GlobalHealth Analytics 50 Submission
Industry: Health Maintenance Organization
GlobalHealth aimed to uncover data insights for the purpose of improving patient and member outcomes. The organization’s goal was to better understand its members’ needs through the use of predictive and prescriptive analytics.
GlobalHealth worked with VitreosHealth, an analytics provider, to analyze its data sets and build algorithms to segment members who may be at risk of health emergencies.
GlobalHealth ran tests to assess the accuracy of its predictive model. The model considers predictive risks such as disease-specific, composite and utilization risks combined with outcomes like hospitalizations and emergency room visits to understand a member’s state of health. Members were categorized as either critical, high utilizers (of benefits), hidden risk or healthy and unknown (e.g., new and young members with short medical histories). VitreosHealth ran the data through regression analysis tests and clinical team members vetted the diagnosis codes.
In one instance, it was discovered that a small percentage of members were being incorrectly identified as chronic diabetics. These members may have been subscribed a steroid and had blood tests taken shortly after and were recorded as having high or low blood sugar levels, which thereby triggered a diagnosis code for hypertension or prediabetes. The algorithm was adjusted and fine-tuned to ensure that data was being interpreted in a precise way.
GlobalHealth launched its proactive outreach program in January 2014. Since then, the company has seen an 18 percent reduction in emergency room encounters and can predict nearly 70 percent of its hospital admissions. The organization has nearly 50,000 members and has contacted approximately 7,000 members through its outreach program.