“Choosing Wisely” interventions can reduce antibiotic overuse at safety-net hospitals, UCLA-led research suggests
A statewide pay-for-performance intervention based on a set of guidelines called Choosing Wisely reduced rates of inappropriate antibiotic prescriptions to treat acute respiratory tract infections by an average of 18 percentage points, from 43% to 25%, across two large Los Angeles safety net hospitals.
Approximately 25% to 50% of all antibiotic prescriptions in the U.S are inappropriate. This can lead to the growth of antibiotic-resistant bacteria and other direct harms that cause more than 35,000 excess deaths per year in the U.S. Many health systems have participated in pay-for-performance interventions to reduce inappropriate antibiotic prescriptions, but these types of interventions are infrequently studied in safety net systems. This is important because pay-for-performance models to improve healthcare quality have a history of working poorly in safety net systems, thus having disparate effects on disadvantaged patients.
Choosing Wisely, launched in 2012 by the American Board of Internal Medicine Foundation, is an initiative aimed at reducing the use of unnecessary medical services and improving patient outcomes.
In 2015, the Los Angeles County Department of Health Services participated in a statewide pay-for-performance program, and one of the target areas was inappropriate antibiotic prescriptions for acute bronchitis, according to Choosing Wisely guidelines.
The researchers conducted a non-randomized trial at LA General Medical Center (formerly Los Angeles County+University of Southern California) and Olive View-UCLA medical centers, two academic safety net hospitals in Los Angeles. Backed by a statewide pay-for-performance program, they used interventions consisting of audit and feedback; clinician education; suggested alternatives; procalcitonin, a test to diagnose lower respiratory tract infections; and public commitment. These interventions were based on the Choosing Wisely campaign to reduce inappropriate antibiotic use for respiratory tract infections that are typically viral (and thus don’t need antibiotics). The researchers also assessed for several unintended consequences from the intervention, such as inappropriately withholding antibiotics.
These multi-component interventions based on Choosing Wisely guidelines can reduce antibiotic overuse without measurable harms at safety-net hospitals that largely serve disadvantaged patients.
“The scientific community has a long track record of understudying the effects of health services interventions among medically underserved populations,” said lead author Dr. Richard Leuchter, clinical instructor of medicine in the division of general internal medicine and health services research at the David Geffen School of Medicine at UCLA. “This study provides real-world evidence that these types of behavioral interventions can reduce antibiotic overuse in less-well resourced patients without causing unintended harm such as decreased appropriate antibiotic use. This has important implications for responsible antibiotic use for the tens of millions of patients served by U.S. safety net health systems each year, and also represents an important advancement in health equity by ensuring that our newest medical practices actually lead to improvements in health for all communities in the U.S.”
Additional study authors are Dr. Catherine Sarkisian, Dr. John Mafi, Carmen Carrillo, Sitaram Vangala, Dr. Oleg Melamed, and Dr. Arthur Jeng of UCLA; Dr. Rebecca Trotzky-Sirr, Dr. Charles Coffey Jr. and Dr. Brad Spellberg of USC; and Dr. Eric Wei of NYC Health + Hospitals. Sarkisian and Mafi are also affiliated with Greater Los Angeles VA Healthcare System and RAND Corporation, respectively.
The study is published in the peer-reviewed American Journal of Managed Care.
The study was funded by the National Heart, Lung, and Blood Institute (R38HL143614), the National Institute on Aging (5K24AG047899-05, P30AG021684-16, and 1K76AG064392-01A1), and the National Center for Advancing Translational Sciences (UL1TR001881, KL2TR001882).