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APLD and Claims 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 imeprative for various reportings in US market. The course details the different types of standard and adhoc KPIs and discusses various used cases around these KPIs. Some of the used case outlined in the course include developing the detailed patient journey, persistency curves, development of SOBs, LOTs, Compliance rates, Adherance rates among others.

What will the course cover

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Detailed understanding of Rx, TRx, NRx, NBRx and other terminologies
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Understanding and difference between APLD, claims and other US datasets including Xponent, DDD, SP etc
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Used cases and applications of different datasets
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Major stakeholders and their interactions along with used case applications
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Zip to Territory mapping and HCP universe understanding
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Standard KPI and Adhoc KPIs reporting and analysis
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Detailed creation of Patient journeys, persistency curves, LOT, SOB etc
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Learning course on Machine Learning, Basic statistical understanding
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Understanding of US Ecosystem and DDD datasets

The Course Includes

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12 Sessions
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5 Exercises
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Downloadable Material
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Job Placement Opportunities in Patient Analytics Profiles
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Mobile and Laptop Accessible
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Lifetime Access
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Certification of Completion

Course Content

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Session 1: Definitions of Rx, NRx, TRx, NBRx, Difference between different APLD datasets
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Session 2: Other sales datasets including Xponent dataset, Business rules applications for various used cases
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Session 3: Calls data and applications of calls datasets, Hierarchy structures and corresponding applications
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Session 4: SF deep dive and sources of data, Therapeutic area understanding and corresponding terminologies
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Session 5: Major stakeholders and their interactions, Data and recipes
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Session 6: Standard KPI reporting and applications, Zip to Territory mapping and HCP universe understanding, SP data understanding
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Session 7: Introduction to Patient journey, claims vs EMR understanding, Understanding of open and closed claims, ICD Codes understanding
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Session 8: Understanding APLD Datasets, How to collect and generate APLD datasets, Type of Data tables
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Session 9: Understanding of Persistency used case, Compliance and Adherance understanding
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Session 10: Learning course on Machine Learning, Basic statistical understanding
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Session 11: Calculations of SOB, LOT, Calculation of Persistancy for 12 months, Understanding of US Ecosystem and DDD datasets
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Session 12: Assessment and exam