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A study examining doctor and patient behavior at three Johns Hopkins Medicine outpatient clinics has found evidence that clinicians spend more face-to-face time with patients when the clinic is on schedule and less when the clinic is running late.
The researchers say the retrospective study, summarized in a report published Oct. 1, 2016, in BMJ Open, confirms for health care services what is a commonly observed phenomenon in grocery store and bank teller lines: Once lines get backed up, service providers become less consistent in their behaviors and “shortchange” time spent with customers in order to catch up.
“We definitely demonstrated that the amount of time physicians spend with patients is influenced by whether doctors perceive their clinics are running on or behind schedule,” according to the study’s clinical leader Kayode Williams, M.D., M.B.A., associate professor of anesthesiology and critical care medicine at the Johns Hopkins University School of Medicine. “There is always tension between spending time with patients so they leave feeling I’ve really listened to them and keeping patients’ wait times down. I believe there is a happy medium that can be met that depends heavily on a consistent flow in the clinic. Waiting is one of the most common complaints about outpatient clinics, so understanding behavior is key to finding ways to see a growing number of patients efficiently while still offering high-value care,” he says.
Williams says the new research was inspired by the results of previous studies, which showed that enforcing patient punctuality reduced variability in patient wait time. The new investigation, he says, was specifically designed to learn whether physicians’ behaviors also affected clinic efficiency.
For this study, the Johns Hopkins team gathered data on patient appointment time, patient arrival time, patient interactions in the clinic and physician-patient interaction from a low-volume pain management clinic, a medium-volume academic pain management clinic and a high-volume radiation oncology service. In all, 23,635 patient-doctor interactions were examined.
The patients at each clinic were sorted into three groups: Group A was composed of those who arrived at the clinic and were present in the examination room before their scheduled appointment time; group B was composed of those who arrived before their appointment time but were not in the examination room until after their appointment time, indicating that the clinic was congested; and group C was composed of those who arrived at the clinic after their appointment time. While many physicians believe that all patients receive the same level of service, analysis of the data revealed that the average time that physicians spent with each group varied.
For the low-volume clinic, the average processing time for groups A, B and C were 38.31, 26.23 and 29.50 minutes, respectively. For the medium-volume clinic, these values were 65.59, 53.53 and 50.91 minutes, respectively. And for the high-volume clinic, the study reported 47.51, 17.59 and 47.90 minutes for groups A, B and C, respectively. While intuition may suggest that adapting behavior to catch up with the clinic’s schedule will help the clinic run smoother, the researchers found that it harms the efficiency of a clinic by adding unpredictable time variability to the system.
To explore the implications of the findings, the researchers plugged their data into a computer model known as discrete event simulation, which artificially expands the sample size to thousands more theoretical patients.
Calculating the impact of their data sample on a computer model of 10,000 doctor-patient sessions, the researchers found that even if patient tardiness is eliminated, physician behavior would cause the clinic to run behind schedule.
This led the researchers to conclude that while patient punctuality is a real factor in lengthening wait times, physician behavior may have a larger impact on the clinic’s efficiency.
“We didn’t originally think that physicians would be aware of the congestion in the clinic because they were not out in the waiting room seeing the congestion,” says Maqbool Dada, Ph.D., professor of operations management and business analytics at Johns Hopkins Carey Business School with a joint appointment in anesthesiology and critical care medicine at the Johns Hopkins University School of Medicine. “But it appears they could sense the rhythm of the clinic.”
To further test their conclusions, the researchers again turned to their computer model to create a “clinic” in which all patients were treated as though they were in group B, receiving the average amount of face-to-face time with physicians. In this model, the researchers saw that both the average time it took to get patients from check-in to checkout and the variability in those times among patients could be reduced by changing clinician behavior to be more consistent across all patients. Considering the same clinic with more consistent behavior, waiting times would drop by 34 percent.
“The take-home message is that one way to ease the trade-off between wait time and face time is to reduce uncertainty in the overall system,” says Chester Chambers, Ph.D., assistant professor of operations management at Johns Hopkins University Carey Business School and an associate faculty member at the Johns Hopkins Armstrong Institute for Patient Safety and Quality.
“If a doctor is more consistent in the amount of time spent with each patient, wait times tend to go down, and it puts less pressure on the doctor to make up the time by rushing,” Chambers adds.
Chambers says the research team is developing protocols to expand similar time management research in more clinics.
Because of the U.S.’s aging population, he says, demand for health services will continue to rise. “We need to make things go smoother so that we can see more patients without sacrificing quality.”
Other researchers involved with this study include Shereef Elnahal, Stephanie Terezakis, Theodore DeWeese and Joseph Herman of the Johns Hopkins University School of Medicine.
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
The authors disclose no competing interests.