title: Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant's Usability.
abstract: BACKGROUND
  Polypharmacy poses threats to patients' health. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP) is a drug optimization process for conducting medication reviews in primary care. To effectively and efficiently incorporate this method into daily practice, the STRIP Assistant--a decision support system that aims to assist physicians with the pharmacotherapeutic analysis of patients' medical records--has been developed. It generates context-specific advice based on clinical guidelines.
  
  
  OBJECTIVE
  The aim of this study was to validate the STRIP Assistant's usability as a tool for physicians to optimize medical records for polypharmacy patients.
  
  
  METHODS
  In an online experiment, 42 physicians were asked to optimize medical records for two comparable polypharmacy patients, one in their usual manner and one using the STRIP Assistant. Changes in effectiveness were measured by comparing respondents' optimized medicine prescriptions with medication prepared by an expert panel of two geriatrician-pharmacologists. Efficiency was operationalized by recording the time the respondents took to optimize the two cases. User satisfaction was measured with the System Usability Scale (SUS). Independent and paired t tests were used for analysis.
  
  
  RESULTS
  Medication optimization significantly improved with the STRIP Assistant. Appropriate decisions increased from 58% without the STRIP Assistant to 76% with it (p < 0.0001). Inappropriate decisions decreased from 42% without the STRIP Assistant to 24% with it (p < 0.0001). Participants spent significantly more time optimizing medication with the STRIP Assistant (24 min) than without it (13 min; p < 0.0001). They assigned it a below-average SUS score of 63.25.
  
  
  CONCLUSIONS
  The STRIP Assistant improves the effectiveness of medication reviews for polypharmacy patients.
authors.affiliation: Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands, m.c.meulendijk@uu.nl.
authors.forename: Michiel C
authors.initials: MC
authors.lastname: Meulendijk
authors.forename: Marco R
authors.initials: MR
authors.lastname: Spruit
authors.forename: A Clara
authors.initials: AC
authors.lastname: Drenth-van Maanen
authors.forename: Mattijs E
authors.initials: ME
authors.lastname: Numans
authors.forename: Sjaak
authors.initials: S
authors.lastname: Brinkkemper
authors.forename: Paul A F
authors.initials: PA
authors.lastname: Jansen
authors.forename: Wilma
authors.initials: W
authors.lastname: Knol
mesh_terms: D000328:Adult; D020000:Decision Support Systems, Clinical; D011307:Drug Prescriptions; D005260:Female; D006801:Humans; D057970:Inappropriate Prescribing; D008297:Male; D054539:Medication Therapy Management; D008875:Middle Aged; D019338:Polypharmacy; D011320:Primary Health Care / Q000379:methods; D012984:Software