Meet the Heroes of Health


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Cleveland Clinic

Cleveland Clinic DR. MICHAEL KATTAN: FROM PATIENT TO PROBLEM-SOLVER

In the early 1990s Dr. Michael Kattan was diagnosed with stage 4 Hodgkin's Lymphoma. He was offered the same prognosis as an 80 year old. Medical prognosis rather than medicine was overly simplistic. This moment changed Dr Kattan’s career and set him off on a mission to make health personalized.

Dr Michael Kattan has co-authored more than 500 articles in peer reviewed journals and is an expert on predictive risk models. Cleveland’s Clinic is now making this knowledge available through the Apervita marketplace, helping clinicians quickly sift through complex EMR data and predict patient risks.

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Med Calc
Med Calc

Med CalcDR. LOUIS LEFF: A PIONEER IN EVIDENCE BASED MEDICINE

Dr. Leff created MedCalc3000, a data analytics tool to help in the assessment of complex collections of risk factors and provide recommendations to his patients on diseases such as diabetes, stroke and heart disease.

All too often, risk scores are not implemented enough in medical practice. Sure, a primary care physician tracks body mass index and pulmonologists will record FEV, but there are thousands of risk scores; both simple and more complex calculators can be leveraged to gain powerful insight into the patient’s health.

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Quotation
Quotation

American CollegeDINO DAMALAS: START A CONVERSATION ABOUT HEALTH RISK TODAY

As CIO at the ACC, Dino Damalas is responsible for bringing a whole new level of sophistication to ACC applications. The goal of the ACC is to make the ASCVD risk estimator available to every physician dealing with cardiovascular risk. By offering the risk estimator through Apervita, ACC will now make it available from within electronic health records (EHRs) and other systems that physicians use everyday.

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Directory
Directory
Quant HC
Quant HC

DR. DANA EDELSON: PREDICT PATIENT RISKS IN REAL TIME

Dr. Edelson at Quant HC is using Apervita to deploy their risk stratification algorithms in real time. They leverage the power of Apervita to avoid the need to deploy it on different platforms at every institution, enabling health providers to deploy it in a single crisp and clean way.

With more than 167,000 in-hospital deaths from cardiac arrest in the USA each year predictive analytics can help clinicians identify those patients most at risk.

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GE JON ZIMMERMAN: UNLEASH THE POWER OF DENIALS IQ

Jon Zimmerman, VP & GM for GE Healthcare, is working closely with Apervita to bring DenialsIQ to the Apervita marketplace. It’s a good illustration of how GE Healthcare partners to deliver greater value for its customers. The process of working denials is overwhelming and is people and process heavy, making it a perfect opportunity for advanced analytics.

Today, over 90% of a traditional claims denials are avoidable. Re-working a denied claim costs roughly $25 per re-claim, yet actionable data about which claims should be re-worked is not widely available.

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DARTNet

EMIDSDR. WILSON PACE: AFFORDABLE POPULATION HEALTH FOR PRIMARY CARE

Dr. Wilson Pace, CEO of the DARTNet Institute, relies on Apervita to distribute analytics through the Apervita platform, facilitating the adoption of primary care protocols. The Apervita marketplace enables PCPs to subscribe to these analytics and the use the resulting insight in workflow, bridging the gap between identifying populations at risk and applying protocols to help reduce patient risk.”

Dr. Rocha is a client of DARTNet. They use the Apervita platform and Dr. Wilson Pace's pathways and protocols to deliver better care to his patients everyday.

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EMIDS

EMIDSSAURABH SINHA: SCALE TO 1,000s OF INSIGHTS IN WEEKS

Saurabh Sinha, CEO of EMIDS, says that Apex is a solution specifically design for the Apervita platform. EMRs have helped create a wealth of digital patient data, yet it can take from 6 to 9 months to put a single risk prediction algorithm, protocol or pathway into practice. With APEX, powered by Apervita, providers and payers can scale health knowledge across the enterprise with 1,000s of predictive health algorithms all at once.

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