scholarly journals Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016

2017 ◽  
Vol 26 (01) ◽  
pp. 125-132
Author(s):  
R. A. Jenders
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Negative Impact ◽  
Clinical Care ◽  
Clinical Decision ◽  
Theory Approach ◽  
Research And Practice ◽  
Work Related ◽  
Active Research

Summary Introduction: Advances in clinical decision support (CDS) continue to evolve to support the goals of clinicians, policymakers, patients and professional organizations to improve clinical practice, patient safety, and the quality of care. Objectives: Identify key thematic areas or foci in research and practice involving clinical decision support during the 2015-2016 time period. Methods: Thematic analysis consistent with a grounded theory approach was applied in a targeted review of journal publications, the proceedings of key scientific conferences as well as activities in standards development organizations in order to identify the key themes underlying work related to CDS. Results: Ten key thematic areas were identified, including: 1) an emphasis on knowledge representation, with a focus on clinical practice guidelines; 2) various aspects of precision medicine, including the use of sensor and genomic data as well as big data; 3) efforts in quality improvement; 4) innovative uses of computer-based provider order entry (CPOE) systems, including relevant data displays; 5) expansion of CDS in various clinical settings; 6) patient-directed CDS; 7) understanding the potential negative impact of CDS; 8) obtaining structured data to drive CDS interventions; 9) the use of diagnostic decision support; and 10) the development and use of standards for CDS. Conclusions: Active research and practice in 2015-2016 continue to underscore the importance and broad utility of CDS for effecting change and improving the quality and outcome of clinical care.

scholarly journals Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016

2017 ◽  
Vol 26 (01) ◽  
pp. 125-132 ◽  
Author(s):  
R. A. Jenders
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Negative Impact ◽  
Clinical Care ◽  
Clinical Decision ◽  
Theory Approach ◽  
Research And Practice ◽  
Work Related ◽  
Active Research

Summary Introduction: Advances in clinical decision support (CDS) continue to evolve to support the goals of clinicians, policymakers, patients and professional organizations to improve clinical practice, patient safety, and the quality of care. Objectives: Identify key thematic areas or foci in research and practice involving clinical decision support during the 2015-2016 time period. Methods: Thematic analysis consistent with a grounded theory approach was applied in a targeted review of journal publications, the proceedings of key scientific conferences as well as activities in standards development organizations in order to identify the key themes underlying work related to CDS. Results: Ten key thematic areas were identified, including: 1) an emphasis on knowledge representation, with a focus on clinical practice guidelines; 2) various aspects of precision medicine, including the use of sensor and genomic data as well as big data; 3) efforts in quality improvement; 4) innovative uses of computer-based provider order entry (CPOE) systems, including relevant data displays; 5) expansion of CDS in various clinical settings; 6) patient-directed CDS; 7) understanding the potential negative impact of CDS; 8) obtaining structured data to drive CDS interventions; 9) the use of diagnostic decision support; and 10) the development and use of standards for CDS. Conclusions: Active research and practice in 2015-2016 continue to underscore the importance and broad utility of CDS for effecting change and improving the quality and outcome of clinical care.

scholarly journals XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study

10.2196/17512 ◽  
2020 ◽  
Vol 4 (10) ◽  
pp. e17512
Author(s):  
Ever Augusto Torres Silva ◽  
Sebastian Uribe ◽  
Jack Smith ◽  
Ivan Felipe Luna Gomez ◽  
Jose Fernando Florez-Arango
Keyword(s):  
Decision Support ◽  
Antenatal Care ◽  
Clinical Decision Support ◽  
Web Application ◽  
Clinical Care ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structure Design ◽  
Mobile App ◽  
Clinical Workflow

Background Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. Objective This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. Methods We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. Results In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. Conclusions Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.

Clinical Decision Support Systems Question and Answering

2018 ◽  
pp. 146-157 ◽  
Author(s):  
David José Murteira Mendes ◽  
Irene Pimenta Rodrigues ◽  
César Fonseca
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Medical Science ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Discourse Representation ◽  
Discourse Representation Theory

A question answering system to help clinical practitioners in a cardiovascular healthcare environment to interface clinical decision support systems can be built by using an extended discourse representation structure, CIDERS, and an ontology framework, Ontology for General Clinical Practice. CIDERS is an extension of the well-known DRT (discourse representation theory) structures, intending to go beyond single text representation to embrace the general clinical history of a given patient represented in an ontology. The Ontology for General Clinical Practice improves the currently available state-of-the-art ontologies for medical science and for the cardiovascular specialty. The chapter shows the scientific and philosophical reasons of its present dual structure with a deeply expressive (SHOIN) terminological base (TBox) and a highly computable (EL++) assertions knowledge base (ABox). To be able to use the current reasoning techniques and methodologies, the authors made a thorough inventory of biomedical ontologies currently available in OWL2 format.

Clinical Decision Support Systems Question and Answering

2021 ◽  
pp. 543-554
Author(s):  
David José Murteira Mendes ◽  
Irene Pimenta Rodrigues ◽  
César Fonseca
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Medical Science ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Discourse Representation ◽  
Discourse Representation Theory

A question answering system to help clinical practitioners in a cardiovascular healthcare environment to interface clinical decision support systems can be built by using an extended discourse representation structure, CIDERS, and an ontology framework, Ontology for General Clinical Practice. CIDERS is an extension of the well-known DRT (discourse representation theory) structures, intending to go beyond single text representation to embrace the general clinical history of a given patient represented in an ontology. The Ontology for General Clinical Practice improves the currently available state-of-the-art ontologies for medical science and for the cardiovascular specialty. The chapter shows the scientific and philosophical reasons of its present dual structure with a deeply expressive (SHOIN) terminological base (TBox) and a highly computable (EL++) assertions knowledge base (ABox). To be able to use the current reasoning techniques and methodologies, the authors made a thorough inventory of biomedical ontologies currently available in OWL2 format.

scholarly journals IT-Enabled Clinical Decision Support: An Empirical Study on Antecedents and Mechanisms

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Rogier van de Wetering
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Health Information ◽  
Clinical Decision Support ◽  
Information Exchange ◽  
Large Scale ◽  
Health Information Exchange ◽  
Clinical Decision ◽  
Future Research ◽  
Cross Sectional

Modern hospitals increasingly make use of innovations and information technology (IT) to improve workflow and patient’s clinical journey. Typical innovative solutions include patient records and clinical decision support systems to enhance the process of decision making by doctors and other healthcare practitioners. However, currently, it remains unclear how hospitals could facilitate and enable such a decision support capability in clinical practice. We ground our work on the resource-based view of the firm and put forth the notion of IT-enabled capabilities which emphasizes critical IT investment and capability development areas that hospitals could exploit in their quest to improve clinical decision support. We develop a research model that explains how “health information exchange” and enhanced “information capability” collectively drive a hospital’s “clinical decision support capability.” We used partial least squares path modeling on large-scale cross-sectional data from 720 European hospitals. Outcomes suggest that health information exchange positively impacts information capability. In turn, information capability complementary partially mediates the relationship between information exchange and clinical decision support. Hence, this research contributes to the literature on clinical decision support and provides valuable insights into how to support such innovative technologies and capabilities in clinical practice. We conclude with a discussion and conclusion. Also, we outline the inherent limitations of this study and outline directions for future research.

scholarly journals Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis

2019 ◽  
Vol 26 (1) ◽  
pp. 642-651
Author(s):  
Laura Schubel ◽  
Danielle L Mosby ◽  
Joseph Blumenthal ◽  
Muge Capan ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Human Factors ◽  
Organ Failure ◽  
Health Information Technology ◽  
Health Information ◽  
Clinical Decision Support ◽  
Clinical Care ◽  
Clinical Decision ◽  
Wide Range

In caring for patients with sepsis, the current structure of electronic health record systems allows clinical providers access to raw patient data without imputation of its significance. There are a wide range of sepsis alerts in clinical care that act as clinical decision support tools to assist in early recognition of sepsis; however, there are serious shortcomings in existing health information technology for alerting providers in a meaningful way. Little work has been done to evaluate and assess existing alerts using implementation and process outcomes associated with health information technology displays, specifically evaluating clinician preference and performance. We developed graphical model displays of two popular sepsis scoring systems, quick Sepsis Related Organ Failure Assessment and Predisposition, Infection, Response, Organ Failure, using human factors principles grounded in user-centered and interaction design. Models will be evaluated in a larger research effort to optimize alert design to improve the collective awareness of high-risk populations and develop a relevant point-of-care clinical decision support system for sepsis.

scholarly journals Estimating the impact of deploying an electronic clinical decision support tool as part of a national practice improvement project

2019 ◽  
Vol 26 (7) ◽  
pp. 630-636 ◽  
Author(s):  
Ellen K Kerns ◽  
Vincent S Staggs ◽  
Sarah D Fouquet ◽  
Russell J McCulloh
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Market Area ◽  
Improvement Project ◽  
Support Tool ◽  
Febrile Infant ◽  
The Impact ◽  
Electronic Clinical Decision Support

Abstract Objective Estimate the impact on clinical practice of using a mobile device–based electronic clinical decision support (mECDS) tool within a national standardization project. Materials and Methods An mECDS tool (app) was released as part of a change package to provide febrile infant management guidance to clinicians. App usage was analyzed using 2 measures: metric hits per case (metric-related screen view count divided by site-reported febrile infant cases in each designated market area [DMA] monthly) and cumulative prior metric hits per site (DMA metric hits summed from study month 1 until the month preceding the index, divided by sites in the DMA). For each metric, a mixed logistic regression model was fit to model site performance as a function of app usage. Results An increase of 200 cumulative prior metric hits per site was associated with increased odds of adherence to 3 metrics: appropriate admission (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.06-1.18), appropriate length of stay (OR, 1.20; 95% CI, 1.12-1.28), and inappropriate chest x-ray (OR, 0.82; 95% CI, 0.75-0.91). Ten additional metric hits per case were also associated: OR were 1.18 (95% CI, 1.02-1.36), 1.36 (95% CI, 1.14-1.62), and 0.74 (95% CI, 0.62-0.89). Discussion mECDS tools are increasingly being implemented, but their impact on clinical practice is poorly described. To our knowledge, although ecologic in nature, this report is the first to link clinical practice to mECDS use on a national scale and outside of an electronic health record. Conclusions mECDS use was associated with changes in adherence to targeted metrics. Future studies should seek to link mECDS usage more directly to clinical practice and assess other site-level factors.

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