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: Methods, systems, and apparatus, including computer programs encoded on computer storage media, to present a video. One of the methods includes obtaining one or more unstructured documents. The method includes obtaining, by a computer system, a data model, the data model identifying a type of fact that can be determined from the one or more unstructured documents. The method includes determining, by the computer system, a channel to extract facts from the document based on the type of fact. The method includes distributing, by the computer system, the one or more unstructured documents to the channel. The method includes extracting, by the channel, facts from the one or more unstructured documents. The method also includes storing the facts in a data model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, to present a video. One of the methods includes obtaining one or more unstructured documents. The method includes obtaining, by a computer system, a data model, the data model identifying a type of fact that can be determined from the one or more unstructured documents. The method includes determining, by the computer system, a channel to extract facts from the document based on the type of fact. The method includes distributing, by the computer system, the one or more unstructured documents to the channel. The method includes extracting, by the channel, facts from the one or more unstructured documents. The method also includes storing the facts in a data model.

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: Methods, systems, and apparatus, including computer programs encoded on computer storage media, to present a video. One of the methods includes obtaining one or more unstructured documents. The method includes obtaining, by a computer system, a data model, the data model identifying a type of fact that can be determined from the one or more unstructured documents. The method includes determining, by the computer system, a channel to extract facts from the document based on the type of fact. The method includes distributing, by the computer system, the one or more unstructured documents to the channel. The method includes extracting, by the channel, facts from the one or more unstructured documents. The method also includes storing the facts in a data model.