International Business Machines Corporation

Francis Campion

Uri Kartoun

Kenney Ng

Charalambos Stavropoulos

Tanya Rudakevych

Paul C Tang

Sophie Batchelder

Veronica Aldous

Fang Lu

Yoonyoung Park

Amy Chiu

Michael J LaScaleia

David Osofsky

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 alerting to ambiguous medical advice through a data analysis system connected to one or more data sources and a client terminal. The data analysis system has an extraction system, a machine learning system, a categorization system, and an alerting system. The data analysis system extracts first information related to outcomes of one or more medical treatments from one or more first data sources, extracts second information related to outcomes of one or more medical treatments from one or more second data sources, and applies machine learning to the extracted first information and second information to develop a classifier for categorizing proposed treatments. The data analysis system also categorizes a proposed treatment or a combination of treatments as potentially harmful based on the classifier, and provides an alert to a client terminal regarding the proposed treatment.

Systems and methods for alerting on ambiguous advice of medical decision support systems

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

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Westwood, MA, United States of America

Francis Campion