decentralized control

Healthcare and the IoT

Patients, care facility staff members, and technical operators need to use and share various medicinal devices, in order to provide appropriate care to patients. We need Trust to enable this sharing of PHI data. In addition the devices will need to store, and exchange PHI data in order for the care to be precise. The mechanics for accessing such data need to be absolutely secure, while the confidence and Trust for ‘who gets access to what’ needs to be absolutely certain.


It’s all about the Relationships

Confirming Trust by establishing and verifying the Identities of the medical IoT devices, humans, and other NPEs in a digital health platform is step one. Step two is forming the Identity Relationships between all three.


And then about the Context

With Trusted Identity Relationships, we can leverage the rich, contextual identity-relationship data for new understanding, learnings, and generate new use cases and value. Persisting secure exchanges with granular and continuous fine-grained access controls allows for advanced eHealth solutions and, most importantly, patients receive better care.


IndyKite for NPEs in Health

In eHealth, roles and context of administrative or technical staff, care facility staff, the patient, care facilities and contracts, and even the devices themselves might change. The context should drive who and what gets access to what, why and how. IndyKite helps healthcare providers capture the context of the patient, which devices / services / staff are providing the care, which care workers are administering the care, and which legal framework governs the care, paving the way for safe and seamless IoT use cases in eHealth and Wellness.

Private & Confidential. The patient has the necessary confidence that their PHI data is secure, and the bridge of trust enables a modern set of digitalized services.

Knowledge Graph & Zero Trust. By combining a contextualized data model with a Zero Trust approach, IndyKite assures secure, safe access to PHI data across humans, devices, and ‘things,’ where necessary, when necessary.

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