Data Quality and Knowledge Creation: A Qualitative Study of Data-usage in Healthcare

Abstract

This thesis explores the data quality and information transformation in the healthcare company Roche Diabetes Care. Through a case study the purpose of this thesis is to understand how data is transformed into meaningful information and how knowledge creation is positively influenced. The theoretical framework of data quality by Wang & Strong (1996) is used to measure the data usage and find patterns in the data-usage process. Furthermore, the DIKW pyramid by Ackoff is used to explain the transformation process from data to information to knowledge, and the linking between these elements. In considering the data usage, four major findings were found to affect the data quality; change, mistake, poor structures and system design. These four incidents are contributing to the data not being properly employed by employees. Therefore, in order for Roche Diabetes Care to improve data quality and make data consumers’ use the data they need to 1. Regularly provide feedback to the data by actively using it. 2. Invest in tools and processes to ensure accuracy. 3. Provide clear and definable data-usage structures to employees. 4. Improve the flexibility and design of the system. Furthermore, the system is the middleman of transforming the data into information, and in order for Roche Diabetes Care to turn the data collected into meaningful information where knowledge creation is positively influenced, it has to encourage employees to share data, information and knowledge among one another. To increase knowledge creation the company should invest resources in tools and procedures that enhances knowledge sharing. This thesis argues that one of the most effective way to increase knowledge creation is to enhance knowledge sharing.