Cerner Innovation, Inc.

Other

Bharat Sutariya

Hugh H Ryan

Mark A Hoffman

Leo V Perez

John Kuckelman

Cole Anthony Erdmann

Kevin John Krizek

Patrick James O'Brien

Benjamin David Wilkerson

Douglas S McNair

Kanakasabha K Kailasam

John Christopher Murrish

Ryan Alan Brush

Megan Kathleen Quick

Amber Buchan

Teresa Smith

Phillip M Stadler

Andrea K Harrington

Jaclynne L Aagesen

Sara J Boswell

Joseph Marcus Overhage

Jeremy A Flores

Robert Charles Amland

Jason Howard

Allison D Foster

Methods, computer systems, and computer-storage medium are provided for providing closed-loop intelligence. A selection of data is received, at a cloud service, from a database comprising data from a plurality of sources in a Fast Healthcare Interoperability Resources (FHIR) format to build a data model. After a feature vector corresponding to the data model is extracted, a selection of an algorithm for a machine learning model to apply to the data model is received. A portion of the selection of data is utilized for training data and test data and the machine learning model is applied to the training data. Once the model is trained, the trained machine learning model can be saved at the cloud service, where it may be accessed by others.

Closed-loop intelligence

Methods are provided for the surveillance and monitoring of a patient's medical care when the patient is treated at two or more medical organizations having different medical record systems. Patient information is received from a first medical organization and populated into an active risk assessment array that monitors the patient's risk for developing a particular disease or condition. Patient information is then received from a second medical organization and populated into the array. It is determined that actionable criteria have been met, and in response, a notification or alert is sent to the medical organizations indicating that the patient is at risk.

Multi-site clinical decision support

Methods, systems, and computer-readable media are provided for building a score plan for a healthcare organization, its providers, its payers, and/or its patients and presenting the results of the score plan on one or more score card user interfaces. Score cards graphically display an entity's progress towards meeting quality measure objectives. The score cards provide information on percentage completion of one or more quality measure objectives by the entity and/or quality measure objectives that may be difficult for the entity to achieve.

Score cards

Systems, methods, and storage media useful in a computer healthcare system to consume clinical quality language queries in a programmatic manner are disclosed. Exemplary implementations may: load a CQL query from a third party; transform the CQL query to a modified structured query language query; load medical data elements from a database record store for each patient in one or more defined patient populations; execute the modified SQL query on medical data elements from the database record store for each patient in one or more defined patient populations; and load results of the modified SQL query.

Systems, methods, and storage media useful in a computer healthcare system to consume clinical quality language queries in a programmatic manner

Methods, systems, and computer-readable media are provided for identifying, stratifying, and prioritizing patients who are eligible for care management services. For each patient, patient health data is used to determine one or more of a disease burden associated with the patient, an amount of health system utilization by the patient, and an amount of money spent on healthcare services for the patient. It is further determined if the patient exceeds a respective threshold value associated with each of these criteria. If the patient exceeds the respective threshold value, the patient is stratified into a category comprising one of high-risk senior, high-risk adult, high-risk pediatrics, or high-risk maternity. The patient may also be prioritized based on one or more factors, and a notification may be sent to the patient informing the patient of his/her eligibility for care management services.

Identification, stratification, and prioritization of patients who qualify for care management services

Methods are provided for validating theoretical improvements in the decision-support processes facilitating surveillance and monitoring of a patient's risk for developing a particular disease or condition and detecting the disease or condition. Patient information is received from a source and populated into an active risk assessment that monitors the patient's risk for developing Sepsis. At least a first and second set of actionable criteria for determining a patient's risk for developing sepsis are received. For each set of actionable criteria, it is determined that actionable criteria have been met. In some embodiments, software agents, operating in a multi-agent computing platform, perform each determination of whether actionable criteria are met. In some embodiments, in response to actionable criteria being met, a notification or alert is provided, and in some embodiments the results of the determinations of each set of actionable criteria are provided to facilitate validation of theoretical improvements.

Clinical decision support for sepsis

Methods, systems, and computer-readable media are provided for aligning a patient who is determined to be eligible for care management services with a care manager. Patient health data is received and is used to generate a patient profile for the patient. The patient profile comprises, for example, demographic information, geographic location, clinical characteristics, patient preferences, a patient need level, a category to which the patient is assigned, and a priority level associated with the patient. A set of characteristics associated with a group of care managers is accessed where the set of characteristics include clinical expertise of the care manager, geographic location of the care manager, workload capacity of the care manager, and the like. Using the patient profile and the set of characteristics associated with the group of care managers, the patient is aligned with a care manager well-suited to help the patient achieve care management goals.

Care management assignment and alignment

Methods, systems, and computer-readable media are provided for automatically generating outreach events for a care management service. Patient health data is received and processed to determine that a patient is eligible for care management services. Upon determining that the patient is eligible for care management services, a welcome-to-service template is selected, populated with patient-specific information, and communicated to the patient. The patient's health data is monitored to determine if there has been a change in care management status for the patient. Upon detecting a change in status, an appropriate template is selected, populated with patient-specific information, and communicated to the patient and/or a care team caring for the patient.

Care management outreach

Methods, systems, and computer storage media are provided for generating simulation graphs using real-time clinical data. A user may indicate one or more scenario variables to apply to an area of interest. A simulation graph is then generated that includes at least an indication of a scenario status. The scenario status indicates an expected result based on the one or more scenario variables selected by the user. The simulation graph may also include a baseline status indicating an expected result should no changes be made to a current environment. Multiple simulation graphs for varying areas of interest may be generated and compared to one another such that a user is able to quickly identify efficient solutions.

Real-time predictive simulation modeling

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Parkville, MO, United States of America

Bharat Sutariya