title: Pharmacoepidemiological modelling: Markov models of antibiotic use in patients with diabetes.
abstract: The importance of time patterns in drug exposure is increasingly recognised in the evaluation of determinants and outcomes of pharmacotherapy. Data on patterns of drug exposure over time in individual patients and populations have been found to provide important 'fingerprint' information on temporal relations between disease course and severity, drug effects, and prognosis. However, data on prescriptions of medicines always need to be interpreted in the light of complementary data on clinical status, diagnosis, co-morbidity and the like.
authors.affiliation: Utrecht University, Department of Pharmacoepidemiology, The Netherlands.
authors.forename: H G M
authors.initials: HG
authors.lastname: Leufkens
mesh_terms: D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D003920:Diabetes Mellitus; D004363:Drug Utilization; D006801:Humans; D008390:Markov Chains; D017891:Pharmacoepidemiology
chemical_list: D000900:Anti-Bacterial Agents