Blue Cross Uses Predictive Analytics to Reduce Costs, Create Better Health Outcomes for Members
Lindsay Knake
| 3 min read
Lindsay Knake is a brand journalist for Blue Cross Blue Shield of Michigan.
About 90% of people who have chronic kidney disease don’t know it.
But through predictive analytics, Blue Cross Blue Shield of Michigan can work with data and physicians to identify members and patients who are at risk for the disease.
Using machine learning and deep Learning, Blue Cross is creating predictive models that identify health problems early, which results in earlier care and lower costs for patients and all members. Predictive analytics builds complex models off a wide range of data points from member claims, demographic, social determinants and medical records. The model identifies factors and trends that indicate a member is at higher risk for a certain medical issue or chronic condition. That allows health care providers to step in to guide care and/or the Blue Cross Care Management team to contact the member directly.
Blue Cross’s advanced analytics teams work with experts and clinicians to determine trends in health conditions, the seriousness of the conditions and what patients need. Team members at Blue Cross rigorously evaluate the models and tools to ensure that the models are accurate and properly align with the clinical strategy.
Success through predictive analytics
Since 2018, Blue Cross has been developing and deploying these models for internal programs. However, in 2023, Blue Cross launched a pilot program for identifying chronic kidney disease (CKD) through analyzing lab results and sharing these results directly with our providers. In a few months, they saw a much higher percentage of people in the pilot program being diagnosed with the disease compared to the control group. The patients in the pilot program were also diagnosed much sooner, allowing for earlier treatment, which is incredibly important to slow the progression of CKD.
Another program is identifying patients who are more likely to be readmitted to the hospital within 30 days of being discharged. This allows our internal care management teams to work closely with patients to ensure they are taking medications correctly, attending follow up appointments and adhering to their care plan to prevent them from going back to the hospital. By looking at risk factors such as acute and chronic conditions, availability of transportation, mental health and support, the health care providers can find ways to address them early.
Some models aim at making treatments and surgeries easier for patients. One model helps to identify people who are likely to have musculoskeletal surgery in the next 12 months and work with them to develop a care plan. It doesn’t necessarily mean the intervention will prevent surgery, but rather make the process go more smoothly.
Blue Cross is developing more models, including identifying patients who are at higher risk of prediabetes. Nearly 98 million Americans have prediabetes and are at risk of developing Type 2 diabetes.
Reducing health care costs for everyone
Ultimately, Blue Cross is creating an easier, more effective health care journey for members. These tools can help identify health conditions earlier and find interventions to prevent worse and more expensive outcomes. Early diagnosis of conditions like chronic kidney disease, which can eventually end up in the loss of kidney function, can slow the progress of the disease and may prevent kidney failure.
Preventing readmission to the hospital also save both money and stress for members and their loves ones.
Blue Cross is developing more predictive analytics models to help members stay healthy and prevent serious conditions. Better health care outcomes and reducing health care costs helps everyone.
Image: Getty Images
Related:
