Privacy in Health-care

Privacy in Health care: Differential Privacy Techniques in Health-care data

Healthcare data is usually of the following type

- Categorical data (codes, drugs, tests, geographical information)

- Numerical data (age, duration of stay in hospital, time since last visit)

Analysts of healthcare domain are accustomed to analyze data in a particular format. They perform various types of analysis by applying techniques like transforms on formatted data. Hence it becomes necessary to provide the data they need in same format.

Addition of Laplace noise to numeric data can distort the values significantly. Differential privacy works under the assumption that individuals are independent of each other. If this assumption is violated then inferences can be made.0

Issues

- Many healthcare datasets are highly correlated or have natural constraints.

- Independent distortions of data may not make sense.

- If two drugs are said to have an effect on a patient and distorted data does not show that effect then dataset is loses trustworthiness.

It is really important to prove that DP in such datasets adds value and provides valid results.

Privacy Budgeting

There are various scenarios in which it is necessary to provide individual information for analysis. In this case it based on the priority of privacy system may have to restrict release of some amount information. This brings us to the concept of privacy budget.

In other domains privacy budget is depicted in terms of epsilon but analysts of healthcare domain may not be comfortable in working with core privacy concepts. So it is necessary to related epsilon to some common notation of privacy to allow easier communication.

Based on certain input query we get a value for a particular patient depicting his/her eligibility for participation in the analysis. Providing unrestricted access to database may reveal extra information. If the individual participates in the analysis then we may add noise to it.

When a query is expected to have large counts than high budget must be provided to ensure that the query can be executed.

Conclusion: Healthcare community still needs to disclose a lot of information hence there is high scope for research data privacy in the healthcare domain.

References:

Fida K. Dankar and Khaled El Emam, Practicing Differential Privacy in Health Care: A Review, Transactions of Data Privacy, http://dl.acm.org/citation.cfm?id=2612156.2612159