Life Sciences

Subject Screening with Robotic Process Automation: Life Sciences

My last blog analyzed site monitoring, and how robotic process automation can enhance it. My next blog discusses life science subject screening and how robotic process automation (RPA) can assist.

Even when sites are able to recruit a large pool of potential subjects, sponsors and CROs see far too many subjects who fail to pass the screening visit (screen failures) and subjects who pass the screening visit only to leave the study early (early terminations). Because sites get paid for every subject visit that occurs, regardless of whether the subject passes or completes the study, both of these situations are costly and lead to tension between the sponsor/CRO and the site/investigator.

This strain can be eased by:

  • Providing site personnel with tools that boost their screening effectiveness and continually monitoring and improving those tools over time
  • Shifting the burden of the screening process away from site personnel
  • Automating the data capture process during the screening visit

Companies tackle this issue effectively in two primary ways, both of which leverage RPA technology and customer experience (CX) principles.

Imagine the following scenario:

A potential clinical subject comes into a site for his screening visit. The nurse performing the screening visit takes out her iPad, brings up the screening app, and follows the interactive prompts to move the potential subject through the various questions and tests.

When the nurse selects or inputs the potential subject’s answers, the app dynamically adjusts the questions that are asked, and their sequence, in a decision tree format that is relevant to the potential subject.

When the nurse performs the tests, the data is automatically captured in the app via wireless connection with the testing device – no data entry is required.

When the screening visit is complete, the nurse submits the results, all of which are automatically transmitted to your EDC system and other clinical systems.

Life Sciences - How Artificial Intelligence Can Enhance the Clinical Data Review and Cleaning Process
How Artificial Intelligence Can Enhance the Clinical Data Review and Cleaning Process

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.

Get the Guide

Additionally, stats about the nurse’s performance and her experience using the app are automatically transmitted (e.g., How long did it take her to move from step to step? How long was the overall visit? On which steps did she seem to struggle?).

Subject Screening

As the sponsor or CRO running the study, you see the individual nurse’s performance and use data, as well as aggregate data from a single site, multiple sites, and all sites in a study. This analytical dashboard allows you to identify positive and negative trends in the screening process, as well as potential issues that need to be clarified or corrected.

Based on the data you see, you recognize that a particular question in the screening process needs clarification. You kick off a workflow to approve the change. Once approved, you make the change and release it for production use. Over time, you see the use data for that question improve.

This is a popular approach to addressing the issue because it is easily attainable and clearly impactful. At its core, this solution reframes the site personnel who perform the screening process as customers and then uses CX principles to provide them with a convenient and engaging tool for completing the process. It also comes with two rather pleasant side effects: it greatly reduces data entry error that can lead to erroneous screen failures and screen passes, and it provides insight into how to continually improve the overall screening process.

A second approach that some industry pioneers adopting works something like this:

A potential clinical subject comes into a site for his screening visit. When he checks in, he is issued an iPad for use during the visit. On the iPad, he finds an interactive app that leads him step-by-step through the screening process. It moves him through questions dynamically, using a decision-tree format that adjusts based on his answers.

When it comes to screening tests, the app moves him through a circuit of digital devices, each designed to perform different tests – a digital scale, a digital blood pressure machine, a digital oximeter, and even a digital toilet, all of which are designed to take readings directly from the patient.

When the potential subject has completed all of the questions and tests, he submits his results and returns the iPad to the front desk. All of his data is automatically transmitted to the site personnel and your EDC system. The data is then automatically analyzed and issued a tentative status of “pass,” which triggers a notification to the site investigator.

Later that day, when the investigator has a moment, he reviews the potential subject’s results and approves his participation in the study. As soon as his status changes to approved, he receives a welcome notification and a request to complete the informed consent process.

While this scenario might seem overly futuristic to some, be assured it is happening, and all signs point to this being the direction the industry is heading. This highly digitized and automated solution significantly reduces the screening burden on-site personnel and significantly increases the accuracy of the data collected during the screening process. It also more closely aligns with patient/subject expectations in the “Age of the Customer,” resulting in a more pleasant and engaging experience for them.

Granted, this solution does take more effort to design and implement, but in the case of large-scale, long-term clinical trials, or of a particular site being involved in several of your trials over time, the return on investment (ROI) is clear.

To learn more about specific clinical trial challenges concerning the pharma-investigator relationship and potential solutions using robotic process automation, you can download the guide here, or fill out the form below.

About the Author

Param Singh has been working in the life sciences industry his entire career. As the director of clinical trial management solutions at Perficient, he developed the clinical trial management team to become one of the best in the industry. Param leads a highly skilled team of implementation specialists and continues to build lasting relationships with clients. He has a knack for resource and project management, which allows clients to achieve success. Param has been with Perficient, via the acquisition of BioPharm Systems, since 2008. Prior to joining the company, he guided the clinical trial management group at Accenture.

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