Fundamentals of Drug Metabolism and Pharmacogenomics Within a Learning Healthcare System Workflow Perspective

2019 ◽  
pp. 59-80
Author(s):  
Matthew K. Breitenstein ◽  
Erin L. Crowgey
Keyword(s):  
Drug Metabolism ◽  
Healthcare System ◽  
Learning Healthcare System

Establishing a learning healthcare system to improve health outcomes for people with epilepsy

2021 ◽  
Vol 117 ◽  
pp. 107805
Author(s):  
Maria A. Donahue ◽  
Susan T. Herman ◽  
Deepika Dass ◽  
Kathleen Farrell ◽  
Alison Kukla ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Healthcare System ◽  
Learning Healthcare System ◽  
Improve Health

A new approach to clinical research: Integrating clinical care, quality reporting, and research using a wound care network-based learning healthcare system

2017 ◽  
Vol 25 (3) ◽  
pp. 354-365 ◽  
Author(s):  
Thomas E. Serena ◽  
Caroline E. Fife ◽  
Kristen A. Eckert ◽  
Raphael A. Yaakov ◽  
Marissa J. Carter
Keyword(s):  
Clinical Research ◽  
Healthcare System ◽  
Wound Care ◽  
Clinical Care ◽  
Care Quality ◽  
New Approach ◽  
Care Network ◽  
Quality Reporting ◽  
Learning Healthcare System

scholarly journals Opportunities and Challenges for Interpreting Rare Variation in Clinically Important Genes

2020 ◽  
Author(s):  
Gregory McInnes ◽  
Andrew G. Sharo ◽  
Megan L. Koleske ◽  
Julie E. H. Brown ◽  
Matthew Norstad ◽  
...  
Keyword(s):  
Healthcare System ◽  
Protein Function ◽  
Rare Variants ◽  
Clinical Importance ◽  
Computational Prediction ◽  
Ethical Challenges ◽  
Inborn Errors ◽  
Rare Variation ◽  
Learning Healthcare System ◽  
The Impact

Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, leaving a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequent frequent variants and associated mechanisms. Variants of unknown significance (VUS) in these genes are discovered at a rate that outpaces current ability to classify them using databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns, and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

scholarly journals Informatics and the Learning Healthcare System

2011 ◽  
Vol 32 (5) ◽  
pp. 334-336 ◽  
Author(s):  
DIANE J. SKIBA
Keyword(s):  
Healthcare System ◽  
Learning Healthcare System

scholarly journals Pharmacotherapy within a learning healthcare system: rationale for the Dutch Santeon Farmadatabase

2017 ◽  
Vol 26 (1) ◽  
pp. 46-50 ◽  
Author(s):  
Ewoudt M W van de Garde ◽  
Bram C Plouvier ◽  
Hanneke W H A Fleuren ◽  
Eric A F Haak ◽  
Kris L L Movig ◽  
...  
Keyword(s):  
Healthcare System ◽  
Learning Healthcare System

scholarly journals Using a network organisational architecture to support the development of Learning Healthcare Systems

2018 ◽  
Vol 27 (11) ◽  
pp. 937-946 ◽  
Author(s):  
Maria T Britto ◽  
Sandra C Fuller ◽  
Heather C Kaplan ◽  
Uma Kotagal ◽  
Carole Lannon ◽  
...  
Keyword(s):  
Healthcare System ◽  
Point Of Care ◽  
Data Entry ◽  
Regulatory Compliance ◽  
Clinical Encounter ◽  
Learning System ◽  
National Academy Of Sciences ◽  
Statistical Process ◽  
Learning Healthcare System ◽  
Communication Policies

The US National Academy of Sciences has called for the development of a Learning Healthcare System in which patients and clinicians work together to choose care, based on best evidence, and to drive discovery as a natural outgrowth of every clinical encounter to ensure innovation, quality and value at the point of care. However, the vision of a Learning Healthcare System has remained largely aspirational. Over the last 13 years, researchers, clinicians and families, with support from our paediatric medical centre, have designed, developed and implemented a network organisational model to achieve the Learning Healthcare System vision. The network framework aligns participants around a common goal of improving health outcomes, transparency of outcome measures and a flexible and adaptive collaborative learning system. Team collaboration is promoted by using standardised processes, protocols and policies, including communication policies, data sharing, privacy protection and regulatory compliance. Learning methods include collaborative quality improvement using a modified Breakthrough Series approach and statistical process control methods. Participants observe their own results and learn from the experience of others. A common repository (a ‘commons’) is used to share resources that are created by participants. Standardised technology approaches reduce the burden of data entry, facilitate care and result in data useful for research and learning. We describe how this organisational framework has been replicated in four conditions, resulting in substantial improvements in outcomes, at scale across a variety of conditions.

The Critical Care Learning Healthcare System: Time to Walk the Walk*

2020 ◽  
Vol 48 (12) ◽  
pp. 1907-1909
Author(s):  
Victoria Surma ◽  
Sapna Kudchadkar ◽  
Melania Bembea ◽  
James C. Fackler
Keyword(s):  
Critical Care ◽  
Healthcare System ◽  
Learning Healthcare System ◽  
System Time
Sign in / Sign up

Export Citation Format

Share Document