Abstract: A system for selecting a health care provider and then monitoring and reporting the selected provider's performance. A processor is programmed to retrieve from the internet and store in a database historical performance data on providers and healthcare data relating to the providers' historical performance. The processor determines which provider should be selected to perform a task, by assessing the providers' historical performances against each other; selecting a provider to perform a task, monitoring post-selection healthcare data relating to the provider's performance of the task, and generating a reporting metric comprising a display of a trend in the selected provider's historical performance and/or the provider's current performance of the task.

Abstract: A system for selecting a health care provider and then monitoring and reporting the selected provider's performance. A processor is programmed to retrieve from the internet and store in a database historical performance data on providers and healthcare data relating to the providers' historical performance. The processor determines which provider should be selected to perform a task, by assessing the providers' historical performances against each other; selecting a provider to perform a task, monitoring post-selection healthcare data relating to the provider's performance of the task, and generating a reporting metric comprising a display of a trend in the selected provider's historical performance and/or the provider's current performance of the task.

Abstract: A method and system being used to provide patient/provider information for use by a medical visual referral tool, the method being carried out by one or more servers, wherein the one or more servers comprises at least one database stored on a computer-readable memory, wherein each of the servers comprises a plurality of electronic computing machines, wherein the electronic computing machines each comprise a processor and a computer-readable memory, and wherein the method comprises: obtaining data from data sources, standardizing the data, storing the data in one or more of the databases, receiving a client request from a client computing machine, processing the client request, and sending a response to the client computing machine, wherein the response provides the patient/provider information usable for the medical visual referral tool, and wherein at least some of the patient/provider information is to be displayed on an electronic geographical map at the client machine.

Abstract: A system for selecting a health care provider and then monitoring and reporting the selected provider's performance. A processor is programmed to retrieve from the internet and store in a database historical performance data on providers and healthcare data relating to the providers' historical performance. The processor determines which provider should be selected to perform a task, by assessing the providers' historical performances against each other; selecting a provider to perform a task, monitoring post-selection healthcare data relating to the provider's performance of the task, and generating a reporting metric comprising a display of a trend in the selected provider's historical performance and/or the provider's current performance of the task.

Abstract: A method maximizes the usefulness of resources to be allocated to a class of patients. The method includes the steps of receiving data on a patient. The date is then partitioned. From the partitioned data, a patient factor score calculation is calculated. In addition, a patient illness correlation score is calculated. From the patient factor score and patient illness correlation score, an Ability to Impact score for each patient is generated to identify uses of resources by which the resources will be applied to the patient to maximize the effectiveness of the resources.

Abstract: A method and system for improving care and reducing adverse events and cost by identifying patent care opportunities and integrating them directly into electronic hospital records and the provider's routine workflow. The invention enables clinicians, care managers and users to improve care and efficiency by assembling data from disparate sources, identifying care opportunities and integrating them directly into the EHR system and their routine workflow, while tracking that the recommended action was taken.

Abstract: Data is combined from multiple independent data stores, and is then queried using a data correlation engine. Contemplated engines preferably keep track of previously run correlations, and then makes those correlations available to clinicians for their own use. For example, a preferred system might provide a listing of correlations run by other clinicians in a particular medical specialty, or a particular community, whether geographic or otherwise. In another example, a preferred system might provide a listing of correlations sorted by popularity, so that the most frequently accessed correlations appear near the top of the list. In any case a clinician could simply view the list, and check off which correlations he/she would like to have run for his/her practice, or practice community.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.

Abstract: A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

Abstract: Data is combined from multiple independent data stores, and is then queried using a data correlation engine. Contemplated engines preferably keep track of previously run correlations, and then makes those correlations available to clinicians for their own use. For example, a preferred system might provide a listing of correlations run by other clinicians in a particular medical specialty, or a particular community, whether geographic or otherwise. In another example, a preferred system might provide a listing of correlations sorted by popularity, so that the most frequently accessed correlations appear near the top of the list. In any case a clinician could simply view the list, and check off which correlations he/she would like to have run for his/her practice, or practice community.

Abstract: A hub-spoke patient information service in which a patient's data can be obtained from a network of independent data sources through a centralized service. The hub of the service stores patient identification information and the spokes store the patient's clinical data. In a preferred embodiment, the spokes are independent sources (e.g. each spoke is generally unrelated to other spokes) and include hospitals, doctor offices, clinics, insurance companies, or other entities that store or track clinical data. Preferably, the data sources use a first authentication to properly identify or authentic the service. Once access is granted, the spoke sources are queried for the patient's data. In response, each data source provides the type of patient data available from the source. The user is shown the types of data available without generally showing the actual data. The user can then select the specific patient data to retrieve from the spoke sources.