GISinc’s innovation partner, GISiP, will attend this year’s HIMSS Conference in Orlando, FL March 9th – 13th.
GISiP will share booth space with GISinc employees with business partner Esri in Booth 1246.
What is MapMasq?
MapMasq is the first product of its kind to tackle protecting the spatial component of patient data and privacy. The tool preserves the anonymity of Patient Health Information (PHI) while still allowing researchers the ability to perform a meaningful analysis.
Though MapMasq could be applied to many markets, GISiP’s primary focus is on the health industry. With a growing demand for patient locational data to drive analytics, privacy becomes a greater concern. In order to meet HIPAA compliance, organizations must find ways to conceal their data. MapMasq offers a statistically based solution that users can employ with confidence.
This product is a calculator, not a single push button solution. Various settings can be adjusted based on the expert knowledge of the user. Custom built documentation is available to guide users in application as well as resources for standards and best practices. Methodologies behind the algorithms used in MapMasq can be found in referenced peer-reviewed journals available at www.mapmasq.com as well as resources for protecting PHI and HIPAA compliance.
Differential Privacy Example:
Uses of MapMasq for PHI Anonymity
Let’s look at this from a use-case perspective. Imagine an organization that has a data warehouse full of valuable PHI and a limited staff to analyze. This information, though valuable, is inert and inaccessible due to the sensitive nature of its contents. MapMasq gives that data the ability to be broadly disseminated to academia, researchers, contractors, or the press to begin applying spatial analytics and discovering potential trends or risks. Through minimizing risk and disclosure avoidance your organization can become part of the solution in the health industry. Application of this tool encourages collaboration across your organization and the industry at large.
K Mean Neighbor - One Method Used by MapMasq
To further expound on a specific use case, imagine you were working with two different agencies. One, the Department of Health that collects information pertaining to homes/offices with known asbestos presence. Another, a local hospital in an overlapping service area as the asbestos study data. Conflating these two data sources could allow for correlations based on observation and relationships. You could potentially isolate a new variable as an indicator. Getting this data into the hands of the right analyst might typically be a bureaucratic feat. MapMasq allows both parties the opportunity to conceal the true addresses and identities of individuals so the information can be passed along to any applicable statistician or analyst to quantify results.
Just image what the future of healthcare could be with this level of PHI protection yet increased analysis of trends and relationships.
Binning and aggregation example:
See us at the HIMSS 2020!