Jim Richards

In part one of this two-part blog series, we outlined a number of challenges that organizations face with clinical data reviews. In today’s post, part two of the series, we’ll take a look at how Oracle Health Sciences Data Management Workbench (DMW) can be used to tackle those challenges. DATA MANAGEMENT WORKBENCH (DMW) OVERVIEW When […]

When it comes to clinical trials, bad data can result in severe consequences. Research and development can become more complicated and lives can be put at risk. Clean clinical data is critical for accurate analysis and reporting, ultimately enabling safer drugs and devices to be brought to market faster. In this two-part blog series, we’ll […]

In the previous post, I talked about varying levels of scrutiny for data review and what happens when recording the user actions. In this post, I will talk about the importance of the user interface for a review. Successfully navigating requirements, design, development, testing, user acceptance and ongoing support of any application requires user involvement […]

As was mentioned in a previous post, providing an easy-to-use interface is important for data review, including filtering, audit data, and User Review Action buttons. The user actions buttons initiate recording that all, or a portion, of a review has been performed. In the previous section, we mentioned a Review Timestamp, which is one of […]

In my last blog post, I presented some thoughts on showing data changed since last review. Today, we will concentrate on the level of scrutiny and what happens when recording the user actions in the review. Not all data may require the same level of scrutiny during a review. Additional focus may need to be […]

In my previous post, we discussed some examples of business rules that might be applied depending on how many people are performing a clinical data review. Today, we’ll discuss approaches for selecting the data that is being reviewed. In any data review that occurs multiple times during the course of a study there are two […]

In a few of my previous blog posts (4 Ways You Can Improve The Clinical Data Review Process and Using On-demand Data With Dynamic Data Writeback In Spotfire), I discussed using Spotfire as an aid for Clinical Review of data along with supporting writeback capabilities to record the user review actions. In the next several […]

In my last post, I discussed performing a clinical data review in Oracle’s Data Management Workbench, which takes value added data into consideration. Today, we’ll take it a step further and add external data into the mix. This scenario extends the data available for review by including data from external partners who may be managing […]

In my previous post, we discussed a simple scenario for reviewing clinical data cleanliness in Oracle’s Data Management Workbench. Today, we’ll discuss a similar process, although this scenario leverages value added data. Establishing value added data is another way to help the clinician to more quickly review the data and spot outliers and questionable data. […]

In my previous blog post entitled Using On-demand Data With Dynamic Data Writeback In Spotfire, I discussed using Spotfire as an aid for Clinical Review of data along with supporting writeback capabilities to record the user review actions.  As a follow-on discussion, I wanted to expand those capabilities to include Clinical Data Cleaning Review in […]

I have worked on a few clinical applications where adding little functions to existing applications can greatly improve an individual’s job function and subsequently benefit the company as a whole. Looking for these little gems isn’t time consuming or difficult as long as we are aware of the system’s capabilities and are able to capitalize […]