title: LERM (Logical Elements Rule Method): a method for assessing and formalizing clinical rules for decision support.
abstract: OBJECTIVE
  The aim of this study was to create a step-by-step method for transforming clinical rules for use in decision support, and to validate this method for usability and reliability.
  
  
  METHODS
  A sample set of clinical rules was identified from the relevant literature. Using an iterative approach with a focus group of mixed clinical and informatics experts, a method was developed for assessing and formalizing clinical rules. Two assessors then independently applied the method to a separate validation set of rules. Usability was assessed in terms of the time required and the error rate, and reliability was assessed by comparing the results of the two assessors.
  
  
  RESULTS
  The resulting method, called the Logical Elements Rule Method, consists of 7 steps: (1) restate the rule proactively; (2) restate the rule as a logical statement (preserving key phrases); (3) assess for conflict between rules; (4) identify concepts which are not needed; (5) classify concepts as crisp or fuzzy, find crisp definitions corresponding to fuzzy concepts, and extract data elements from crisp concepts; (6) identify rules which are related by sharing patients, actions, etc.; (7) determine availability of data in local systems. Validation showed that the method was usable with rules from various sources and clinical conditions, and reliable between users provided that the users agree on a terminology and agree on when the rule will be evaluated.
  
  
  CONCLUSIONS
  A method is presented to assist in assessing clinical rules for their amenability to decision support, and formalizing the rules for implementation. Validation shows that the method is usable and reliable between users. Use of a terminology increases reliability but also the error rate. The method is useful for future developers of systems which offer decision support based on clinical rules.
authors.affiliation: Department of Medical Informatics, Academic Medical Center, Meibergdreef 15, 1105 AZ Amsterdam, The Netherlands. s.k.medlock@amc.uva.nl
authors.forename: Stephanie
authors.initials: S
authors.lastname: Medlock
authors.forename: Dedan
authors.initials: D
authors.lastname: Opondo
authors.forename: Saeid
authors.initials: S
authors.lastname: Eslami
authors.forename: Marjan
authors.initials: M
authors.lastname: Askari
authors.forename: Peter
authors.initials: P
authors.lastname: Wierenga
authors.forename: Sophia E
authors.initials: SE
authors.lastname: de Rooij
authors.forename: Ameen
authors.initials: A
authors.lastname: Abu-Hanna
mesh_terms: D000465:Algorithms; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D009426:Netherlands; D012984:Software; D012985:Software Design