Risk-based monitoring of clinical data

1. A method, implemented by a computing device, for generating an audit trail for monitoring clinical data, the method comprising:

receiving clinical data comprising patient data and investigator site data, wherein the investigator site data comprises safety metrics;

accepting and rejecting respective portions of the clinical data by applying a risk-based monitoring policy comprising one or more policy rules to the clinical data, wherein applying the risk-based monitoring policy comprises applying, to the clinical data, a machine-learning algorithm, wherein applying the machine-learning algorithm comprises:

learning, over time, patterns in the patient data and investigator site data of the clinical data;

receiving, over time, input from users regarding risk indicators in the learned patterns; and

maintaining, over time, a knowledge library based on the learned patterns and received input, wherein the accepting and rejecting of the portions of the clinical data is based on the maintained knowledge library;

generating an audit trail for the clinical data based on applying the risk-based monitoring policy to the clinical data, the audit trail comprising the clinical data and corresponding audit data, the audit data comprising:

identification of the accepted and rejected portions of the clinical data;

identification of one or more of the policy rules of the risk-based monitoring policy used in the accepting and rejecting of the respective portions of the clinical data;

one or more timestamps corresponding to when each of the accepting and rejecting of the respective portions took place.

2. The method of claim 1 , wherein applying the risk-based monitoring policy comprises applying, to the clinical data, one or more of a manual workflow or a predefined automated workflow.

3. The method of claim 1 , wherein the one or more policy rules comprises a policy rule that requires:

segmenting the clinical data into a relevant segment and a remainder;

identifying the relevant segment as being comprised in one of the accepted and rejected portions; and

timestamping one or more of the relevant segment and the remainder.

4. The method of claim 1 , wherein the audit data further comprises a digital signature certifying application of a corresponding policy rule identified in the audit data.

5. The method of claim 1 , wherein the patient data comprises, for at least one patient, demographic data, safety data, efficacy data and a medical history.

6. The method of claim 1 , wherein the investigator site data comprises productivity, quality, and risk for an investigated clinical site.

7. The method of claim 1 , further comprising configuring the risk-based monitoring policy by receiving a policy rule of the one or more policy rules from a user of the computing device.

8. The method of claim 1 , wherein the one or more of the policy rules comprises a policy rule that requires review of the clinical data by a medical reviewer and the generating of the audit trail for the clinical data.

9. The method of claim 1 , wherein the one or more of the policy rules comprises a policy rule that requires review of the clinical data by a statistical reviewer and the generating of the audit trail for the clinical data.

10. A computing device for generating an audit trail for monitoring clinical data, the computing device comprising:

interface circuitry configured to exchange signals over one or more data paths of the computing device;

processing circuitry communicatively coupled to the interface circuitry and configured to:

receive clinical data comprising patient data and investigator site data via the interface circuitry, wherein the investigator site data comprises safety metrics;

accept and reject respective portions of the clinical data by applying a risk-based monitoring policy comprising one or more policy rules to the clinical data, wherein applying the risk-based monitoring policy comprises applying, to the clinical data, a machine-learning algorithm, wherein applying the machine-learning algorithm comprises:

learning, over time, patterns in the patient data and investigator site data of the clinical data;

receiving, over time, input from users regarding risk indicators in the learned patterns; and

maintaining, over time, a knowledge library based on the learned patterns and received input, wherein the accepting and rejecting of the portions of the clinical data is based on the maintained knowledge library;

generate an audit trail for the clinical data based on applying the risk-based monitoring policy to the clinical data, the audit trail comprising the clinical data and corresponding audit data;

wherein the audit data comprises:

identification of the accepted and rejected portions of the clinical data;

identification of one or more policy rules of the risk-based monitoring policy used in the accepting and rejecting of the respective portions of the clinical data;

one or more timestamps corresponding to when each of the accepting and rejecting of the respective portions took place.

11. The computing device of claim 10 , wherein applying the risk-based monitoring policy comprises applying, to the clinical data, one or more of a manual workflow or a predefined automated workflow.

12. The computing device of claim 10 , wherein the one or more policy rules comprises a policy rule that requires:

segmenting the clinical data into a relevant segment and a remainder;

identifying the relevant segment as being comprised in one of the accepted and rejected portions; and

timestamping one or more of the relevant segment and the remainder.

13. The computing device of claim 10 , wherein the audit data further comprises a digital signature certifying application of a corresponding policy rule identified in the audit data.

14. The computing device of claim 10 , wherein the patient data comprises, for at least one patient, demographic data, safety data, efficacy data and a medical history.

15. The computing device of claim 10 , wherein the investigator site data comprises productivity, quality, and risk for an investigated clinical site.

16. The computing device of claim 10 , wherein the processing circuitry is further configured to configure the risk-based monitoring policy by receiving a policy rule of the one or more policy rules from a user of the computing device.

17. The computing device of claim 10 , wherein the one or more of the policy rules comprises a policy rule that requires review of the clinical data by a medical reviewer and the generating of the audit trail for the clinical data.

18. The computing device of claim 10 , wherein the one or more of the policy rules comprises a policy rule that requires review of the clinical data by a statistical reviewer and the generating of the audit trail for the clinical data.

19. A non-transitory computer readable medium storing a computer program product for controlling a programmable computing device in a communication network, the computer program product comprising software instructions that, when run on the programmable computing device, cause the programmable computing device to:

receive clinical data comprising patient data and investigator site data via interface circuitry, wherein the investigator site data comprises safety metrics;

accept and reject respective portions of the clinical data by applying a risk-based monitoring policy comprising one or more policy rules to the clinical data, wherein applying the risk-based monitoring policy comprises applying, to the clinical data, a machine-learning algorithm, wherein applying the machine-learning algorithm comprises:

learning, over time, patterns in the patient data and investigator site data of the clinical data;

receiving, over time, input from users regarding risk indicators in the learned patterns; and

maintaining, over time, a knowledge library based on the learned patterns and received input, wherein the accepting and rejecting of the portions of the clinical data is based on the maintained knowledge library;

generate an audit trail for the clinical data based on applying the risk-based monitoring policy to the clinical data, the audit trail comprising the clinical data and corresponding audit data, the audit data comprising:

identification of the accepted and rejected portions of the clinical data;

identification of one or more policy rules of the risk-based monitoring policy used in the accepting and rejecting of the respective portions of the clinical data;

one or more timestamps corresponding to when each of the accepting and rejecting of the respective portions took place.