Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection

Lazarus, Ross; Kleinman, Ken; Dashevsky, Inna; DeMaria, Alfred; Platt, Richard

doi:10.1186/1471-2458-1-9

Cited by 141 publications

(110 citation statements)

References 10 publications

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“…For example a patient first visits her regular physician and then goes to the ED the next day. When all information comes from the same data provider, such as a health insurance company, it is sometimes possible to remove such duplicates [56], but it is a much more challenging problem when there are multiple data providers. Modifications to approaches using multiple data sources are needed to take the duplicate encounters by the same person into account.…”

Section: Open Research Questionsmentioning

confidence: 99%

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

Rolka

Burkom

Cooper

et al. 2007

Statistics in Medicine

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The objective of this report is to provide a basis to inform decisions about priorities for developing statistical research initiatives in the field of public health surveillance for emerging threats. Rapid information system advances have created a vast opportunity of secondary data sources for information to enhance the situational and health status awareness of populations. While the field of medical informatics and initiatives to standardize healthcare-seeking encounter records continue accelerating, it is necessary to adapt analytic and statistical methodologies to mature in sync with sibling information science technologies. One major right-of-passage for statistical inference is to advance the optimal application of analytic methodologies for using multiple data streams in detecting and characterizing public health population events of importance. This report first describes the problem in general and the data context, then delineates more specifically the practical nature of the problem and the related issues. Approaches currently applied to data with time-series, statistical process control and traditional inference concepts are described with examples in the section on Statistics and the Role of the Analytic Surveillance Data Monitor. These are the techniques that are providing substance to surveillance professionals and enabling use of multiple data streams. The next section describes use of a more complex approach that takes temporal as well as spatial dimensions into consideration for detection and situational awareness regarding event distributions. The space-time statistic has successfully been used to detect and track public health events of interest. Important research questions which are summarized at the end of this report are described in more detail with respect to the methodological application in the respective sections. This was thought to help elucidate the research requirements as summarized later in the report. Following the description of the space-time scan statistical application; this report extends to a less traditional area of promise given what has been observed in recent application of analytic methods. Bayesian networks (BNs) represent a conceptual step with advantages of flexibility for the public health surveillance community. Progression from traditional to the more extending statistical concepts in the context of the dynamic status quo of responsibility and challenge, leads to a conclusion consisting of categorical research needs. The report is structured by design to inform judgment about how to build on practical systems to achieve better analytic outcomes for public health surveillance. There are references to research issues throughout the sections with a summarization at the end, which also includes items previously unmentioned in the report.

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Section: Open Research Questionsmentioning

confidence: 99%

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

Rolka

Burkom

Cooper

et al. 2007

Statistics in Medicine

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show abstract

“…Although space-time detection schemes may sometimes prove to be more powerful at anomaly detection than purely temporal analysis [5,6], spatial data remains scarce. Today, many public 5205 in eastern Massachusetts and having health insurance through a major insurer in the region [14][15][16][17]. Specifically, the data set consists of counts of new episodes of illness by date of medical encounter and by syndrome during the five-year period of 1 January 2000-31 December 2004.…”

Section: Introductionmentioning

confidence: 99%

Multi‐syndrome analysis of time series using PCA: A new concept for outbreak investigation

Mohtashemi

Kleinman

Yih

2007

Statistics in Medicine

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To date, despite widespread availability of time series data on multiple syndromes, multivariate analysis of syndromic data remains under-explored. We present a non-parametric multivariate framework for early detection of temporal anomalies based on principal components analysis of historical data on multiple syndromes. We introduce simulated outbreaks of different shapes and magnitudes into the historical data, and compare the detection sensitivity and timeliness of the multi-syndrome detection method with those of uni-syndrome. We find that the multi-syndrome detection framework provides a powerful tool for identifying such designated abnormalities in the data and significantly improves upon the detection sensitivity and timeliness of uni-syndrome analysis. The proposed multivariate framework requires minimal preprocessing of the data and can be easily adopted in settings where temporal information on multiple syndromes are routinely collected and processed, and thus can be an integral component of real-time surveillance systems.

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“…Many examples of these systems can be found. [5][6][7][8][9][10][11][12][13][14][15][16][17] A comparison of some of the systems has also been published. 18 The strengths of these systems include large populations that can be placed under surveillance; previously, it was often the case that only those meeting reportable disease conditions were followed.…”

Section: Existing Prototype Systemsmentioning

confidence: 99%

Innovative surveillance methods for rapid detection of disease outbreaks and bioterrorism: results of an interagency workshop on health indicator surveillance

2003

Disaster Management & Response

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Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection

Abstract: Background: Gaps in disease surveillance capacity, particularly for emerging infections and bioterrorist attack, highlight a need for efficient, real time identification of diseases.

Cited by 141 publications

References 10 publications

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

Multi‐syndrome analysis of time series using PCA: A new concept for outbreak investigation

Innovative surveillance methods for rapid detection of disease outbreaks and bioterrorism: results of an interagency workshop on health indicator surveillance

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