title: Evaluation of methods to estimate missing days' supply within pharmacy data of the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN).
abstract: The extent to which days' supply data are missing in pharmacoepidemiologic databases and effective methods for estimation is unknown. We determined the percentage of missing days' supply on prescription and patient levels for oral anti-diabetic drugs (OADs) and evaluated three methods for estimating days' supply within the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN).
  
  
  
  We estimated the percentage of OAD prescriptions and patients with missing days' supply in each database from 2009 to 2013. Within a random sample of prescriptions with known days' supply, we measured the accuracy of three methods to estimate missing days' supply by imputing the following: (1) 28 days' supply, (2) mode number of tablets/day by drug strength and number of tablets/prescription, and (3) number of tablets/day via a machine learning algorithm. We determined incidence rates (IRs) of acute myocardial infarction (AMI) using each method to evaluate the impact on ascertainment of exposure time and outcomes.
  
  
  
  Days' supply was missing for 24 % of OAD prescriptions in CPRD and 33 % in THIN (affecting 48 and 57 % of patients, respectively). Methods 2 and 3 were very accurate in estimating days' supply for OADs prescribed at a consistent number of tablets/day. Method 3 was more accurate for OADs prescribed at varying number of tablets/day. IRs of AMI were similar across methods for most OADs.
  
  
  
  Missing days' supply is a substantial problem in both databases. Method 2 is easy and very accurate for most OADs and results in IRs comparable to those from method 3.
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.|Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: Kirsten J
authors: KJ
authors: Lum
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: Craig W
authors: CW
authors: Newcomb
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.|Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: Jason A
authors: JA
authors: Roy
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.|Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: Dean M
authors: DM
authors: Carbonari
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.|Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: M Elle
authors: ME
authors: Saine
authors: Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors: Serena
authors: S
authors: Cardillo
authors: IMS Health, London, UK.
authors: Harshvinder
authors: H
authors: Bhullar
authors: Clinical Practice Research Datalink, London, UK.
authors: Arlene M
authors: AM
authors: Gallagher
authors: Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. vincentl@mail.med.upenn.edu.|Center for Pharmacoepidemiology Research and Training, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. vincentl@mail.med.upenn.edu.|Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. vincentl@mail.med.upenn.edu.
authors: Vincent
authors: V
authors: Lo Re
mesh_terms: D000368:Aged; D016208:Databases, Factual / Q000706:statistics & numerical data*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy / Q000453:epidemiology; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000453:epidemiology; D010594:Pharmacies / Q000706:statistics & numerical data*; D013607:Tablets; D006113:United Kingdom / Q000453:epidemiology
chemical_list: D007004:Hypoglycemic Agents; D013607:Tablets
keywords: Clinical Practice Research Datalink (CPRD); Days’ supply; Electronic medical record databases; Missing data; Pharmacoepidemiology; The Health Improvement Network (THIN)