Abstract: Servers of a clinical trial support network have digital data processors which execute an automated tracking and prediction model for patient engagement. The model is linked with an interfacing tool used by doctor managing a group of patients and an interfacing tool used by patients for real time capture of events. The system processes factor values to generate and track in real time a patient engagement index. The system uses the factor values to maintain a taxonomy of factor values. The system is also programmed to determine values of characteristics derived from the factors, such as a characteristic indicating time-based trend of a factor. Another advantageous characteristic is impact of multiple occurrences of a factor.

Abstract: A clinical data management system has databases, processors in servers which are programmed to process clinical data and communicate with user interfaces and external systems interfaces, and at least one database. The system imports source data from disparate clinical site sources into staging databases at refresh intervals, maintains data models, and maps data from the staging databases into the data models, and feeds data from the data models into data delivery databases. There is a uniform refresh frequency for the staging databases. The system output is regularly updated data for clinical site performance, quality and risk metrics to a clinical study team. The data mapper servers identify each of a plurality of source data stages, and transform data from each stage to one or more data models according to one or more mapsets, each mapset defining a transformation.

Abstract: A clinical data management system (1) has databases (20), processors in servers (2-4) which are programmed to process clinical data and communicate with user interfaces and external systems interfaces, and at least one database. The system imports source data from disparate clinical site sources into staging databases at refresh intervals, maintains data models, and maps data from the staging databases into the data models, and feeds data from the data models into data delivery databases. There is a uniform refresh frequency for the staging databases. The system output is regularly updated data for clinical site performance, quality and risk metrics to a clinical study team. The data mapper servers identify each of a plurality of source data stages, and transform data from each stage to one or more data models according to one or more mapsets, each mapset defining a transformation.

Abstract: A clinical trial data capture system has clinical site computers (6), each registered with a site and having thick client software, and a server (2) programmed to receive clinical data from the site computers and to analyse said data in real time. The server (2) automatically determines if a site computer is outside of an allowed region, indicating unauthorised use, and takes an action such as clearing the computer's data. Each site computer performs cycle management by maintaining a workflow (14) per patient, and imposes a consent gate through to subsequent workflow stages of patient treatment with n visits V1 . . . Vi . . . Vn, and treatment follow-up. A distribution lplot is generated (27) for parameters when data is close to thresholds and a threshold may be automatically modified accordingly.

Abstract: A clinical data management system (1) has databases (20), processors in servers (2-4) which are programmed to process clinical data and communicate with user interfaces and external systems interfaces, and at least one database. The system imports source data from disparate clinical site sources into staging databases at refresh intervals, maintains data models, and maps data from the staging databases into the data models, and feeds data from the data models into data delivery databases. There is a uniform refresh frequency for the staging databases. The system output is regularly updated data for clinical site performance, quality and risk metrics to a clinical study team. The data mapper servers identify each of a plurality of source data stages, and transform data from each stage to one or more data models according to one or more mapsets, each mapset defining a transformation.