We trust our doctors with our lives, but the sad and frightening fact is that doctors can get things wrong. Approximately 100,000 Americans die each year due to medical errors, and recent studies have found that 10 to 15 percent of all clinical decisions regarding patient diagnosis and treatment are erroneous.
A team of researchers led by Damon Centola, professor and director of the Network Dynamics Group at the Annenberg School for Communication at the University of Pennsylvania, has discovered a simple, effective way to reduce errors in patient diagnosis and treatment -; use structured networks to connect clinicians with other clinicians.
In a study published today in the journal Proceedings of the National Academy of Sciences (PNAS), researchers shared results from a multi-year study involving nearly 3,000 physicians in the United States.
They found that when presented with a case study and asked to make recommendations about a patient’s diagnosis and treatment, clinicians who were shown their colleagues’ diagnostic decisions on an anonymous basis were, on average, twice as accurate in their recommendations as clinicians who made their own decisions.
Simply put, doctors make fewer mistakes when they have a support network.
“The big risk with these information-sharing networks,” says Centola, who is the Elihu Katz Professor of Communication, Sociology, and Engineering, “is that while some doctors may improve, there can be an averaging effect that causes better doctors to make worse decisions. But that doesn’t happen. Instead of regression to the mean, there is steady improvement: the worst clinicians get better, while the best don’t get worse.’
Study co-author Elaine Kung of UC San Francisco and San Francisco General Hospital and Trauma Center says, “We are increasingly realizing that clinical decision-making must be viewed as a team effort involving multiple clinicians and the patient. This study highlights that having other clinicians available for consultation at the time of decision-making improves clinical care.”
More than the wisdom of clinical crowds
For several months, the researchers tested the doctors’ treatment and diagnosis solutions through an app they created and distributed on Apple’s App Store specifically for this purpose.
After signing up for a trial period and downloading the app, doctors were prompted to rate a clinical case -; based on documented cases of real-life patients -; over three circles. At the beginning of each round, clinicians read the case study, then were given two minutes to answer two questions.
The first question asked physicians to rate the patient’s diagnostic risk (eg, what is the probability that a patient with chest pain will have a heart attack in the next 30 days?) from 1 to 100. The second question asked physicians to recommend the correct treatment among several options (eg, send home, give aspirin, or refer for observation).
Each clinician was randomly assigned to one of two groups: either a control group, whose members answered all questions in isolation, or an experimental group, in which participants were connected through a social network with other anonymous clinicians whose answers they could see.
During the second and third rounds, participants in the control group had the same experience as in the first round, answering questions in isolation. But participants in the network condition could see the average risk ratings made by their peers in the social network during the previous round.
Each participant was given the opportunity to revise their answers from round to round, regardless of whether they were on a social network or not.
Centola’s team used the same experimental design to study seven different clinical cases, each from areas of medicine known to exhibit high rates of diagnostic or therapeutic errors.
The researchers found that the overall accuracy of clinicians’ decisions increased twice as much in the networks than in the control groups. Moreover, among the initially worst-performing clinicians, the networks produced a 15% increase over controls in the proportion of clinicians who ultimately made the correct referral.
“We can use physicians’ networks to improve their performance,” Centola says. “Doctors talk to each other, and we’ve known that for a long time. The real discovery here is that we can structure information-sharing networks between doctors to greatly increase their clinical intelligence.”
Leveling the playing field
Personal consultation networks in medicine are usually hierarchical with senior practitioners at the top and junior doctors at the bottom. “Younger doctors with different perspectives, cultural and personal, are coming into the medical community and are influenced by these top-down networks,” Centola says. “This is how persistent bias creeps into the medical community.”
The researchers made efforts to recruit clinicians of various ages, specialties, experience and geographic locations for the experiment.
They found that anonymized egalitarian networks erased the barriers of status and seniority that the researchers say limit many aspects of learning in medical networks. Centola notes that “egalitarian online networks increase the diversity of voices influencing clinical decisions. As a result, we’ve found that decision-making improves across the board for a wide variety of specialties.”
In the doctor’s office
“We don’t have to reinvent the wheel to apply these findings,” says Centola. “Some hospitals, particularly in low-resource areas, rely on e-consultation technologies where the clinician sends a message to an outside specialist to get advice. It usually takes 24 to 72 hours to get a response. Why not send this inquiry to a network of specialists instead of just one person?’
Centola notes that each experimental trial takes less than 20 minutes. What’s more, he says, networks don’t have to be huge. In fact, 40 members is ideal.
“Forty people in a network gives you a dramatic jump in the collective intelligence of clinicians,” Centola says. “The increasing returns above that — going from, say, 40 to 4,000 — are minimal.”
The researchers are currently working to implement their network technology in doctor’s offices. The Hospital of the University of Pennsylvania has already funded a pilot of this program, which should begin later this year.
source:
University of Pennsylvania