BACKGROUND: Antibiotic prescribing for upper respiratory tract infections (URTIs) is widespread, is often inappropriate, and may contribute to antibiotic resistance among community-acquired pathogens, such as Streptococcus pneumoniae. METHODS: A multifaceted intervention involving health care professionals and patients was introduced to a small rural Utah community and included the repetitive use of printed diagnostic and treatment algorithms by professionals. Data on the quantity and class of antibiotic prescribing, which were collected from multiple sources, were measured for the intervention period (from January through June) in 2001 and compared with data for the baseline period during the same months in 2000. RESULTS: Medicaid claims data revealed that the percentage of patients in the community who received antibiotics for URTIs during the intervention period was 15.6% less than that for the baseline period, whereas the percentage in the rest of rural Utah was relatively stable, with a 1.5% decrease (P=.006). The greatest impact of the intervention was on prescribing for acute bronchitis (decreases of 56.1% and 1.7% in the community and rural Utah, respectively; P=.024) and on prescribing of macrolides (decreases of 13.4% and 0.2% in the community and rural Utah, respectively; P<.001). Community pharmacy data likewise revealed a 17.5% decrease in the rate of antibiotic prescribing during the intervention period (P<.001), with the largest decrease observed for macrolide prescribing (50.9%; P<.001). Chart review data, in contrast, revealed no significant decrease in the percentage of patients with URTI who were prescribed an antibiotic (3.8%; P=.49), although there was a significant decrease of 11.2% in macrolide use (P=.045). CONCLUSIONS: A multifaceted intervention involving the repetitive use of printed algorithms resulted in modest improvements in antibiotic prescribing for outpatient URTIs, although one data source did not corroborate this. However, macrolide prescribing decreased sharply, irrespective of the source of data.
BACKGROUND: Antibiotic prescribing for upper respiratory tract infections (URTIs) is widespread, is often inappropriate, and may contribute to antibiotic resistance among community-acquired pathogens, such as Streptococcus pneumoniae. METHODS: A multifaceted intervention involving health care professionals and patients was introduced to a small rural Utah community and included the repetitive use of printed diagnostic and treatment algorithms by professionals. Data on the quantity and class of antibiotic prescribing, which were collected from multiple sources, were measured for the intervention period (from January through June) in 2001 and compared with data for the baseline period during the same months in 2000. RESULTS: Medicaid claims data revealed that the percentage of patients in the community who received antibiotics for URTIs during the intervention period was 15.6% less than that for the baseline period, whereas the percentage in the rest of rural Utah was relatively stable, with a 1.5% decrease (P=.006). The greatest impact of the intervention was on prescribing for acute bronchitis (decreases of 56.1% and 1.7% in the community and rural Utah, respectively; P=.024) and on prescribing of macrolides (decreases of 13.4% and 0.2% in the community and rural Utah, respectively; P<.001). Community pharmacy data likewise revealed a 17.5% decrease in the rate of antibiotic prescribing during the intervention period (P<.001), with the largest decrease observed for macrolide prescribing (50.9%; P<.001). Chart review data, in contrast, revealed no significant decrease in the percentage of patients with URTI who were prescribed an antibiotic (3.8%; P=.49), although there was a significant decrease of 11.2% in macrolide use (P=.045). CONCLUSIONS: A multifaceted intervention involving the repetitive use of printed algorithms resulted in modest improvements in antibiotic prescribing for outpatient URTIs, although one data source did not corroborate this. However, macrolide prescribing decreased sharply, irrespective of the source of data.
Authors: Alike W van der Velden; Eefje J Pijpers; Marijke M Kuyvenhoven; Sarah K G Tonkin-Crine; Paul Little; Theo J M Verheij Journal: Br J Gen Pract Date: 2012-12 Impact factor: 5.386
Authors: Michael A Rubin; Kim Bateman; Sharon Donnelly; Gregory J Stoddard; Kurt Stevenson; Reed M Gardner; Matthew H Samore Journal: J Am Med Inform Assoc Date: 2006-08-23 Impact factor: 4.497
Authors: Seung Yeon Song; Joo Hee Shin; Su Yeong Hyeon; Donguk Kim; Won Ku Kang; Soo-Han Choi; Yae-Jean Kim; Eun Young Kim Journal: PLoS One Date: 2017-05-17 Impact factor: 3.240