Abstract: Described herein is a graphical intervention test development system. The graphical intervention test development system provides a graphical intervention test development environment that facilitates computer-based design of an intervention test. The graphical intervention test development environment provides a graphical user interface (GUI) and visualizations of various aspects of an intervention test therein. The graphical intervention test development environment further provides a control interface through which a user can manipulate control parameters that affect outcomes of the intervention test.

Abstract: A system for tracking adverse events may include at least one processing device programmed to receive a request from a user to record an adverse event experienced by a patient; receive a search term input by the user; identify, in an adverse event database and based on the search term, at least one database record for an adverse event, wherein the at least one database record includes an adverse event type and at least one characteristic; receive, via an input field, a rating of the at least one characteristic for the patient; generate an adverse event record based on the adverse event type and the rating; and store the adverse event record in an adverse event log.

Abstract: A system for tracking adverse events may include at least one processing device programmed to receive a request from a user to record an adverse event experienced by a patient; receive a search term input by the user; identify, in an adverse event database and based on the search term, at least one database record for an adverse event, wherein the at least one database record includes an adverse event type and at least one characteristic; receive, via an input field, a rating of the at least one characteristic for the patient; generate an adverse event record based on the adverse event type and the rating; and store the adverse event record in an adverse event log.

Abstract: A model-assisted system and method for predicting health care services. In one implementation, a model-assisted system may comprise a least one processor programmed to access a database storing a medical record associated with a patient and analyze the medical record to identify a characteristic of the patient. The processor may determine a patient risk level indicating a likelihood that the patient will require a health care service within a predetermined time period; compare the patient risk level to a predetermined risk threshold; and generate a report indicating a recommended intervention for the patient. The processor may further determine a calibration factor indicating a difference between an average patient risk level and an average actual healthcare service usage for a first group of patients; and determine, based on the calibration factor, a bias relative to a second group of patients.

Abstract: A model-assisted system and method for predicting health care services. In one implementation, a model-assisted system may comprise a least one processor programmed to access a database storing a medical record associated with a patient and analyze the medical record to identify a characteristic of the patient. The processor may determine a patient risk level indicating a likelihood that the patient will require a health care service within a predetermined time period; compare the patient risk level to a predetermined risk threshold; and generate a report indicating a recommended intervention for the patient. The processor may further determine a calibration factor indicating a difference between an average patient risk level and an average actual healthcare service usage for a first group of patients; and determine, based on the calibration factor, a bias relative to a second group of patients.

Abstract: A model-assisted system and method for predicting health care services. In one implementation, a model-assisted system may comprise a least one processor programmed to access a database storing a medical record associated with a patient and analyze the medical record to identify a characteristic of the patient. The processor may determine a patient risk level indicating a likelihood that the patient will require a health care service within a predetermined time period; compare the patient risk level to a predetermined risk threshold; and generate a report indicating a recommended intervention for the patient. The processor may further determine a calibration factor indicating a difference between an average patient risk level and an average actual healthcare service usage for a first group of patients; and determine, based on the calibration factor, a bias relative to a second group of patients.

Abstract: A graphical user interface for displaying an electronic medical record associated with a patient is provided. The graphical user interface may include an area configured to display patient information, which may include at least a name of the patient. The graphical user interface may also include an indicator displayed in association with the name of the patient. The indicator may include information specifying that the patient is potentially eligible for one or more trials, the patient is participating in one or more trials, or the patient has completed one or more trials.

Abstract: A system for providing guideline concordance may include at least one processing device programmed to receive, via a graphical user interface of a user device, a search term associated with a drug; access a structured database to identify, based on the search term, a description of at least one regimen that includes the search term; display, via the graphical user interface, a selectable identifier of the at least one regimen; receive, via the graphical user interface, a selection of a regimen, wherein the regimen is associated with the drug; generate, based on the structured database, one or more indications that are concordant for the regimen; receive, via the graphical user interface, a selection of a concordant indication; and store, in an electronic health record database, a patient record with information identifying the selected regimen and the selected indication.

Abstract: A computer-implemented system for managing electronic medical records may include one or more processors configured to receive, via a user interface of a user device, a user input for adding a new trial and create a new trial portfolio based on the received user input. The portfolio may comprise patient eligibility criteria associated with the new trial. The one or more processors may also be configured to automatically create a patient-trial matching algorithm for the new trial based on the trial eligibility criteria and determine, based on electronic patient medical records associated with a plurality of patients and the patient-trial matching algorithm, at least one suggested patient determined to be eligible for the new trial. The one or more processors may further be configured to transmit, to the user device, instructions for displaying information representing the at least one suggested patient in the user interface.

Abstract: A system for tracking adverse events may include at least one processing device programmed to receive a request from a user to record an adverse event experienced by a patient; receive a search term input by the user; identify, in an adverse event database and based on the search term, at least one database record for an adverse event, wherein the at least one database record includes an adverse event type and at least one characteristic; receive, via an input field, a rating of the at least one characteristic for the patient; generate an adverse event record based on the adverse event type and the rating; and store the adverse event record in an adverse event log.