%0 Journal Article %1 Lum2017 %A Lum, Kirsten J %A Newcomb, Craig W %A Roy, Jason A %A Carbonari, Dena M %A Saine, M Elle %A Cardillo, Serena %A Bhullar, Harshvinder %A Gallagher, Arlene M %A Re, Vincent Lo %D 2017 %J European journal of clinical pharmacology %K ClinicalPracticeResearchDatalink(CPRD) Days’supply Electronicmedicalrecorddatabases Missingdata Pharmacoepidemiology TheHealthImprovementNetwork(THIN) %N 1 %P 115-123 %R 10.1007/s00228-016-2148-4 %T Evaluation of methods to estimate missing days' supply within pharmacy data of the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN). %U http://link.springer.com/10.1007/s00228-016-2148-4 http://www.ncbi.nlm.nih.gov/pubmed/27787616 %V 73 %X PURPOSE 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). METHODS 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. RESULTS 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. CONCLUSIONS 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.

@article{Lum2017, abstract = {PURPOSE 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). METHODS 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. RESULTS 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. CONCLUSIONS 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.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Lum, Kirsten J and Newcomb, Craig W and Roy, Jason A and Carbonari, Dena M and Saine, M Elle and Cardillo, Serena and Bhullar, Harshvinder and Gallagher, Arlene M and Re, Vincent Lo}, biburl = {https://www.bibsonomy.org/bibtex/2e4c177184be5a0706fff78b143efe082/jepcastel}, doi = {10.1007/s00228-016-2148-4}, interhash = {0d13d6c7feeccac2effccff37d310d40}, intrahash = {e4c177184be5a0706fff78b143efe082}, issn = {1432-1041}, journal = {European journal of clinical pharmacology}, keywords = {ClinicalPracticeResearchDatalink(CPRD) Days’supply Electronicmedicalrecorddatabases Missingdata Pharmacoepidemiology TheHealthImprovementNetwork(THIN)}, month = {1}, note = {Databases}, number = 1, pages = {115-123}, pmid = {27787616}, timestamp = {2023-02-03T11:44:35.000+0100}, 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).}, url = {http://link.springer.com/10.1007/s00228-016-2148-4 http://www.ncbi.nlm.nih.gov/pubmed/27787616}, volume = 73, year = 2017 }