Modeling Helps Blue Cross Offer Preventive Care

Orlando - Blue Cross of Idaho wanted more information on what treatments its members were receiving and whether providers were following established clinical guidelines.
The Boise-based payer also sought to identify patients that may be at risk for chronic conditions so they could receive the necessary preventive care, says Mary Jo Kleinfeldt, R.N., director of medical and quality management.
The payer is using a predictive modeling system from Orlando, Fla.-based MEDai Inc., also known as Medical Artificial Intelligence. The application enables the insurer to identify and reach out to members that may be at risk or remind those with chronic conditions that they need to see a doctor and have the necessary tests performed.
The company also has a provider performance module that determines whether physicians are following established clinical guidelines. “We are able to look at things that have been statistically analyzed and target areas for improvement,” she says.
Payers are showing more interest in this proactive care management, says Lynne Dunbrack, program director of payer research at Health Industry Insights, a division of research firm IDC, Framingham, Mass. “Payers are investing in systems that support the ability to identify at-risk or near at-risk patients,” she says.
Being able to spot at-risk patients and potentially help them avoid a disease could potentially save millions of dollars. For example, the treatment of diabetes-related complications alone accounts for more than half of the nearly $100 billion associated with diabetes management, the remainder being direct treatment expenses, according to IDC. “Chronic diseases are preventable, and being able to identify patients and reach out to them in proactive care management is the next frontier in controlling health care costs,” Dunbrack says.
The Idaho payer hasn’t done a full analysis of cost savings from using the system. But the plan has seen a substantial increase in the number of diabetic patients that have their hemoglobin A1C monitoring performed in a timely way. Some physicians have improved their compliance with this guideline by as much as 31%, Kleinfeldt says.
MEDai’s software taps into Blue Cross of Idaho’s claims system. The systems reviews CPT codes and other information, cleans and scrubs it, then models the data and returns it to the payer every quarter, Kleinfeldt says. The payer has been using the system to review its 425,000 patients’ information since December 2005.
By watching the CPT codes, the system is able to monitor whether appropriate care is being delivered. Every quarter, the payers’ “health coaches” are able to review the data and see which patients are following the necessary treatments. For example, if a patient is a diabetic and hasn’t had a hemoglobin A1C or eye exam, the MEDai system will notify staff, who will then reach out to the patient. The technology monitors compliance with 21 clinical guidelines, Kleinfeldt says.
The payers’ case managers and health coaches access the information through an application on their desktops, Kleinfeldt says. Blue Cross of Idaho’s next step is to offer the data through a Web portal for both its employees and affiliated physicians. The data would be available on a quarterly basis.
The payer doesn’t reward or penalize providers for following the evidence-based rules, but it has started giving 400 of its affiliated primary care physicians the data so they can see where they stand, Kleinfeldt says. The data is delivered to the physicians twice a year on a CD. “Doctors don’t know if patients are getting their prescriptions filled,” Kleinfeldt says. “The information we provide shows whether they’re getting it filled and whether or not they have had tests done.”
The payer has been providing the data to physicians for about a year, Kleinfeldt says. The data shows how well the doctor is following c inical guidelines and if a patient is following prescribed treatments. Two group practices have started their own quality improvements projects because of the data from the payer, Kleinfeldt says.

The system also has enabled the payer to identify areas where it and patients can save money, Kleinfeldt says. For example, one patient who had a condition that required monthly infusions took a day off work each week to go to the clinic and have the procedure performed.
By using MEDai, the payer was able to spot this and took action to enable her to have the procedure done in her home on Saturdays. “It not only saves us money, it’s less expensive and more convenient for the member,” Kleinfeldt says.

Source: Health Data Management