Patent Issued for Systems and methods for computing with private healthcare data (USPTO 11848082): Nference Inc.

2024 JAN 05 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Anand, Akash (Bhagalpur, IN), Aravamudan, Murali (Andover, MA, US), Ardhanari, Sankar (Chapel Hill, NC, US), Awasthi, Samir (Jamaica Plain, MA, US), Barve, Rakesh (Bangalore, IN), Murugadoss, Karthik (Cambridge, MA, US), Naqvi, Shamim (Morristown, NJ, US), Rajasekharan, Ajit (West Windsor, NJ, US), Soundararajan, Venkataramanan (Andover, MA, US), Wagner, Tyler (Boston, MA, US), filed on September 27, 2022, was published online on December 19, 2023.

The patent’s assignee for patent number 11848082 is Nference Inc. (Cambridge, Massachusetts, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Hospitals, healthcare providers and care givers collect large amounts of data from patients. It is a necessary part of the processes by which healthcare is provided to members of the public. Typically, a patient provides data to the care giver as a part of receiving treatment for his/her ailments. This data is stored by the care giver and may be used later, inter alia, for research purposes. In another typical scenario data may be collected from consumers via one or more devices, e.g., pulse oximeter, glucose monitor, smart watch, fitness bracelet, etc. In such use cases, the collected data is often used to analyze a patient’s health in a continuous manner or over a period of time. Consequently, huge amounts of patient information may be accumulated by service providers.

“Many aspects of patient data collected by care givers and service providers may be subject to privacy regulations. The usefulness and benefit of processing data collected from patients is clear and acknowledged by the public. However, there is a growing concern of maintaining the privacy of user data, particularly when the data can be used to identify the patient. Such concerns are the basis of HIPAA (Health Insurance Portability and Accountability Act) regulations initially passed in 1996 by the US Congress. Many other countries have also promulgated similar regulations and legislations. Generally, HIPAA and other regulations limit the release of personal information that may result in identification of members of the public or details of their physical attributes or biometric data.

“There is thus a need to enable biomedical (and other types of) data to be analyzed by computational processes under the constraint of maintaining the privacy of the individual patient or consumer. Such a system and methods will consequently be of great commercial, social and scientific benefit to society.

“Various objectives, features, and advantages of the disclosed subject matter can be more fully appreciated with reference to the following detailed description of the disclosed subject matter when considered in connection with the following drawings, in which like reference numerals identify like elements.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “A truly astonishing amount of information has been collected from patients and consumers pertaining to their health status, habits, environment, surroundings, and homes. Increasingly, this information is being processed by computer programs utilizing machine learning and artificial intelligence models. Such computer programs have shown remarkable progress in analyzing and predicting consumer health status, incidence and treatment of diseases, user behavior, etc. Furthermore, since the collected data may contain patient biometric and other personal identification attributes, there is a growing concern that such computer programs may allow the identities of patients and consumers to be learned. Accordingly, enterprises interested in analyzing healthcare data containing private attributes are concerned with maintaining privacy of individuals and observing the relevant regulations pertaining to private and personal data, such as HIPAA (Health Insurance Portability and Accountability Act 1996) regulations.

“In addition to HIPAA, many other regulations have been enacted in various jurisdictions, such as GDPR (General Data Protection Regulations) in the European Union, PSD2 (Revised Payment Services Directive), CCPA (California Consumer Privacy Act 2018), etc.

“In the following descriptions, the terms “user information,” personal information,” “personal health information (“PHI”),” “healthcare information data or records,” “identifying information,” and PII (Personally Identifiable Information) may be used interchangeably. Likewise, the terms “electronic health records (“EHR”)” and “data records” may be used interchangeably.

“One approach to handling private data is to encrypt all the records of a dataset. Encrypted text is sometimes referred to as ciphertext; decrypted text is also referred to as plaintext. Encryption may be described, by way of analogy, as putting the records of the dataset in a locked box. Access to the records of the locked box is then controlled by the key to the locked box. The idea is that only authorized entities are allowed access to the (decryption) key.

“Some regulations (e.g., HIPAA) require that healthcare data be stored in encrypted form. This is also sometimes referred to as “encryption at rest.””

The claims supplied by the inventors are:

“1. A method comprising: constructing an isolated memory partition that forms a secure enclave, wherein the secure enclave is available to one or more processors for running one or more application computing processes in isolation from one or more unauthorized computing processes running on the one or more processors; and pre-provisioning software within the secure enclave, wherein the pre-provisioned software is configured to execute instructions of the one or more application computing processes on the one or more processors by: receiving at least one of input data or the instructions for the one or more application computing processes in an encrypted form; loading the input data into the secure enclave; loading one or more programs for analyzing the input data into the secure enclave; running the one or more programs for analyzing the input data using the secure enclave; decrypting the at least one of input data or instructions using one or more cryptographic keys; executing the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generating a proof of execution that proves that the one or more instructions of the one or more application computing processes operated on the received input data; encrypting the output data using the one or more cryptographic keys; and providing external access to the encrypted output data and the proof of execution.

“2. The method of claim 1, further comprising: receiving, by the one or more processors, from a data provider, the input data; and receiving, by the one or more processors, from an instruction provider corresponding to an entity other than the data provider, the one or more programs for analyzing the input data.

“3. The method of claim 2, further comprising de-identifying the input data prior to loading the set of clinical data records into the secure enclave, wherein de-identifying the input data comprises removing information that identifies one or more individuals or entities from the input data.

“4. The method of claim 3, wherein the input data comprises clinical data that is de-identified by removing personally identifying information (PII) from the clinical data.

“5. The method of claim 2, further comprising providing a decryption key associated with the data or the instructions of the one or more application computing processes inside the secure enclave to the data provider or the instruction provider, respectively.

“6. The method of claim 2, further comprising associating an input de-identification probability with input data prior to loading the input data into the secure enclave, wherein the secure enclave maintains the input de-identification probability in the output data.

“7. The method of claim 2, wherein the input data and the one or more programs for analyzing the input data are loaded into the secure enclave in a same transaction.

“8. The method of claim 1, further comprising connecting the secure enclave to a web server running inside a second secure enclave and causing the output data of the secure enclave to be displayed as a web page on a web client or web browser.

“9. The method of claim 8, wherein the input data being processed by the web server inside a secure enclave is not accessible to the web browser or the web client.

“10. The method of claim 8, wherein the output data displayed via the web server is associated with a cryptographic object associated with the secure enclave.

“11. The method of claim 1, further comprising receiving the input data or instructions from a curation service, wherein the curation service determines that the input data or instructions are privacy-preserving.

“12. The method of claim 1, wherein the secure enclave is communicatively coupled to one or more other secure enclaves to form a pipeline, wherein the output data from the secure enclave is provided as input data to a subsequent secure enclave in the pipeline.

“13. The method of claim 12, wherein the proof of execution comprises a cryptographic object.

“14. The method of claim 13, wherein the cryptographic object is a representation of the contents of the secure enclave.

“15. The method of claim 14, wherein the representation of the contents of the secure enclave proves that no unauthorized computer program operated on the input data.

“16. The method of claim 14, wherein the representation of the contents of the secure enclave proves that an input de-identification probability associated with the input data was maintained by the secure enclave.

“17. The method of claim 14, wherein the cryptographic object is linked with one or more other cryptographic objects representing contents of the one or more other secure enclaves in the pipeline.

“18. The method of claim 1, wherein running the one or more computing processes in the secure enclave further comprises generating a unique signature for the secure enclave based on the at least one of input data or instructions.

“19. The method of claim 1, wherein the received input data and the instructions of the one or more application computing processes are not accessible to any other secure enclaves linked to the secure enclave in a pipeline.

“20. The method of claim 19, wherein the received input data and instructions of the one or more application computing processes is not accessible to an operator of the pipeline.

“21. The method of claim 1, wherein the one or more unauthorized computing processes include at least one privileged software, privileged firmware, or a network interface process.

“22. The method of claim 1, wherein the input data comprises a set of clinical data records.

“23. A system comprising: a non-transitory memory; and one or more hardware processors configured to read instructions from the non-transitory memory that, when executed, cause the one or more hardware processors to perform operations comprising: constructing an isolated memory partition that forms a secure enclave, wherein the secure enclave is available to the one or more hardware processors for running one or more application computing processes in isolation from one or more unauthorized computing processes running on the one or more hardware processors; and pre-provisioning software within the secure enclave, wherein the pre-provisioned software is configured to execute instructions of the one or more application computing processes on the one or more processors by: receiving at least one of input data or the instructions for the one or more application computing processes in an encrypted form; loading the input data into the secure enclave; loading one or more programs for analyzing the input data into the secure enclave; running the one or more programs for analyzing the input data using the secure enclave; decrypting the at least one of input data or instructions using one or more cryptographic keys; executing the one or more application computing processes based on the decrypted at least one of input data or instructions to generate output data; generating a proof of execution that proves that the one or more instructions of the one or more application computing processes operated on the received input data; encrypting the output data using the one or more cryptographic keys; and providing external access to the encrypted output data and the proof of execution.

“24. The system of claim 23, wherein the operations further comprise: receiving from a data provider, a set of clinical data records; receiving from an entity other than the data provider, a program for analyzing the set of clinical data records; loading the set of clinical records and the program for analyzing the set of clinical data records into the secure enclave; and running the program for analyzing the set of clinical data records using the secure enclave.

“25. The system of claim 24, wherein the operations further comprise deidentifying the set of clinical data records prior to loading the set of clinical data records into the secure enclave.

“26. The system of claim 24, wherein the operations further comprise providing a decryption key associated with the secure enclave to the data provider.

“27. The system of claim 23, wherein the operations further comprise connecting the secure enclave to a web browser running inside a second secure enclave and causing the output data of the secure enclave to be displayed as a web page on a web client or web browser.

“28. The system of claim 23, wherein the secure enclave is communicatively coupled to one or more other secure enclaves to form a pipeline, wherein the output data from the secure enclave is provided as input data to a subsequent secure enclave in the pipeline.

“29. The system of claim 23, wherein the proof of execution comprises a cryptographic object.

“30. The system of claim 23, wherein running the one or more computing processes in the secure enclave further comprises generating a unique signature for the secure enclave based on the at least one of input data or instructions.”

There are additional claims. Please visit full patent to read further.

For additional information on this patent, see: Anand, Akash. Systems and methods for computing with private healthcare data. U.S. Patent Number 11848082, filed September 27, 2022, and published online on December 19, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11848082)&db=USPAT&type=ids

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