TY - JOUR
T1 - Using model checking for critiquing based on clinical guidelines
AU - Groot, P.
AU - Hommersom, A.
AU - Lucas, P.F.
AU - Merk, R.
AU - ten Teije, A.C.M.
AU - van Harmelen, F.A.H.
AU - Serban, R.C.
PY - 2009
Y1 - 2009
N2 - Objective: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. Methods and material: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. Results: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data. © 2008 Elsevier B.V. All rights reserved.
AB - Objective: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. Methods and material: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. Results: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data. © 2008 Elsevier B.V. All rights reserved.
U2 - 10.1016/j.artmed.2008.07.007
DO - 10.1016/j.artmed.2008.07.007
M3 - Article
SN - 0933-3657
VL - 46
SP - 19
EP - 36
JO - Artificial Intelligence in Medicine
JF - Artificial Intelligence in Medicine
IS - 1
ER -