scholarly journals Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design

2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Roosan Islam ◽  
Charlene R. Weir ◽  
Makoto Jones ◽  
Guilherme Del Fiol ◽  
Matthew H. Samore
Keyword(s):  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Clinical Reasoning ◽  
Clinical Decision ◽  
Support Design

Red Book Point-of-Care Clinical Decision Support Tool

2018 ◽  
Keyword(s):  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Health Care Professionals ◽  
Point Of Care ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Pediatric Health Care ◽  
Flip Chart

This convenient flip chart provides pediatric health care professionals with point-of-care guidance on the assessment, prevention, and treatment of childhood infectious diseases. https://shop.aap.org/red-book-pediatric-infectious-diseases-clinical-decision-support-chart/

scholarly journals Machine learning for clinical decision support in infectious diseases: a narrative review of current applications

2020 ◽  
Vol 26 (5) ◽  
pp. 584-595 ◽  
Author(s):  
N. Peiffer-Smadja ◽  
T.M. Rawson ◽  
R. Ahmad ◽  
A. Buchard ◽  
P. Georgiou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Narrative Review

scholarly journals Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science Approach

10.2196/19676 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e19676
Author(s):  
Katy E Trinkley ◽  
Michael G Kahn ◽  
Tellen D Bennett ◽  
Russell E Glasgow ◽  
Heather Haugen ◽  
...  
Keyword(s):  
Decision Support ◽  
Best Practices ◽  
Implementation Science ◽  
Clinical Decision Support ◽  
Integrated Approach ◽  
Clinical Decision ◽  
Lessons Learned ◽  
Support Design ◽  
Robust Implementation ◽  
Sustainability Model

Background Clinical decision support (CDS) design best practices are intended to provide a narrative representation of factors that influence the success of CDS tools. However, they provide incomplete direction on evidence-based implementation principles. Objective This study aims to describe an integrated approach toward applying an existing implementation science (IS) framework with CDS design best practices to improve the effectiveness, sustainability, and reproducibility of CDS implementations. Methods We selected the Practical Robust Implementation and Sustainability Model (PRISM) IS framework. We identified areas where PRISM and CDS design best practices complemented each other and defined methods to address each. Lessons learned from applying these methods were then used to further refine the integrated approach. Results Our integrated approach to applying PRISM with CDS design best practices consists of 5 key phases that iteratively interact and inform each other: multilevel stakeholder engagement, designing the CDS, design and usability testing, thoughtful deployment, and performance evaluation and maintenance. The approach is led by a dedicated implementation team that includes clinical informatics and analyst builder expertise. Conclusions Integrating PRISM with CDS design best practices extends user-centered design and accounts for the multilevel, interacting, and dynamic factors that influence CDS implementation in health care. Integrating PRISM with CDS design best practices synthesizes the many known contextual factors that can influence the success of CDS tools, thereby enhancing the reproducibility and sustainability of CDS implementations. Others can adapt this approach to their situation to maximize and sustain CDS implementation success.

Travel-screening documentation to enable the “Identify–Isolate–Inform” framework for emerging infectious diseases: It’s all in the details

2020 ◽  
Vol 41 (12) ◽  
pp. 1449-1451
Author(s):  
Sarimer M. Sánchez ◽  
Eileen F. Searle ◽  
David Rubins ◽  
Sayon Dutta ◽  
Winston Ware ◽  
...  
Keyword(s):  
Decision Support ◽  
Middle East ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Early Phase ◽  
Emerging Infectious Diseases ◽  
Clinical Decision ◽  
Middle East Respiratory Syndrome ◽  
Symptom Screening ◽  
Patients At Risk

AbstractThe early phase of the coronavirus disease 2019 (COVID-19) pandemic and ongoing efforts for mitigation underscore the importance of universal travel and symptom screening. We analyzed adherence to documentation of travel and symptom screening through a travel navigator tool with clinical decision support to identify patients at risk for Middle East Respiratory Syndrome.

scholarly journals Infectious disease outbreaks: how online clinical decision support could help

2018 ◽  
Vol 5 (4) ◽  
pp. 218-220
Author(s):  
Kieran Walsh
Keyword(s):  
Infectious Disease ◽  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Mobile Apps ◽  
Disease Outbreaks ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Clinical Decision Support Tool

This paper describes an evaluation of how doctors might use an online clinical decision support tool to improve the care that they would provide to patients with infectious disease and what features they would expect in such a clinical decision support tool. Semistructured interviews were conducted by telephone with doctors to evaluate the utility of a clinical decision support tool in helping them to improve the care that they would provide to patients with infectious disease and to assess the features that they would value in such a tool. The doctors were primarily interested in how they could use the tool to improve care. They were short of time and so needed to be able to access the content that they needed really quickly. They expected content that was both evidence based and current, and they used a range of devices to access the content. They used desktops, laptops, mobiles and sometimes mobile apps. Doctors view the utility of clinical decision support in the management of rare infectious diseases from a number of perspectives. However, they primarily see utility in the tools as a result of their capacity to improve clinical practice in infectious diseases.

Designing Clinical Decision Support Systems in Health Care

2011 ◽  
pp. 552-561
Author(s):  
Wullianallur Raghupathi
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Clinical Reasoning ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Rule Based ◽  
Viable Systems ◽  
Systemic Nature

Clinical decision support systems have historically focused on formal clinical reasoning. Most of the systems are rule-based and very few have become fully functional prototypes or commercially viable systems that can be deployed in real situations. The attempts to build large-scale systems without examining the intrinsic systemic nature of the clinical process have resulted in limited operational success and acceptance. The clinical function, another area of medical activity, has emerged rapidly offering potential for clinical decision support systems. This article discusses the systemic differences between clinical reasoning and clinical function and suggests that different design methodologies be used in the two domains. Clinical reasoning requires a holistic approach, such as an intelligent multiagent, incorporating the properties of softness, openness, complexity, flexibility, and generality of clinical decision support systems, while traditional rule-based approaches are sufficient for clinical function applications.

scholarly journals Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science Approach (Preprint)

2020 ◽  
Author(s):  
Katy E Trinkley ◽  
Michael G Kahn ◽  
Tellen D Bennett ◽  
Russell E Glasgow ◽  
Heather Haugen ◽  
...  
Keyword(s):  
Decision Support ◽  
Best Practices ◽  
Implementation Science ◽  
Clinical Decision Support ◽  
Integrated Approach ◽  
Clinical Decision ◽  
Lessons Learned ◽  
Support Design ◽  
Robust Implementation ◽  
Sustainability Model

BACKGROUND Clinical decision support (CDS) design best practices are intended to provide a narrative representation of factors that influence the success of CDS tools. However, they provide incomplete direction on evidence-based implementation principles. OBJECTIVE This study aims to describe an integrated approach toward applying an existing implementation science (IS) framework with CDS design best practices to improve the effectiveness, sustainability, and reproducibility of CDS implementations. METHODS We selected the Practical Robust Implementation and Sustainability Model (PRISM) IS framework. We identified areas where PRISM and CDS design best practices complemented each other and defined methods to address each. Lessons learned from applying these methods were then used to further refine the integrated approach. RESULTS Our integrated approach to applying PRISM with CDS design best practices consists of 5 key phases that iteratively interact and inform each other: multilevel stakeholder engagement, designing the CDS, design and usability testing, thoughtful deployment, and performance evaluation and maintenance. The approach is led by a dedicated implementation team that includes clinical informatics and analyst builder expertise. CONCLUSIONS Integrating PRISM with CDS design best practices extends user-centered design and accounts for the multilevel, interacting, and dynamic factors that influence CDS implementation in health care. Integrating PRISM with CDS design best practices synthesizes the many known contextual factors that can influence the success of CDS tools, thereby enhancing the reproducibility and sustainability of CDS implementations. Others can adapt this approach to their situation to maximize and sustain CDS implementation success.

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