International Business Machines Corporation

Merative US L.p.

Charalambos Stavropoulos

Uri Kartoun

Kenney Ng

Paul C Tang

Francis Campion

Tanya Rudakevych

Zhen Liu

Yoonyoung Park

Cathy Honghui Xia

Sophie Batchelder

Amy Chiu

Wuqin Lin

Veronica Aldous

Amarendra Das

Michael J LaScaleia

David Osofsky

A plurality of attributes are extracted from a plurality of electronic health records, where each electronic health record is associated with a patient in a plurality of patients. Additionally, a training data set and a scoring data set are generated based on the plurality of attributes, and a patient similarity model is trained based on the training data set. A precision cohort is identified, where the precision cohort includes patients in the plurality of patients from the scoring data set that are similar to a first patient based on an electronic health record of the first patient and the similarity model. At least one result statistic for each of a plurality of treatments given to patients in the precision cohort is determined, and a first treatment of the plurality of treatments is selected for the first patient based at least in part on the determined result statistics.

Generating personalized treatment options using precision cohorts and data driven models

A notation assistant system has a machine learning system, a notation processing system, a scoring system, and a suggestion system. The machine learning system trains a classifier for rating a factor related to a clinical narrative note that describes a patient's health status. The notation processing system processes a clinical narrative note and the scoring system determines a factor rating, such as a completion score or a clarity score. The scoring system provides the factor rating to an end-user device to display to a user. The notation assistant system is configured to perform a method as a user is entering a clinical narrative note to provide real-time feedback, such as the factor rating. The suggestion system is configured to provide suggestions for modifying the clinical narrative note to improve the rating factor. The notation assistant system applies to patient health conditions such as a health status of a patient's heart for a patient receiving care for congestive heart failure.

Notation assistant system for providing feedback on a clinical narrative note

A system and method for assigning assessment tasks includes determining tasks in need of completion, where the tasks include assessing a set of documents containing medical patient data and providing a judgment (e.g., classification or label) based on the contents of the document. A process also includes selecting one or more reviewers based on the one or more tasks and providing one or more documents from the set of documents to each of the selected one or more reviewers for completion of the one or more tasks. The process further includes receiving a result of the one or more tasks after completion by the selected one or more reviewers and storing the result in an electronic medical record database.

System for assignment of assessment tasks based on task criteria and reviewer credentials

A system and associated method for assessing level of completeness of healthcare data storage based on collected data. The system includes a collection system, a measurement system, an expectation system, and an alerting system. In a method of assessing the health of stored data, the system collects real-time data from at least one data source, determines measurements for a plurality of parameters based on the collected data, and generates expectations for a future period of time for the plurality of parameters based on data analysis technique. The system also compares the expectations for the future period of time to subsequent measurements collected for that period of time to determine whether the subsequent measurements satisfy an expectation threshold and provide an alert to a client terminal. The alert is a result of the comparison of the expectations and the subsequent measurements and provides an assessment of data storage quality and alerts on anticipated deficiencies.

Systems and methods for determining data storage health and alerting to breakdowns in data collection

The invention is a method and apparatus for on-demand resource planning for unified messaging services. In one embodiment, multiple clients are served by a single system, and existing system resources are allocated among all clients in a manner that optimizes system output and service provider profit without the need to increase system resources. In one embodiment, resource allocation and job scheduling are guided by individual service level agreements between the service provider and the clients that dictate minimum service levels that must be achieved by the system. Jobs are processed in a manner that at least meets the specified service levels, and the benefit or profit derived by the service provider is maximized by prioritizing incoming job requests within the parameters of the specified service levels while meeting the specified service levels. Thus, operation and hardware costs remain substantially unchanged, while system output and profit are maximized.

Method and apparatus for on-demand resource allocation and job management

Growing community of inventors

Hastings-on-Hudson, NY, United States of America

Charalambos Stavropoulos