title: Impact of Prescription Patterns on Compliance With Follow-Up Visits at an Urban Teaching Primary Care Continuity Clinic.
abstract: BACKGROUND
  Although limiting prescription refills is considered as a strategy to increase compliance with the treatment regimen and follow-up, no literature exists to support its effectiveness. We sought to investigate whether decreasing the number of prescription refills affects no-show rate at an urban teaching primary care continuity clinic in New York.
  
  
  METHODS
  Eight teaching attending physicians and 19 residents implemented a "new prescribing strategy" from February 9 to 22, 2012, which limited the number of refills only to cover until the next intended clinic visit. All adult patient visits were included if follow-up visits were requested to be scheduled within 3 months and prescriptions were given through an electronic prescription system. No-show rates for the first follow-up visits up to 120 days from the initial visits during the interventional period were compared with those during the baseline period (December 15-28, 2011).
  
  
  RESULTS
  Two hundred twenty-one patients in the baseline period and 278 in the interventional period were included in the analysis. Median total supply of prescription was 6 and 3 months, respectively (P < .001). The no-show rates were not significantly different between the 2 periods (19.0% [42/221] vs 16.6% [46/278], P = .5). In multivariate regression analysis, the no-show rate did not change significantly during the interventional period compared with the baseline period (odds ratio [OR] 1.0; 95% confidence interval, 0.6-1.5; P = .8). Younger age (OR 1.03 per year, P = .008), male gender (OR 2.0, P = .003), Medicaid or Medicare insurance (OR 3.7, P = .01; OR 4.2, P = .02), and diagnosis of diabetes (OR 1.8, P = .04) or asthma (OR 2.0, P = .03) were associated with higher no-show rates.
  
  
  CONCLUSIONS
  Reducing the number of refills did not significantly affect no-show rates in the immediate follow-up. Alternative strategies should be considered to minimize no-shows.
authors.affiliation: Division of Preventive Medicine, Mayo Clinic, Rochester, MN, USA sorita.atsushi@mayo.edu.
authors.forename: Atsushi
authors.initials: A
authors.lastname: Sorita
authors.affiliation: Department of Medicine, Albert Einstein College of Medicine-Beth Israel Medical Center, New York, NY, USA.
authors.forename: Tomohiro
authors.initials: T
authors.lastname: Funakoshi
authors.affiliation: Department of Medicine, Albert Einstein College of Medicine-Beth Israel Medical Center, New York, NY, USA.
authors.forename: Glenn
authors.initials: G
authors.lastname: Kashan
authors.affiliation: University Medical Practice Associates, New York, NY, USA.
authors.forename: Edwin R
authors.initials: ER
authors.lastname: Young
authors.affiliation: Department of Medicine, Albert Einstein College of Medicine-Beth Israel Medical Center, New York, NY, USA.
authors.forename: Jayson
authors.initials: J
authors.lastname: Park
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009519:New York City; D000067455:No-Show Patients / Q000706:statistics & numerical data*; D016017:Odds Ratio; D009819:Office Visits / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011320:Primary Health Care / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012737:Sex Factors
keywords: no-show; outpatient; prescription pattern; teaching continuity clinic