title: Clinical decision support to improve blood pressure control in hemodialysis patients: a nonrandomized controlled trial.
abstract: BACKGROUND
  Computer-based clinical decision support aims to improve the quality of patient care. The utility of decision support for improving blood pressure control in hemodialysis patients is unknown.
  
  
  METHODS
  This was a nonrandomized controlled trial of adult patients receiving chronic in-center hemodialysis during the period of April 1, 2005, to September 30, 2006, in 1 of the 2 major university-based renal programs in Alberta, Canada. Physicians in the intervention center were provided with twice-monthly audits and printed management suggestions based on guideline-recommended blood pressure targets. The same data were available to physicians in the control group but without audit and feedback decision support.
  
  
  RESULTS
  Eight hundred and thirty hemodialysis patients were receiving dialysis treatment at the time the study was initiated. Preintervention and postintervention blood pressure data were available for 361 patients. The primary outcome, the proportion of postdialysis systolic blood pressures at target over 12 months, did not differ between the intervention and the control programs (unadjusted odds ratio 0.59; 95% confidence interval [95% CI], 0.34-1.02, p = 0.06; adjusted odds ratio 0.62; 95% CI, 0.35-1.11, p = 0.11). There was no significant difference between the intervention and control groups in other measures of blood pressure such as the mean change in postdialysis systolic blood pressures (unadjusted mean difference 4 mm Hg, 95% CI, -1 to 9, p = 0.36; adjusted mean difference 2 mm Hg, 95% CI, -1 to 5, p = 0.19).
  
  
  CONCLUSIONS
  In this population of chronic hemodialysis patients, a computer-based clinical decision support system was not associated with improved blood pressure control.
authors.affiliation: Division of Nephrology, University of Alberta, Edmonton, Alberta, Canada.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Thompson
authors.forename: Brenda
authors.initials: B
authors.lastname: Hemmelgarn
authors.forename: Natasha
authors.initials: N
authors.lastname: Wiebe
authors.forename: Sumit
authors.initials: S
authors.lastname: Majumdar
authors.forename: Scott
authors.initials: S
authors.lastname: Klarenbach
authors.forename: Kailash
authors.initials: K
authors.lastname: Jindal
authors.forename: Braden
authors.initials: B
authors.lastname: Manns
authors.forename: Garth
authors.initials: G
authors.lastname: Mortis
authors.forename: Patricia
authors.initials: P
authors.lastname: Campbell
authors.forename: Marcello
authors.initials: M
authors.lastname: Tonelli
mesh_terms: D000368:Aged; D000416:Alberta / Q000453:epidemiology; D000959:Antihypertensive Agents / Q000627:therapeutic use*; D001794:Blood Pressure / Q000187:drug effects*; D001795:Blood Pressure Determination; D003660:Decision Support Systems, Management / Q000592:standards; D003661:Decision Support Techniques; D004360:Drug Therapy, Computer-Assisted / Q000592:standards; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000188:drug therapy* / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians'; D011237:Predictive Value of Tests; D015995:Prevalence; D006435:Renal Dialysis / Q000009:adverse effects*; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy*; D012307:Risk Factors; D013599:Systole; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D000959:Antihypertensive Agents