Eden Prairie, MN, United States
Eden Prairie, MN, United States

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Patent
Optum Inc | Date: 2014-05-07

An HTTP web-native bridge includes an HTTP server that exposes native mobile modules through a RESTful web service. A full HTTP feature set may be utilized to interact with the native mobile modules to access native features and functionalities of a mobile device by a web service. The HTTP web-native bridge may be implemented without including additional libraries in the web service code or requiring web service developers to write application programming interface code.


A system and method for identifying relationships and correlations between community healthcare attributes includes automatically displays relationships between selected community health measures. A correlation tool automatically computes correlations between a selected main measure and each other measures in a set of community health measures for selected communities. The correlation tool automatically displays a ranked list of the other community health measures based on their correlation to the selected main measure. A relationship tool automatically computes correlations between selected measures in the set of community health measures for selected communities. The relationship tool displays a correlation graph indicating values of the selected measures for each of a selected set of communities. An adjusted correlation graph is automatically displayed to indicate adjusted values of the selected measures to accommodate a selected third measure as a control variable.


Patent
Optum Inc | Date: 2015-03-23

A health information system includes a health information data storage machine and a healthcare analytics processor configured to extract healthcare related commentary of healthcare consumers from a social media data storage machine and match portions of the healthcare related commentary to health information of the social media commentators in a combined health information data source. The healthcare analytics processor identifies relationships between consumer sentiment expressed in the social media information and consumer experiences, product usage, diagnoses and outcomes recorded in the health information. Benchmarks and measures of healthcare outcomes and treatments are generated based on matching consumer commentary and consumer sentiments with corresponding indications of actual healthcare experiences of the commentator recorded in the health information.


Systems, methods, and apparatuses for maintaining and processing proprietary or sensitive data using an application implemented in a split/hybrid-cloud system are described. The split/hybrid system utilizes cloud and local platforms, while complying with customer security concerns and HIPAA security standards. Configuration of the application occurs in a cloud platform whereas processing of proprietary or sensitive data occurs within a customers local computing environment. The customer may create their own unique application configuration that is stored in the cloud platform and that is delivered back to the customer as a package that includes both the unique application configuration as well as general application configuration requirements. The customer may implement the package within one or more local computing environments while managing the application from a single site that is separated from proprietary or sensitive data.


A system and method that provides for integrated data entry and workflow capabilities through one or more computing devices provided to personnel who work at various stations throughout a facility. Automated identification, record updates, workflow management, and alerts are facilitated through the computing devices, which include a headset that includes one or more input devices such as a microphone, a speaker, a camera, and/or a visual display device.


Patent
Optum Inc | Date: 2015-05-29

Computer program products, methods, systems, apparatus, and computing entities for extracting lab result data from lab reports are provided. In one example embodiment, an example computing device receives a lab report. The computing device identifies one or more relevant portions of the lab report. The computing device then generates parsed lab report data from only the identified one or more relevant portions of the lab report. Subsequently, the computing device extracts patient information and lab results from the parsed lab report data. Using various embodiments of the present invention, patient information and lab results can be efficiently extracted for incorporation into structured data sets maintained, for example, by a healthcare company.


The present application discloses systems and methods for systematically identifying situations, improving processes, and producing proactive, actionable results to address customer inquiries. The systems and methods produce actionable proactive results (i.e., actions to be taken by predicting a likelihood of a customer interacting with an organization, such as an insurance provider). This allows an organization to avoid unnecessary and/or repeat customer contacts and inquiries, which generate protracted work and the need for case management and escalations. In addition, the systems and methods improve first contact resolution metrics and customer experience, by predicting the need for an interaction without having to communicate with the customer.


Patent
Optum Inc | Date: 2014-09-03

In general, embodiments of the present invention provide systems, methods and computer readable media for a healthcare similarity engine that uses healthcare data to identify a set of similar patients. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving a similarity request including a patient X data vector representing attributes of a particular patient X and a set of similarity parameters; calculating a set of similarity metrics using the patient X data vector and the set of similarity parameters; ranking the population of patients based on their respective similarity metrics; and generating a neighborhood subset of the population of patients most similar to patient X by selecting the top-ranked patients. Another aspect of the subject matter can be embodied in methods that include the actions of providing a display of a graphical representation of a healthcare similarity request input dashboard.


Patent
Optum Inc | Date: 2014-09-03

In general, embodiments of the present invention provide systems, methods and computer readable media for a healthcare similarity engine that uses healthcare data to identify a set of similar patients. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving a similarity request including a patient X data vector representing attributes of a particular patient X and a set of similarity parameters; calculating a set of similarity metrics using the patient X data vector and the set of similarity parameters; ranking the population of patients based on their respective similarity metrics; and generating a neighborhood subset of the population of patients most similar to patient X by selecting the top-ranked patients. Another aspect of the subject matter can be embodied in methods that include the actions of providing a display of a graphical representation of a healthcare similarity request input dashboard.


Embodiments of the present invention provide concepts for correcting optical character recognition (OCR) errors from and OCR scan result by sequentially applying an anagram hash (AH) and Levenshtein-Distance (LD) measurement for concurrent character identity-based (machine code) and character shape-based (OCR-Key) corrections. The OCR-Key classifies characters by shape into one or more disjoint and overlapping classes. Similar shaped-based classes appearing in consecutive characters are appended to a cardinality term, a repetition count of the class. The LD measurement groups OCR-Keys and differentiates on both class and cardinality to arrive at a shape-based mismatch error between competing candidate words from an associated dictionary and a target word from the OCR scan. The shape-based LD measurement errors are then functionally merged with the character identity-based deletion, substitution, and insertion errors to find a minimum error for the set of candidate words, corresponding to the preferred candidate word match to the target word.

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