Evaluation of rational nonsteroidal anti-inflammatory drugs and gastro-protective agents use; association rule data mining using outpatient prescription patterns

BMC Medical Informatics and Decision Making

Research Article

Mark McEvoy¹  John Attia¹  Oraluck Pattanaprateep²  Ammarin Thakkinstian² 

[1] Centre for Clinical Epidemiology and Biostatistics, and Hunter Medical Research Institute, The University of Newcastle, Newcastle, NSW, Australia;Section for Clinical Epidemiology and Biostatistics, The Faculty of Medicine Ramathibodi Hospital, Mahidol University, 270 Rama VI Rd., Ratchathewi, 10400, Bangkok, Thailand;

关键词: Data mining;    Association rule;    Apriori algorithm;    Prescription patterns;    Rational drug use;    Hospital;    Data warehouse;    Nonsteroidal anti-inflammatory drugs;    Gastro-protective agents;   

DOI  :  10.1186/s12911-017-0496-3

 received in 2017-02-01, accepted in 2017-06-28,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundNonsteroidal anti-inflammatory drugs (NSAIDs) and gastro-protective agents should be co-prescribed following a standard clinical practice guideline; however, adherence to this guideline in routine practice is unknown. This study applied an association rule model (ARM) to estimate rational NSAIDs and gastro-protective agents use in an outpatient prescriptions dataset.MethodsA database of hospital outpatients from October 1st, 2013 to September 30th, 2015 was searched for any of following drugs: oral antacids (A02A), peptic ulcer and gastro-oesophageal reflux disease drugs (GORD, A02B), and anti-inflammatory and anti-rheumatic products, non-steroids or NSAIDs (M01A). Data including patient demographics, diagnoses, and drug utilization were also retrieved. An association rule model was used to analyze co-prescription of the same drug class (i.e., prescriptions within A02A-A02B, M01A) and between drug classes (A02A-A02B & M01A) using the Apriori algorithm in R. The lift value, was calculated by a ratio of confidence to expected confidence, which gave information about the association between drugs in the prescription.ResultsWe identified a total of 404,273 patients with 2,575,331 outpatient visits in 2 fiscal years. Mean age was 48 years and 34% were male. Among A02A, A02B and M01A drug classes, 12 rules of associations were discovered with support and confidence thresholds of 1% and 50%. The highest lift was between Omeprazole and Ranitidine (340 visits); about one-third of these visits (118) were prescriptions to non-GORD patients, contrary to guidelines. Another finding was the concomitant use of COX-2 inhibitors (Etoricoxib or Celecoxib) and PPIs. 35.6% of these were for patients aged less than 60 years with no GI complication and no Aspirin, inconsistent with guidelines.ConclusionsAround one-third of occasions where these medications were co-prescribed were inconsistent with guidelines. With the rapid growth of health datasets, data mining methods may help assess quality of care and concordance with guidelines and best evidence.

【 授权许可】

CC BY   
© The Author(s). 2017