title: Impact analysis studies of clinical prediction rules relevant to primary care: a systematic review.
abstract: OBJECTIVE
  Following appropriate validation, clinical prediction rules (CPRs) should undergo impact analysis to evaluate their effect on patient care. The aim of this systematic review is to narratively review and critically appraise CPR impact analysis studies relevant to primary care.
  
  
  METHODS
  Primary care.
  
  
  METHODS
  Adults and children.
  
  
  METHODS
  Studies that implemented the CPR compared to usual care were included.
  
  
  METHODS
  Randomised controlled trial (RCT), controlled before-after, and interrupted time series.
  
  
  METHODS
  Physician behaviour and/or patient outcomes.
  
  
  RESULTS
  A total of 18 studies, incorporating 14 unique CPRs, were included. The main study design was RCT (n=13). Overall, 10 studies reported an improvement in primary outcome with CPR implementation. Of 6 musculoskeletal studies, 5 were effective in altering targeted physician behaviour in ordering imaging for patients presenting with ankle, knee and neck musculoskeletal injuries. Of 6 cardiovascular studies, 4 implemented cardiovascular risk scores, and 3 reported no impact on physician behaviour outcomes, such as prescribing and referral, or patient outcomes, such as reduction in serum lipid levels. 2 studies examined CPRs in decision-making for patients presenting with chest pain and reduced inappropriate admissions. Of 5 respiratory studies, 2 were effective in reducing antibiotic prescribing for sore throat following CPR implementation. Overall, study methodological quality was often unclear due to incomplete reporting.
  
  
  CONCLUSIONS
  Despite increasing interest in developing and validating CPRs relevant to primary care, relatively few have gone through impact analysis. To date, research has focused on a small number of CPRs across few clinical domains only.
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Emma
authors.initials: E
authors.lastname: Wallace
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland Medical school, Radboud University, Nijmegen, The Netherlands.
authors.forename: Maike J M
authors.initials: MJ
authors.lastname: Uijen
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Barbara
authors.initials: B
authors.lastname: Clyne
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Atieh
authors.initials: A
authors.lastname: Zarabzadeh
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Claire
authors.initials: C
authors.lastname: Keogh
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland Department of Clinical Therapies, University of Limerick, Limerick, Ireland.
authors.forename: Rose
authors.initials: R
authors.lastname: Galvin
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Susan M
authors.initials: SM
authors.lastname: Smith
authors.affiliation: HRB Centre for Primary Care Research, Royal College of Surgeons in Ireland, Dublin 2, Ireland.
authors.forename: Tom
authors.initials: T
authors.lastname: Fahey
mesh_terms: D003657:Decision Making; D003661:Decision Support Techniques; D006801:Humans; D065186:Interrupted Time Series Analysis; D011320:Primary Health Care / Q000592:standards*; D016032:Randomized Controlled Trials as Topic; D012307:Risk Factors
keywords: clinical prediction rule; impact analysis; risk prediction