TY - JOUR
T1 - Application of the logical elements rule method for formalization of clinical rules: case study of ACOVE-NLI
AU - Medlock, Stephanie
AU - Eslami, Saeid
AU - Opondo, Dedan
AU - Askari, Marjan
AU - de Rooij, Sophia
AU - Abu-Hanna, Ameen
PY - 2012
Y1 - 2012
N2 - The Logical Elements Rule Method (LERM) is a step-wise method for formalizing if-then clinical rules. We applied LERM to a set of 40 clinical rules used in pharmacological quality assessment initiatives to assess (1) the amenability of the rules to formalization for decision support application (2) comparing adherence to rules that can and cannot be formalized, and (3) the usefulness of LERM as a tool for this task. Five rules could not be formalized, all due to unclear decision criteria. The adherence to ambiguous, non-formalizable rules was significantly lower than for formalizable ones ( <0.001). We modified LERM with three additions for this task: (a) adding the sub-step of restating the rules in a consistent natural-language grammar before decomposing them into normal form, (b) creating rules to use in lieu of a controlled vocabulary, and (c) adding the requirement that a time frame must be defined for all medications (before hospitalization, current medication, new medication, or discharge medication). Although the clinical rules in this sample are all stated as semi-structured if-then recommendations and are used in quality assessment initiatives, many ambiguities and inconsistencies in the clinical rules were identified by using LERM
AB - The Logical Elements Rule Method (LERM) is a step-wise method for formalizing if-then clinical rules. We applied LERM to a set of 40 clinical rules used in pharmacological quality assessment initiatives to assess (1) the amenability of the rules to formalization for decision support application (2) comparing adherence to rules that can and cannot be formalized, and (3) the usefulness of LERM as a tool for this task. Five rules could not be formalized, all due to unclear decision criteria. The adherence to ambiguous, non-formalizable rules was significantly lower than for formalizable ones ( <0.001). We modified LERM with three additions for this task: (a) adding the sub-step of restating the rules in a consistent natural-language grammar before decomposing them into normal form, (b) creating rules to use in lieu of a controlled vocabulary, and (c) adding the requirement that a time frame must be defined for all medications (before hospitalization, current medication, new medication, or discharge medication). Although the clinical rules in this sample are all stated as semi-structured if-then recommendations and are used in quality assessment initiatives, many ambiguities and inconsistencies in the clinical rules were identified by using LERM
M3 - Article
C2 - 22874225
SN - 0926-9630
VL - 180
SP - 421
EP - 426
JO - Studies in health technology and informatics
JF - Studies in health technology and informatics
ER -