This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious ...
Increasing recognition of the role and value of theory in improvement work in healthcare offers the prospect of capitalising upon, and consolidating, actionable lessons from synthesis of improvement projects and initiatives. We propose that informed ...
OBJECTIVE: Survey data sets are important sources of data, and their successful exploitation is of key importance for informed policy decision-making. We present how a survey analysis approach initially developed for customer satisfaction research in...
INTRODUCTION: Health services research generates useful knowledge. Promotion of implementation of this knowledge in medical practice is essential. Prior to initiation of a major study on rural emergency departments (EDs), we deployed two knowledge tr...
This Perspective discusses 12 key facts derived from 50 years of health services research and argues that this knowledge base can stimulate innovative thinking about how to make health care systems safer, more efficient, more cost effective, and more...
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jan 29, 2015
Traditional analytic methods are often ill-suited to the evolving world of health care big data characterized by massive volume, complexity, and velocity. In particular, methods are needed that can estimate models efficiently using very large dataset...
Artificial intelligence (AI) and machine learning (ML) are important tools across many fields of health and medical research. Pharmacoepidemiologists can bring essential methodological rigor and study design expertise to the design and use of these t...
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVES: To reflect on the achievements of the Agency for Healthcare Research and Quality's (AHRQ) Digital Healthcare Research Program over the past 20 years, evaluate its impact on US healthcare quality and safety, and outline current and future ...
Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, providing critical insights and supporting clinical decisions, particularly in the age of big data. This paper serves as an introductory guide for heal...
Studies in health technology and informatics
Jun 29, 2023
Artificial intelligence (AI) tends to emerge as a relevant component of medical care, previously reserved for medical experts. A key factor for the utilization of AI is the user's trust in the AI itself, respectively the AIt's decision process, but A...
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