WASHINGTON -- A hospital pneumonia survival rate of 93 percent may sound good, but knowing that it's actually merely "fair" can help people pick a better hospital, according to new research. A "good" survival rate would be from 95 percent to 98 percent, medical experts say.
Better use of quality-of-care ratings can lead to greater consumer control, more effective health-care choices, and provider competition over quality instead of cost, says a report published by the American Psychological Association.
The findings are timely, given the ongoing debate over health-care and health-insurance reform. Providers and the media are showering decision-makers with raw numbers about everything from those pneumonia survival rates to the percentage of heart attack patients given key drugs and post-stay patient ratings. Typical measurements describe hospitals, nursing homes, doctors, treatments and health-insurance plans.
When it's hard to interpret the numbers, people are tempted to choose based on cost, such as monthly premiums, or even how they feel at the moment, said a report on the research, which was published in the September issue of the Journal of Experimental Psychology: Applied.
In four different studies, researchers asked people to pick fictional hospitals and health-insurance plans based on cost and quality-of-care data. Across the studies, getting the numbers in context strongly influenced decisions. People took quality data into account to a significantly greater degree when they were shown how the experts would rate the information.
When participants saw quality ratings expressed in context, in ranges such as "good," "fair" and "poor," they weighed quality more and cost less than participants who saw the same numbers out of context, the researchers found. For example, when choosing health-insurance plans, 54 percent of participants chose a higher-quality plan when given its numbers in context, while 39 percent chose it when given numbers out of context. Similarly, among older adults, 54 percent chose higher-quality plans when the numbers were evaluated; only 35 percent chose them when the numbers were without context.
Participants shown how to evaluate health-care data also leaned less on their momentary moods, which had nothing to do with quality measures.
The four studies involved 303 people age 18 to 64; 207 participants age 65 to 99 (an important group given the choices faced by older adults); 218 people age 18 to 51; and 83 students up to age 37. The studies were led by Ellen Peters, PhD, of Decision Research, a non-profit research group in Eugene, Ore., and the University of Oregon.
Being helped to interpret the numbers made the biggest difference for people who were less good with numbers generally. For them, such guidance helped them rise above the passing moods that they reported.
"Information providers cannot present 'just the facts,'" the authors wrote. If helped to integrate quality-of-care information into their judgments and reduce reliance on cost, people can make better decisions, they asserted.
The same goes for those making public policy and allocating health-care dollars. "Decision-makers need help in interpreting not only what the numbers are but what they mean," wrote the authors.
"Without [such help], today's world of instantaneous information could lead to a greater influence of irrelevant sources of affect [mood] and emotion, especially for the less numerate among us."
Article: "Bringing Meaning to Numbers: The Impact of Evaluative Categories on Decisions," Ellen Peters, PhD, and Nathan F. Dieckmann, PhD, Decision Research, Eugene, Ore., and University of Oregon; Daniel Västfjäll, PhD, Decision Research, Eugene, Ore. and Goteborg University; C. K. Mertz, Decision Research, Eugene, Ore.; Paul Slovic, Decision Research, Eugene, Ore., and University of Oregon; Journal of Experimental Psychology: Applied, Vol. 15, No. 3.
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Ellen Peters can be reached at firstname.lastname@example.org or at (541) 485-2400.
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