RA Clinical Decision Tool Helps Improve Treatment Selection, Tracking

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases in the country with total health care costs approaching $19 billion each year. Over time, the chronic inflammation, left unabated can lead to progression of joint disease and irreversible destruction. The key to successfully treating this dreaded disease is to rapidly control the illness and maintain control.

We have come a long way from when I was first trained in the 1970’s where high dose aspirin, gold injections, sulfasalazine, and other marginal drugs were the mainstay. Now, biologics and small molecules targeting a number of different pathways are capable of providing at least some relief for most patients with RA. But, of note, not one drug works on more than a fraction of the patients to produce a deep and durable response; a fact that should have physicians and health plans demanding good tracking tools. This is especially true as these therapies all cost about $50,000 to $60,000 per patient per year.

Rheumatologists have developed very effective tracking methods; the same ones utilized in clinical trials designed to measure the efficacy and safety of the mainstays of therapy, the biologic and targeted therapies.

However, current electronic health records (EHRs) are not designed to track a disease as complex as RA. They are built on proprietary platforms that lack inter-operability standards, create data silos, fragment the total clinical picture, and require the use of narrative based, unstructured data. This makes following an individual patient over time difficult and leads to difficulty in obtaining prior approval for drugs that are excluded from the formulary in the common event of less than full remission. 

And, as I have written in the past, this leads to the inability to reflectively aggregate these patients into a dataset that can truly track long-term outcomes over large populations.  This also leads to challenges in being able to track overall chronological outcomes even for an individual patient. 

As our medical system rapidly moves to a value-based payment model, at both the federal and commercial levels, better data will become the foundation for a better health care system. 

If a rheumatologist were to specifically design a real-time clinical decision support and population health platform for RA, he/she would create a learning system that could accurately and precisely measure all of the nuances of RA in a cost-effective, scalable, and actionable manner. This platform would be designed to create dashboards on every patient, identify trends, predict outcomes, influence therapy choices, and improve care— all in real time. It would be easy to use and would be able to visually show patients their progress and be able to quickly prepare all of the needed data for any prior-authorizations required by insurers.

This system would also be able to accurately determine when a patient is entering a deep response or alternatively, measure when low levels of efficacy are being seen. To reiterate: the vast majority of those patients receiving $50,000 to $60,000 worth of drugs are receiving less than perfect improvement in their symptoms and joint findings on x-rays.

This system would be able to measure, at the individual joint level, joint pain and swelling, sedimentation rate, physician visual analogue scales (VAS), medication reactions, timeline to achieve low disease activity, co-morbidities, lab values, comparative DMARD and bDMARD efficacy and safety, and the standard Disease Activity Score (DAS), CDAI and Rapid 3 scales—all in a visually pleasing screen view.

Additionally, the platform would be able to report the outcomes for the RA population.  And of utmost importance, it must be agnostic and seamlessly integrated to any EHR platform so it can add value with domain specific real time information, keeping the patient record in the EHR system as the true source document.

But, rheumatologists do not need to wait for this system; it already exists in a platform called JointMan, developed by Discus Analytics, LLC, a Spokane, WA company. Drs. Howard Kenney, Gary Craig, Jeffrey Butler, Sean LaSalle, and Eric Muelleralong with co-founder Karen Ferguson MS, were quick to realize that traditional population health analytics are built into claims data, which can attain quick results but lack the depth required to understand a disease as complex as rheumatology. Karen has a 20 year history working in health care and is the past president of the Washington State Group Management Association and Empire Medical Group Managers Association and realized the managed care implications of a system like JointMan.  Together, they created a rheumatology solution that didn’t require clinicians to spend more time documenting or additional staff to manually enter redundant data. It was important to reduce the administrative barriers with instant aggregated data to provide actionable business intelligence around population states, reimbursement, treatment patterns, resource utilization, and other key performance indicators.

JointMan was specifically designed to be seamlessly integrated into any EHR, reduce data entry, simplify business processes, and increase the quality of the data within the medical record. It is also designed to help sustain the financial health of the rheumatology practice as it changes to the value-based model. It can work with or without connecting to the EHR and provides mapping using HL7 and API interfaces. It is HIPAA and HITECH compliant, as one would expect. JointMan requires no new hardware and, being cloud based, can be accessed via any internet browser. Of interest is that it can be up and running within 2 to 4 weeks at a very affordable cost. 

RA drug costs are among the highest of all of the self administered drugs in the specialty pharmacy category. Perhaps JointMan can fulfill a dream of rheumatologists, payers and specialty pharmacy providers: provide a tool to help with optimal medication selection 2) coordinate prescribing among providers; 3) provide clear timeframes for medication duration and follow-up; and 4) improve adherence.

Why do health plans and specialty pharmacies not mandating the use of this tool for all RA patients?  Why indeed?