A global pharmaceutical company is using Qlik Sense and Komment, the native writeback extension, to solve several complex use cases within their clinical trial and pharmacovigilance activities.
The pharmaceutical industry has historically been supported by SAS and Excel when transforming, reviewing and analyzing data. However, in recent years we have seen a transformation where the industry is moving to more flexible tools such as Qlik Sense. In this short article we highlight just a few of the many possible use cases for Qlik Sense in combination with a writeback solution such as Komment.
The company uses Komment to add and change data in their apps to solve critical tasks such as:
Basically all companies spend a lot of time reconciling data between two systems and the current pharmaceutical company was no exception. They needed a reliable way to help lower the time spent on looking for duplicate records, and help match records unrecognized by the system as duplicates. With the use of Komment and its writeback functionality they have been able to perform their data reconciliation much faster and at a higher quality.
This was to a great deal due to the fact that the end users no longer needed to switch between multiple systems when performing the data reconciliation. Before, all of the steps where a manual process conducted by a trial manager who'd previously spend valuable time finding matching and missing protocol deviations (PDs) between the two systems.
The second solution was built to keep track of case report submissions and compliance. As a case was received there was a regulatory reporting requirement dependent on the nature of the case and the company wanted to get an overview of the report submission timeliness with regards to the regulations. The solution was also designed to keep track of incoming and outgoing reports for reconciliation with external sites. For this app the customer requested a way of being able to add comments and categorizations to a case or report. For this we used naturally used Komment. That made it possible to append all the necessary meta data as well as create a viable audit trail for regulatory purposes.
The final use case we will mention here, was to create an Qlik Sense app that could continuously monitor and track any potential increases in reporting for specific adverse events. This procedure was previously handled using Excel and automated reports directly from the source system. There was however very limited information accessible in these automated reports and so the company wanted us to display comprehensive case details and history aside from the statistics.
We created a highly flexible,dynamic set of calculations that allowed for the end users to specify date range, product and events and compare the frequencies with the ones from FDA's external database FAERS. This, bundled with Komment on three different data points, served as a quick, stable, and dynamic way for the end user to independently explore, annotate and mine the data. The end users could now perform their reporting on any given interval, without having to prompt or involve other departments. They could annotate, document and display their findings in accordance with regulations and perform continuous signal detection when needed.
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