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Items: 1 to 20 of 121

1.

Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems: a validation study in three European countries.

Coloma PM, Valkhoff VE, Mazzaglia G, Nielsson MS, Pedersen L, Molokhia M, Mosseveld M, Morabito P, Schuemie MJ, van der Lei J, Sturkenboom M, Trifirò G; EU-ADR Consortium..

BMJ Open. 2013 Jun 20;3(6). pii: e002862. doi: 10.1136/bmjopen-2013-002862.

2.

Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk.

Valkhoff VE, Coloma PM, Masclee GM, Gini R, Innocenti F, Lapi F, Molokhia M, Mosseveld M, Nielsson MS, Schuemie M, Thiessard F, van der Lei J, Sturkenboom MC, Trifirò G; EU-ADR Consortium..

J Clin Epidemiol. 2014 Aug;67(8):921-31. doi: 10.1016/j.jclinepi.2014.02.020.

PMID:
24794575
3.

Positive predictive value of ICD-9 codes 410 and 411 in the identification of cases of acute coronary syndromes in the Saskatchewan Hospital automated database.

Varas-Lorenzo C, Castellsague J, Stang MR, Tomas L, Aguado J, Perez-Gutthann S.

Pharmacoepidemiol Drug Saf. 2008 Aug;17(8):842-52. doi: 10.1002/pds.1619.

PMID:
18498081
4.

Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.

Cutrona SL, Toh S, Iyer A, Foy S, Daniel GW, Nair VP, Ng D, Butler MG, Boudreau D, Forrow S, Goldberg R, Gore J, McManus D, Racoosin JA, Gurwitz JH.

Pharmacoepidemiol Drug Saf. 2013 Jan;22(1):40-54. doi: 10.1002/pds.3310.

5.

Determining the predictive value of Read/OXMIS codes to identify incident acute myocardial infarction in the General Practice Research Database.

Hammad TA, McAdams MA, Feight A, Iyasu S, Dal Pan GJ.

Pharmacoepidemiol Drug Saf. 2008 Dec;17(12):1197-201. doi: 10.1002/pds.1672.

PMID:
18985705
6.

A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data.

Chung CP, Rohan P, Krishnaswami S, McPheeters ML.

Vaccine. 2013 Dec 30;31 Suppl 10:K41-61. doi: 10.1016/j.vaccine.2013.03.075. Review.

PMID:
24331074
7.

Assessment of the Accuracy of Using ICD-9 Codes to Identify Uveitis, Herpes Zoster Ophthalmicus, Scleritis, and Episcleritis.

Pimentel MA, Browne EN, Janardhana PM, Borkar DS, Tham VM, Uchida A, Vinoya AC, Acharya NR.

JAMA Ophthalmol. 2016 Sep 1;134(9):1001-6. doi: 10.1001/jamaophthalmol.2016.2166.

PMID:
27387135
8.

Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records.

Kiyota Y, Schneeweiss S, Glynn RJ, Cannuscio CC, Avorn J, Solomon DH.

Am Heart J. 2004 Jul;148(1):99-104.

PMID:
15215798
9.

Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database.

Lo Re V 3rd, Haynes K, Goldberg D, Forde KA, Carbonari DM, Leidl KB, Hennessy S, Reddy KR, Pawloski PA, Daniel GW, Cheetham TC, Iyer A, Coughlin KO, Toh S, Boudreau DM, Selvam N, Cooper WO, Selvan MS, VanWormer JJ, Avigan MI, Houstoun M, Zornberg GL, Racoosin JA, Shoaibi A.

Pharmacoepidemiol Drug Saf. 2013 Aug;22(8):861-72. doi: 10.1002/pds.3470.

10.

Accuracy of International Classification of Diseases, 9th Revision, Clinical Modification codes for upper gastrointestinal complications varied by position and age: a validation study in a cohort of nonsteroidal anti-inflammatory drugs users in Friuli Venezia Giulia, Italy.

Pisa F, Castellsague J, Drigo D, Riera-Guardia N, Giangreco M, Rosolen V, Clagnan E, Zanier L, Perez-Gutthann S, Barbone F.

Pharmacoepidemiol Drug Saf. 2013 Nov;22(11):1195-204. doi: 10.1002/pds.3504.

PMID:
23959537
11.

Towards improved coding of acute myocardial infarction in hospital discharge abstracts: a pilot project.

Cox JL, Melady MP, Chen E, Naylor CD.

Can J Cardiol. 1997 Apr;13(4):351-8.

PMID:
9141966
12.

The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity.

Sigakis MJ, Leffert LR, Mirzakhani H, Sharawi N, Rajala B, Callaghan WM, Kuklina EV, Creanga AA, Mhyre JM, Bateman BT.

Anesth Analg. 2016 Sep;123(3):731-8. doi: 10.1213/ANE.0000000000001436.

PMID:
27387839
13.

Use of electronic health records to ascertain, validate and phenotype acute myocardial infarction: A systematic review and recommendations.

Rubbo B, Fitzpatrick NK, Denaxas S, Daskalopoulou M, Yu N, Patel RS; UK Biobank Follow-up and Outcomes Working Group., Hemingway H.

Int J Cardiol. 2015;187:705-11. doi: 10.1016/j.ijcard.2015.03.075. Review.

14.

A study to determine the sensitivity and specificity of hospital discharge diagnosis data used in the MICA study.

McAlpine R, Pringle S, Pringle T, Lorimer R, MacDonald TM.

Pharmacoepidemiol Drug Saf. 1998 Sep;7(5):311-8.

PMID:
15073977
15.

Case definitions for acute myocardial infarction in administrative databases and their impact on in-hospital mortality rates.

Metcalfe A, Neudam A, Forde S, Liu M, Drosler S, Quan H, Jetté N.

Health Serv Res. 2013 Feb;48(1):290-318. doi: 10.1111/j.1475-6773.2012.01440.x.

16.

Evaluation of ICD-9-CM codes for craniofacial microsomia.

Luquetti DV, Saltzman BS, Vivaldi D, Pimenta LA, Hing AV, Cassell CH, Starr JR, Heike CL.

Birth Defects Res A Clin Mol Teratol. 2012 Dec;94(12):990-5. doi: 10.1002/bdra.23059.

17.

Use of electronic health record data to identify skin and soft tissue infections in primary care settings: a validation study.

Levine PJ, Elman MR, Kullar R, Townes JM, Bearden DT, Vilches-Tran R, McClellan I, McGregor JC.

BMC Infect Dis. 2013 Apr 10;13:171. doi: 10.1186/1471-2334-13-171.

18.

Validation of methods for assessing cardiovascular disease using electronic health data in a cohort of Veterans with diabetes.

Floyd JS, Blondon M, Moore KP, Boyko EJ, Smith NL.

Pharmacoepidemiol Drug Saf. 2016 Apr;25(4):467-71. doi: 10.1002/pds.3921.

PMID:
26555025
19.

Positive predictive value of International Classification of Diseases, 10th revision, diagnosis codes for cardiogenic, hypovolemic, and septic shock in the Danish National Patient Registry.

Lauridsen MD, Gammelager H, Schmidt M, Nielsen H, Christiansen CF.

BMC Med Res Methodol. 2015 Mar 20;15:23. doi: 10.1186/s12874-015-0013-2.

20.

Validation of a coding algorithm to identify patients with hepatocellular carcinoma in an administrative database.

Goldberg DS, Lewis JD, Halpern SD, Weiner MG, Lo Re V 3rd.

Pharmacoepidemiol Drug Saf. 2013 Jan;22(1):103-7. doi: 10.1002/pds.3367.

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