title: Phantom Prescribing: Examining the Frequency of Antimicrobial Prescriptions Without a Patient Visit.
abstract: OBJECTIVE To investigate the scale of antimicrobial prescribing without a corresponding visit, and to compare the attributes of patients who received antimicrobials with a corresponding visit with those who did not have a visit. DESIGN Retrospective cohort. METHODS We followed up 185,010 Medicare patients for 1 year after an acute myocardial infarction. For each antimicrobial prescribed, we determined whether the patient had an inpatient, outpatient, or provider claim in the 7 days prior to the antimicrobial prescription being filled. We compared the proportions of patient characteristics for those prescriptions associated with a visit and without a visit (ie, phantom prescriptions). We also compared the rates at which different antimicrobials were prescribed without a visit. RESULTS We found that of 356,545 antimicrobial prescriptions, 14.75% had no evidence of a visit in the week prior to the prescription being filled. A higher percentage of patients without a visit were identified as white (P<.001) and female (P<.001). Patients without a visit had a higher likelihood of survival and fewer additional cardiac events (acute myocardial infarction, cardiac arrest, stroke, all P<.001). Among the antimicrobials considered, amoxicillin, penicillin, and agents containing trimethoprim and methenamine were much more likely to be prescribed without a visit. In contrast, levofloxacin, metronidazole, moxifloxacin, vancomycin, and cefdinir were much less likely to be prescribed without a visit. CONCLUSIONS Among this cohort of patients with chronic conditions, phantom prescriptions of antimicrobials are relatively common and occurred more frequently among those patients who were relatively healthy. Infect Control Hosp Epidemiol 2017;38:273-280.
authors.affiliation: 1Department of Biostatistics,University of Iowa,Iowa City,Iowa.
authors.forename: Benjamin N
authors.initials: BN
authors.lastname: Riedle
authors.affiliation: 2Department of Pharmacy Practice and Science,University of Iowa,Iowa City,Iowa.
authors.forename: Linnea A
authors.initials: LA
authors.lastname: Polgreen
authors.affiliation: 1Department of Biostatistics,University of Iowa,Iowa City,Iowa.
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Cavanaugh
authors.affiliation: 2Department of Pharmacy Practice and Science,University of Iowa,Iowa City,Iowa.
authors.forename: Mary C
authors.initials: MC
authors.lastname: Schroeder
authors.affiliation: 3Department of Internal Medicine,University of Iowa,Iowa City,Iowa.
authors.forename: Philip M
authors.initials: PM
authors.lastname: Polgreen
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000890:Anti-Infective Agents / Q000145:classification* / Q000627:therapeutic use; D000073602:Antimicrobial Stewardship; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D006278:Medicare / Q000191:economics; D009203:Myocardial Infarction / Q000628:therapy; D000067455:No-Show Patients / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012959:Socioeconomic Factors; D017741:Survivors / Q000706:statistics & numerical data*; D014481:United States
chemical_list: D000890:Anti-Infective Agents