Guide to Best Data Management Practices for Data Analysis

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.

Data Curation vs. Data Enrichment

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 [...]

Three simple ways to refresh your data management practices

Three simple ways to refresh your data management practices Since we're all about saving time,  we already did the hard work for you by creating the list below of three (reasonable) data management goals to tackle. These goals are sure [...]

Leveraging Research Data to Enhance Quality Improvement Initiatives

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.

Prometheus Joins AMA Initiative to Improve Health Data Interoperability for More Effective Patient Care

Prometheus Joins AMA Initiative to Improve Health Data Interoperability for More Effective Patient Care The American Medical Association has announced an ambitious new initiative to dramatically improve the organization and interoperability of fragmented health data, and has recruited thought leaders [...]

Good Data Management Practices for Data Analysis: Part 3, Relational Databases

Good Data Management Practices for Data Analysis: Part 3, Relational Databases As we illustrated in the first post in this series, data cleaning and data transformation are two major bottlenecks in data analysis. Both can be streamlined by using more [...]

Good Data Management Practices for Data Analysis: Part 2, Tidy Data

Good Data Management Practices for Data Analysis: Part 2, Tidy Data Note: This post draws heavily from concepts described in an article, slide deck, and presentation by Hadley Wickham, Assistant Professor of Statistics at Rice University and Chief Scientist at [...]

Good Data Management Practices for Data Analysis: Part 1

Good Data Management Practices for Data Analysis: Part 1 As far as research experiences go, it’s hard to beat the moment when you finally get to analyze and interpret the data you worked so hard to obtain. Unfortunately, it’s common [...]

A Brief Introduction to Clinical Nomenclatures

A Brief Introduction to Clinical Nomenclatures Vocabulary management systems in electronic health records (EHRs) standardize how medical information is communicated. Although primarily intended to improve patient care, they also benefit researchers by bringing structure to complicated, nuanced, and dynamic health [...]

Help! I’m Drowning in a Sea of Changing Data!

Help! I’m Drowning in a Sea of Changing Data! Tips for Getting Control of Your Data When It Feels Like Your Data Controls You (So You Can Finally Sleep At Night) Not everyone will admit to having this problem, but [...]