Abstract: Methods are provided for sharing patient information by way of an online collaboration system. A requesting clinician, through an online networking system, identifies one or more clinicians with whom the requesting clinician wishes to collaborate by sending at least one patient-focused clinical data element. For the clinicians who have been identified as not being authorized to access patient-identifying data, the at least one patient-focused clinical data element is de-identified such that it no longer includes any patient-identifying data. The de-identified patient-focused clinical data element is then communicated to the clinicians not allowed access to the patient-identifying information.

Abstract: Methods, systems, and computer-readable media are provided to detect similarities between two or more clinical documents. It is determined that a clinician is currently inputting data into a first clinical document that is associated with a patient. A selectable option is provided on a user interface into which the clinician is currently inputting the data. An indication is received that the selectable option has been selected by the clinician. An algorithm is applied to identify the second clinical document from a plurality of clinical documents. At least a portion of the inputted data in the first clinical document and at least a portion of data in the second clinical document are transformed to generate a new representation of the first clinical document that indicates the similarities that are potentially inaccurate or inappropriate between the first clinical document and the second clinical document.

Abstract: Methods, systems, and computer-readable media are provided to detect incremental changes in clinical documents associated with a patient. A user selection is received indicating that a user wants to compare two or more clinical documents that are associated with the patient or authored by the same clinician, enabling the user to become up-to-date on the patient's care. A first clinical document and a second clinical document are identified. For the first clinical document and the second clinical document, differences are algorithmically determined. The first clinical document is transformed into a new representation of the first clinical document. Further, the second clinical document is transformed into a new representation of the second clinical document. One or more of the new representations of the first and the second clinical documents are displayed, assisting the user to quickly find and understand the differences between the documents.

Abstract: Methods, systems, and computer-readable media are provided to detect similarities in clinical documents that might be inaccurate or inappropriate. A first clinical document and a second clinical document that are to be compared are identified. This identification of the documents is based on times associated with the first and second clinical documents, an identity of clinicians who authored the first and second clinical documents, an identity of patients associated with the first and second clinical documents, a type of the first and second clinical documents, or contents of the first and second clinical documents. The first clinical document is compared to a portion of the second clinical document. A report is automatically generated, where the report indicates the similarities between the portion of the first clinical document and the portion of the second clinical document that are potentially inaccurate or inappropriate.

Abstract: Methods, systems, and computer storage media are provided for converting a source in a first terminology to a target in a different terminology. A source in a first terminology may be converted to a target in a second terminology using cross maps that map sources to all possible matching targets, probability data derived from frequency data illustrating a frequency of selection for targets in relation to specific sources, lexical matching algorithms indicating targets with highest lexical matches for specific sources, or a combination thereof. Any one, or a combination, of the data above may be used to identify a probabilistically most relevant target in a desired terminology.

Abstract: Methods, systems, and computer-storage media are provided for searching a plurality of clinical documents associated with a patient. A searchable timeline is presented on a graphical user interface; the searchable timeline has a plurality of icons representing clinical documents created for the patient. The icons overlay the timeline at points in time corresponding to when the icon's respective document was created. Selection of an icon initiates the presentation of the icon's respective document. Preference and filter options enable a user to filter the clinical documents based on, for example, health concepts that have been identified for the patient.

Abstract: Computerized methods and systems for using user-attribute ontologies to calculate anonymity levels are provided. A semi-automated mechanism permits selective and optionally progressive exposure of demographic and clinical information to other members of a medical social network group that a member has joined. When a user decides to join a medical social network group (which may be based upon system suggestion or initiated of the user's own accord), he or she selects or creates a profile that has a statistically validated degree of anonymity, ranging from fully anonymous to fully transparent. Based upon a user's elected level of exposure, only certain data is exposed to the rest of the group's membership. Thus, the user is permitted to personally balance the tension between exposing a level of information that may render him or her personally identifiable and exposing enough information to obtain meaningful advice and/or camaraderie.

Abstract: A system and method for generating interactive visualizations of clinical relationships is provided. The method includes determining what entities have had some clinical contact with an entity of interest and collecting data regarding each entity and each entity's contacts with the entity of interest. The collected data can be filtered to remove unwanted entities and properties. Algorithms are applied to generate clinical relevance scores, which represent the relationship between the entities and the entity of interest. In addition, each entity is assigned components that allow for some executable behavior when an entity is selected in a display. Finally, the appropriate visualization is selected and a display of the relationships is generated.

Abstract: A method, system, and medium are provided for searching an electronic medical record. Search results are returned in response to a search query. The search query may be one or more designated medical concepts. The search results may be displayed according to a ranking that determines which search results are likely to be the most responsive to a query submitted by a particular clinician based on matching the most important clinical concepts in each document to the most important clinical concepts in the search query.

Abstract: A computer-implemented method for facilitating placement of health care order entry is provided. The method includes receiving input indicative of a desired healthcare order. The order has certain terms therein that are normalized. The method also finds possible order matches for the normalized terms, and calculates a rough score for the possible order matches. The method refines the rough score with a rough score adjustment, and then ranks the found possible order matches from the most-likely to match the desired order to the least-likely based upon the refined rough score. These possible order matches can then be displayed to the user for selection.

Abstract: A method, system, and medium are provided for searching an electronic medical record. Search results are returned in response to a search query. The search query may be one or more designated medical concepts. The search results may be displayed according to a ranking that determines which search results are likely to be the most responsive to a query submitted by a particular clinician based on matching the most important clinical concepts in each document to the most important clinical concepts in the search query.

Abstract: Methods are provided for sharing patient information by way of an online collaboration system. A requesting clinician, through an online networking system, identifies one or more clinicians with whom the requesting clinician wishes to collaborate by sending at least one patient-focused clinical data element. For the clinicians who have been identified as not being authorized to access patient-identifying data, the at least one patient-focused clinical data element is de-identified such that it no longer includes any patient-identifying data. The de-identified patient-focused clinical data element is then communicated to the clinicians not allowed access to the patient-identifying information.

Abstract: A system and associated methods for orchestrating a collaboration session are disclosed. One method involves orchestrating a collaboration session between a requesting clinician and another clinician where information is exchanged electronically. According to the method, requests for collaboration sessions are received by a computer system from the requesting clinician, with a given request related to a piece of patient-focused clinical data. Each request is analyzed to build a roster of potentially available clinicians for collaboration. A collaboration session is then facilitated between the requesting clinician and one or more of the potentially available clinicians on the roster.

Abstract: A system and associated methods for orchestrating a collaboration session are disclosed. One method involves orchestrating a collaboration session between a requesting clinician and another clinician where information is exchanged electronically. According to the method, requests for collaboration sessions are received by a computer system from the requesting clinician, with a given request related to a piece of patient-focused clinical data. Each request is analyzed to build a roster of potentially available clinicians for collaboration. A collaboration session is then facilitated between the requesting clinician and one or more of the potentially available clinicians on the roster.

Abstract: Computerized methods and systems for using user-attribute ontologies to calculate anonymity levels are provided. A semi-automated mechanism permits selective and optionally progressive exposure of demographic and clinical information to other members of a medical social network group that a member has joined. When a user decides to join a medical social network group (which may be based upon system suggestion or initiated of the user's own accord), he or she selects or creates a profile that has a statistically validated degree of anonymity, ranging from fully anonymous to fully transparent. Based upon a user's elected level of exposure, only certain data is exposed to the rest of the group's membership. Thus, the user is permitted to personally balance the tension between exposing a level of information that may render him or her personally identifiable and exposing enough information to obtain meaningful advice and/or camaraderie.

Abstract: A computer-implemented method for facilitating placement of health care order entry is provided. The method includes receiving input indicative of a desired healthcare order. The order has certain terms therein that are normalized. The method also finds possible order matches for the normalized terms, and calculates a rough score for the possible order matches. The method refines the rough score with a rough score adjustment, and then ranks the found possible order matches from the most-likely to match the desired order to the least-likely based upon the refined rough score. These possible order matches can then be displayed to the user for selection.

Abstract: A system and associated methods for orchestrating a collaboration session are disclosed. One method involves orchestrating a collaboration session between a requesting clinician and another clinician where information is exchanged electronically. According to the method, requests for collaboration sessions are received by a computer system from the requesting clinician, with a given request related to a piece of patient-focused clinical data. Each request is analyzed to build a roster of potentially available clinicians for collaboration. A collaboration session is then facilitated between the requesting clinician and one or more of the potentially available clinicians on the roster.

Abstract: A computer-implemented method for facilitating placement of health care order entry is provided. The method includes receiving input indicative of a desired healthcare order. The order has certain terms therein that are normalized. The method also finds possible order matches for the normalized terms, and calculates a rough score for the possible order matches. The method refines the rough score with a rough score adjustment, and then ranks the found possible order matches from the most-likely to match the desired order to the least-likely based upon the refined rough score. These possible order matches can then be displayed to the user for selection.

Abstract: A method, system, and medium are provided for searching an electronic medical record. Search results are returned in response to a search query. The search query may be one or more designated medical concepts. The search results may be displayed according to a ranking that determines which search results are likely to be the most responsive to a query submitted by a particular clinician based on matching the most important clinical concepts in each document to the most important clinical concepts in the search query.

Abstract: A system and associated methods are disclosed for managing clinical notification delivery and related compliance monitoring. In certain embodiments, the clinical notifications are automatically driven by healthcare information associated with a specific patient, and are delivered to an electronic device of the patient at a remote location. Thereafter, compliance monitoring may be initiated to log the patient's intent to act in accordance with the notification. For instance, in certain embodiments, the notification relates to a reminder regarding scheduled medication administration for the particular patient, where a reply to the notification indicates whether the patient is following the scheduled medication administration.