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TSI Genomics API Powers MedTek21 Population Health Platform

MedTek21 implements Translational Software’s Genomics API to improve interoperability between applications for safer and more effective prescription medications.

By Elizabeth O'Dowd

Transitional Software Inc. (TSI) has announced that MedTek21 has selected their Genomics API to provide pharmacogenomics (PGx)-based monitoring for MedTek21’s population health and medication risk management platform.

MedTek21 API

MedTek21 hopes the partnership will improve their ability to identify medication risks based on a patient’s unique genetic profile for the prescription of safer and more effective medications.

TSI’s application programming interface (API) will enable PGx-based prescribing within MedTek21’s population health and medication risk management platform and allow clinicians real-time access to the continuous analysis of newly prescribed medications for more informed treatment.

Currently, MedTek21 is used by organizations to improve care quality and outcomes for their patients.

“The integration of genomic information into population health management programs provides a more complete picture of the patient to help reduce medication risks and costs for healthcare organizations on an ongoing basis,” said Don Rule, CEo of TSI. “By using PGx data, clinicians can prescribe the right medication with less trial-and-error to protect at-risk populations, prevent adverse events and provide the most cost-effective care possible.”

Genomic testing has gained popularity as the starting place for better personalized medicine, but the amount of raw data involved is challenging to work with. APIs are required to connect organizations with data sources so the data they are searching for can be presented to them in a usable format.

For MedTek21, PGx testing is growing because clinicians need to understand how an individual’s unique genomic markers predict drug responses. Using the TSI API, MedTek21 seeks to better understand collected data to reduce fall risks, side effects, and adverse events.

“Patient indications and medications are continuously changing, especially in chronic populations,” stated Steve Salvitti, CEO of MedTek21. “TSI’s robust PGx API dramatically improves the speed and efficiency at which we can connect clinicians, healthcare providers and payers to vital PGx information and real-time drug-gene analytics. This revolutionary PGx decision support capability is helping our healthcare partners proactively improve quality of care for the most at-risk patients.”

As population health continues to grow as a healthcare priority, the use of APIs will grows along with it as a means to communicate data in different formats for the purpose of sharing data within or between organizations for the purpose of gaining a better understanding of treating diseases and how patients react to certain treatments based on specified statistics.

Last month, Weill-Cornell Medicine introduced an online genomics databank that uses an API to connect the Cerner laboratory information system at Weill-Cornell to the New York Presbyterian Hospital to make it easier for personalized medicine researchers and clinicians to collaborate to produce a wider repository of knowledge used to treat cancer patients.

“A critical component of clinical genomic testing is the generation of accurate and informative reports containing clinical-grade interpretations of genomic alterations,” reported HealthITAnalytics.com.

Weill-Cornell Medicine and MedTek21 are using APIs in a similar fashion, as a way to streamline the integration process into an automated workflow. While MedTek21 is a population health program and risk management vendor, both organizations are charged with using APIs to deliver useable information for better results.

By working with MedTek21, TSI continues their mission to deliver PGx intelligence to enable healthcare providers to make informed decisions at the point of care based on a patient’s genetic profile. The company’s proprietary PGx platform and API provides real-time support and alerts clinicians to potential drug-gene interactions a patient may experience from certain medications.

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