Advanced search
Publication Cover
Clinical Epidemiology Volume 12, 2020 - Issue
Submit an article Journal homepage
208
Views
12
CrossRef citations to date
0
Altmetric
Original Research

External Validation of an Algorithm to Identify Patients with High Data-Completeness in Electronic Health Records for Comparative Effectiveness Research

Kueiyu Joshua Lin1 Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;2 Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USACorrespondence[email protected]
View further author information
,
Gary E Rosenthal3 Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USAView further author information
,
Shawn N Murphy4 Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA;5 Research Information Science and Computing, Partners Healthcare, Somerville, MA, USAView further author information
,
Kenneth D Mandl6 Computational Health Informatics Program, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USAORCID Iconhttps://orcid.org/0000-0002-9781-0477View further author information
ORCID Icon,
Yinzhu Jin1 Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USAView further author information
,
Robert J Glynn1 Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USAORCID Iconhttps://orcid.org/0000-0002-0697-8996View further author information
ORCID Icon &
Sebastian Schneeweiss1 Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USAView further author information
 show all
Pages 133-141 | Published online: 04 Feb 2020

References

  • Smith M, Stuckhardt I. Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. National Academies Press; 2012.
  • Randhawa GS. Building electronic data infrastructure for comparative effectiveness research: accomplishments, lessons learned and future steps. J Comp Eff Res. 2014;3(6):567–572. doi:10.2217/cer.14.7325494561
  • Corley DA, Feigelson HS, Lieu TA, McGlynn EA. Building data infrastructure to evaluate and improve quality: pCORnet. J Oncol Pract. 2015;11(3):204–206. doi:10.1200/JOP.2014.00319425980016
  • Weber GM, Adams WG, Bernstam EV, et al. Biases introduced by filtering electronic health records for patients with “complete data”. J Am Med Inform Assoc. 2017;24(6):1134–1141. doi:10.1093/jamia/ocx07129016972
  • Lin KJ, Glynn RJ, Singer DE, Murphy SN, Lii J, Schneeweiss S. Out-of-system care and recording of patient characteristics critical for comparative effectiveness research. Epidemiology. 2018;29(3):356–363. doi:10.1097/EDE.000000000000079429283893
  • Da Silva JA, Jacobs JW, Kirwan JR, et al. Safety of low dose glucocorticoid treatment in rheumatoid arthritis: published evidence and prospective trial data. Ann Rheum Dis. 2006;65(3):285–293. doi:10.1136/ard.2005.03863816107513
  • Hennessy S. Use of health care databases in pharmacoepidemiology. Basic Clin Pharmacol Toxicol. 2006;98(3):311–313. doi:10.1111/j.1742-7843.2006.pto_368.x16611207
  • Fang MC, Fan D, Sung SH, et al. Validity of using inpatient and outpatient administrative codes to identify acute venous thromboembolism: the CVRN VTE study. Med Care. 2016;55:e137–e143.
  • Lin KJ, Singer DE, Glynn RJ, Murphy SN, Lii J, Schneeweiss S. Identifying patients with high data completeness to improve validity of comparative effectiveness research in electronic health records data. Clin Pharmacol Ther. 2018;103(5):899–905. doi:10.1002/cpt.v103.528865143
  • Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med. 2009;28(25):3083–3107. doi:10.1002/sim.369719757444
  • Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care. 2005;43(5):480–485. doi:10.1097/01.mlr.0000160417.39497.a915838413
  • Wahl PM, Rodgers K, Schneeweiss S, et al. Validation of claims-based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially-insured population. Pharmacoepidemiol Drug Saf. 2010;19(6):596–603. doi:10.1002/pds.v19:620140892
  • Andrade SE, Harrold LR, Tjia J, et al. A systematic review of validated methods for identifying cerebrovascular accident or transient ischemic attack using administrative data. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):100–128. doi:10.1002/pds.231222262598
  • Tamariz L, Harkins T, Nair V. A systematic review of validated methods for identifying venous thromboembolism using administrative and claims data. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):154–162. doi:10.1002/pds.234122262602
  • Waikar SS, Wald R, Chertow GM, et al. Validity of international classification of diseases, ninth revision, clinical modification codes for acute renal failure. J Am Soc Nephrol. 2006;17(6):1688–1694. doi:10.1681/ASN.200601007316641149
  • Cushman M, Tsai AW, White RH, et al. Deep vein thrombosis and pulmonary embolism in two cohorts: the longitudinal investigation of thromboembolism etiology. Am J Med. 2004;117(1):19–25. doi:10.1016/j.amjmed.2004.01.01815210384
  • Cunningham A, Stein CM, Chung CP, Daugherty JR, Smalley WE, Ray WA. An automated database case definition for serious bleeding related to oral anticoagulant use. Pharmacoepidemiol Drug Saf. 2011;20(6):560–566. doi:10.1002/pds.210921387461
  • Myers RP, Leung Y, Shaheen AA, Li B. Validation of ICD-9-CM/ICD-10 coding algorithms for the identification of patients with acetaminophen overdose and hepatotoxicity using administrative data. BMC Health Serv Res. 2007;7:159. doi:10.1186/1472-6963-7-15917910762
  • Franklin JM, Rassen JA, Ackermann D, Bartels DB, Schneeweiss S. Metrics for covariate balance in cohort studies of causal effects. Stat Med. 2014;33(10):1685–1699. doi:10.1002/sim.605824323618
  • Gagne JJ, Glynn RJ, Avorn J, Levin R, Schneeweiss S. A combined comorbidity score predicted mortality in elderly patients better than existing scores. J Clin Epidemiol. 2011;64(7):749–759. doi:10.1016/j.jclinepi.2010.10.00421208778

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.