The new buzz word in the outcomes world is "risk adjustment." Yup, it really is. I've seen it on websites describing an outcomes management system in the last 6 months compared to last year. Why is this happening?
This is happening because the fee for service payment model will soon be obsolete. Payers are moving into value based purchasing type models. In the rehabilitation world, payers have been zeroing in on an episode of care and negotiating for a pre-defined level of quality. To do this properly, risk adjusted, aggregate data is required.
I'm envisioning a huge problem. The problem is that the majority will be searching for an outcomes product for their organization. They will know they need risk adjusted data and will focus on ensuring their product of choice has the risk adjustment feature. Check that off the list of needs, right?
First off, for any new payment model focused on quality and analyzing aggregated data, yes, you really do need a system that can adequately risk adjust data. Risk adjustment attempts to equalize patients for comparison purposes. Do not immediately accept that risk adjusting is risk adjusting is risk adjusting.
As you research solutions that include risk adjustment, have a few questions handy to help you determine if the system will adequately risk adjust your data.
You and I both know that a typical 70 year old female who has chronic knee pain is not going to have the same amount of change in function that an 18 year old male who just experienced recent knee sprain. The typical risk adjustment factors include gender, age and acuity. Although that's a fantastic start for any newly budding outcomes system, it really isn't adequate enough for you and your patients. Do you know why? Two 70 year old females who are experiencing knee pain that has been ongoing for more than 6 months need additional factors to help create an apples to apples comparison.
Risk adjustment has occurred in the health care world historically in the payer world. Payers focus on cost. Payers learned that only using subscriber demographic data captured 3-5% of variation of cost. (Not very much, right? This means the payer really couldn't predict their costs very well.) From the reading I've done, health-based risk adjustment systems (subscriber characteristics and claims data) can explain 14-20% of variation of cost when predicting expenditures. Risk adjusting isn't new and has been used to predict the cost of care.
In the rehabilitation world, you'll be looking for a system that has a robust risk adjustment process. Via the risk adjustment process, you want the system to account for as much variation as possible. The more robust, the higher the amount of explained variance. The reason you want a higher percentage of variance explained is because the comparison to benchmarked data is going to be more fair and accurate. And, in any upcoming payment model focused on paying for quality, you definitely want to receive the highest payment category for your services.
You know how you provide your patients with qualitative questions that should be asked with big decisions like surgery? Like... how long will it take for me to recover after surgery? Or what will my quality of life be like after surgery? I'm going to give you my two question recommendation to help you determine what outcomes system is the best for you:
What factors are risk adjusted?
How much variance is explained via the risk adjustment process?