Developing a comprehensive database with sensitive health information: A profile of people living with HIV in Newfoundland and Labrador, Canada

• Published in: International Journal of Population Data Science
• Main Authors: Shabnam Asghari, Sarah Boyd, John Knight, Jillian Blackmore, Oliver Hurley, Jill Allison, Laura Gilbert, Jeff Dowden, Phil Lundrigan
• Format: Article in Journal/Newspaper
• Language: English
• Published: Swansea University 2020
• Subjects: Database development; HIV; Demography. Population. Vital events; HB848-3697; Newfoundland; Canada
• Online Access: https://doi.org/10.23889/ijpds.v5i1.1144; https://doaj.org/article/920f0766ff7f4c9bb240a3a430ac2ea2

Introduction Developing a comprehensive cohort of people living with HIV (PLHIV) to help improve healthcare has long been the vision of researchers, clinicians and decision makers. The development of this kind of database is challenging and requires strict adherence to privacy and confidentiality policies. We explored procedures, activities and events in database development. Objectives To understand processes of developing a database with sensitive health information in Newfoundland and Labrador (NL), and to investigate procedures and activities to develop the database within its environmental context. Methods A narrative case study was used to explain the challenges and procedures involved in developing a database for our population. The development of the PLHIV cohort in NL is provided as an example to demonstrate the complexity of the process. We linked three datasets that included patient-level data for PLHIV: 1. laboratory data; 2. HIV clinic data; 3. health administrative data, which allowed for the creation of a large database containing many variables describing the PLHIV cohort in the province. Results We developed a de-identified cohort of 251 PLHIV that contained 178 variables. Our case study showed database development is an iterative process. The main challenges were ensuring patient privacy and data confidentiality are not compromised and working with multi-custodian data. These challenges were addressed by establishing a data governance team. Conclusions It is important that policy be implemented to merge siloed data sources in order to provide researchers with accurate and complete data that is required to conduct sound and precise research with maximum benefits for treatment and policy-making to improve health outcomes.