"In December, doctors at a VA hospital in Oregon decided to admit an 81-year-old patient. He was dehydrated, malnourished, plagued by skin ulcers and broken ribs -- in the medical professionals’ opinion, he was unable to care for himself at home. Administrators, however, overruled them.
Was there no bed for this poor man? No, the facility had plenty of beds; in fact, on an average day, more than half of the beds are empty, awaiting patients. Was there no money or medicine to care for him? No, and no. Reporting by the New York Times suggests that Walter Savage was, perversely, turned away because he was too sick. Very sick patients tend to worsen the performance measures by which VA hospitals are judged."
"in the 1990s, New York and Pennsylvania started publishing mortality data on hospitals and surgeons who did coronary bypasses. The idea was that more informed consumers would steer themselves toward the teams with the better statistics -- theoretically good for patients, bad for slacking providers. The reality was less ideal: In those states, surgeons seem to have started doing more operations on healthier patients, while turning away the sickest ones who might otherwise have benefited."
"purchasing managers who have cozy arrangements to buy a certain amount of product from their vendors in December, and ship it back in January, in order to help some sales director make quarterly targets … universities that compete to turn away as many students as possible, because doing so makes them rise in the U.S. News rankings … law schools that hired their own graduates for temporary make-work jobs in order to boost the schools’ employment statistics. All metrics will be gamed, and the games always have costs. And when the metrics involve our health, those costs can be very high indeed."
Wednesday, January 10, 2018
How Metrics Or Formulas That Supposedly Measure Quality Of Services Can Create Incentives To Engage In Misleading Behavior
See Metrics and Their Unintended Consequences: The best intentions combine with imprecise data for perverse effects in health care and education by Megan McArdle. Excerpts: