scholarly journals Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision

2016 ◽  
Vol 25 (S 01) ◽  
pp. S103-S116 ◽  
Author(s):  
D. F. Sittig ◽  
A. Wright ◽  
B. Middleton
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Technology Implementation ◽  
Information Technologies ◽  
Healthcare Delivery ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Clinical Workflow ◽  
Health Maintenance ◽  
Effective Use

Summary Objective: The objective of this review is to summarize the state of the art of clinical decision support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide a vision of what CDS might look like 25 years hence, or circa 2040. Method: Informal review of the medical literature with iterative review and discussion among the authors to arrive at six axes (data, knowledge, inference, architecture and technology, implementation and integration, and users) to frame the review and discussion of selected barriers and facilitators to the effective use of CDS.Result: In each of the six axes, significant progress has been made. Key advances in structuring and encoding standardized data with an increased availability of data, development of knowledge bases for CDS, and improvement of capabilities to share knowledge artifacts, explosion of methods analyzing and inferring from clinical data, evolution of information technologies and architectures to facilitate the broad application of CDS, improvement of methods to implement CDS and integrate CDS into the clinical workflow, and increasing sophistication of the end-user, all have played a role in improving the effective use of CDS in healthcare delivery. Conclusion: CDS has evolved dramatically over the past 25 years and will likely evolve just as dramatically or more so over the next 25 years. Increasingly, the clinical encounter between a clinician and a patient will be supported by a wide variety of cognitive aides to support diagnosis, treatment, care-coordination, surveillance and prevention, and health maintenance or wellness.

scholarly journals Computerized Clinical Decision Support: Contributions from 2014

2015 ◽  
Vol 24 (01) ◽  
pp. 119-124 ◽  
Author(s):  
V. Koutkias ◽  
J. Bouaud ◽  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Information Technologies ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Editorial Team ◽  
Bibliographic Databases ◽  
Health Information Technologies ◽  
Selection Of

Summary Objective: To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results: Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions: As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

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.

scholarly journals Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges

2017 ◽  
Vol 25 (3) ◽  
pp. 1091-1104 ◽  
Author(s):  
Mirza Mansoor Baig ◽  
Hamid GholamHosseini ◽  
Aasia A Moqeem ◽  
Farhaan Mirza ◽  
Maria Lindén
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Hospital Care ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Smartphone Applications ◽  
Clinical Workflow ◽  
Healthcare Applications ◽  
Wide Range

Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians’ acceptability, as well as the low impact on the medical professionals’ decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.

Implementation of wide-scale pharmacogenetic testing in primary care

2019 ◽  
Vol 20 (12) ◽  
pp. 903-913 ◽  
Author(s):  
Natasha Petry ◽  
Jordan Baye ◽  
Aissa Aifaoui ◽  
Russell A Wilke ◽  
Roxana A Lupu ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Healthcare Delivery ◽  
Clinical Decision ◽  
Interdisciplinary Teams ◽  
Gene Interactions ◽  
Support Tools ◽  
Wide Scale ◽  
The Impact

The convergence of translational genomics and biomedical informatics has changed healthcare delivery. Institutional consortia have begun implementing lab testing and decision support for drug–gene interactions. Aggregate datasets are now revealing the impact of clinical decision support for drug–gene interactions. Given the pleiotropic nature of pharmacogenes, interdisciplinary teams and robust clinical decision support tools must exist within an informatics framework built to be flexible and capable of cross-talk between clinical specialties. Navigation of the challenges presented with the implementation of five steps to build a genetics program infrastructure requires the expertise of multiple healthcare professionals. Ultimately, this manuscript describes our efforts to place pharmacogenomics in the hands of the primary care provider integrating this information into a patient’s healthcare over their lifetime.

Effective use of a clinical decision-support system to advance antimicrobial stewardship

2012 ◽  
Vol 69 (18) ◽  
pp. 1543-1544 ◽  
Author(s):  
Jean Patel ◽  
John S. Esterly ◽  
Marc H. Scheetz ◽  
Maureen K. Bolon ◽  
Michael J. Postelnick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Antimicrobial Stewardship ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Effective Use

Knowledge Bases, Clinical Decision Support Systems, and Rapid Learning in Oncology

2015 ◽  
Vol 11 (2) ◽  
pp. e206-e211 ◽  
Author(s):  
Peter Paul Yu
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Rapid Learning ◽  
Types Of Knowledge ◽  
Different Types

This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into clinical decision support systems.

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