title: A randomized outpatient trial of a decision-support information technology tool.
abstract: BACKGROUND
  Decision-support information technology is often adopted to improve clinical decision making, but it is rarely rigorously evaluated. Congress mandated the evaluation of Problem-Knowledge Couplers (PKC Corp, Burlington, Vt), a decision-support tool proposed for the Department of Defense's new health information network.
  
  
  METHODS
  This was a patient-level randomized trial conducted at 2 military practices. A total of 936 patients were allocated to the intervention group and 966 to usual care. Couplers were applied before routine ambulatory clinic visits. The primary outcome was quality of care, which was assessed based on the total percentage of any of 24 health care quality process measures (opportunities to provide evidence-based care) that were fulfilled. Secondary outcomes included medical resources consumed within 60 days of enrollment and patient and provider satisfaction.
  
  
  RESULTS
  There were 4639 health care opportunities (2374 in the Coupler group and 2265 in the usual-care group), with no difference in the proportion of opportunities fulfilled (33.9% vs 30.7%; P = .12). Although there was a modest improvement in performance on screening/preventive measures, it was offset by poorer performance on some measures of acute care. Coupler patients used more laboratory and pharmacy resources than usual-care patients (logarithmic mean difference, 71 dollars). No difference in patient satisfaction was observed between groups, and provider satisfaction was mixed.
  
  
  CONCLUSIONS
  This study provides no strong evidence to support the utility of this decision-support tool, but it demonstrates the value of rigorous evaluation of decision-support information technology.
authors.affiliation: Yale-New Haven Health, Yale University School of Medicine, New Haven, Conn., USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Apkon
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Mattera
authors.forename: Zhenqiu
authors.initials: Z
authors.lastname: Lin
authors.forename: Jeph
authors.initials: J
authors.lastname: Herrin
authors.forename: Elizabeth H
authors.initials: EH
authors.lastname: Bradley
authors.forename: Michael
authors.initials: M
authors.lastname: Carbone
authors.forename: Eric S
authors.initials: ES
authors.lastname: Holmboe
authors.forename: Cary P
authors.initials: CP
authors.lastname: Gross
authors.forename: Jared G
authors.initials: JG
authors.lastname: Selter
authors.forename: Amy S
authors.initials: AS
authors.lastname: Rich
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
mesh_terms: D000328:Adult; D000553:Ambulatory Care / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data; D001291:Attitude of Health Personnel; D003362:Cost-Benefit Analysis; D020000:Decision Support Systems, Clinical / Q000191:economics / Q000295:instrumentation* / Q000706:statistics & numerical data*; D005260:Female; D005431:Florida; D006295:Health Resources / Q000706:statistics & numerical data; D006772:Hospitals, Military / Q000706:statistics & numerical data; D006801:Humans; D007629:Kentucky; D008297:Male; D008403:Mass Screening / Q000295:instrumentation / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D010043:Outcome and Process Assessment, Health Care; D017060:Patient Satisfaction / Q000706:statistics & numerical data; D011315:Preventive Medicine / Q000295:instrumentation / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000706:statistics & numerical data