Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units

Schurink, Carolina A. M.; Lucas, Peter; Hoepelman, I. M.; Bonten, Marc J. M.

doi:10.1016/s1473-3099(05)70115-8

Cited by 86 publications

(61 citation statements)

References 32 publications

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“…85 CDSSs can take many forms, including comprehensive computerized disease management systems that can integrate clinical data, medication orders, and laboratory and microbiology results to suggest anti-infective therapy and alert clinicians about potential suboptimal management of infections. [86][87][88][89] Several studies of rapid blood culture diagnostics report favorable outcomes when rapid test results are reported together with CDSSs that provide actionable guidance for clinicians through antimicrobial stewardship team oversight [90][91][92][93][94][95][96][97] or even templated comments contained within the result report. 84 Increasingly, electronic health records platforms such as Epic and Cerner are incorporating CDSSs to enhance antimicrobial stewardship.…”

Section: Treatment Implications Of Rapid Detection Of Crementioning

confidence: 99%

Clinical and laboratory considerations for the rapid detection of carbapenem-resistant Enterobacteriaceae

Banerjee

Humphries

2016

Virulence

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Carbapenem resistance among the Enterobacteriaceae has become a significant clinical and public health dilemma. Rapid administration of effective antimicrobials and implementation of supplemental infection control practices is required to both improve patient outcomes and limit the spread of these highly resistant organisms. However, carbapenem-resistant Enterobacteriaceae (CRE)-infected patients are predominantly identified by routine culture methods, which take days to perform. Rapid genomic and phenotypic methods are currently available to accelerate the identification of carbapenemaseproducing CRE. Effective use of these technologies is reliant on close collaboration between clinical microbiology, infection prevention, antimicrobial stewardship and infectious diseases specialists. This review discusses the performance characteristics of these technologies to date, and describes strategies for their optimal implementation.

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Section: Treatment Implications Of Rapid Detection Of Crementioning

confidence: 99%

Clinical and laboratory considerations for the rapid detection of carbapenem-resistant Enterobacteriaceae

Banerjee

Humphries

2016

Virulence

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“…The explosive growth of data requires them to learn and remember many details so they can prescribe the right medication, in the right amount, for the right patient. The possible approaches to dealing with this problem are by means of electronic medical records (EMR) [1][2][3][4][5] and clinical decision support systems (CDSS) [6][7][8][9][10]. Through knowledge discovery from these disciplines of medical informatics, the medical prescription process can be facilitated and hence the quality of prescription decisions can be improved [46].…”

Section: Introductionmentioning

confidence: 99%

A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

Ting

Kwok

Tsang

et al. 2011

Knowledge-Based Systems

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ObjectiveWith the increased complexity and uncertainty in drug information, issuing medical prescriptions has become a vexing issue. As many as 240,000 medicines are available on the market, so this paper proposes a novel approach to the issuing of medical prescriptions. The proposed process will provide general practitioners (GPs) with medication advice and suggest a range of medicines for specific medical conditions by taking into consideration the collective pattern as well as the individual preferences of physicians' prescription decisions. Methods and MaterialA hybrid approach is described that uses a combination of case-based reasoning (CBR) and Bayesian reasoning. In the CBR process, all the previous knowledge retrieved via similarity measures is made available for the reference of physicians as to what medicines have been prescribed (to a particular patient) in the past. After obtaining the results from CBR, Bayesian reasoning is then applied to model the prescription experience of all physicians within the organization. By comparing the two sets of results, more refined recommendations on a range of medicines are suggested along with the ranking for each recommendation. ResultsTo validate the proposed approach, a Hong Kong medical center was selected as a testing site. Through application of the hybrid approach in the medical center for a period of one month, the results demonstrated that the approach produced satisfactory performance in terms of user satisfaction, ease of use, flexibility and effectiveness. In addition, the proposed approach yields better results and a faster learning rate than This is the Pre-Published Version. 2 when either CBR or Bayesian reasoning are applied alone. ConclusionEven with the help of a decision support system, the current approach to anticipating what drugs are to be prescribed is not flexible enough to cater for individual preferences of GPs, and provides little support for managing complex and dynamic changes in drug information. Therefore, with the increase in the amount of information about drugs, it is extremely difficult for physicians to write a good prescription. By integrating CBR and Bayesian reasoning, the general practitioners' prescription practices can be retrieved and compared with the collective prescription experience as modeled by probabilistic reasoning. As a result, physicians can select the drugs which are supported by informed evidential decisions. That is, they can take into consideration the pattern of decisions made by other physicians in similar cases.

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“…Clinical decision support systems (CDSS) are commonly used in the infectious diseases field for diagnostic assistance, guidance in the prescription of antiinfectives, biosurveillance, and vector control (Global Infectious Disease and Epidemiology Network, http://www.gideononline.com, and [60,61,62,63,64,65,66,67]). Vocabulary resources, such as classifications of drug types, serve as a source of knowledge for CDSS.…”

Section: Uses Of Ontologies In Informatics-driven Research and Carementioning

confidence: 99%

Infectious Disease Ontology

Cowell

Smith

2009

Infectious Disease Informatics

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In the last decade, technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. More recently, ontologies have been shown to have significant benefits both for the analysis of data resulting from high-throughput technologies and for automated reasoning applications, and this has led to organized attempts to improve the structure and formal rigor of ontologies in ways that will better support computational analysis and reasoning. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology suite of interoperable ontology modules that together cover the entire infectious disease domain.

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Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units

Cited by 86 publications

References 32 publications

Clinical and laboratory considerations for the rapid detection of carbapenem-resistant Enterobacteriaceae

Clinical and laboratory considerations for the rapid detection of carbapenem-resistant Enterobacteriaceae

A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

Infectious Disease Ontology

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