Study finds that a 10% difference in patient satisfaction ratings predict a 2.8% difference in mortality rates, and a 1.9% difference in 30 day readmission rates.
Hospital quality metrics are difficult to interpret and may be biased by patient demographics and the breakdown of services provided, but patient satisfaction was found to predict quality metrics.
Excerpt: “The relatively recent movements toward transparency and quality in health care have collided to produce dozens of publicly available hospital quality metrics. You might consider studying them in advance of your next hospital visit. But how do you know if the metrics actually mean anything?
“There are valid reasons to be suspicious of measurements of hospital quality. One longstanding concern is that some hospitals may disproportionately attract sicker patients, who are more likely to have worse health outcomes. That could cause those hospitals to appear less effective than they actually are. Statistical techniques can mitigate but not completely eliminate this bias.
“A related problem is that measurement of the quality of a hospital can be biased if it doesn’t take into account the socioeconomic status of the population it serves — and many such metrics do not. For example, a hospital in a wealthy region serves patients with more resources, relative to a hospital in a poorer region. If greater patient resources translate into better health — and a lot of research suggests they do — the hospital in the wealthy region may appear to be of higher quality. But that isn’t necessarily because of the care it delivers.
“Because of issues like these, one study found that approaches to rating hospitals don’t agree on which hospitals are high or low in quality. … A recent study, however, shows that there is at least a bit of signal within the noise. The study, by health economists at M.I.T. and Vanderbilt, found that hospitals that score better on certain metrics reduce mortality.”
“According to the study, a hospital with a satisfaction score that is 10 percentage points higher — 70 percent of patients satisfied versus 60 percent, for example — has a mortality rate that is 2.8 percentage points lower and a 30-day readmission rate that is 1.9 percentage points lower. This is consistent with earlier work, described by my colleague Aaron Carroll, that found an association between better Yelp ratings of hospitals and lower mortality rates and readmission rates for certain conditions.”
“The very best hospitals by these measures can reduce the odds of death within a year by 14 percent relative to the very worst hospitals, for example.”
Source: New York Times
WBB Take: The ability of patient quality and safety metrics to predict patient satisfaction have often been criticized for bias, lack of validity, and low reliability. Conversely, the meaning of high or low patient satisfaction scores has been a topic of fierce debate in the healthcare industry. Variation in satisfaction scores may have little to do with clinical quality or even the quality of clinician interactions with patients. Some very well-publicized and ubiquitous patient satisfaction metrics have been criticized for resulting in too much focus on aspects of care that have little to do with care quality, but drive up costs. Examples exist of low patient satisfaction scores related to the waiting-room seating, cafeteria food, and displayed artworks, and have resulted in inordinate amounts of money and attention being spent on the purely superficial and decorative rather than on improving care quality and health outcomes.
However, some satisfaction scores are indeed an unbiased predictor of clinical performance, and can be a valuable tool as a leading indicator of potential quality and safety issues. Taken as a tool rather than as a goal, patient satisfaction scores can be used to warn of potential quality and safety risks. As such, patient satisfaction metrics should be carefully selected for their ability to form part of a comprehensive quality improvement toolbox.
Cited by Matthew Loxton