Calgary Thrives: Data sharing and linkage in the not-for-profit sector. - Jagodzinski, Robert; Pritchard, Katharin; Lau, Jason; Berzins, Sandy; Perry, Robert; Jafri, Komal; Armstrong, Debra; Pang, Lily (International Journal of Population Data Science, 2018)
Introduction Compared to the public sector, not-for-profits are less focused on cross-agency data linkage. Technical capacity is often secondary to addressing caseloads and protecting clients. Clients’ privacy is paramount and can be perceived as a barrier to collaboration between agencies. However, collaboration could streamline referrals and better assist vulnerable populations. Objectives and Approach Six not-for-profit agencies in Calgary, Canada participated in a data sharing project to measure various aspects of poverty and link data to determine cross-agency service usage. With this goal in mind, agencies examined their consent and data sharing practices to assess barriers to data sharing. There was a thorough exploration of client consent and how a client’s context can enable or limit data sharing. Cross-agency program usage was assessed among participating agencies using a privacy-preserving record linkage (PPRL) methodology. Results Amongst the six participating agencies, four were deemed to have adequate technical capacity to share data. A contributing factor to the willingness of agencies to share data was the development of LinkWise: a PPRL software created and developed by PolicyWise. Linkage rates amongst three agencies were compared. Rates ranged from 47.8% to 0.23%. A higher linkage rate between two agencies indicated a small community based agency which provided many referrals to a larger agency, such as a food bank. Lower linkage rates on client intake may indicate an agency with many clients. It may also indicate differing socio-economic brackets for their clients’ catchment area. Conclusion/Implications While capacity, caseloads, and privacy protection restrict data sharing, not-for-profit agencies would benefit from a data sharing strategy. Linking data represent opportunities for collaboration within a significantly resource constrained sector. Moreover, it could more effectively address issues of vulnerable populations, streamline referrals for services, and facilitate quality improvement.