Automated processing of laboratory reports has the potential of yielding significant amounts of useful data, which on its own or in combination with other data can be used to obtain meaningful insights into an individuals' health.
Finding and getting access to clinical trials can be challenging if not daunting for patients. For those who don’t qualify for a study, but still want to gain access to the medicine, there are a few newer options: compassionate use and right to try.
As organizations reach their digitization goals, they now are facing new challenges. Current healthcare systems are generally adequate at answering specific questions for end-users by may be limited in addressing more complex questions.
As the industry prepares for the new age of hybrid and decentralized trials there is a heightened focus on data (quality, volume and validity), metrics and operational efficiency. Learn more at SCOPE 2020.
A variety of digitized data tools is currently enabling health professionals in the management of routine activities. When leveraged, these tools can elevate a healthcare organization from one operating at an industry-best level to one that performs at a transformational pace. Here, Part 2 explores data mining tools and intelligent bots.
Metadata management in clinical R&D is centered on the concept that each piece of data collected for a clinical trial, as defined by that trial’s protocol, can be managed independently. Each piece of metadata and logical groupings of many metadata items together can be governed and managed in the organization. This includes version control, data edit rules for that data item, and transformation rules for that data item as it changes to support the analysis process. In...