title: The influence of payer mix on electronic prescribing by physicians.
abstract: BACKGROUND
  Limited studies have examined electronic prescribing (e-prescribing) adoption in physician office practices. Specifically, none have explored the influence of payer mix on e-prescribing adoption among physicians.
  
  
  OBJECTIVE
  This study examines the impact of practice composition of Medicare, Medicaid, and private insurance on e-prescribing adoption among physicians.
  
  
  METHODS
  Logistic regression was used to analyze data collected from a large-scale information technology-related survey of Florida physicians.
  
  
  RESULTS
  After controlling for practice and physician characteristics, physicians with the highest (odds ratio = 1.67, 95% confidence interval = 1.01-2.78) and above-average (odds ratio [OR] = 1.83, 95% confidence interval = 1.04-3.22) volume of Medicare patients were significantly more likely to e-prescribe as compared with those in the low-volume category. No differences in adoption were found across all Medicaid and private insurance practice composition categories.
  
  
  CONCLUSIONS
  Our findings support the notion that direct incentives, such as those in the Medicare Modernization Act of 2003, may influence physician adoption of e-prescribing.
authors.affiliation: Health Services Administration, University of Alabama at Birmingham, USA. davidau@uab.edu
authors.forename: David W
authors.initials: DW
authors.lastname: Au
authors.forename: Nir
authors.initials: N
authors.lastname: Menachemi
authors.forename: Anantachai
authors.initials: A
authors.lastname: Panjamapirom
authors.forename: Robert G
authors.initials: RG
authors.lastname: Brooks
mesh_terms: D000328:Adult; D016001:Confidence Intervals; D003625:Data Collection; D004059:Diffusion of Innovation; D055695:Electronic Prescribing / Q000191:economics* / Q000706:statistics & numerical data*; D005260:Female; D005431:Florida; D006751:Hospital Information Systems / Q000706:statistics & numerical data*; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D016017:Odds Ratio; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011320:Primary Health Care / Q000706:statistics & numerical data; D017149:Private Sector / Q000706:statistics & numerical data; D012051:Reimbursement Mechanisms; D012052:Reimbursement, Incentive; D013038:Specialization / Q000706:statistics & numerical data; D014481:United States