The Economics of Big Data in Healthcare: A Case Study of the ICD-9 to ICD-10 Transition

Abstract

This thesis attempts to provide a methodological and qualitative analysis of the trend in data usage in the healthcare industry and highlight the importance of economic evaluation in big data for healthcare. The paper explores the need for economic evaluation of the current data usage scenario in Canada via a case study on the ICD-9 to ICD-10 transition and illustrates the gaps in data availability. Detailed formulae for calculating the costs and benefits of the transition is provided, while a comprehensive guideline illustrates how the cost calculations would differ between the different provinces of Alberta, Manitoba, Saskatchewan and British Columbia. The paper also presents an overview of the upcoming ICD-11 transition and provides a framework for conducting an economic evaluation of the ICD-10 to ICD-11 transition. In conclusion, the thesis finds that although considerable progress has been made, significant improvements in data utilization is required to reap the full benefits of health data available and enable efficient economic evaluation.