The Influenza Data Summary: A Prototype Application for Visualizing National Influenza Activity

Podgornik, Michelle N.; Postema, Alicia S.; English, Roseanne; Uhde, Kristin Broome; Bloom, Steve; Hicks, Peter; McMurray, Paul; Copeland, J. R. M.; Brammer, Lynnette; Thompson, W.; Bresee, Joseph S.; Tokars, Jerome I.

doi:10.1007/978-3-540-72608-1_15

Cited by 4 publications

(4 citation statements)

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“…The recently created COVID-19 dashboards fall into the same category of applications [ 109 ]. Mapping also surfaced as a popular method for health resource monitoring, particularly for the planning of health care services [ 41 , 56 , 62 , 64 , 67 , 73 , 77 , 78 , 80 , 87 , 110 , 111 ].…”

Section: Discussionmentioning

confidence: 99%

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

Chishtie¹,

Bielska²,

Barrera³

et al. 2022

J Med Internet Res

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Background Simple visualizations in health research data, such as scatter plots, heat maps, and bar charts, typically present relationships between 2 variables. Interactive visualization methods allow for multiple related facets such as numerous risk factors to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big health care data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support. Objective The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods, and tools being used in population health and health services research (HSR) and their subdomains in the last 15 years, from January 1, 2005, to March 30, 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals, and co-design of applications. Methods We adapted standard scoping review guidelines with a peer-reviewed search strategy: 2 independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sectors. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and HSR, as well as their subdomains such as epidemiologic surveillance, health resource planning, access, and use and costs among diverse clinical and demographic populations. Results In this companion review to our earlier systematic synthesis of the literature on visual analytics applications, we present findings in 6 major themes of interactive visualization applications developed for 8 major problem categories. We found a wide application of interactive visualization methods, the major ones being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality, and studying medication use patterns. The data sources included mostly secondary administrative and electronic medical record data. In addition, at least two-thirds of the applications involved participatory co-design approaches while introducing a distinct category, embedded research, within co-design initiatives. These applications were in response to an identified need for data-driven insights into knowledge generation and decision support. We further discuss the opportunities stemming from the use of interactive visualization methods in studying global health; inequities, including social determinants of health; and other related areas. We also allude to the challenges in the uptake of these methods. Conclusions Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and HSR. Such applications are being fast used by academic and health care agencies for knowledge discovery, hypotheses generation, and decision support. International Registered Report Identifier (IRRID) RR2-10.2196/14019

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Section: Discussionmentioning

confidence: 99%

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

Chishtie¹,

Bielska²,

Barrera³

et al. 2022

J Med Internet Res

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“…The BioIntelligence Center, composed of several analysts, reviews the data daily and provides reports to state and local health departments and to the CDC Emergency Operations Center. A specialized Influenza Module [ 24 , 25 ] summarizes data from 3 traditional sources supplied by the Influenza Division at CDC [ 26 ], and from 5 automated sources via BioSense. The sub-syndrome designated "influenza-like illness" captures free-text data that mention "flu" or "influenza" and ICD-9CM codes of 487; however, the Influenza Module uses the following combination of sub-syndromes for influenza surveillance: influenza-like illness or (fever and cough) or (fever and upper respiratory infection).…”

Section: Discussionmentioning

confidence: 99%

“…While the same visit may be classified as showing >1 disease indicator, counts from these 2 categories are analyzed separately and not added together. BioSense, like other automated systems, can monitor seasonal influenza activity [ 24 , 25 ] and recognize large increases in visits for some general surveillance concepts; however, a more substantial contribution to public health practice awaits the ability to access data that is more specific than chief complaints and diagnoses. Nevertheless, to our knowledge this report presents the largest collation of automated surveillance data yet assembled.…”

Section: Discussionmentioning

confidence: 99%

Summary of data reported to CDC's national automated biosurveillance system, 2008

Tokars

English

McMurray

et al. 2010

BMC Med Inform Decis Mak

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BackgroundBioSense is the US national automated biosurveillance system. Data regarding chief complaints and diagnoses are automatically pre-processed into 11 broader syndromes (e.g., respiratory) and 78 narrower sub-syndromes (e.g., asthma). The objectives of this report are to present the types of illness and injury that can be studied using these data and the frequency of visits for the syndromes and sub-syndromes in the various data types; this information will facilitate use of the system and comparison with other systems.MethodsFor each major data source, we summarized information on the facilities, timeliness, patient demographics, and rates of visits for each syndrome and sub-syndrome.ResultsIn 2008, the primary data sources were the 333 US Department of Defense, 770 US Veterans Affairs, and 532 civilian hospital emergency department facilities. Median times from patient visit to record receipt at CDC were 2.2 days, 2.0 days, and 4 hours for these sources respectively. Among sub-syndromes, we summarize mean 2008 visit rates in 45 infectious disease categories, 11 injury categories, 7 chronic disease categories, and 15 other categories.ConclusionsWe present a systematic summary of data that is automatically available to public health departments for monitoring and responding to emergencies.

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“…StudyValues, n (%) SettingAlibrahim et al (2014) [38],Barrento and De Castro Neto (2017) [39], [40], BenRamadan et al (2017)[43], BenRamadan et al (2018)[44], Bjarnadottir et al (2016)[46],Brownstein et al (2010) [47],Henley et al (2018) [52],Hosseinpoor et al (2018) [53],Jia et al (2015) [56],Kirtland et al (2014) [58],Ko and Chang (2018) [59],Kubasek et al (2013) [61],Lanzarone et al (2016) [62], Lopez-DeFede et al (2011)[63],Mahler et al (2015) [64],Marshall et al (2017) [65], Mitrpanont et al (2017)[67],Moni et al (2015) [68],Monsen et al (2015) [69],Monsivais et al (2018) [70],Mozumder et al (2018) [71],Pachauri et al (2014)[73],Palmer et al (2019) [74],Pike et al (2017) [76],Podgornik et al (2007) [77],Pur et al (2007) …”

mentioning

confidence: 99%

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review (Preprint)

Chishtie¹,

Bielska²,

Barrera-Machuca³

et al. 2021

Preprint

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BACKGROUND Simple visualizations in health research data, such as scatter plots, heat maps and bar charts typically present relationships between two variables. Interactive visualization methods allow for multiple related facets, such as multiple risk factors, to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big healthcare data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support. OBJECTIVE The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods and tools being employed in population health and HSR, and their sub-domains in the last 15 years, from 1 January 2005 to 30 March 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals and co-design of applications. METHODS We adapted standard scoping review guidelines, with a peer reviewed search strategy, two independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sector. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and health services research, and their sub-domains such as epidemiologic surveillance, health resource planning, access, utilization and costs, among diverse clinical and demographic populations. RESULTS As a companion review to our earlier systematic synthesis of literature on visual analytic applications, we present findings in six major themes of interactive visualization applications developed for eight major problem categories. We found a wide application of interactive visualization methods, the major being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality and studying medication use patterns. Data sources included mostly secondary administrative and electronic medical record data. Additionally, at least two-third applications involved participatory co-design approaches, while introducing a distinct category ‘embedded research’ within co-design initiatives. These applications were in response to an identified need for data-driven insights towards knowledge generation and decision support. We further discuss the opportunities from the use of interactive visualization methods towards studying global health, inequities including social determinants of health, and other related areas. We also allude to the challenges in the uptake of these methods. CONCLUSIONS Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and health services research. Such applications are being fast utilized by academic and health care agencies for knowledge discovery, hypotheses generation and decision support. CLINICALTRIAL Protocol registration: RR1-10.2196/14019 Related first review: RR2-10.2196/14019 INTERNATIONAL REGISTERED REPORT RR2-10.2196/14019

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The Influenza Data Summary: A Prototype Application for Visualizing National Influenza Activity

Cited by 4 publications

References 3 publications

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review

Summary of data reported to CDC's national automated biosurveillance system, 2008

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review (Preprint)

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