25 Apr 2018 Blog
Current Gaps in Clinical Data Management

When it comes to data management, there are a lot of data gaps that requires filling. Below are the areas of data management where the industry is facing problems. If any of this sounds familiar, you might need help!

Data Capturing & Aggregation: The prevalence of ‘data heterogeneity’ in clinical trials is what makes data capturing and aggregation a complex process. Capturing data is yet to be perfected because it comes in different forms and formats. It is generated from multiple devices used by practitioners who follow distinct regulatory protocols. The cleanliness of clinical data is also subject to issues like non-adherence and data variability which arise due to a different set of on-site challenges. This primary challenge stifles the data lifecycle, affecting analytics and quality of insights.

Data Cleaning & Discrepancy Management: Clinical trials deal with unstructured data all the time. Though digital documents such as EDCs, EHRs and ePROs are embraced in clinical trial projects, use of PCRFs cannot be eliminated completely. This fractional use of PCRFs and multi-source aggregation adds to the complexity of data cleanliness. Clean data, devoid of discrepancies, ensures use of accurate and rationale datasets for further analytics.

Data Storage & Data Security: Data storage and security issues always give rise to the debate of ‘on-site or cloud model’ since it is coined with the function of cost. In either case, care must be taken to establish disaster recovery, cost efficiency, immunity against security breaches and healthcare specific compliance with HIPAA security rule.

Data Stewardship & Data Querying: Clinical data has longer shelf life, as it not just used for the current and specific research, it is archived for future research too. Sometimes, the trials also have traces of unutilized datasets that can solve disconnected healthcare issues. Owning and retrieving such data among the large volumes of data repository over time is an area that needs attention. Having historical and secondary data handy can resolve many issues. These also raise red flags through the procedure that pertain to data updation, interoperability and sharing.

About MaxisIT

At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical data, allows efficient data quality management, clinical reviews, and statistical computing.

Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring. MaxisIT’s Integrated Technology Platform is purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Analytics in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate”.

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