title: Using String Metrics to Identify Patient Journeys through Care Pathways.
abstract: Given a computerized representation of a care pathway and an electronic record of a patient's clinical journey, with potential omissions, insertions, discontinuities and reordering, we show that we can accurately match the journey to a particular route through the pathway by converting the problem into a string matching one. We discover that normalized string metrics lead to more unique pathway matches than non-normalized string metrics and should therefore be given preference when using these techniques.
authors.affiliation: Centre for Health Informatics, University of Manchester, Manchester, UK ; Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK.
authors.forename: Richard
authors.initials: R
authors.lastname: Williams
authors.affiliation: Centre for Health Informatics, University of Manchester, Manchester, UK ; Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK.
authors.forename: Iain E
authors.initials: IE
authors.lastname: Buchan
authors.affiliation: Centre for Health Informatics, University of Manchester, Manchester, UK.
authors.forename: Mattia
authors.initials: M
authors.lastname: Prosperi
authors.affiliation: Centre for Health Informatics, University of Manchester, Manchester, UK ; Greater Manchester Primary Care Patient Safety Translational Research Centre, University of Manchester, Manchester, UK.
authors.forename: John
authors.initials: J
authors.lastname: Ainsworth
mesh_terms: D000465:Algorithms; D019091:Critical Pathways; D057286:Electronic Health Records; D006801:Humans; D020521:Stroke / Q000628:therapy; D006113:United Kingdom