scholarly journals Big Data And New Knowledge In Medicine: The Thinking, Training, And Tools Needed For A Learning Health System

2014 ◽  
Vol 33 (7) ◽  
pp. 1163-1170 ◽  
Author(s):  
Harlan M. Krumholz
2018 ◽  
Vol 45 (10) ◽  
pp. e845-e847 ◽  
Author(s):  
Kayte Spector-Bagdady ◽  
Reshma Jagsi

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 613 ◽  
Author(s):  
Rafael Carnicero ◽  
David Rojas ◽  
Ignacio Elicegui ◽  
Javier Carnicero

This article identifies the main challenges of the National Health Service of Spain and proposes its transformation into a Learning Health System. For this purpose, the main indicators and reports published by the Spanish Ministries of Health and Finance, Organization for Economic Co-operation and Development (OECD) and World Health Organization (WHO) were reviewed. The Learning Health System proposal is based on some sections of an unpublished report, written by two of the authors under request of the Ministry of Health of Spain on Big Data for the National Health System. The main challenges identified are the rising old age dependency ratio; health expenditure pressures and the likely increase of out-of-pocket expenditure; drug expenditures, both retail and consumed in hospitals; waiting lists for surgery; potentially preventable hospital admissions; and the use of electronic health record (EHR) data to fulfil national health information and research objectives. To improve its efficacy, efficiency, and quality, the National Health Service of Spain should be transformed into a Learning Health System. Information and communication technologies (IT) enablers are a fundamental tool to address the complexity and vastness of health data as well as the urgency that clinical and management decisions require. Big Data solutions are a perfect match for that problem in health systems.


2016 ◽  
Vol 6 (9) ◽  
Author(s):  
Edward Abraham ◽  
◽  
Carlos Blanco ◽  
Celeste Castillo Lee ◽  
Jennifer B. Christian ◽  
...  

2021 ◽  
Author(s):  
Jennie David ◽  
Catalina Berenblum Tobi ◽  
Samantha Kennedy ◽  
Alexander Jofriet ◽  
Madeleine Huwe ◽  
...  

2017 ◽  

As machine-readable data comes to play an increasingly important role in everyday life, researchers find themselves with rich resources for studying society. The novel methods and tools needed to work with such data require not only new knowledge and skills, but also a new way of thinking about best research practices. This book critically reflects on the role and usefulness of big data, challenging overly optimistic expectations about what such information can reveal, introducing practices and methods for its analysis and visualisation, and raising important political and ethical questions regarding its collection, handling, and presentation.


Author(s):  
Jose M. Juarez ◽  
Susan Craw ◽  
J. Ricardo Lopez-Delgado ◽  
Manuel Campos

Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from model-based systems since it can learn incrementally as new data is available, storing new cases in its case-base. This means that it can benefit from readily available new data, but also case-base maintenance (CBM) is essential to manage the cases, deleting and compacting the case-base. In the 50th anniversary of CNN (considered the first CBM algorithm), new CBM methods are proposed to deal with the new requirements of Big Data scenarios. In this paper, we present an accessible historic perspective of CBM and we classify and analyse the most recent approaches to deal with these requirements.


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