In society’s increasingly computerized world, the intensification of electronic data collection is resulting in large volumes of new data (known as big data). This is creating new opportunities for secondary uses of this data, particularly in the healthcare sector. The opportunities for secondary uses of healthcare data include constructive studies, research, policy assessment and other endeavors that could produce beneficial results such as improved healthcare quality and finding cures for diseases. However, protecting the privacy of individuals represented in data presents a challenge to the secondary utility of healthcare data. De-identifying data by removing any information that could be used to uniquely identify individuals is a potential solution to the challenge of protecting individual privacy. Hence, this research identifies a practical process for applying anonymizing techniques through a process model designed to handle requests for healthcare data.