Revisiting Readmissions as a Quality Metric for Hospitals and Anesthesiologists

The first Alert this month looked at preventable hospital readmissions and ways to attempt to reduce the rate, which was 12.3 percent for Medicare patients in 2011.  There is much more to say on the topic, including an interesting study published in the June 2013 issue of Health Affairs, Limits of Readmission Rates in Measuring Hospital Quality Suggest the Need for Added Metrics by Matthew J. Press and colleagues.

This study concluded that 30-day readmission rates fluctuated and that they were not well correlated with other measures of hospital performance.  At most, therefore readmission rates should complement other quality indicators and not be considered on their own. 

Unplanned readmissions have taken on a sizeable role in quality measurement in the last few years, because they are such an accessible proxy for other measures.  CMS is not just reducing payments to hospitals with higher-than–expected readmission rates for certain diagnoses, but it is also publishing hospital-specific rates on its Hospital Compare website and is funding institutions that implement collaborative initiatives to bring rates down through the $500 million Community-Based Care Transitions Program.    

Anesthesiologists are well aware of the shortcomings of readmission rates as measures of quality. Of particular concern to the specialty, many of the clinical and management processes that go into preventing an unplanned readmission will always be under the control of others. Since readmissions will most likely remain an active measure for at least a few years, and since anesthesiologists can expect invitations or other opportunities to take on responsibility for reducing the rates, it may be helpful to be conversant with the Limits of Readmission study.

The researchers looked at risk-standardized, all-cause readmission rates and mortality rates in 2009 and 2011 for heart attack, heart failure and pneumonia hospitalizations for nearly 4,000 hospitals on the Hospital Compare website.  They ranked all the hospitals in quartiles based on their readmission rates and examined how hospitals moved from one quartile to another during the study period.  The analysis revealed that only 1.7 percentage points separated the bottom quartile from the top quartile for heart attacks in 2009, with similar results for the other two conditions studied.

Over the two-year period, hospitals with higher readmission rates tended to improve while hospitals that started out with the lowest rates tended to experience increases in readmissions.  These changes were due in part to regression to the mean.

The study also examined the relationship between unplanned readmission rates and hospital performance on certain process and outcome indicators for the three conditions, as well as on case volumes and teaching status.  The authors found weak or even inverse correlations between readmission rates and commonly used hospital quality measures including 30-day mortality rates, volume, teaching status and composite process-measure performance.  Hospitals in the quartile with the highest process-measure performance, for example, had average readmission rates of 19.8 percent, 25.0 percent, and 18.4 percent for the three conditions respectively, compared with 20.0 percent, 24.9 percent, and 18.5 percent for hospitals in the quartile with the lowest performance.  Hospitals with relatively high readmission rates had relatively low mortality rates (which may mean only that more patients survive long enough to be readmitted). 

As a result, the researchers submit that using readmission rates to evaluate hospital quality is a flawed approach.  “Hospital performance could be judged not just by all-cause readmission rates but by developing and using measures of preventable readmissions,” they state, and:

[The] findings suggest that comparisons of readmission rates within and between hospitals over time should account for regression to the mean and that other measures of hospital performance during care transitions could augment the use of readmission rates. We also recommend that policy makers build on current efforts that take a communitywide approach to measuring readmission rates and distributing incentives to reduce them.

The article thus offers solid arguments against the exclusive (or over weighted) use of all-cause readmission data to differentiate between hospitals—and by extension anesthesiologists—for payment or quality improvement purposes.  This does not mean, of course, that providers should work less hard to limit the rate of preventable readmissions.  At the same time, the search for meaningful quality metrics must continue.