Can Machine Learning Fix This Coding Compliance Crisis?
"Arizona Medical Doctors" (disguised) seeks a cost-effective solution to improve its medical claims coding quality. The new Vice President of Revenue Cycle Management learns that a contract was signed with a software firm to develop and implement, for the first time, an artificial intelligence (AI) solution that will combine natural language interpretation and machine learning for Evaluation & Management (E&M) medical coding. If it works, the new system will improve E&M coding quality at a very low cost compared with the company's current human quality control process. The VP needs to decide whether to go forward and if so, how to mitigate the significant project and business risks. The case introduces students to two branches of artificial intelligence: natural language interpretation (newer, riskier technology than speech recognition) and machine learning. Students are challenged to recognize the relationship between IT project risks and business risks, spot high-level IT project risks and consider how to mitigate them, and to consider implications for managing rapidly-evolving emerging technologies in health care and other contexts.