Protecting confidentiality of patients and study participants is mission-critical across the health care continuum, yet poses obstacles for the sharing and analysis of health data. Confidentiality protection can retard research from the individual to the population level, but solutions to this important problem are often unsatisfactor and even absent in many applied settings. Recent advances in cryptography for the first time support the analysis of confidential data in the encrypted space (e.g. make it homomorphic) - meaning analyses can be conducted on encrypted data with potentially little if any risk of revealing confidential information. This has enormous potential for accelerating research since confidential data would not have to be decrypted to allow analysis and dissemination of the results, but this potential has yet to be evaluated within the context of human subjects research. This project will perform an exploratory evaluation of homomorphic cryptography for the geospatial analysis of confidential health data and will accomplish four aims:
Aim 1 : Build a prototype secure multi-party computation (SCM) platform for the computation of mathematical operations required in geospatial analyses. The platform will implement geospatial analysis protocols on encrypted data such that the identity of individuals cannot be reconstructed or deduced. We will evaluate security of the approach using external expert testing designed to reconstruct identity of individuals. This exploratory project will evaluate the computational performance of the following geospatial operations on encrypted data: (1) Spatial weight calculations for residential locations;(2) cluster/hotspot analysis;(3) calculation of rates of late stage diagnosis by race;and (4) calculation of relative and absolute disparities in stage at diagnosis. These have been selected to be representative of the geospatial computations frequently undertaken in geohealth analyses.
Aim 2 : Apply the prototype systems to assess racial disparities in stage at diagnosis for prostate and breast cancers. This will evaluate practical feasibility using previously analyzed data, and will determine whether the results with the not-encrypted data are reproducible.
Aim 3 : Formally evaluate the approach and formulate recommendations using an independent working group convened by the North American Association of Central Cancer Registries to include stake-holders including health researchers, IRB Chairs and committee members, experts in confidentiality protection, Directors of disease registries and cryptographers.
Aim 4 : Disseminate the recommendations and results of the feasibility analysis though peer-reviewed publications and presentations at scientific meeting. This highly innovative and high-impact project potentially will accelerate human health research, leading to earlier advances in treatment and improvements in our nation's health.

Public Health Relevance

Exploratory evaluation of homomorphic cryptography for confidentiality protection The National Institutes of Health is investing 100's of millions in interoperable electronic health records that are expected to revolutionize health care and disease control and surveillance. Most of the data records for these systems include personal identifiers - Names, addresses, and related health information, whose confidentiality must be protected under HIPPA and other regulations. However, confidentiality protection is proving to be a major impediment to public health research. This project will evaluate the feasibility of homomorphic encryption technology that make possible, for the first time ever, analysis without having to decrypt the data. This advance is expected to significantly accelerate research that involves accessing and/or linking confidential data.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Exploratory/Developmental Grants (R21)
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Biomedical Library and Informatics Review Committee (BLR)
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Sim, Hua-Chuan
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Ann Arbor
United States
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