Surgical network, instrument, and cloud responses based on validation of received dataset and authentication of its source and integrity
A system for validating data purportedly generated in a medical procedure is disclosed. The system includes a medical hub, at least one remote server communicatively coupled to the medical hub, and a medical instrument communicatively coupled to the medical hub. The system is configured to access the data, validate the data to determine if the data is validly generated by the medical procedure, determine that the data contains at least one flaw or error, and improve data integrity by preventing the at least one flaw or error from being integrated into a larger dataset associated with the at least one remote server.
1. A system for validating data generated in performance of a medical procedure, the system comprising:
a medical hub;
at least one remote server communicatively coupled to the medical hub; and
a medical instrument communicatively coupled to the medical hub;
wherein the system is configured to:
access data associated with a medical procedure;
analyze the accessed data to determine validity of the accessed data, wherein valid data comprises unaltered data generated in the performance of the medical procedure and invalid data comprises altered data modified or created outside of the medical procedure;
determine that the accessed data is generated from a validated medical instrument;
determine that the accessed data contains at least one error; and
prevent the integration of the at least one error into a larger dataset associated with the at least one remote server, wherein the larger dataset provides real time contextual information for intraoperative or perioperative changes, wherein preventing the at least one error from being integrated into the larger dataset comprises:
flagging the at least one error in the accessed data; and
identifying the validated medical instrument as containing a systematic error, wherein identifying the validated medical instrument as containing the systematic error comprises;
configuring the validated medical instrument into a controlled situation;
running a predefined routine on the validated medical instrument during the controlled situation; and
comparing a response by the validated medical instrument during the predefined routine to a result.
2. The system of claim 1 , wherein the system is further configured to:
analyze the accessed data to determine that there is a presence or an absence of a sequential trend or pattern in the accessed data, and wherein the sequential trend or pattern is common to surgical procedures;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data does not contain the sequential trend or pattern.
3. The system of claim 1 , wherein the system is further configured to:
identify an encrypted validation checksum key associated with the medical instrument;
wherein determining that the accessed data contains the at least one error comprises determining that at least part of the accessed data does not match with the encrypted validation checksum key.
4. The system of claim 1 , wherein the system is further configured to:
analyze the accessed data to determine that there is a presence or an absence of a sequential trend or pattern in the accessed data, and wherein the sequential trend or pattern is unique to a type of surgical procedure that occurred when the accessed data was generated;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data does not contain the unique sequential trend or pattern.
5. The system of claim 1 , wherein the system is further configured to:
receive a report of a malicious actor from another medical hub;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data contains a characteristic consistent with the report of the malicious actor.
6. The system of claim 1 , wherein preventing the at least one error from being integrated into the larger dataset comprises isolating the at least one error from the larger dataset and integrating the remainder of the accessed data into the larger dataset.
7. The system of claim 1 , wherein preventing the at least one error from being integrated into the larger dataset comprises determining that the at least one error is a result of the accessed data being altered and removing the accessed data from being integrated into the larger dataset.
8. A method for validating data generated in a medical procedure, the method comprising:
accessing, by a processor of at least one remote server, data generated in the performance of a medical procedure;
analyzing, by the processor, the accessed data to determine validity of the accessed data, wherein valid data comprises unaltered data generated in the performance of the medical procedure and invalid data comprises altered data modified or created outside of the medical procedure;
determining, by the processor, that the accessed data is generated from a validated medical instrument;
determining, by the processor, that the accessed data contains at least one error; and
preventing, by the processor, the integration of the at least one error into a larger dataset associated with the at least one remote server, wherein the larger dataset provides real time contextual information for intraoperative or perioperative changes, wherein preventing the at least one error from being integrated into the larger dataset comprises:
flagging the at least one error in the accessed data; and
identifying the validated medical instrument as containing a systematic error, wherein identifying the validated medical instrument as containing the systematic error comprises:
configuring the validated medical instrument into a controlled situation;
running a predefined routine on the validated medical instrument during the controlled situation; and
comparing a response by the validated medical instrument during the predefined routine to a result.
9. The method of claim 8 , further comprising:
analyzing, by the processor, the accessed data to determine that there is a presence or an absence of a sequential trend or pattern in the accessed data, and wherein the sequential trend or pattern is common to surgical procedures;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data does not contain the sequential trend or pattern.
10. The method of claim 8 , further comprising:
identifying, by the processor, an encrypted validation checksum key associated with a medical instrument;
wherein determining that the accessed data contains the at least one error comprises determining that at least part of the accessed data does not match with the encrypted validation checksum key.
11. The method of claim 8 , further comprising:
analyzing, by the processor, the accessed data to determine that there is a presence or an absence of a sequential trend or pattern in the accessed data, and wherein the sequential trend or pattern is unique to a type of surgical procedure that occurred when the accessed data was generated;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data does not contain the unique sequential trend or pattern.
12. The method of claim 8 , further comprising:
receiving, by the processor, a report of a malicious actor from a medical hub;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data contains a characteristic consistent with the report of the malicious actor.
13. The method of claim 8 , wherein preventing the at least one error from being integrated into the larger dataset comprises isolating the at least one error from the larger dataset and integrating the remainder of the accessed data into the larger dataset.
14. The method of claim 8 , wherein preventing the at least one error from being integrated into the larger dataset comprises determining that the at least one error is a result of the accessed data being altered and removing the accessed data from being integrated into the larger dataset.
15. A non-transitory computer readable medium comprising instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising:
accessing data associated with a medical procedure, through a processor of at least one remote medical server;
analyzing the accessed data to determine validity of the accessed data, wherein valid data comprises unaltered data generated in the performance of the medical procedure and invalid data comprises altered data modified or created outside of the medical procedure;
determining that the accessed data is generated from a validated medical instrument;
determining that the accessed data contains at least one error; and
preventing the integration of the at least one error into a larger dataset associated with the at least one remote medical server, wherein the larger dataset provides real time contextual information for intraoperative or perioperative changes, wherein preventing the at least one error from being integrated into the larger dataset comprises:
flagging the at least one error in the accessed data; and
identifying the validated medical instrument as containing a systematic error, wherein identifying the validated medical instrument as containing the systematic error comprises:
configuring the validated medical instrument into a controlled situation;
running a predefined routine on the validated medical instrument during the controlled situation; and
comparing a response by the validated medical instrument during the predefined routine to a result.
16. The non-transitory computer readable medium of claim 15 , wherein the operations further comprise:
analyzing the accessed data to determine that there is a presence or an absence of a sequential trend or pattern in the accessed data, and wherein the sequential trend or pattern is common to surgical procedures;
wherein determining that the accessed data contains the at least one error comprises determining that the accessed data does not contain the sequential trend or pattern.