SERVICE

Standardized baseline business rules that eliminate ambiguity around common work developed across various Oncology teams

Leveraged in-house domain expertise in standardizing the complex rules around LoT-Regimen creation by taking into consideration indication-specific nuances; provides accelerated start to the projects and enables quicker turnaround

Indications supported

Effort saving during the execution phase

Cross-Functional Team Consumption Enabled

“D Cube Analytics brought to the table strong domain knowledge and Therapeutic Area expertise.

The collaboration led to incredible work that eliminated the bottleneck that we had in terms of consuming reports between cross-functional teams due to varied business rules and definitions.”

Objective

The value and relevance of an analytical output are driven by the quality of the business rules being used for the analysis. More often than not, many Analytics COE organizations and Business groups come across counter-intuitive and conflicting insights across analyses.

One of the top reasons for the same is the lack of robustness and standardization in the business rules being used. The issue is especially more prominent in therapeutic areas like Oncology, where the treatment patterns are relatively more complicated.

For truly productizing the Analytical processes, organizations need to give special focus in handling the above variances possible in business rules.

Introduction

D Cube Analytics proposed taking a holistic approach that will require collaborating with all relevant teams in understanding their current approach and requirements in order to go through the consolidation and standardization process that will have less variance in the business rules during any analytics application.

By this exercise, we would ensure that the end result is a creation of a one-stop solution that will be used across different teams for their analytical needs.

Solution

Coming up with robust and relevant business rules requires not only the therapeutic area knowledge but also the understanding of the limitations of input data sources.

With the experience of working on all major therapeutic areas and many popular syndicated data sources, D Cube Analytics developed libraries of business rules suitable for analytical processes like Patient Cohorts creation, LoT and Regimen Assignment, Source of Business tracking, Adherence, and Persistence calculation, etc.

These business rule libraries are consumed by the users in the form of code process blocks in the analytical process flows.

Outcome

  1. Quicker turnaround of the analytics requests enabled by productized analytics delivery approach
  2. Faster consumption of analytical outputs driven by increased transparency of underlying business rules
  3. Access to baseline rules that can be used as accelerators for developing customized business rules for any new indication being studied

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