Abstract:
Two socially motivated behavioral interventions can effectively reduce inappropriate antibiotic prescribing by primary care physicians, according to a study published today in the Journal of the American Medical Association. Infection Control.tips spoke with the principal author about the rationale for the interventions and the implications of the study findings. Infection Control.tips also spoke with an independent expert who affirms the effectiveness of the approach and offers additional advice.
Background:
Roughly half of the antibiotics prescribed in the United States are for conditions for which the drugs have no benefit (Linder et al., 2013). In addition to being ineffective, inappropriately prescribed antibiotics can cause harm: patients may experience adverse events; health care costs rise; and antibiotic-resistant bacteria thrive (O’Neill, 2016). The Centers for Disease Control and Prevention has estimated that at least two million illnesses and 23,000 deaths annually are caused by antibiotic-resistant bacteria in the United States alone (Obama, 2014). Nevertheless, despite clinical guidelines and many efforts to change prescribing patterns, the over-prescription of antibiotics persists (Barnett, 2014 and Fairlie, 2012).
The Problem
Many inappropriate antibiotic prescriptions are the result of bias, according to principal study author Jason Doctor, PhD, director of health informatics at the University of Southern California’s Schaeffer Center for Health Policy and Economics in Los Angeles. One example is ‘reciprocity.’ “If a patient feels sick with an acute respiratory infection and drives or takes the bus all the way to the doctor, it is not only to get better; it also signals support of the doctor’s practice. The doctor may feel he or she has to do something for the patient (like prescribe an antibiotic–even though an antibiotic is not warranted and unlikely to help) as a form of reciprocity for the visit—instead of telling the patient to go home and rest.”
Many inappropriate antibiotic prescriptions are the result of bias
Prompted in part by the book “Nudge” (Thaler, 2009), which brings together a substantial amount of evidence for reciprocity and other biases, Doctor and his colleagues have been testing interventions that “leverage other social cues that compete against these biases” to reduce antibiotic overuse.
The Interventions
For the current study (Meeker, 2016), the researchers tested three behavioral interventions (“nudges”):
Suggested alternatives provided prompts on patients’ electronic health records (EHRs) urging physicians to consider other options, as appropriate;
Accountable justification prompted physicians to provide free-text justifications in the EHRs for antibiotic prescriptions; and
Peer comparison sent emails to physicians comparing their antibiotic prescribing rates with those dubbed “top performers”—i.e., those with the lowest inappropriate prescribing rates.
Study participants included 248 physicians from 47 primary care practices in Boston and Los Angeles, who were randomly assigned to receive no intervention (control group) or the interventions described above, alone or in combination, for a period of 18 months. All participants received education about appropriate antibiotic prescribing. Data were collected at baseline (before the start of the study) from 14,753 patient visits for acute respiratory tract infections for which antibiotics were not appropriate, and from 16,959 similar visits during the study period.
The Findings
All practices reduced their inappropriate antibiotic prescribing rates during the course of the study. Rates decreased from 24 percent to 13 percent in the control group; from 22 percent to 6 percent in the group prompted with suggested alternatives; from 23 percent to 5 percent—a statistically significant decrease—in the group that provided accountable justification; and from 20 percent to 4 percent for the peer comparison group, also statistically significant.
Can these interventions be used effectively in different types of practice settings? “If your clinic has an EHR, these interventions can be applied there,” said Doctor. He noted that practices participating in the study were diverse, including some that were affiliated with academic medical centers and others that were low-income, federally qualified health centers.
Going forward, the research team will continue to test behavioral interventions aimed at reducing antibiotic overprescribing. They also will be looking at other problems, such as opioid prescribing, according to Doctor. “We believe we can help nudge doctors toward making better decisions around pain management—decisions that involve helping patients build the necessary skills to improve their function and quality of life, and that focus less on driving down pain scores.”
The Comment
Dr. Rodney E. Rohde, professor and chair of the Clinical Laboratory Science Program at Texas State University and a long-time advocate of reducing inappropriate antibiotic prescribing (Rohde, 2011; Rohde, 2012), told InfectionControl.tips that the study was well conceived and that “with the proper research design, it could be implemented not only in clinical settings, but in other areas such as prisons and university health centers, where peer pressure to use antibiotics judiciously may be even weaker than in a typical hospital setting.”
Behavioral change strategies are needed
Behavioral change strategies are needed, Rohde emphasized, because while “many physicians say all the right things, and most likely know that overuse and inappropriate antibiotic prescribing is ‘bad,’ they still may take the easy way out to satisfy patients’ wants. That’s why every infection should be confirmed by a laboratory test (unless it’s a life-and-death situation requiring immediate use of a broad-spectrum antibiotic) to ensure that the patient gets the right treatment.
“Patients and the general public also need to be educated about when antibiotics are appropriate and when they are not, and change their behavior during doctor visits,” Rohde continued. “Then both groups will be working synergistically to help solve the problem.”
References:
Barnett ML, Linder JA. Antibiotic prescribing for adults with acute bronchitis in the United States, 1996-2010. JAMA. 2014;311(19):2020-2022.
Fairlie T, Shapiro DJ, Hersh AL, Hicks LA. National trends in visit rates and antibiotic prescribing for adults with acute sinusitis. Arch Intern Med. 2012;172(19):1513-1514.
Linder JA. Antibiotic Prescribing for acute respiratory infections—success that’s way off the mark: comment on “A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis.” JAMA Intern Med. 2013;173(4):273-275.
Meeker D, Linder JA, Fox CR, Friedberg MW, Persell SD, Goldstein NJ, Knight TK, Hay JW, Doctor JN. Effect of Behavioral Interventions on Inappropriate
Antibiotic Prescribing Among Primary Care Practices: A Randomized Clinical Trial
JAMA. 2016;315(6):562-570. doi:10.1001/jama.2016.0275
Obama B (2014). Executive Order — Combating Antibiotic-Resistant Bacteria https://www.whitehouse.gov/the-press-office/2014/09/18/executive-order-combating-antibiotic-resistant-bacteria; accessed 2/8/16
O’Neill J (2016) Tackling drug-resistant infections globally: an overview of our work. The Review on Antimicrobial Resistance. http://amr-review.org/sites/default/files/Tackling%20drug-resistant%20infections%20-%20An%20overview%20of%20our%20work_LR_NOCROPS.pdf; accessed 2/8/16
Rohde RE. Methicillin Resistant Staphylococcus aureus (MRSA): Knowledge, Learning, and Adaptation: I guess everything changes when it happens to you – their stories. LAP LAMBERT Academic Publishing, 2011.
Rohde RE and Ross-Gordon J. MRSA model of learning and adaptation: a qualitative study among the general public. BMC Health Services Research 201212:88. DOI: 10.1186/1472-6963-12-88
Thaler RH and Sunstein CR (2009). Nudge: Improving Decisions About Health, Wealth, and Happiness. Penguin Books.
