute febrile illnesses in Southern China: Findings from a two-year sentinel surveillance project, 2017–2019. PLoS One 2022; 17:e0270586. [PMID: 35763515 PMCID: PMC9239456 DOI: 10.1371/journal.pone.0270586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 06/13/2022] [Indexed: 11/19/2022] Open
Abstract
Background Southern China is at risk for arborvirus disease transmission, including Zika virus and dengue. Patients often present to clinical care with non-specific acute febrile illnesses (AFI). To better describe the etiology of AFI, we implemented a two-year AFI surveillance project at five sentinel hospitals in Yunnan and Guangdong Provinces. Methods Between June 2017 and August 2019, we enrolled patients between 2 and 65 years of age presenting at one sentinel hospital in Mengla County, Yunnan, and four in Jiangmen City, Guangdong, with symptoms of AFI (acute onset of fever ≥ 37.5°C within the past 7 days) without respiratory symptoms or diarrhea. Demographic, epidemiologic, and clinical information was obtained and entered into a web-based AFI surveillance database. A custom TaqMan Array card (TAC) was used to test patients’ whole blood specimens for 27 different pathogens using real-time polymerase chain reaction assays. Results During the two-year project period, 836 patients were enrolled; 443 patients from Mengla County and 393 patients from Jiangmen City. The median age was 33 years [range: 2–65], and most were hospitalized [641, 77%]. Of 796 patients with valid TAC results, 341 (43%) were positive for at least one of the 10 unique pathogens detected. This included 205 (26%) patients positive for dengue virus, 60 (8%) for Orientia tsutsugamushi, and 42 (5%) for Coxiella burnetii. Ten patients (1%) in Jiangmen City tested positive for malaria, 8 of whom reported recent travel outside of China. TAC results were negative for 455 (57%) patients. None of the patients had a positive TAC detection for Zika virus. Conclusions The project detected variability in the etiology of AFI in Southern China and highlighted the importance of differential diagnosis. Dengue, O. tsutsugamushi, and C. burnetii were the most frequently identified pathogens among enrolled AFI patients. As a non-notifiable disease, the frequent detection of C. burnetii is noteworthy and warrants additional investigation. The project provided a framework for routine surveillance for persons presenting with AFI.
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Wang X, Rainey JJ, Goryoka GW, Liang Z, Wu S, Wen L, Duan R, Qin S, Huang H, Kharod G, Rao CY, Salyer SJ, Behravesh CB, Jing H. Using a One Health approach to prioritize zoonotic diseases in China, 2019. PLoS One 2021; 16:e0259706. [PMID: 34797849 PMCID: PMC8604330 DOI: 10.1371/journal.pone.0259706] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 10/26/2021] [Indexed: 12/24/2022] Open
Abstract
Background China is vulnerable to zoonotic disease transmission due to a large agricultural work force, sizable domestic livestock population, and a highly biodiverse ecology. To better address this threat, representatives from the human, animal, and environmental health sectors in China held a One Health Zoonotic Disease Prioritization (OHZDP) workshop in May 2019 to develop a list of priority zoonotic diseases for multisectoral, One Health collaboration. Methods Representatives used the OHZDP Process, developed by the US Centers for Disease Control and Prevention (US CDC), to prioritize zoonotic diseases for China. Representatives defined the criteria used for prioritization and determined questions and weights for each individual criterion. A review of English and Chinese literature was conducted prior to the workshop to collect disease specific information on prevalence, morbidity, mortality, and Disability-Adjusted Life Years (DALYs) from China and the Western Pacific Region for zoonotic diseases considered for prioritization. Results Thirty zoonotic diseases were evaluated for prioritization. Criteria selected included: 1) disease hazard/severity (case fatality rate) in humans, 2) epidemic scale and intensity (in humans and animals) in China, 3) economic impact, 4) prevention and control, and 5) social impact. Disease specific information was obtained from 792 articles (637 in English and 155 in Chinese) and subject matter experts for the prioritization process. Following discussion of the OHZDP Tool output among disease experts, five priority zoonotic diseases were identified for China: avian influenza, echinococcosis, rabies, plague, and brucellosis. Conclusion Representatives agreed on a list of five priority zoonotic diseases that can serve as a foundation to strengthen One Health collaboration for disease prevention and control in China; this list was developed prior to the emergence of SARS-CoV-2 and the COVID-19 pandemic. Next steps focused on establishing a multisectoral, One Health coordination mechanism, improving multisectoral linkages in laboratory testing and surveillance platforms, creating multisectoral preparedness and response plans, and increasing workforce capacity.
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Affiliation(s)
- Xin Wang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jeanette J. Rainey
- Division of Global Health Protection, United States Centers for Disease Control and Prevention, Beijing, China
| | - Grace W. Goryoka
- National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Zuoru Liang
- Center for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuyu Wu
- Division of Global Health Protection, United States Centers for Disease Control and Prevention, Beijing, China
| | - Liming Wen
- Yinchuan Animal Center for Disease Control and Prevention, Yinchuan, Ningxia, China
| | - Ran Duan
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuai Qin
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haodi Huang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Grishma Kharod
- National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Carol Y. Rao
- Division of Global Health Protection, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Stephanie J. Salyer
- Division of Global Health Protection, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Casey Barton Behravesh
- National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America
| | - Huaiqi Jing
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail:
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Fazaeli S, Khodaveisi T, Vakilzadeh AK, Yousefi M, Ariafar A, Shokoohizadeh M, Mohammad-Pour S. Development, Implementation, and User Evaluation of COVID-19 Dashboard in a Third-Level Hospital in Iran. Appl Clin Inform 2021; 12:1091-1100. [PMID: 34879405 PMCID: PMC8654579 DOI: 10.1055/s-0041-1740188] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/11/2021] [Indexed: 12/18/2022] Open
Abstract
INTRODUCTION The implementation of a dashboard enables managers to make informed and evidence-based decisions through data visualization and graphical presentation of information. This study aimed to design and implement a COVID-19 management dashboard in a third-level hospital in Mashhad, Iran. MATERIALS AND METHODS This descriptive developmental applied study was conducted in the second half of 2020 in three stages, using user-centered design methodology in four phases: (1) specification of the application context, (2) specification of requirements, (3) creation of design solutions, and (4) evaluation of designs. Data collection in each phase was performed through holding group discussions with the main users, nominal group techniques, interviews, and questioners. The dashboard prototype for the data display was designed using the Power BI Desktop software. Subsequently, users' comments were obtained using the focus group method and included in the dashboard. RESULTS In total, 25 indicators related to input, process, and output areas were identified based on the findings of the first stage. Moreover, eight items were introduced by participants as dashboard requirements. The dashboard was developed based on users' feedback and suggestions, such as the use of colors, reception of periodic and specific reports based on key performance indicators, and rearrangement of the components visible on the page. The result of the user satisfaction survey indicated their satisfaction with the developed dashboard. CONCLUSION The selection of proper criteria for the implementation of an effective dashboard is critical for the health care organization since they are designed with a high-tech and content-based environment. The dashboard in the present study was a successful combination of clinical and managerial indicators. Future studies should focus on the design and development of dashboards, as well as benchmarking by using data from several hospitals.
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Affiliation(s)
- Somayeh Fazaeli
- Medical Records and Health Information Technology Department, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Taleb Khodaveisi
- Department of Health Information Technology, School of Allied Medical Sciences, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Ali Khorsand Vakilzadeh
- Department of Complementary and Chinese Medicine, School of Persian and Complementary Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mehdi Yousefi
- Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Atousa Ariafar
- Imam Reza Educational, Research and Medical Institution, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mohsen Shokoohizadeh
- Medical Records and Health Information Technology Department, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Saeed Mohammad-Pour
- Department of Health Economics, School of Management and Medical Information, Iran University of Medical Sciences, Tehran, Iran
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Ivanković D, Barbazza E, Bos V, Brito Fernandes Ó, Jamieson Gilmore K, Jansen T, Kara P, Larrain N, Lu S, Meza-Torres B, Mulyanto J, Poldrugovac M, Rotar A, Wang S, Willmington C, Yang Y, Yelgezekova Z, Allin S, Klazinga N, Kringos D. Features Constituting Actionable COVID-19 Dashboards: Descriptive Assessment and Expert Appraisal of 158 Public Web-Based COVID-19 Dashboards. J Med Internet Res 2021; 23:e25682. [PMID: 33577467 PMCID: PMC7906125 DOI: 10.2196/25682] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/09/2020] [Accepted: 01/31/2021] [Indexed: 11/25/2022] Open
Abstract
Background Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. Objective The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (“why”), content and data (“what”), and analyses and displays (“how” they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. Methods We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. Results A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are “close to home”; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. Conclusions COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.
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Affiliation(s)
- Damir Ivanković
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Erica Barbazza
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Véronique Bos
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Óscar Brito Fernandes
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands.,Department of Health Economics, Corvinus University of Budapest, Budapest, Hungary
| | - Kendall Jamieson Gilmore
- Laboratorio Management e Sanità, Institute of Management and Department EMbeDS, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Tessa Jansen
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Pinar Kara
- Danish Center for Clinical Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.,Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
| | - Nicolas Larrain
- OptiMedis AG, Hamburg, Germany.,Hamburg Center for Health Economics, University of Hamburg, Hamburg, Germany
| | - Shan Lu
- School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bernardo Meza-Torres
- Department of Clinical and Experimental Medicine, University of Surrey, Surrey, United Kingdom.,Nuffield Department of Primary Care and Health Services, University of Oxford, Oxford, United Kingdom
| | - Joko Mulyanto
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands.,Department of Public Health and Community Medicine, Faculty of Medicine, Universitas Jenderal Soedirman, Purwokerto, Indonesia
| | - Mircha Poldrugovac
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Alexandru Rotar
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Sophie Wang
- OptiMedis AG, Hamburg, Germany.,Hamburg Center for Health Economics, University of Hamburg, Hamburg, Germany
| | - Claire Willmington
- Laboratorio Management e Sanità, Institute of Management and Department EMbeDS, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Yuanhang Yang
- Danish Center for Clinical Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.,Department of Psychiatry, Aalborg University Hospital, Aalborg, Denmark
| | | | - Sara Allin
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Niek Klazinga
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
| | - Dionne Kringos
- Department of Public and Occupational Health, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands
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Moolenaar RL, Cassell CH, Knight NW. Lessons Learned in Global Health Security Implementation. Health Secur 2020; 18:S4-S7. [PMID: 32004134 DOI: 10.1089/hs.2019.0157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- Ronald L Moolenaar
- Ronald L. Moolenaar, MD, is Associate Director for Science; Cynthia H. Cassell, PhD, is Lead for Applied Research; and Nancy W. Knight, MD, is Division Director; all in the Division of Global Health Protection, Center for Global Health, US Centers for Disease Control and Prevention, Atlanta, GA. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention
| | - Cynthia H Cassell
- Ronald L. Moolenaar, MD, is Associate Director for Science; Cynthia H. Cassell, PhD, is Lead for Applied Research; and Nancy W. Knight, MD, is Division Director; all in the Division of Global Health Protection, Center for Global Health, US Centers for Disease Control and Prevention, Atlanta, GA. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention
| | - Nancy W Knight
- Ronald L. Moolenaar, MD, is Associate Director for Science; Cynthia H. Cassell, PhD, is Lead for Applied Research; and Nancy W. Knight, MD, is Division Director; all in the Division of Global Health Protection, Center for Global Health, US Centers for Disease Control and Prevention, Atlanta, GA. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention
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Egli A, Schrenzel J, Greub G. Digital microbiology. Clin Microbiol Infect 2020; 26:1324-1331. [PMID: 32603804 PMCID: PMC7320868 DOI: 10.1016/j.cmi.2020.06.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 06/15/2020] [Accepted: 06/20/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient use of big data, machine learning, and artificial intelligence in clinical microbiology requires a profound understanding of data handling aspects. OBJECTIVE This review article summarizes the most important concepts of digital microbiology. The article gives microbiologists, clinicians and data scientists a viewpoint and practical examples along the diagnostic process. SOURCES We used peer-reviewed literature identified by a PubMed search for digitalization, machine learning, artificial intelligence and microbiology. CONTENT We describe the opportunities and challenges of digitalization in microbiological diagnostic processes with various examples. We also provide in this context key aspects of data structure and interoperability, as well as legal aspects. Finally, we outline the way for applications in a modern microbiology laboratory. IMPLICATIONS We predict that digitalization and the usage of machine learning will have a profound impact on the daily routine of laboratory staff. Along the analytical process, the most important steps should be identified, where digital technologies can be applied and provide a benefit. The education of all staff involved should be adapted to prepare for the advances in digital microbiology.
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Affiliation(s)
- A Egli
- Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland; Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
| | - J Schrenzel
- Laboratory of Bacteriology, University Hospitals of Geneva, Geneva, Switzerland
| | - G Greub
- Institute of Medical Microbiology, University Hospital Lausanne, Lausanne, Switzerland
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