Blog: Sleep & Respiratory Healthcare

press release
Predictive Analytics For Therapy Adherence

With predictive analytics in Somnoware, physicians can estimate the likelihood of 90-day therapy compliance and implement suitable intervention strategies. 

95.pngSomnoware, a leading provider of digital health technology, announces the addition of predictive analytics to its patient care management module. Using this new feature, sleep physicians can now predict the likelihood of 90-day therapy compliance even before a patient has been initiated on continuous positive airway pressure (CPAP), oral, or other forms of sleep apnea therapy. 

This platform uses predictive machine learning to estimate a patient’s probability of therapy compliance at any time in the future—and updates it daily. This feature can significantly enhance a physician’s ability to provide patient care and improve therapy adherence. 

Sleep apnea is a serious disease that can reduce a patient’s lifespan by 5-7 years; doubling the likelihood of heart failure and stroke. Unfortunately, 40% of diagnosed patients completely stop using the prescribed therapy within the first year. Even for patients who continue use, masks are often not changed at the ideal 3-month interval and supplies are not restocked. As a result, there is a significant drop in the efficacy of therapy over time. Somnoware arms sleep physicians with rich data and insights that enable them to take proactive actions to improve therapy adherence. Instead of having to wait several months to ascertain short-term compliance, physicians can now start taking actions based on the patient’s predicted compliance right after they are put on therapy.

When a new patient is set up for a diagnostic sleep test, the Somnoware platform automatically pulls detailed patient data from their electronic medical records (EMR), patient questionnaires, and prior lab visits. This data includes socio-demographic characteristics, indicator variables, comorbidities, and past patient behavior. Somnoware uses this data to build a machine learning model of the patient, and makes short and long-term predictions of compliance even before the patient goes on therapy. As more data comes in, the model automatically updates its predictions. Hence, physicians can easily monitor trends in patient compliance and the likely impact of their interventions on both immediate and long-term outcomes. This brings patients closer to physicians during long-term therapy.

“The new predictive machine learning feature in Somnoware is yet another example of our commitment to provide sleep physicians with actionable, data-driven insights,” says Dr. Raj Misra, Chief Data Scientist of Somnoware. “Our goal is to bring valuable information to physicians early, so it can be used for proactive patient care management.”

About Somnoware

Somnoware is transforming respiratory healthcare by reducing cost and improving care management. Our cloud-based software enables care providers to estimate population risk, automate diagnosis workflow, better manage chronic care, and optimize patient outcomes. We provide unique insights by driving interoperability and applying patented artificial intelligence algorithms to patient data integrated from hundreds of sources. Headquartered in Sunnyvale, California, our customer base includes leading healthcare systems, accountable care organizations, independent test labs, and service companies. For more information, please visit or follow us on twitter @somnoware.

The company offers the industry’s leading respiratory healthcare management platform that integrates with over 150 software systems and devices. The platform is currently used by one in five pulmonologists in the United States. Physicians get instant access to diagnostic test data, e-signature capability, one-click DME ordering, PAP compliance data, and the ability to conduct end-to-end patient care management. Diagnostic test centers can automate their complete workflow including scheduling at multiple centers, inventory management, automated reporting, therapy ordering, and accreditation. Using Somnoware, customers are able to reduce time to diagnosis by up to 80% resulting in significant reduction in cost of care and increased provider capacity.

To learn more about Somnoware, please contact Raj Misra at media(at)somnoware(dot)com.

Topics: sleep test report, clinical sleep data, sleep health management, sleep center software, sleep center emr, cpap adherence, cpap compliance, sleep medicine software, press release, pinned


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