Prometheus Research Blog
Leveraging Research Data to Enhance Quality Improvement Initiatives GalleryClinical Informatics Solutions for Health Care Registries, Clinical Research Trends & Tips, Data Management for Scientific Research, Data Sharing in Clinical Research, Healthcare Quality Improvement
Does quality improvement really matter and do we need to convince you that it’s important to advancing state-of-the-art healthcare? This is the debate that has been raging amongst us recently and, after much thought and discussion, we came to the conclusion that it does matter, but that we don’t need to convince you…. Everyone working in healthcare today already understands why quality improvement is important and that it will have an vital impact on state-of-the-art healthcare.
In this article on data management best practices for data analysis, we’ll look at 3 distinct sections that will provide you with a well-rounded strategy that can be implemented with your organization’s data: data cleaning and transformation, tidy data and tidy tools, and managing data. Click here to learn more.
As you well know, Common Rule is the federal policy for the protection of human test subjects. Published in 1991, it has been updated and amended along the way, including the most recent revision—aka the Final Rule—which goes into effect on July 19, 2018. Changes have been made and agreed upon between sixteen different federal departments and agencies, spearheaded by the U.S, Department of Health and Human Services.
In this article, we’ll examine 10 healthcare quality improvement trends that will impact the healthcare industry for years to come. Learn more here!
Data Curation vs. Two Flavors of Data Enrichment Data curation is about improving the quality of the data you already have. It usually involves redaction of cases and measures that don’t meet a quality standard, e.g., removing cases or observations [...]
In this article we will examine the top 7 challenges of mastering clinical data registries. Understanding each individual demand will help you better build out a CDR capable of compiling mass amounts of data, supporting vast amounts of complex research, and leveraging your findings to their full potential.