Secure compute can allow you to build secure collaborative health care data record linkage system
Patient data could get scattered across multiple health care organizations. It could especially occur for chronic diseases such as asthma where patients may receive care at multiple institutions within a region.
Without proper record linkage and data duplication, many of the disease specific conditions may be over-represented. For example, it is reported that after cross-institution deduplication, the number of records related to diabetes reduced 24.0%, asthma reduced 28.0%, and myocardial infarction reduced 10.9%.
The data belonging to multiple healthcare organizations could be linked, cleaned and analyzed to build machine learning models, get useful statistics and insights into the underlying disease.
For example, such infrastructure could be used to build a machine learning model (e.g., logistic regression) to understand the relationship between air pollution to asthma attacks for each race group. Furthermore, linked and cleaned data could be used to understand health care and disease trends and can be used to provide statistical insights.
Our SecureCompute platform enables customer to securely build collaborative record linkage and machine learning models.
Read more on our white paper.