Patient Safety Data from Medicare Creates a Stir

This article from the Chicago Tribune lays out nicely some of the diverse viewpoints on some of the latest quality data to be posted publicly by Medicare - complication rates. At the heart of the matter is that the data being reported is derived from claims (bills) submitted to Medicare, and therefore it was never intended by the hospital to be a reflection of quality. Given that academic medical centers are more likely to find themselves on the list of "high complication rates", they are creating a stir in Chicago, Boston, and other medical meccas about the unreliability of the data. Not only is the data being publicly posted in order to drive consumer awareness and transparency, but CMS has announced that it will penalize hospitals who are in the highest tier of complication rates. There's clearly a lot at stake for all parties.

At the same time its refreshing to hear about the perspective of an institution such as Geisinger Medical Center - "We're perfectly fine with the way CMS does public reporting data," said Dr. John Bulger, chief quality officer at the Geisinger Medical Center in Danville, Pa., which is among the hospitals listed by CMS with substantially more complications than the average hospital. "At Geisinger, we would never shy away from the number and say, 'We don't need to get better than this.'"

This needs to be the key point for posting quality data publicly - how can we improve? what does this teach us about our patient care? how do we compare to other hospitals like us? do we really believe we are as safe as we think we are? Insight can often be painful, and it is tempting to rush to judgment both from the government side for thinking that the data is reliable enough to base payments on; and also on the part of hospitals who feel that they need to attack the data in order to defend their reputation or superiority.

Performance improvement starts first and foremost with a sense of humility, a desire to improve, and realization that improvement can and must be made. Much like the commendable approach taken by Geisinger,  it would serve all parties much better if the focus were placed on the improvement rather than on the strengths or weaknesses of data.