Solving the Hospital Readmissions Problem

Posted on March 6, 2014 I Written By

John Lynn is the Founder of the blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

One of the most interesting things I wrote about thanks to the HIMSS conference was what I called the real cause of hospital readmissions. I’m still interested in working with more hospitals to verify the data that’s presented in that blog post, but I’ll be surprised if it doesn’t play out as an important finding when it comes to reducing hospital readmissions.

In the post, I probably was a little aggressive in my statements about how the hospital can reduce readmissions through their own actions versus depending on home health, primary care doctors, or post-acute care providers. The good news is that my great readers always hold me accountable when I step too far over the line. In this case, Richard D. Tomlinson, RN, BSME, CMUP and Founder & CEO of Nuclei Health Consultancy, offered up a deeper perspective on the complexities associated with solving the hospital readmission problem.

I would like to take a moment to provide some perspective relative to your blog post today.

Hospital readmissions are, of course, clinically complex at times. In actuality, the risk for readmission can be influenced/increased due to lack of or missed opportunity for interventions prior to patient discharge. Effective quality measures, and robust analytics, with effective data feedback and clinical governance, can be deployed as components to an overall readmission reduction strategy; more on that later.

When we discuss readmissions we must consider the fact every case is unique; the circumstances, follow up care, coordination with 3rd party caregivers/providers (e.g. home health), level of transitional intervention, cultural influences, income levels, environment, stress levels. These factors are difficult to quantify, yet I do believe there is a way to translate these factors into reasonable algorithms.

I mentioned readmission as a strategy. Hospital readmission with most health systems I have worked with do not view it in strategic terms, and they must in my opinion in order to be effective (it could be argued Very often, initiatives are tactile in their core and therefore do not have a genesis of the strategic perspective when planning/implementing. As such, critical components such as clinical governance and workflow changes within the readmioften fall by the wayside or are missed completely. Add to that BI tools in the market today are not addressing predictive analysis for readmission risk as a dynamic in the overall care plan. A future-state, effective, model in my opinion would incorporate all the aforementioned factors, and in real-time track these factors and provide the care team with dynamic risk for readmission. That, combined with robust strategic tools and models in place, would have in my view significant outcomes.

Readmission engineering must be redesigned and retooled before any ROI level discussion can take place. Thank you for your fine Site and information exchange. All the Best, RDT.

I agree completely that the hospital readmission problem is not a simple problem. However, I still think a lot of people are looking in the wrong place. I look forward to digging into this problem a lot more. Reducing hospital readmissions is great for everyone involved.