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 from the beginning. Clinical Data Review is no different. User involvement is paramount throughout the process, especially on how they will be interacting with the application. That single design element can make or break an application.
- Involve users in the Requirements
- Involve the users in the Design – interactively – starting with Mock-Ups and descriptions of the process
- Involve the users in the unit testing/exposure to the user experience well before User Acceptance Testing
- Ensure users have adequate support through User Acceptance testing, including training, test scenarios, expected behavior
- Provide adequate release/white glove treatment for new functionality
This guide analyzes how artificial intelligence – including machine learning – can be used by pharmaceutical and medical device companies to improve the clinical data review and cleansing process.
To summarize all the blog posts in which we recently discussed the basic design decisions and business rules that impact the implementation of Clinical Data Review, I’d like to reiterate several points.
Without question, there are many design considerations for a Clinical Data Review application and these will widely vary from business to business. But, here are some of the common critical design decisions I like to focus on:
- Determine business rules, such as Individual Review, Group Review and Team Review
- Determine how to identify new and changed data for a reviewer
- Determine which data requires additional scrutiny and develop plans to support that scrutiny
- Determine the granularity of a review and how you will record a review action
- Work closely with the users throughout the process
With that said, what requirements and design criteria do you find effective in providing support for Clinicians and Medical Monitors in the Clinical Data Review processes?
If you are interested in learning how Perficient can help improve your clinical data review process, please send us an email or fill out the “contact us” form in the footer of this page.