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Virtual patient identifier (vPID): Improving patient traceability using anonymized identifiers in Japanese healthcare
Jumpei Sato1, Naohiro Mitsutake2, Hiroyuki Yamada1
1Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan.
Objective:
Japan's national-level healthcare insurance claims database (NDB) is a collective database that contains the entire information on healthcare services being provided to all citizens. However, existing anonymized identifiers (ID1 and ID2) have a poor capability of tracing patients' claims in the database, hindering longitudinal analyses. This study presents a virtual patient identifier (vPID), which we have developed on top of these existing identifiers, to improve the patient traceability.
Methods:
vPID is a new composite identifier that intensively consolidates ID1 and ID2 co-occurring in an identical claim to allow to collect claims of each patient even though its ID1 or ID2 may change due to life events or clerical errors. We conducted a verification test with prefecture-level datasets of healthcare insurance claims and enrollee history records, which allowed us to compare vPID with the ground truth, in terms of an identifiability score (indicating a capability of distinguishing a patient's claims from another patient's claims) and a traceability score (indicating a capability of collecting claims of an identical patient).
Results:
The verification test has clarified that vPID offers significantly higher traceability scores (0.994, Mie; 0.997, Gifu) than ID1 (0.863, Mie; 0.884, Gifu) and ID2 (0.602, Mie; 0.839, Gifu), and comparable (0.996, Mie) and lower (0.979, Gifu) identifiability scores.
Discussion:
vPID is seemingly useful for a wide spectrum of analytic studies unless they focus on sensitive cases to the design limitation of vPID, such as patients experiencing marriage and job change, simultaneously, and same-sex twin children.
Conclusion:
vPID successfully improves patient traceability, providing an opportunity for longitudinal analyses that used to be practically impossible for NDB. Further exploration is also necessary, in particular, for mitigating identification errors.
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