Researchers find a simple, effective way to reduce medical errors

We put our lives in the hands of the doctors we trust, yet the sad and unsettling truth is that they sometimes make mistakes. According to recent studies, 10 to 15% of clinical decisions on patient diagnosis and treatment are incorrect, and this contributes to the approximately 100,000 American deaths each year that are the result of medical errors.

Using structured networks to link clinicians with other clinicians can help reduce errors in patient diagnosis and treatment, according to 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.

The findings of a multi-year study involving around 3,000 clinicians across the United States were disclosed by the researchers in a paper that was just published in the journal Proceedings of the National Academy of Sciences (PNAS).

They discovered that when clinicians were given a case study and asked to offer diagnosis and treatment recommendations for a patient, those who were shown the anonymous diagnostic choices of their peers made recommendations that were, on average, twice as accurate as those who made their own decisions.

Simply simply, having a support system helps doctors make fewer mistakes.

While some doctors may get better as a result of these information-sharing networks, there may be an averaging effect that causes better doctors to make worse choices. But it isn’t what actually occurs. The worst clinicians become better, while the best don’t get worse, therefore there is persistent improvement rather than regression to the mean.

Damon Centola, the Elihu Katz Professor of Communication, Sociology, and Engineering

Clinical decision-making should be seen as a team effort that includes several physicians and the patient as well, according to study co-author Elaine Khoong of the University of California, San Francisco and the San Francisco General Hospital and Trauma Center. This study emphasizes how having access to additional clinicians while making clinical decisions enhances patient care.

More than just the wisdom of clinical crowds

Through an app they created and published on Apple’s App Store expressly for this purpose, the researchers examined clinicians’ treatment and diagnostic decisions over the course of several months.

Doctors were asked to assess a clinical case over the course of three rounds after downloading the app and signing up for a trial. The case was based on actual, documented patient instances. Each round began with the doctors reading the case study, after which they had two minutes to respond to two questions.

In the first question, medical professionals had to determine the patient’s diagnostic risk (for instance, what is the likelihood that a patient with chest symptoms will experience a heart attack within the next 30 days?). 1 to 100. Doctors were prompted by the second query to suggest the best course of action from a list of possibilities (e.g., send patient home, administer aspirin, or refer for observation).

Each clinician was randomly allocated to one of two groups: either the control group, whose members responded to all questions in isolation, or the experimental group, in which participants were linked to other anonymous clinicians in a social network whose responses they could view.

The participants in the control group answered questions alone during rounds two and three, just like they did in round one. The average risk estimations produced by their peers during the prior round might be seen by players in the network state, though.

Whether they belonged to a social network or not, every participant had the chance to edit their responses from one round to the next.

Seven distinct clinical cases from fields of medicine known to have high rates of diagnostic or therapeutic mistake were examined by Centola’s team using the same experimental methodology.

The researchers discovered that in the networks compared to the control groups, the total accuracy of physicians’ decisions increased by a factor of two. Additionally, the networks increased the proportion of doctors who ultimately made the right suggestion by 15% compared to controls among the initially poorest performing clinicians.

According to Centola, “We can use doctor networks to improve their performance.” We’ve long known that doctors converse with one another. The real finding here is that by structuring doctor information-sharing networks, clinical intelligence may be greatly increased.

Leveling the playing field

Medical in-person consultation networks are frequently hierarchical, with more experienced practitioners at the top and younger physicians at the bottom. Younger physicians who have diverse cultural and personal viewpoints enter the medical field and are impacted by these top-down networks, according to Centola. This is how ingrained biases enter the medical profession.

For the trial, the researchers made an attempt to enlist clinicians from a variety of geographic locations, specialties, and ages.

The researchers discovered that seniority and status barriers—which limit many aspects of learning in medical networks—were eliminated by anonymised egalitarian networks. Egalitarian internet networks broaden the range of voices affecting clinical decisions, according to Centola. We discovered that decision-making gets better overall for a number of specialties as a result.

In the doctor’s office

To put these results into practice, Centola asserts that we need not reinvent the wheel. “Some institutions, particularly those with limited resources, rely on e-consult technology, which allow a doctor to message an outside expert for counsel. Response times typically range from 24 to 72 hours. Instead of just one individual, why not send this question to a group of experts?

Each experimental trial, according to Centola, lasted less than 20 minutes. Furthermore, he asserts that networks don’t have to be enormous. Actually, 40 members would be perfect.

“Forty people in a network gets you a steep jump in clinicians’ collective intelligence,” claims Centola. “The increasing returns above that — going, say, from 40 to 4,000 — are minimal.”

Currently, the researchers are attempting to introduce their network technology to doctor’s offices. This program’s pilot phase, which will start later this year, has already been financed by the Hospital of the University of Pennsylvania.

Source:

Pennsylvania State University

Journal citation

Experimental evidence for structured information-sharing networks minimizing medical errors, Centola, D., et al. 2023. DOI: 10.1073/pnas.2108290120. PNAS.

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