KenSci

KenSci's Current COVID-19 Response and Solutions

The following information was supplied by the vendor and has not been validated by KLAS.

Mobile command center for COVID-19 response
Capacity management, census tracking, and system-wide supply planning

KenSci’s mobile command center for COVID-19 is currently being deployed at three sites on the East Coast. coming in from HL7 feeds, labs, EMRs, and workforce management tools. The solution has two key capabilities:nurses and hospitalists access bed availability and system-wide supplies on the go in real time. The solution leverages real time dataThis solution helps charge

kensci mobile command center covid19
  • Real-time hospital census for bed management: Hospital capacity planning and census tracking, updated in real time, based on test results and bed availability.
  • System-wide supply planning: Comprehensive views refreshed in real time for beds and personnel availability across wards, discharge plans, huddle tools, and roll up at a system level, spanning multiple hospitals.

Various population health management resources
Drill down view of case data, community risk-stratification tools, FHIR-based data ingestion, and other resources to fight COVID-19

Population Health for COVID-19

The solution includes two key capabilities requested by customers:

  • A localized, drill-down view by zip code of case data: KenSci has built a daily-updated visualization based on data shared by Johns Hopkins, made available for free to all customers.
  • A community risk-stratification tool that helps hospitals leverage a population and cohort analyzer to identify members in the community that are at greatest risk for community-acquired COVID-19, based on prior history, comorbidity, and SDOH. By leveraging prebuilt flags and segments in an easy-to-use analytical experience, health system administrators and outreach coordinators can quickly identify cohorts that might be at greatest risk of complications from COVID-19.

FHIR-Based Data Ingestion for Multiparty Coordination

As the pressure mounts for health systems to be better prepared for fixed resources, such as using negative pressure rooms, ICU beds, and ventilators, real-time data access becomes critical in routing patients (and healthcare providers) safely through the system. To take advantage of open data standards being adopted across the industry, KenSci, in partnership with Microsoft, is announcing a new offering to convert NRT messages like HL7 (ADT, ORU, ORM, etc.) into a single common data model using FHIR specifications. Through this initiative, customers can take advantage of the Azure Marketplace with an add-on to include a mobile command center—a native app that provides real-time census, bed availability, and other important metrics.

Discharge Planning and LOS Updates for COVID-19

Along with the updates to our patient flow offering, KenSci is also releasing a set of updates to our patient huddle tool that is used across health systems to help with discharge planning. The tool reads EMR data in batch form and presents case managers and hospitalists with a view into case predictions, including expected discharge date, observation overstay indicator, risk of readmission, and predicted discharge disposition. To quickly identify COVID-19 case impact, the tool has added three new indicators to flag suspect cases, cases awaiting results, and confirmed cases. Through a set of simple configurations, existing customers can take advantage of this offering with their already licensed huddle tool.

Currently Being Codeveloped and Expected General Availability in a Few Weeks

  • ED Overload Predictions in Context of COVID-19: KenSci is partnering with leading health systems in Washington, Oregon, and California to deploy a real-time ED load prediction, including ED census predictions, ED wait times, staffing requirements, and ambulance-arrival predictions. By training models based on data from the CDC and hospitals, we are helping our customers plan and anticipate for COVID-19-related case surge at the ED.
  • At-Risk Patient Engagement and Remote Monitoring: KenSci is customizing a recommendation system, built earlier for diabetes, to engage and nudge the general and high-risk populations based on SDOH, prior medical history, and demographic data and to increase awareness for healthy behavior. With the ability to download or push these cohorts to patient engagement tools, we can quickly generate targeted outreach campaigns to educate our community about available resources during this time of high anxiety. Customers are embedding nudges and behavior modification in current engagement apps and integrating data from wearables to leverage machine learning and drive behavior that can flatten the curve.

Software Overall Score Data collected since May 2019

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