Master APLD pharma datasets, Xponent, SP & claims analytics. Learn patient journeys, adherence metrics, and KPI reporting to excel in pharmaceutical analytics.
The course covers wide range of scope starting from detailed therapeutic area and US market understanding. The course further details the different types of APLD and claims datasets along with differences among the datasets. The course also outlines other US datasets including SP, DDD, HCOS, Xponent which are imperative for various reportings in US market. The course details the different types of standard and adhoc KPIs and discusses various use cases around these KPIs. Some of the use cases outlined in the course include developing the detailed patient journey, persistency curves, development of SOBs, LOTs, Compliance rates, Adherence rates among others.
Detailed understanding of Rx, TRx, NRx, NBRx and other terminologies
Understanding and difference between APLD, claims and other US datasets including Xponent, DDD, SP etc
Use cases and applications of different datasets
Major stakeholders and their interactions along with use case applications
Zip to Territory mapping and HCP universe understanding
Standard KPI and Adhoc KPIs reporting and analysis
Detailed creation of Patient journeys, persistency curves, LOT, SOB etc
Learning course on Machine Learning, Basic statistical understanding
Understanding of US Ecosystem and DDD datasets
12 Sessions
5 Exercises
Downloadable Material
Job Placement Opportunities
Mobile & Laptop Accessible
Lifetime Access
Certification of Completion
Definitions of Rx, NRx, TRx, NBRx, Difference between different APLD datasets
Other sales datasets including Xponent dataset, Business rules applications for various use cases
Calls data and applications of calls datasets, Hierarchy structures and corresponding applications
SF deep dive and sources of data, Therapeutic area understanding and corresponding terminologies
Major stakeholders and their interactions, Data and recipes
Standard KPI reporting and applications, Zip to Territory mapping and HCP universe understanding, SP data understanding
Introduction to Patient journey, claims vs EMR understanding, Understanding of open and closed claims, ICD Codes understanding
Understanding APLD Datasets, How to collect and generate APLD datasets, Type of Data tables
Understanding of Persistency use case, Compliance and Adherence understanding
Learning course on Machine Learning, Basic statistical understanding
Calculations of SOB, LOT, Calculation of Persistency for 12 months, Understanding of US Ecosystem and DDD datasets
Assessment and exam
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