Using InRule for Population and Wellness Management
One of the most exciting things about my job is working directly with customers as they frame out a solution from scratch. Over the years I have had the pleasure of working with several clients as they created solutions for improving quality of care through the application of risk detection and wellness rules. With all the changes coming down the pike for health care, I thought it would be interesting to talk about how rules are a key part of the future of population health management.
Health care organizations are becoming more proactive with keeping their population as healthy as possible. To do this, they need to increase care for everyone above and beyond just covering the costs for those that are already seeking care on their own. The concerns of early detection and ongoing treatment management are key to this movement and both also happen to be ripe for rules.
Depending on the types of data that are available, rules can be used in a variety of ways with regards to population management. An insurance company might only have high level information like diagnosis codes, doctor visits, prescription data, and lab requests. Whereas, a health care provider might have much more detailed patient history, including things like lab results, identified risk factors, and even canceled appointments.
With regards to chronic diseases, early detection is key. With very early detection, perpetual management can be as easy as a couple of prescriptions and occasional blood tests, resulting in a very minor impact on daily life. With later stage detection, the options for treatment escalate dramatically in terms of impact on daily life, life expectancy, and ongoing treatment costs. Once diagnosed, the patient’s adherence to a treatment regimen becomes equally important. Regardless of when they were diagnosed, patients who fail to stay on top of their treatment regimen are much more likely to move into more advanced stages of the disease. Minor improvements in either of these areas can have an enormous impact on quality of life and the respective cost of treatment.
It takes surprisingly little data to empower experts. With a patient’s doctor visit history and lab requests, an insurance company is able to use rules to determine that it is time for a physical and proactively notify the insured that it is time to schedule an appointment. Something as simple as encouraging an insured to get a physical can result in early detection of a chronic disease.
One client I worked with was managing a substantial population using on-staff doctors and chronic disease experts that manually applied their expertise through case review. The manual approach was not covering nearly as much ground as they needed to and they wanted to scale via rules-based automation. Instead of having experts look at cases, they now use InRule to manage complex logic. This frees the experts up to write rules for the combinations of indicators they were previously looking for manually. By empowering their experts to define the rules for detection, along with the prescriptive actions to take based on the severity of the detection, the client estimated that their savings in the first year alone was already into the millions!
Solutions for population management and wellness management must meet the following criteria:
- The required vocabulary must be designed to allow experts to express their knowledge in rules
- The web of patient data must be stitched together such that the necessary pieces of consideration are available to the author from rules
- The directives coming from the rule engine must be integrated into real world actions across both systems and people
After the vocabulary is in place, the next step is to connect all the required data. There are typically many different systems involved with varying degrees of support for integration. Some implementations run the rules in batch to do things like recommend physicals and inquire about missed prescriptions. Others have used a complex event processing approach where each new piece of information about a patient is processed real-time. Depending on what they are looking for, a rule might trigger a manual review of the case, or perhaps something more sophisticated like automatically scheduling an appointment.
Population heath management is an exciting canvas for rules. Much like using a drug interaction database before filling a prescription, using rules for population management leverages technology to take the data we have and the risks we know about and apply them on a far larger scale than was previously possible. Empowering an expert to catch an overlooked risk, identifying a missed prescription, or sending a reminder to get a physical, can truly save the day!