PMU71 Real World Data Availability in Latin America: Assessment and Implications for Research and Healthcare Decision Making

2021 ◽  
Vol 24 ◽  
pp. S157
Author(s):  
H. Monsanto ◽  
C. Parellada ◽  
J. Orengo ◽  
J.S. Velasco ◽  
Bavel J van ◽  
...  
Keyword(s):  
Decision Making ◽  
Latin America ◽  
Real World ◽  
Data Availability ◽  
Healthcare Decision ◽  
Real World Data ◽  
World Data ◽  
Healthcare Decision Making

PNS118 Real World Evidence (RWE) Use in Latin America Healthcare Decision Making: An Stakeholder Survey Analysis.

2021 ◽  
Vol 24 ◽  
pp. S194
Author(s):  
L. Costa ◽  
A.L. Hincapie ◽  
R. Gilardino ◽  
B. Tang ◽  
G. Julian ◽  
...  
Keyword(s):  
Decision Making ◽  
Latin America ◽  
Real World ◽  
Healthcare Decision ◽  
Survey Analysis ◽  
Healthcare Decision Making ◽  
Real World Evidence

scholarly journals Time to really share real-world data?

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1054 ◽  
Author(s):  
Sophie Graham ◽  
Laura McDonald ◽  
Radek Wasiak ◽  
Michael Lees ◽  
Sreeram Ramagopalan
Keyword(s):  
Clinical Trials ◽  
Real World ◽  
Open Science ◽  
Healthcare Decision ◽  
High Likelihood ◽  
Real World Data ◽  
World Data ◽  
Healthcare Decision Making ◽  
Effective Use ◽  
Opening Up

Data other than that from clinical trials are important for healthcare decision making. However, unlike the vocal calls seen for more open access to trial data, there are limited efforts being made to ensure that agencies that collect real-world data (RWD) share this, despite its importance. There are many RWD sources across the world that could be readily exploited for research once shared. There are policy and privacy questions that need to be tackled, but opening up and sharing RWD offers remarkable potential for improvements in care for individuals and more effective use of limited healthcare resources. Open science should become the standard for RWD as well as clinical trials, especially those that have a high likelihood to influence practice.

scholarly journals Real-World Evidence in Healthcare Decision Making: Global Trends and Case Studies From Latin America

2019 ◽  
Vol 22 (6) ◽  
pp. 739-749 ◽  
Author(s):  
Nahila Justo ◽  
Manuel A. Espinoza ◽  
Barbara Ratto ◽  
Martha Nicholson ◽  
Diego Rosselli ◽  
...  
Keyword(s):  
Decision Making ◽  
Latin America ◽  
Case Studies ◽  
Real World ◽  
Healthcare Decision ◽  
Global Trends ◽  
Healthcare Decision Making ◽  
Real World Evidence

Quality criteria for Real-World Data in pharmaceutical research and healthcare decision making. An Austrian Expert Consensus (Preprint)

2021 ◽  
Author(s):  
Peter Klimek ◽  
Dejan Baltic ◽  
Martin Brunner ◽  
Alexander Degelsegger-Marquez ◽  
Gerhard Garhöfer ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Research ◽  
Real World ◽  
Pharmaceutical Medicine ◽  
Pharmaceutical Research ◽  
Quality Criteria ◽  
Clinical Decision ◽  
European Medicines Agency ◽  
Real World Data ◽  
World Data

UNSTRUCTURED Real-world data (RWD) collected in routine healthcare processes and transformed to real-world evidence (RWE) has become increasingly interesting within research and medical communities to enhance medical research and support regulatory decision making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which quality RWD must meet in order to be acceptable for decision making within regulatory or routine clinical decision support. An Austrian expert group led by GPMed (Gesellschaft für Pharmazeutische Medizin, Austrian Society for Pharmaceutical Medicine) reviewed drafted guidelines, published recommendations or viewpoints to derive a consensus statement on quality criteria for RWD to be used more effectively for medical research purposes beyond registry-based studies discussed in the European Medicines Agency (EMA) guideline for registry-based studies

Automated Diagnosis through Ontologies and Logical Descriptions

2013 ◽  
pp. 117-134
Author(s):  
Alejandro Rodríguez-González ◽  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
José Emilio Labra Gayo ◽  
Juan Miguel Gómez-Berbís ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Systems ◽  
Real World ◽  
Information Age ◽  
Semantic Technologies ◽  
Automated Diagnosis ◽  
Real World Data ◽  
World Data ◽  
Degree Of Maturity ◽  
Automate Diagnosis

The combination of the burgeoning interest in efficient and reliable Health Systems and the advent of the Information Age represent both a challenge and an opportunity for new paradigms and cutting-edge technologies reaching a certain degree of maturity. Hence, the use of Semantic Technologies for Automated Diagnosis could leverage the potential of current solutions by providing inference-based knowledge and support on decision-making. This paper presents the ADONIS approach, which harnesses the use of ontologies and the underlying logical mechanisms to automate diagnosis and provide significant quality results in its evaluation on real-world data scenarios.

scholarly journals Real-world data: how they can help to improve quality of care

2021 ◽  
Vol 8 ◽  
pp. 134-139
Author(s):  
Giovanni Corrao ◽  
Giovanni Alquati ◽  
Giovanni Apolone ◽  
Andrea Ardizzoni ◽  
Giuliano Buzzetti ◽  
...  
Keyword(s):  
Public Health ◽  
Quality Of Care ◽  
Real World ◽  
Ethical Issues ◽  
Data Availability ◽  
Quality Data ◽  
Real World Data ◽  
World Data ◽  
Critical Issues

The current COVID pandemic crisis made it even clearer that the solutions to several questions that public health must face require the access to good quality data. Several issues of the value and potential of health data and the current critical issues that hinder access are discussed in this paper. In particular, the paper (i) focuses on “real-world data” definition; (ii) proposes a review of the real-world data availability in our country; (iii) discusses its potential, with particular focus on the possibility of improving knowledge on the quality of care provided by the health system; (iv) emphasizes that the availability of data alone is not sufficient to increase our knowledge, underlining the need that innovative analysis methods (e.g., artificial intelligence techniques) must be framed in the paradigm of clinical research; and (v) addresses some ethical issues related to their use. The proposal is to realize an alliance between organizations interested in promoting research aimed at collecting scientifically solid evidence to support the clinical governance of public health.

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