A configurable identity matching algorithm for community care management

Abstract

Systematic performance management for complex patient care is challenging. Heterogeneous healthcare data silos and inconsistent patient identity, coupled with patient privacy regulations, limit our ability to correlate healthcare data for complex patients. Cloud computing is an emerging technology that could be leveraged to address the issue of heterogeneous healthcare data silos if a regional health authority provided data hosting with appropriate data sharing agreements and identity management, in order to correlate healthcare data for complex patients. This paper introduces a configurable identity matching algorithm for correlating shared data from multiple stakeholders into a common data model to support performance management of community healthcare. The authors illustrate its use in a case study of cloud-hosted performance management for community care of complex patients at a regional health authority in Canada.

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Acknowledgements

This work was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Graduate Scholarship (OGS). The authors would like to thank the anonymous reviewers for their helpful comments.

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Correspondence to Benjamin Eze.

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Eze, B., Kuziemsky, C. & Peyton, L. A configurable identity matching algorithm for community care management. J Ambient Intell Human Comput 11, 1007–1020 (2020). https://doi.org/10.1007/s12652-019-01252-y

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Keywords

  • Healthcare interoperability
  • Performance management
  • Record linkage
  • Community care
  • Cloud computing
  • Performance management