CloudMedx announced new capabilities to its healthcare data analytics platform that enables clinicians and hospital staff to identify, enroll, and track care and treatment for patients in need of chronic care management.
The CloudMedx Analytics Platform combines machine learning and big data analytics to generate real-time health insights in care and treatment to improve patient outcomes. Using predictive risk analyses, CloudMedx helps physicians identify people who are at risk for debilitating illnesses in time for intervention and one-on-one support that can help them reverse their risk or minimize their potential for serious complications, according to a news release.
CloudMedx said its analytics platform integrates with labs, pharmacies and hospitals to capture relevant clinical and financial information at the point of care, which is then shared with all necessary healthcare participants across the continuum.
New features within the CloudMedx Analytics Platform that support CCM include patient engagement, curated care plans, integration of information workflows such as adding multiple EHRs into the care coordination workflow, and staff coordination.
With the new CCM capabilities, healthcare professionals can identify patients who qualify for CCM, engage them in care plans and generate daily and monthly reports on specific CCM activities, such as calls made, time sent and associated eligible payments.
The Centers for Medicare and Medicaid Services pays care providers for delivering CCM services because they save money that would otherwise be spent on costly future events such as complications, hospital readmissions and emergency room visits. CMS estimates that two-thirds of Medicare beneficiaries have two or more chronic conditions. A year and a half into the CCM program, however, CMS data shows this group is underserved.
CloudMedx automated the workflow of identifying, stratifying, enrolling, and communicating with patients directly through its portal. And the vendors APIs can allow its analytics platform to be integrated directly into existing workflows and EHRs.
