Nashville-based healthcare data science company, Medalogix, announced today its newest product, Medalogix Care. This home health utilization management solution leverages predictive analytics and optimization technology to provide guidance on patient care plans to healthcare providers, based on the historical analysis of millions of patient records, care plans and outcomes.
The announcement comes after Vanderbilt University Medical Center’s Health Economists peer-reviewed Medalogix’s models and found them to be more accurate than the Center for Medicare and Medicaid Services’ (CMS) publicly available risk adjustment models.
“Healthcare is behind the curve as it relates to data science, even as the biggest tech companies are investing billions of dollars in machine learning. Google, Amazon, Microsoft and IBM are leading the charge while the worldwide spend for Artificial Intelligence is projected to grow to nearly $20 billion in 2018 alone, which represents a 54% increase over the previous year,” said Elliott Wood, president and CEO of Medalogix. “Machine learning technology allows us to do more for patients that need additional clinical attention. That’s what drives our company – we strive to help others do more with less. Great technology alone won’t get us there, but great technology in the hands of great clinicians will be a giant step forward.”
Medalogix Care analyzes each patient’s clinical and functional assessment and provides an objective determination of how many home health visits a patient may need to achieve the desired outcome.
Medalogix’s data scientists identified several trends that were surprising. For example, based on analysis of multiple patient populations, Medalogix found a clear trend of diminishing returns and reduced visit effectiveness for some patients earlier in the home health episode of care than what was expected. With the industry average number of visits provided per episode ranging between 15 and 19 visits per episode, this will create resource capacity for an agency’s higher risk patient population. Early simulations of the data suggest that a home health agency should be able to reduce visits by a significant amount while achieving the same or better outcomes. With the ability to optimize episodes and resources, patients with high-risk needs are likely to get more care than what they’ve experienced historically.
The pilot program of Medalogix Care began in October 2017 with long-time customer Encompass Health. “We spend a lot of time and resources ensuring the data we collect is accurate. Our nursing and rehabilitation professionals are excellent at caring for patients in the home setting, but building a ‘just right’ care plan is very difficult because there are literally hundreds of factors to consider for each patient,” said Bud Langham, chief clinical officer at Encompass Health-Home Health and Hospice. “Having evidence-based recommendations and statistical support to augment our clinical decision-making is critical as we continue to move toward a value-based system. As an industry, we have to get there to ensure our patients receive the right care, by the right disciplines, at the right time.”
Early feedback from the clinical users piloting the technology have said the evidence-based recommendations provide an objective resource for evaluating patient-specific visit needs, augmenting the field staff recommendations and experience.
