We outline the structure and content of a Prometheus cannabis dispensary registry utilizing RexRegistry to monitor patients to fulfill their duty of care and differentiate themselves from recreational marijuana shop fronts.
We outline how medical marijuana dispensaries and legislators can establish the ability of the dispensaries to risk manage their patient base by demonstrating a commitment to monitoring and reporting of response to botanical marijuana in the process of care.
One of the more puzzling features of the embrace of medical marijuana programs by state governments in the US is the lack of established dispensary standards for monitoring the use and impact. Discover the importance of required audit standards and the role of site-specific registries in reducing barriers to the acceptance of medical marijuana by providers, patients, and health agencies.
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 is the organization and integration of data collected from various sources. Data enrichment is a general term that refers to processes used to enhance, refine or otherwise improve raw data. Enrichment contributes to making data a valuable asset for almost any modern business or enterprise. It also shows the common imperative of proactively using this data in various ways.
7 Challenges of Mastering Clinical Data Registries GalleryAutomating Health Care, Clinical Informatics Solutions for Health Care Registries, Clinical Research Trends & Tips, Data Management for Scientific Research, Mastering Clinical Data Registries
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.
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 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.
Good Data Management Practices for Data Analysis: Part 3, Relational Databases GalleryClinical Research Trends & Tips, Data Management for Scientific Research, Data Sharing in Clinical Research, Information Design & Usability
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 [...]
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 [...]
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 [...]
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! 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 [...]
NLP: Tapping Into EHR Text Fields Electronic health records (EHRs) are digitizing valuable medical data on a massive scale. However, up to 70% of meaningful information for medical registries, outcomes researchers, and clinicians is held within practitioner notes. These free [...]
The New Face of Research Surveys: Opportunities and Challenges Surveys have historically been one of the most important tools available for conducting empirical research. Today, they continue to be prominent within social and behavioral science research and play growing roles in [...]
The Pitfalls of Spreadsheet Data Management Spreadsheet software is almost as ubiquitous as the personal computer itself. Even in rigorous research contexts, programs like Microsoft Excel offer an environment for ad hoc analyses, back-of-the-envelope calculations, dashboard prototyping, and more. But [...]
EHRs for Clinical Outcomes Research: How to Maintain Researcher Productivity GalleryClinical Informatics Solutions for Health Care Registries, Clinical Research Trends & Tips, Data Management for Scientific Research, Data Sharing in Clinical Research
EHRs for Clinical Outcomes Research: How to Maintain Researcher Productivity Opportunities for advancing clinical outcomes research are on the rise. This is largely thanks to electronic health records (EHRs)—a patient care tool that is already capturing meaningful clinical information on an [...]
Research Trends: Repurposing Healthcare Registries to Improve Quality, Performance, and Outcomes With the growing digitization of the patient record and care in general, the medical registry has become increasingly important. Having a centralized data repository tailored to a specific set [...]
Automating Care: Where We’re Going and How We’ll Get There In clinical contexts, “automation” is a buzzword. It’s meant to inspire images of doctors' offices filled with computers as they calculate ways to improve patient outcomes at lower costs. This [...]
How to Reshape Long-Format Excel Data into Wide-Format SPSS Data As a provider of integrated data management services, we often answer a wide variety of questions relating to data manipulation. One of the most common questions that we encounter is [...]
How Amazon Reminded Us That Not All Business Associates Agreements (BAAs) Are Created Equal Ever since Amazon announced that it was changing its policy to sign BAAs for HIPAA-compliant data storage, we’ve been eager and excited. That sentiment soon turned [...]
Data Sharing in Clinical Research Suppose you and I are clinical researchers who both work in the Boston area. We want to collaborate on a project together. We’re interested in finding genetic markers of treatment response and non-response among patients [...]
Tips for Getting Control of Your Data: Back to Basics, Nouns and Verbs In our last installment of Tips for Getting Control of Your Data series, we suggested using a revision control system to help keep track of your data files as they [...]
The Perils of Disposable Data Management A researcher collects the first batch of data from her research study. She excitedly cuts and pastes the data from multiple spreadsheets to get it into one master spreadsheet. Eager to make sure the [...]
Redundancy is Evil: Learn to Share Data Between Google Spreadsheets Use the ImportRange() function to share data between Google spreadsheets and to generally make life more satisfying An important goal in data management is to avoid redundancy. We Prometheans despise [...]
Form Design Tip 3: Avoid Redundancy Most studies require multiple forms to capture all necessary participant information: a medical history form, a family history form, a demographic information form, a previous diagnoses form, etc. If any of the forms capture [...]
Form Design Tip 2: Usability The best practice form design mantra: the most important thing is usability. No one collects data without the intention of analyzing it. Similarly, no one designs forms to elicit information that won't be useful at some [...]
Can a data sharing plan advance your research goals? Most investigators think of data sharing plans as yet another annoying administrative requirement. Here comes some clueless funding agency with this wacky idea that another researcher might actually use your data! [...]
Form Design Tip 1: Dos and Don’ts of Form Design Did you know that changing even the smallest item on a form after data collection has begun could compromise data quality? Editing items during or after data collection can lead [...]