title: Effect of electronic prescription on attainment of cholesterol goals.
abstract: BACKGROUND
  Although recent federal mandate provides incentives for physicians to use electronic prescribing (e-prescribing), clinical end points to support its use are lacking.
  
  
  OBJECTIVE
  E-prescribing should improve low-density lipoprotein (LDL) goal attainment.
  
  
  METHODS
  In this retrospective cohort study, we queried the electronic medical records (Allscripts Electronic Health Record [EHR]) of a multispecialty outpatient academic medical practice to identify patient encounters during which consecutive lipid panels were drawn in 2007 (n = 2218). The EHR did not include a clinical decision tool for guideline adherence but did include formulary decision support (FDS), which informs physicians about drug costs specific to each patient. Logistic regression was used to examine whether the odds of reaching LDL goal were influenced by e-prescribing and adjusted for characteristics known to affect prescribing patterns and goal attainment.
  
  
  RESULTS
  Of 796 patients not at LDL goal at baseline, 49% (n = 393) were at goal at follow-up. Patients receiving an e-prescription with FDS were 59% more likely to achieve LDL goal than those with a manual prescription (95% confidence interval [CI]: 1.12-2.25). Superior LDL goal attainment may be from lower cost of medications; patients with an e-prescription were significantly more likely to receive a generic statin than patients with a manual prescription (38% vs 22.9%; P = 0.0004), and for each $10 increase in prescription price, the likelihood of being at goal decreased by 5% (odds ratio = 0.95; 95% CI: 0.93-0.98).
  
  
  CONCLUSIONS
  Our study is the first to demonstrate that e-prescribing with FDS is associated with improved LDL goal attainment. Therefore, e-prescribing can deliver tangible clinical gains to patients, likely from improved adherence to more affordable treatment.
authors.affiliation: Department of Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
authors.forename: Katherine C
authors.initials: KC
authors.lastname: Michelis
authors.forename: Bassel
authors.initials: B
authors.lastname: Hassouna
authors.forename: Mina
authors.initials: M
authors.lastname: Owlia
authors.forename: Linda
authors.initials: L
authors.lastname: Kelahan
authors.forename: Heather A
authors.initials: HA
authors.lastname: Young
authors.forename: Brian G
authors.initials: BG
authors.lastname: Choi
mesh_terms: D000046:Academic Medical Centers; D000368:Aged; D015415:Biomarkers / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood*; D003661:Decision Support Techniques; D004219:District of Columbia; D016527:Drug Costs; D016568:Drugs, Generic / Q000191:economics / Q000627:therapeutic use*; D050171:Dyslipidemias / Q000097:blood / Q000188:drug therapy* / Q000191:economics; D055695:Electronic Prescribing / Q000191:economics / Q000706:statistics & numerical data*; D005260:Female; D005569:Formularies as Topic; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000191:economics / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D010818:Practice Patterns, Physicians' / Q000191:economics / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D016896:Treatment Outcome; D016903:Drug Monitoring
chemical_list: D015415:Biomarkers; D008078:Cholesterol, LDL; D016568:Drugs, Generic; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors