Abstract: A medical information navigation engine (“MINE”) is provided. In some embodiments, the system computes a current patient encounter vector for a current patient encounter, and then an optimal patient encounter vector is computed by assuming a best case patient encounter in accordance with the organizational objectives. The system is then able to compute the difference between the best case encounter and the current patient encounter. This difference is used to compute a corresponding payoff using an intelligent matrix.

Abstract: A medical information navigation engine (“MINE”) includes a medical information interface, a reconciliation engine, and an intent-based presentation engine. The medical information interface receives medical information from a plurality of medical sources, which is subsequently reconciled by the reconciliation engine. The intent-based presentation engine clusters the reconciled medical information by applying at least one clustering rule to the reconciled medication information. The clustered reconciled medical information can be presented to a user.

Abstract: A medical information navigation engine (“MINE”) includes a medical information interface, a reconciliation engine and an intent-based presentation engine. The medical information interface receives medical information from a plurality of medical sources, which is subsequently reconciled by the reconciliation engine. The intent-based presentation engine clusters the reconciled medical information by applying at least one clustering rule to the reconciled medication information. The clustered reconciled medical information can be presented to a user.

Abstract: A medical information navigation engine (“MINE”) is capable of inferring referral activity not reported into a referral workflow system by utilizing intent-based clustering of medical information. The intent based clustering reconciles received medical data, from a variety of sources, and then clusters the data by applying one or more clustering rules. After the referrals not otherwise reported are inferred, they may be utilized to generate metrics that can be utilized to enhance patient care, and reduce costs. Metrics may be generated for both in-network and out-of-network referrals in order to distinguish differences in reporting activity.

Abstract: A medical information navigation engine (“MINE”) is capable of inferring referral activity not reported into a referral workflow system by utilizing intent-based clustering of medical information. The intent based clustering reconciles received medical data, from a variety of sources, and then clusters the data by applying one or more clustering rules. After the referrals not otherwise reported are inferred, they may be utilized to generate metrics that can be utilized to enhance patient care, and reduce costs. Metrics may be generated for both in-network and out-of-network referrals in order to distinguish differences in reporting activity.

Abstract: A medical information navigation engine (“MINE”) is provided. In some embodiments, the system computes a current patient encounter vector for a current patient encounter, and then an optimal patient encounter vector is computed by assuming a best case patient encounter in accordance with the organizational objectives. The system is then able to compute the difference between the best case encounter and the current patient encounter. This difference is used to compute a corresponding payoff using an intelligent matrix.

Abstract: A medical information navigation engine (“MINE”) is capable of inferring referral activity not reported into a referral workflow system by utilizing intent-based clustering of medical information. The intent based clustering reconciles received medical data, from a variety of sources, and then clusters the data by applying one or more clustering rules. After the referrals not otherwise reported are inferred, they may be utilized to generate metrics that can be utilized to enhance patient care, and reduce costs. Metrics may be generated for both in-network and out-of-network referrals in order to distinguish differences in reporting activity.

Abstract: A medical information navigation engine (MINE) for transacting medical information by receiving medical information from a medical sources, identifying, mapping, and consolidating the received medical information by a back-end medical processor, presenting access to specific relevant data, based on a user's security privileges, within the identified, mapped, and consolidated medical information, based on user-specific functions or roles by a front-end medical processor, and generating user-customized processed medical information to a plurality of users, with at least a portion of the user-customize processed medical information being provided to each of the plurality of users based on its relevancy to each user's specific function or role and each user's associated security privileges.

Abstract: A medical information navigation engine (MINE) for transacting medical information by receiving medical information from a medical sources, identifying, mapping, and consolidating the received medical information by a back-end medical processor, presenting access to specific relevant data, based on a user's security privileges, within the identified, mapped, and consolidated medical information, based on user-specific functions or roles by a front-end medical processor, and generating user-customized processed medical information to a plurality of users, with at least a portion of the user-customize processed medical information being provided to each of the plurality of users based on its relevancy to each user's specific function or role and each user's associated security privileges.

Abstract: A method of transacting medical information includes receiving medical information from a medical sources, identifying, mapping, and consolidating the received medical information by a back-end medical processor, providing access to specific relevant data, based on a user's security privileges, within the identified, mapped, and consolidated medical information, based on user-specific functions or roles by a front-end medical processor, and generating user-customized processed medical information to a plurality of users, with at least a portion of the user-customized processed medical information being provided to each of the plurality of users based on its relevancy to each user's specific function or role and each user's associated security privileges.

Abstract: A health information management system is provided which includes the ability to identify explicit referral activity reported into a referral workflow system, infer referral activity not reported into the referral workflow system utilizing intent-based clustering of medical information, and generate reporting metrics from the inferred and explicit referral activity. Additionally, a referral suggestion may be generated for an identified condition. Physicians are selected within a geographic area who are properly specialized for the condition. This group is then filtered based upon patient preferences and default preferences in order to generate physician referrals.

Abstract: A method is disclosed to receive health information request (HIR), including health information request query (HIRQ) and health information request data (HIRD), and to metatag the received HIR. The metatagged HIR is reconciled based on a semantic concept and HIRS is returned.

Abstract: Systems and methods to generate a final event stream are provided. The system collects information from a wide variety of sources, and then parses, normalizes, and indexes the information. This generates an initial event stream that can be tagged and then iteratively processed to generate a final event stream. The processing includes first order logic querying and knowledge extraction to infer additional events which is added to the event stream. The final event stream is used by a knowledge exchange for consumption by applications. These applications may be internal applications and/or third party applications. This system may be particularly useful in use with medical information, or any other big data enterprise system.

Abstract: A medical information navigation engine (“MINE”) includes a medical information interface, a reconciliation engine and an intent-based presentation engine. The medical information interface receives medical information from a plurality of medical sources, which is subsequently reconciled by the reconciliation engine. The intent-based presentation engine clusters the reconciled medical information by applying at least one clustering rule to the reconciled medication information. The clustered reconciled medical information can be presented to a user.

Abstract: Systems and methods to generate a final event stream are provided. The system collects information from a wide variety of sources, and then parses, normalizes, and indexes the information. This generates an initial event stream that can be tagged and then iteratively processed to generate a final event stream. The processing includes first order logic querying and knowledge extraction to infer additional events which is added to the event stream. The final event stream is used by a knowledge exchange for consumption by applications. These applications may be internal applications and/or third party applications. This system may be particularly useful in use with medical information, or any other big data enterprise system.

Abstract: A medical information navigation engine (“MINE”) includes a medical information interface, a reconciliation engine and an intent-based presentation engine. The medical information interface receives medical information from a plurality of medical sources, which is subsequently reconciled by the reconciliation engine. The intent-based presentation engine clusters the reconciled medical information by applying at least one clustering rule to the reconciled medication information. The clustered reconciled medical information can be presented to a user.

Abstract: Systems and methods to generate a final event stream are provided. The system collects information from a wide variety of sources, and then parses, normalizes, and indexes the information. This generates an initial event stream that can be tagged and then iteratively processed to generate a final event stream. The processing includes first order logic querying and knowledge extraction to infer additional events which is added to the event stream. The final event stream is used by a knowledge exchange for consumption by applications. These applications may be internal applications and/or third party applications. This system may be particularly useful in use with medical information, or any other big data enterprise system.

Abstract: A medical information navigation engine is useful in association with at least one electronic health record system. The engine decouples identifying information from clinical data from electronic health records. The clinical data includes clinical narrative having discrete data and textual data. The identifying information is stored. Additionally, the identifying information is associated with a token in the clinical data. The clinical data may then be indexed. The discrete data and the textual data in the clinical data may then be mined. Mining includes extracting at least one relevant event from the discrete data and the textual data. Next, the clinical data and identifying information may be reintegrated using the token. The event associated with the mined discrete data and textual data may then be exported. The system may also provide a validation tool for users, including clinicians, to search and view clinical data. The exported event may be used to alter treatment of a patient.

Abstract: A health information management system is provided which includes the ability to identify explicit referral activity reported into a referral workflow system, infer referral activity not reported into the referral workflow system utilizing intent-based clustering of medical information, and generate reporting metrics from the inferred and explicit referral activity. Additionally, a referral suggestion may be generated for an identified condition. Physicians are selected within a geographic area who are properly specialized for the condition. This group is then filtered based upon patient preferences and default preferences in order to generate physician referrals.

Abstract: A method is disclosed to receive health information request (HIR), including health information request query (HIRQ) and health information request data (HIRD), and to metatag the received HIR. The metatagged HIR is reconciled based on a semantic concept and HIRS is returned.