Methods and systems for assessing clinical outcomes

Abstract

Described herein are methods and systems useful for characterizing clinical outcomes of a subject. Provided herein includes computer-assessed methods, medical information systems, and computer-readable instructions that can aid an end-user in diagnosis, prognosis, and treatment of a clinical outcome.

Description

CROSS-REFERENCE[0001]This application claims the benefit of U.S. Provisional Application No. 61 / 039,721, fled Mar. 26, 2008, which application is incorporated herein by reference.BACKGROUND OF THE INVENTION[0002]Conventional methods for assessing a patient's clinical outcome are primarily based on clinicians' judgment and past experience. The conventional methods generally involve laboratory tests, patient surveys and office visits at isolated time points, all of which are not scalable for a time series analysis, especially for one that tracks or predicts the trend of a patient's clinical outcome in real time. Intrinsic to the conventional methodologies is the profound drawback that a relatively small set of information such as a single clinician's personal preference is taken into consideration in reaching a clinical decision. As such, under the existing medical system, patient care becomes increasingly difficult when multiple variables are involved. In particular, there lacks a sy...

AI Technical Summary

Benefits of technology

[0004]The present invention provides a medical information system for subject data analysis. In one aspect, a system of the present invention is particularly useful for advancing the future of blood testing and data analysis. For example, the system can be part of an integrated infrastructure built around real-time, point-of-care consumer blood monitoring devices which analyze a small blood sample (e.g., 500 ul, 50 ul, 25 ul, 10 ul or even less) and wirelessly transmit that information to a database which integrates real-time data with stored data from disparate databases (patient record, genetic / genomic information, data from pivotal trials) into one central repository. The system then allows for the automatic application of multivariate, multidimensional mathematics to the data repository to perform specific commands or tasks, e.g., mapping real-time PK / PD dynamically in the context of the pathophysiology of a given medical condition.

[0005]In another aspect, a system of the present invention can be used to improve the label of key drugs through adaptive clinical studies which generate publications for label expansions for new indications, patient subpopulations, and for ameliorating safety concerns. The development of such a system for home, real-time blood monitoring has significant implications which allow one to collect information which is otherwise not available through the use of the conventional laboratory testing.

Problems solved by technology

The conventional methods generally involve laboratory tests, patient surveys and office visits at isolated time points, all of which are not scalable for a time series analysis, especially for one that tracks or predicts the trend of a patient's clinical outcome in real time.

Intrinsic to the conventional methodologies is the profound drawback that a relatively small set of information such as a single clinician's personal preference is taken into consideration in reaching a clinical decision.

As such, under the existing medical system, patient care becomes increasingly difficult when multiple variables are involved.

In particular, there lacks a system and method to effect a multi-dimensional analysis in which a large set of biomarkers are used to aid in the diagnosis, prognosis, and treatment of a clinical outcome or the design and execution of a clinical trial.

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