The ImproveCareNow Quality Improvement (QI) Team at the University of Michigan has been working very hard at improving their QI processes.  They now have had a long trend of improving remission rates from one population management report (PMR) to the next. But like any good researcher, they had to ask themselves: is this a real improvement in disease status for our patients, or an artifact of better data?


Physician Leader Dr. Jeremy Adler thought that major contributors to improved remission rates over the past year include: 1) improved processes with more complete data collection, 2) educating clinicians who misunderstood the methodology and consistently misclassified visits, and 3) new and improved PMR process, in that order.


Dr. Adler's team began digging through their data, and leaned a few things.  In the interest of helping others in the ImproveCareNow Network - which is what collaborative medicine is all about -  the Michigan team shared what they learned from analyzing their data.

Here is what the Michigan Team learned - in Dr. Adler's words:


University of Michigan QI Team Analysis of Remission Rates 1. We are still collecting data on paper forms (we just went live with EPIC).  We had a high rate of visits with missed data capture.  So many of the data points were old.  We made many attempts to improve return rates of data forms, which eventually improved our data collection rates.  We also have had several changes in our forms designed to help highlight questions that were frequently missed.


So I went through our pre-visit planning (PVP) forms to manually calculate remission rates from the column "PGA Remission Status" (# patients in remission / # total patients).  I then went through Excel to exclude the data points where the data were >200 days old.


On the enclosed graph, the red line represents the original remission rate from the PMR. The blue line represents remission rates with data >200 days old excluded.  I was surprised to see that there is very little difference.  I suspect that this means that when we miss data collection, we miss it for everyone, not just sick patients.


2. I then learned that a provider had a misunderstanding of the Physician Global Assessment (PGA), and was routinely classifying based on overall disease course, rather than disease activity at the time of the visit.  I then went into excel to exclude all the data from that provider (green line).  Again the remission rates did not change substantially.


3. This leads me to believe that our improvement in remission rates may be true improvements in disease status.  The improvement in remission rates starting in April-May coincides with when we began routinely having population management meetings, and routinely acting on our findings.


University of North Carolina at Chapel Hill QI Team Quote about Population Management

Built by Veracity Media on NationBuilder