Title: Can Machine Learning Fix Our Coding Compliance Crisis?
Authors: S. J. Skeete, and Janis L. Gogan
Publication Date: 2019
This case study will enable students to learn about contract, develop and implement AI-based software
for Evaluation and Management (E/M) coding. In addition, case study will provide you with inside
information to deal with similar projects in terms of risk and how to decide how to proceed with right
plan to have controls in place to help prevent risks from materializing and to detect problems that
might nevertheless arise during the project. Furthermore, it looks into the following aspects of internal
auditing:
• Draw on PEST analysis to prepare for predictable surprises/crises.
• Identify specific predictable business risks which can result from a flawed system or a software
development project that runs behind schedule.
• Assess an organization’s IT project management resources (assets and capabilities) and identify
necessary resources that are missing or weak.
• Proactively identify project risks in a planned IT project, and implement appropriate
preventive, detective, and corrective controls.
Suggested Supplemental Readings:
Johnston, M. The transformation of healthcare with AI and machine learning.
InformationWeek
October 16, 2018. www.informationweek.com/big-data/ai-machine-learning/the-transformationof- healthcare-with-ai-and-machine-learning/a/d-id/1333039?print=yes
Case Study Questions
Q1. What business risks might AMD face if they do not improve coding accuracy?
Q2. From her discussions with AMD CIO (Darren Edwards) and other AMD managers, what can
Barbara McMahon infer about the AMD IS organization’s strengths and weaknesses?
Q3. Why does McMahon feel uncomfortable about this project? What project risks are evident?
Q4. McMahon is considering several alternative courses of action; what do you recommend she do?
