Embedding machine learning in healthcare is slowly moving into mainstream. Still a very noisy market with what seems like 100s of start-ups. Through the noise emerges vendors that at early stage are applying machine learning to solve some of healthcare's most pressing problems. The use case getting the most traction in the market is the application of machine learning to predictive analytics, particularly to identify patient's with clinical and financial risk. Other applications include automating medical record review to validate Hierarchical Condition Coding (HCC), a process that was manual and caused friction between payers and providers, improving patient engagement for care management through mobile technology and identifying variation in clinical practice and recommending best practices.
The initial introduction of machine learning in healthcare was slow to catch on as healthcare organizations struggled to gain the expertise to understand the relevant data, create algorithms, and consume the applications across their organizations. Embedding machine learning in applications is allowing the democratization of the technology. IDC recently published a report, IDC Innovators: Machine Learning in Healthcare, 2017 () that profiled four vendors: Apixio, Ayasdi, CognitiveScale and Wellframe. These vendors have revenue less than $100m and they were selected because they have used machine learning to address a variety of challenges in healthcare. Future IDC reports will focus on vendors embedding machine learning in predictive analytics to identify at-risk patients.
Vendor summaries from the IDC Innovators report include:
- Apixio’s, HCC Profiler assists healthcare payers identify incomplete diagnostic coding (risk adjustment) that impacts Medicare Advantage reimbursement. Medical record review occurs using machine learning mitigating manual record review. Apixio has documented increased reimbursement for payers, improved coding accuracy and coder productivity.
- Ayasdi combines topographical data analysis (TDA) with machine learning in both the healthcare and financial services industries. In healthcare, the company is addressing key challenges including population health management and variation in clinical practice. Ayasdi's Collaboration Program engages academic institutions, non-governmental organizations (NGO), and nonprofits in collaborative efforts to benefit society.
- CognitiveScale describes its machine-learning products as the "digital brains" that augments decisions and learns continuously. CognitiveScale's offerings include two products, Engage, which supports customer engagement, and Amplify, which augments worker expertise and process intelligence. Commerce and financial services clients round out the vertical industries using CognitiveScale products.
- Wellframe offers the market a machine learning–driven mobile technology application to help patients manage both acute and chronic illness. Wellframe provides routine and timely communication regarding compliance to care plans, health and wellness messaging, reminders, and alerts. Wellframe uses machine learning in its analytics to determine next best action.
While these four vendors offer a wide range of applications in healthcare there are others gaining momentum in the market.