Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
29287301
The term "digital health" is currently the most comprehensive term that includes all information and communication technologies in healthcare, including e-health, mobile health, telemedicine, big data, health apps and others. Digital health can be se...
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...
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
25773546
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...
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...
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...
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 ...
We are experiencing astonishing developments in the areas of big data and artificial intelligence. They follow a pattern that we have now been observing for decades: according to Moore's Law,the performance and efficiency in the area of elementary ar...
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 ...
OBJECTIVE: To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from fu...