title: Improving patient safety in hospitals: Contributions of high-reliability theory and normal accident theory.
abstract: OBJECTIVE
  To identify the distinctive contributions of high-reliability theory (HRT) and normal accident theory (NAT) as frameworks for examining five patient safety practices.
  
  
  METHODS
  We reviewed and drew examples from studies of organization theory and health services research.
  
  
  METHODS
  After highlighting key differences between HRT and NAT, we applied the frames to five popular safety practices: double-checking medications, crew resource management (CRM), computerized physician order entry (CPOE), incident reporting, and root cause analysis (RCA).
  
  
  RESULTS
  HRT highlights how double checking, which is designed to prevent errors, can undermine mindfulness of risk. NAT emphasizes that social redundancy can diffuse and reduce responsibility for locating mistakes. CRM promotes high reliability organizations by fostering deference to expertise, rather than rank. However, HRT also suggests that effective CRM depends on fundamental changes in organizational culture. NAT directs attention to an underinvestigated feature of CPOE: it tightens the coupling of the medication ordering process, and tight coupling increases the chances of a rapid and hard-to-contain spread of infrequent, but harmful errors.
  
  
  CONCLUSIONS
  Each frame can make a valuable contribution to improving patient safety. By applying the HRT and NAT frames, health care researchers and administrators can identify health care settings in which new and existing patient safety interventions are likely to be effective. Furthermore, they can learn how to improve patient safety, not only from analyzing mishaps, but also by studying the organizational consequences of implementing safety measures.
authors.affiliation: Department of Preventive Medicine, University of Tennessee Health Science Center, 66 North Pauline, Suite 463, Memphis, TN 38163, USA.
authors.forename: Michal
authors.initials: M
authors.lastname: Tamuz
authors.forename: Michael I
authors.initials: MI
authors.lastname: Harrison
mesh_terms: D006739:Hospital Administration; D019300:Medical Errors / Q000517:prevention & control; D050316:Medical Order Entry Systems; D008510:Medication Systems, Hospital; D008962:Models, Theoretical; D012308:Risk Management; D017751:Safety Management / Q000458:organization & administration*; D014481:United States