Customers trust KenSci to help them make more of their data

In the report, “Healthcare AI 2019: ACTUALIZING THE POTENTIAL OF ARTIFICIAL INTELLIGENCE.” by KLAS Research, KenSci was given a score of 92.8* score out of 100 based on interviews with seven customers. The findings among interviewing customers, corroborate KenSci as an engaged partner providing customers with Data Science expertise. All of the customers interviewed stated that KenSci played a part in their long-term plans and that they would buy again.

Built by doctors, data scientists and developers… For healthcare

KenSci’s AI Platform for Digital Health is engineered to ingest, transform, and integrate disparate sources of healthcare data to assist plans in managing the care of their members.  Payers and ACOs leverage KenSci’s platform and Solutions to identify members at high risk of preventable ED and acute inpatient events,  claims that might indicate waste & abuse, and levers to optimize care management activities. KenSci’s Solutions use advanced analytics to recognize patterns in large volumes of data, helping care managers view the granular details of members' histories and predict future risk to aid in timing and prioritizing engagement.

See how SCAN Health is doing more with KenSci

Solutions for Health Plans

KenSci’s pre-built ML models enable health plans to build and deploy applications at ease, accelerating their AI journey towards ROI. With KenSci, healthcare payors are able to gain granular insights into the health of their population and adjust for risk accordingly.

  • Avoidable Hospitalization Prediction

    Identify members with acute or chronic condition burden that could exacerbate and lead to acute hospitalization. KenSci’s Avoidable Hospitalization Solution aims to anticipate the needs of members with ambulatory care sensitive conditions (ACSCs) - both acute, such as UTIs, or chronic, such as diabetes. Members with ACSCs are more likely to have hospitalizations that the Agency for Healthcare Research and Quality (AHRQ) deems potentially avoidable since primary care may be able to mitigate hospitalization.

  • Benefits Optimization

    Enhance care coordination and promote treatment and care practices for at-risk members. Using KenSci’s Benefits Optimization, your organization can ensure your members use benefits that improve health and promote higher-value healthcare services. Helping members in high-risk cohorts navigate and optimize their benefits will be necessary to realize the potential of your plan designs.

  • HCC Optimization

    Improve HCC coding accuracy and ensure risk-adjusted cost coverage across your membership using KenSci’s ML-enhanced solution for suspect diagnoses. KenSci’s model will highlight the data footprint that supports a member’s suspected diagnoses, calling a user’s attention to relevant events in the chart.

  • Chronic Condition Stratification

    With many members avoiding traditional settings of care, or foregoing preventative care, anticipate chronic condition progression. The risk factors in each member cohort with a chronic condition are many: a combination of access concerns, utilization history, comorbidity burden, polypharmacy, and cost variables. KenSci’s Chronic Condition Stratification Solution learns from your membership to model Per Member Per Month expenditures and utilization habits. It separates your members into “like” cohorts and stratifies members within each group across a variety of predictions, supplying insights on risk factors for your care managers to build the appropriate intervention plan.

  • Opioid Prescribing Analysis

    Seek undesirable prescribing behaviors with statistical significanceKenSci’s experience in pharmacy claims and ability to normalize behaviors among peer cohorts come together in its Opioid Prescribing Analysis Solution. With this tool, a Pharmacy Team will can identify unexpected and undesirable prescribing behaviors.

Avoidable Hospitalization Prediction

Identify members with acute or chronic condition burden that could exacerbate and lead to acute hospitalization. KenSci’s Avoidable Hospitalization Solution aims to anticipate the needs of members with ambulatory care sensitive conditions (ACSCs) - both acute, such as UTIs, or chronic, such as diabetes. Members with ACSCs are more likely to have hospitalizations that the Agency for Healthcare Research and Quality (AHRQ) deems potentially avoidable since primary care may be able to mitigate hospitalization.

Better in-patient care

AHRQ reports that this totaled up to 3.5 million potentially preventable inpatient stays in 2017.  As recently as November 2020, researchers find that avoidable hospitalizations still represent a significant source of disparities among ethnic and dual eligible members.  KenSci’s Solution helps care managers identify members who may need self-management assistance or specialty care. This solution is utilized by health plan care managers and shared risk medical groups and provides risk risk factors to help with  prioritization of multidisciplinary care coordination.

Here's how

Benefits Optimization

Enhance care coordination and promote treatment and care practices for at-risk members. Using KenSci’s Benefits Optimization, your organization can ensure your members use benefits that improve health and promote higher-value healthcare services. Helping members in high-risk cohorts navigate and optimize their benefits will be necessary to realize the potential of your plan designs.

Do more with Benefits Optimization

Examples of Benefits Optimization include: - Identifying dual-eligible members who may meet the necessary criteria to receive services rendered at home (Nursing Facility Level of Care)

Determining which members may be best-suited for ambulatory surgery due to low risk of post-acute complications or extended length of stay

KenSci can help

HCC Optimization

Improve HCC coding accuracy and ensure risk-adjusted cost coverage across your membership using KenSci’s ML-enhanced solution for suspect diagnoses. KenSci’s model will highlight the data footprint that supports a member’s suspected diagnoses, calling a user’s attention to relevant events in the chart.

Stay ahead with KenSci 

A machine learning solution ensures there are no rules to author or maintain. As clinical practice evolves, the system will pick up the new sources of signal. Validate the system’s selections and it will continue to recommend suspect diagnoses for your eligible members. By ensuring your members have well-documented conditions, you will also identify them for rules-based quality measures and workflows, affording them more appropriate engagement and preventative care.

Integrate with your risk-bearing medical groups

Rather than send out your charts for review by a third party, reroute your suspect diagnoses back into clinical workflows. KenSci’s AI Platform for Digital Health can push data back into EMR systems for use in cohort design or alerts at the point of care.

Talk to us to know more

Chronic Condition Stratification

With many members avoiding traditional settings of care, or foregoing preventative care, anticipate chronic condition progression. The risk factors in each member cohort with a chronic condition are many: a combination of access concerns, utilization history, comorbidity burden, polypharmacy, and cost variables. KenSci’s Chronic Condition Stratification Solution learns from your membership to model Per Member Per Month expenditures and utilization habits. It separates your members into “like” cohorts and stratifies members within each group across a variety of predictions, supplying insights on risk factors for your care managers to build the appropriate intervention plan.

Do more with KenSci’s solution for Chronic Conditions

Examples include

Likelihood of diabetes progression from pre-diabetes, or from uncomplicated to complicated diabetes

Risk of increasing burden due to chronic kidney disease (CKD)

Learn more

Opioid Prescribing Analysis

Seek undesirable prescribing behaviors with statistical significanceKenSci’s experience in pharmacy claims and ability to normalize behaviors among peer cohorts come together in its Opioid Prescribing Analysis Solution. With this tool, a Pharmacy Team will can identify unexpected and undesirable prescribing behaviors.

KenSci’s solution for Opioid Prescribing analysis

The tool begins by normalizing habits among prescribers treating similar member cohorts, and highlights those who are behaving in unexpected ways. Analyses range from MME “jumps” - large steps in average MME between visits - to identifying those prescribers who are inconsistently seeing and following up with the members to whom they are prescribing opioids. “The application of ML techniques is not punitive but an opportunity to improve safety and patient care.” – says Diana Bottari, Lead Physician Opioid Mitigation Strategies- Advocate Aurora Healthcare

See how Advocate Aurora Health used KenSci’s Opioid Prescribing Analysis to counsel prescribers on their behaviors and impact change.

Talk to us to know more

Forge Your Path

KenSci’s AI Platform for Digital Health enables health plans to build and deploy applications with ease, accelerating their AI journey towards ROI.  It features key investments such as:

• Native functionality to collapse related claims into a single visit event

• A rich set of features pre-built with your needs in mind, emphasizing utilization history, enrollment history, Medicare-standard flat files, chronic condition status and disease progression, and medication usage.

• Our framework is extensible to support new data sources and feature types.  Bring along your HL7 feeds, lab results, surveys and health risk assessments, and remote patient monitoring data - you can build models to support them.

More features. More models.

Feature and Model Training utilities to reflect claims run-out, new enrollee status, and “cold start” - a core set of features available from your administrative claims.

Lookups for industry-standard semantic source systems, such as NDC, ICD10, CPT/HCPCS, and more.

A native data connector for PowerBI or API endpoints for on-demand model scoring

EMR Integration where necessary for your risk-sharing medical groups or delegated partners, with SMART on FHIR support

Leaders at the core of transformation

Hear from them
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Combating COPD at a National Level

KenSci is enabling NHS Greater Glasgow and Clyde to identify patients are the risk of COPD even before they are admitted

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Leveraging data to fight COVID-19 with SLUHN

Experts from St. Luke’s University Health Network, Microsoft and KenSci, share how to be more effective while managing hospital operations during COVID-19

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WW Business with Kathy Ireland

KenSci and INTEGRIS Health were featured on the Worldwide business with Kathy Ireland, to talk about using AI for better care

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Transforming Data to AI

KenSci's platform allows healthcare organizations to tap into the vast amounts of data and transform them into AI led insights

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AI Best Practices with IU Health

Hear from three industry experts who are on top of the AI game on what it takes to deploy right, deploy fast and get your AI orchestration to demonstrate a big win.

Integris

Rush University prepares to combat COVID-19

When the call to prepare for COVID-19 arrived, Rush University turned to KenSci to stand up the Realtime Command Center.

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Use your existing data and get started with your first AI solution… quickly

Our experts can guide you through every leg of the AI journey, and help deliver tangible ROI. Talk to us today

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Access Our Latest Thinking

Research, blogs, and other whitepapers on AI Led healthcare transformation

Case Study

See how Advocate Aurora Health is working on fighting the opioid battle

May 13, 2020

Blog

How to accelerate the movement of data onto Azure in FHIR format

March 17, 2020

Webinar

SLUHN is fighting COVID-19 by staying ahead with a real-time command center

September 4, 2020

PodCast

HIT Like a girl~ Health from Corinne Stroum on Healthcare Informatics

August 12, 2020

Press Release

SCAN Health and KenSci are leveraging AI to help the senior members

August 11, 2020