Apparatus and method for prediction and management of participant compliance in clinical research

• US 7,415,447 B2
• Filed: 01/03/2006
• Issued: 08/19/2008
• Est. Priority Date: 04/02/2001
• Status: Expired due to Fees

• Current Assignee: eResearchTechnology, Inc. (Explorer Holdings, Inc.)
• Original Assignee: Invivodata Incorporated (Explorer Holdings, Inc.)
• Inventors: Shiffman, Saul, Paty, Jean A., Hufford, Michael R.
• Primary Examiner(s): Holmes; Michael B
• Application Number:
  US11/324,504
• Publication Number:
  US 20060184493A1
• Time in Patent Office: 959 Days
• Field of Search: None
• US Class Current: 706/47
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 90/00 Systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not involving significant data processing
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A system for developing and implementing empirically derived algorithms to generate decision rules to determine participant noncompliance and fraud with research protocols in clinical trials allows for the identification of complex patterns of variables that detect or predict participant noncompliance and fraud with research protocol, including performance and enrollment goals, in the clinical trial. The data may be used to overall predict the performance of any participant in a clinical trial, allowing selection of participants that tend to produce useful, high-quality results. The present invention can also be used to monitor participant compliance with the research protocol and goals to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of noncompliance, from minor noncompliance needing only corrective feedback, to significant noncompliance requiring participant removal from the clinical trial or from future clinical trials. The algorithms and decision rules can also be domain-specific, such as detecting non-compliance or fraud among subjects in a cardiovascular drug trial, or demographically specific, such as taking into account gender, age or location, which provides for algorithms and decision rules to be optimized for the specific sample of participants being studied.

Claims

1. A computer implemented method of determining noncompliance of a participant in a clinical trial, comprising the steps of:

providing historical participant compliance data;

generating at least one algorithm for determining participant noncompliance by quantitative analysis of the historical participant compliance data;

applying the at least one algorithm to determine participant compliance; and

outputting notice of noncompliance.

2. The method of claim 1, further comprising the step of translating the at least one algorithm into at least one decision rule for use with a clinical trial.

3. The method of claim 2, further comprising the step of selecting the participant for a prospective clinical trial based on the at least one decision rule.

4. The method of claim 3, further comprising the step of dropping the participant from the clinical trial based on the at least one decision rule when the algorithm identifies the participant as noncompliant.

5. The method of claim 1, wherein the participant is a particular clinical trial site, and the historical participant compliance data includes enrollment levels in previous clinical trials conducted by the particular clinical trial site.

6. The method of claim 1, wherein the participant is a particular clinical trial site, and the historical participant compliance data includes achievement of target enrollment levels in previous clinical trials conducted by the particular clinical trial site.

7. The method of claim 1, wherein the participant is a particular clinical trial site, and the historical participant compliance data includes data regarding the compliance of a clinical trial site with research protocols in previous clinical trials.

8. The method of claim 7, wherein the data regarding compliance of a clinical trial site with research protocols relates to at least one of:

training provided to subjects, monitoring of subjects during a clinical trial and compliance of subjects participating in clinical trials conducted by the clinical trial site.

9. The method of claim 1, wherein the historical participant compliance data includes compliance data for subjects in clinical trials involving the participant.

10. The method of claim 1, further comprising the step of storing the historical participant compliance data in a database.

11. The method of claim 10, wherein the database stores historical participant compliance data for a plurality of participants in a clinical trial.

12. The method of claim 11, wherein at least one algorithm for determining participant noncompliance by quantitative analysis of the historical participant compliance data is generated for each participant.

13. The method of claim 1, wherein the historical participant compliance data is collected at an earlier point in time during the clinical trial.

14. The method of claim 1, wherein the historical participant compliance data is collected during a previous clinical trial.

15. The method of claim 1, wherein the participant is one of:

a medical professional conducting the clinical trial, a subject in the clinical trial, an administrator of the clinical trial, an investigator, a study coordinator, a data collector, a clinical trial monitor, a clinical trial site, a sponsoring pharmaceutical company and a contract research organizations that provides training for clinical trial sites and personnel.

30. The method of claim 11, further comprising the step of ranking the plurality of participants based on a likelihood of each participant complying with protocols for a future clinical trail, determined by an algorithm associated with each participant.

16. A computer implemented method of identifying a suitable clinical trial site for conducting a clinical trial, comprising the steps of:

providing a database storing historical compliance data for a plurality of clinical trial sites;

performing a statistical analysis of the historical compliance data for each clinical trial site to predict compliance in a future clinical trial; and

selecting a clinical trial site that is predicted to comply with research protocols.

17. The method of claim 16, wherein the database ranks clinical trial sites according to a likelihood of compliance in a future clinical trial.

18. The method of claim 17, wherein the database ranks clinical trial sites in a specific therapeutic category.

19. The method of claim 16, wherein the historical compliance data includes enrollment levels for prior clinical trials.

20. The method of claim 16, wherein the historical compliance data includes a ratio between a number of clinical trials conducted and a number of clinical trials in which target enrollment levels were achieved.

21. The method of claim 16, wherein the historical compliance data includes compliance of subjects participating in previous clinical trials conducted by each clinical trial site with research protocols.

22. The method of claim 16, wherein the historical compliance data relates to at least one of:

training provided to subjects by the clinical trial site and monitoring of subjects during a clinical trial.

23. A computer implemented method of predicting success of a clinical trial involving a selected clinical trial participant, comprising the steps of:

providing historical compliance data from a clinical trial involving the clinical trial participant;

performing a quantitative analysis of the data to identify whether the participant is likely to produce data in compliance with research protocol in the future; and

identifying whether the participant is likely to produce data in compliance with research protocols in the future.

24. The method of claim 23, wherein the historical compliance data is collected in a previous clinical trial from the clinical trial for which success is predicted.

25. The method of claim 23, wherein the historical compliance data is collected at an earlier point in the clinical trial for which success is predicted.

26. The method of claim 23, wherein the statistical analysis predicts compliance in a future clinical trial.

27. The method of claim 23, further comprising the step of selecting the participant for a clinical trial based on the quantitative analysis.

28. The method of claim 23, further comprising the step of dropping the participant from the clinical trial for which success is predicted based on the quantitative analysis.

29. The method of claim 23, wherein the research protocol includes performance goals of a clinical trial.