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ACDM19 Speaker Details

Rudolf Coetzee

Rudolf Coetzee

Perficient

Biography:

Rudolf Coetzee is Perficient’s Director of Strategic Accounts and Company Operations EMEA, focusing on supporting clients with focus on information services/technology business architecture, as well as on new IT trends including cognitive/AI, digital, cloud & mobile computing, Internet of Things, and innovation. Bringing together industry experts to collaborate on finding innovative technologies predominantly used in the R&D space of clinical data management, pharmacovigilance, clinical trials operations, data warehousing with the integration of digital transformation & AI technologies into clinical trials and patient services.

Joining Perficient 7 years ago and prior to joining Perficient, Coetzee worked in +13 years in Public and Private Healthcare as a Clinical Scientist Audiologist and founded a staffing & digital marketing firm.


Title of Session: Utilising Artificial Intelligence in Medical Coding

Description of Session:

Medical coding workload increases year-on-year. Provision of medically-appropriate, reliable and reproducible safety information is a prerequisite for a sound risk-benefit assessment of medicinal products. Adequate quality of code assignments is a key prerequisite to fulfil this requirement. Medical coding must accurately and efficiently support the retrieval and evaluation of safety data.

It can be challenging to find a sufficient number of medical coders with the appropriate skills and attitude required to process the large number of terms to be coded on a daily basis. The need to achieve operational targets can conflict with the innate, and essential, drive for quality. Even with a user-friendly coding system it can take a year to train new team members in company-specific coding practices. Artificial Intelligence/ Cognitive Computing is increasingly being used in many aspects of the pharma. We will discuss how Machine Learning and AI can be used in medical coding to achieve more without increasing team size or impacting quality.

Learning Objectives:

Gain an understanding of the potential use of AI in medical coding

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