scholarly journals The Digital Twin: Modular Model-Based Approach to Personalized Medicine

2021 ◽  
Vol 7 (2) ◽  
pp. 223-226
Author(s):  
Jan Gaebel ◽  
Johannes Keller ◽  
Daniel Schneider ◽  
Adrian Lindenmeyer ◽  
Thomas Neumuth ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Medical Knowledge ◽  
Clinical Decision ◽  
Heterogeneous Data ◽  
Clinical Decisions ◽  
Web Based ◽  
Digital Twin ◽  
Flexible System ◽  
Description Framework

Abstract To overcome obstacles and complexity of decision making in clinical oncology, we propose an integrated clinical decision support approach; the Digital Twin. We analyse the reasons for frustration in applying clinical decision support and provide a multi-levelled approach to implementing a flexible system to support and strengthen clinical decisions. Describing medical patterns and contexts with Resource Description Framework (RDF) allows for standardised way of connecting medical knowledge and processing modules. Having flexible web-based interfaces integrated a multitude of heterogeneous data processing systems to either make clinical data available altogether, or provide calculations and assessments. Transition of the Digital Twin to clinical practice promises effective assistance and safer clinical decisions.

scholarly journals Challenges involved in establishing a web-based clinical decision support tool in community health centers

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 100488
Author(s):  
Rachel Gold ◽  
Mary Middendorf ◽  
John Heintzman ◽  
Joan Nelson ◽  
Patrick O'Connor ◽  
...  
Keyword(s):  
Decision Support ◽  
Community Health ◽  
Clinical Decision Support ◽  
Community Health Centers ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Health Centers ◽  
Web Based ◽  
Support Tool ◽  
Clinical Decision Support Tool

Clinical Decision Support Systems

2021 ◽  
pp. 1-7
Author(s):  
Andreas Teufel ◽  
Harald Binder
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Support Systems ◽  
Medical Knowledge ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Current Status ◽  
Care Providers

<b><i>Background:</i></b> By combining up-to-date medical knowledge and steadily increasing patient data, a new level of medical care can emerge. <b><i>Summary and Key Messages:</i></b> Clinical decision support systems (CDSSs) are an arising solution to handling rich data and providing them to health care providers in order to improve diagnosis and treatment. However, despite promising examples in many areas, substantial evidence for a thorough benefit of these support solutions is lacking. This may be due to a lack of general frameworks and diverse health systems around the globe. We therefore summarize the current status of CDSSs in medicine but also discuss potential limitations that need to be overcome in order to further foster future development and acceptance.

scholarly journals Mobilising computable biomedical knowledge: challenges for clinical decision support from a medical knowledge provider

2020 ◽  
Vol 27 (2) ◽  
pp. e100121 ◽  
Author(s):  
Kieran Walsh ◽  
Chris Wroe
Keyword(s):  
Decision Support ◽  
Problem Solving ◽  
Patient Outcomes ◽  
Clinical Decision Support ◽  
Healthcare Professionals ◽  
Medical Knowledge ◽  
Clinical Decision ◽  
Biomedical Knowledge ◽  
Procedural Skills ◽  
Safety Standards

IntroductionThis paper summarises a talk given at the first UK workshop on mobilising computable biomedical knowledge on 29 October 2019 in London. It examines challenges in mobilising computable biomedical knowledge for clinical decision support from the perspective of a medical knowledge provider.MethodsWe developed the themes outlined below after personally reflecting on the challenges that we have encountered in this field and after considering the barriers that knowledge providers face in ensuring that their content is accessed and used by healthcare professionals. We further developed the themes after discussing them with delegates at the workshop and listening to their feedback.DiscussionThere are many challenges in mobilising computable knowledge for clinical decision support from the perspective of a medical knowledge provider. These include the size of the task at hand, the challenge of creating machine interpretable content, the issue of standards, the need to do better in tracing how computable medical knowledge that is part of clinical decision support impacts patient outcomes, the challenge of comorbidities, the problem of adhering to safety standards and finally the challenge of integrating knowledge with problem solving and procedural skills, healthy attitudes and professional behaviours. Partnership is likely to be essential if we are to make progress in this field. The problems are too complex and interrelated to be solved by any one institution alone.

Guidance DS: A web-based clinical decision support system for antimicrobial stewardship in hospitals

2009 ◽  
Vol 42 (12) ◽  
pp. 354-358
Author(s):  
Karin Thursky ◽  
Marion Robertson ◽  
Susan Luu ◽  
James Black ◽  
Michael Richards ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Antimicrobial Stewardship ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Web Based
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