3 practical tips for cost-effective clinical monitoring

Originally posted by Jenya Konikov-Rozenman on May 31, 2016 in Clinical Trial Monitoring


clinical data management for decision making in clinical trial monitoring

Can you use technology to reduce the costs of your clinical trial and shorten your time from study data lock to regulatory submission?  Jenya talks about how medtech developers can save money and reduce their time to market.

If you are a medtech company and conducting a multi-center clinical trial, the question of cost of clinical data capture and site monitoring is crucial.

In this article, we will discuss 3 practical ways, you can save money, improve the ROI of your budget by up to10X, improve the quality of your site monitoring and reduce the amount of time it takes to produce your statistical report at the end of the study.

Tip #1 – Do it in the cloud. Forget paper.

In many cases, we see small biomed and biotech sponsors performing paper-based studies, only to discover that their monitoring was too little and too late and that their costs were too high and too unexpected. The average cost of a paper-based trial with 100 subjects is about $1000/subject. Add to that another $20-30K for site monitoring and you have a price tag of $130K. Contrary to your expectations, a cloud-based SaaS (software as a service) solution that combines Electronic data capture with clinical data monitoring as a service can run you as little as $50K for a 12 month trial, yielding cost savings of over 100 percent.

Tip #2 – Use an integrated data capture and clinical data monitoring solution

There are 2 components to cloud-based data management – the data collection part (aka EDC) and the clinical monitoring as a service piece. It is important that your cloud-based clinical data management solution seamlessly integrates both pieces. This is for several reasons:

1. Time. By using a SaaS-based solution that integrates data collection with data monitoring, you eliminate a painful, costly and time consuming process of data export, ETL (extract, translate and load), mapping data fields to your clinical monitoring requirements and producing reports in Excel and repeating the process daily or weekly.

2. Data security. Export of your clinical data to an analyst Windows PC workstation exposes your data to malware and attackers that may steal your intellectual property. Data security is crucial for your clinical trial data management and there is no conceivable reason to place it at risk by downloading to a workstation. There are better solutions.

3. Flexibility and scalability. As your study ramps up, you will discover new monitoring needs. There will be new requirements for data collection, and monitoring and letters to file to be written. Combining these 2 capabilities into one solution helps you enhance patient safety and reduce trial cost and risk by enabling you to quickly design and implement your own monitoring strategies and processes.

4. Do it in real time. When data collection and clinical monitoring happen in real time it is easier to ensure compliance with the study protocol. A clinical trial is a scientific experiment and unexpected things do happen not to mention issues with sites. By capturing issues in real-time, you can fix issues in real-time and eliminate avoidable rework at the end of the study after data lock. Elimination of avoidable rework during the study will have a dramatic effect on your time to statistical report and reduce it by as much as 10X from 6 months to 6 weeks. This is similar to manufacturing where the cost of remedying a defect after shipping the product is 100X higher then fixing it in the design phase.

5. Be proactive. By combining data collection and monitoring in the cloud, you can quickly identify under-performing sites and problematic data, make good decisions with real-time enrollment and help your sites increase their productivity and quality by sharing clinical operations and clinical conduct metrics.

Tip #3 Don’t confuse SDV with clinical quality

SDV (source document verification) performed on-site by study monitors has low value and less than 2% impact on your endpoint. This is for a very simple reason. SDV is a process that detects whether the data entered into the EDC matches the data on the paper forms that the sites used. SDV does not measure clinical conduct. This is a crucial insight.

If SDV only contributes 2% or less actionable intelligence to your study endpoints, then why bother optimizing SDV which is a low value-add activity? You can do SDV or not do SDV, it doesn’t really matter.
However, clinical data monitoring as a service enables you to place your management focus on clinical conduct, a far more valuable activity than comparing paper source documents to online data that was validated by EDC edit checks.
Summary

By using a cloud-based holistic clinical data management system, you can increase value and lower costs and reduce time to report. Contact us to learn more.