A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets

References

• National Health Interview Survey [Internet]. 2015.
   Google Scholar
• Masoli M, Fabian D, Holt S, Beasley R, Global Initiative for Asthma (GINA) Program. The global burden of asthma: executive summary of the GINA Dissemination Committee report. Allergy. 2004;59(5):469–478. doi:10.1111/j.1398-9995.2004.00526.x.
   PubMed Web of Science ®Google Scholar
• Worldwide variation in prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and atopic eczema: ISAAC. The International Study of Asthma and Allergies in Childhood (ISAAC) Steering Committee. Lancet. 1998;351(9111):1225–1232.
   PubMed Web of Science ®Google Scholar
• Worldwide variations in the prevalence of asthma symptoms: the International Study of Asthma and Allergies in Childhood (ISAAC). Eur Respir J. 1998;12(2):315–335.
   PubMed Web of Science ®Google Scholar
• Lai CK, Beasley R, Crane J, Foliaki S, Shah J, Weiland S, the ISAAC Phase Three Study Group. Global variation in the prevalence and severity of asthma symptoms: phase three of the International Study of Asthma and Allergies in Childhood (ISAAC). Thorax. 2009;64(6):476–483. doi:10.1136/thx.2008.106609.
   PubMed Web of Science ®Google Scholar
• Variations in the prevalence of respiratory symptoms, self-reported asthma attacks, and use of asthma medication in the European Community Respiratory Health Survey (ECRHS). Eur Respir J. 1996;9(4):687–695.
   PubMed Web of Science ®Google Scholar
• Sembajwe G, Cifuentes M, Tak SW, Kriebel D, Gore R, Punnett L. National income, self-reported wheezing and asthma diagnosis from the World Health Survey. Eur Respir J. 2010;35(2):279–286. doi:10.1183/09031936.00027509.
   PubMed Web of Science ®Google Scholar
• Sá-Sousa A, Jacinto T, Azevedo L, Morais-Almeida M, Robalo-Cordeiro C, Bugalho-Almeida A, Bousquet J, Fonseca J. Operational definitions of asthma in recent epidemiological studies are inconsistent. Clin Transl Allergy. 2014;4(1):24. doi:10.1186/2045-7022-4-24.
   PubMedGoogle Scholar
• Van Wonderen KE, Van Der Mark LB, Mohrs J, Bindels PJE, Van Aalderen WMC, Ter Riet G. Different definitions in childhood asthma: how dependable is the dependent variable? Eur Respiratory J. 2010;36(1):48–56. doi:10.1183/09031936.00154409.
   PubMed Web of Science ®Google Scholar
• (GINA) GIfA. 2018. Global strategy for asthma management and prevention. Available from: http://www.ginasthma.org/.
   Google Scholar
• Ducharme FM, Dell SD, Radhakrishnan D, Grad RM, Watson WT, Yang CL, Zelman M. Diagnosis and management of asthma in preschoolers: A Canadian Thoracic Society and Canadian Paediatric Society position paper. Can Respir J. 2015;22(3):135–143. doi:10.1155/2015/101572.
   PubMed Web of Science ®Google Scholar
• Wi C-I, Sohn S, Rolfes MC, Seabright A, Ryu E, Voge G, Bachman KA, Park MA, Kita H, Croghan IT, et al. Application of a natural language processing algorithm to asthma ascertainment. An automated chart review. Am J Respir Crit Care Med. 2017;196(4):430–437. doi:10.1164/rccm.201610-2006OC.
   PubMed Web of Science ®Google Scholar
• Wi C-I, Sohn S, Ali M, Krusemark E, Ryu E, Liu H, Juhn YJ. Natural language processing for asthma ascertainment in different practice settings. J Allergy Clin Immunol Pract. 2018;6(1):126–131. doi:10.1016/j.jaip.2017.04.041.
   PubMed Web of Science ®Google Scholar
• Juhn Y, Liu H. Artificial intelligence approaches using natural language processing to advance EHR-based clinical research. J Allergy Clin Immunol. 2020;145(2):463–469. doi:10.1016/j.jaci.2019.12.897.
   PubMed Web of Science ®Google Scholar
• Miller JE. Predictors of asthma in young children: does reporting source affect our conclusions? Am J Epidemiol. 2001;154(3):245–250. doi:10.1093/aje/154.3.245.
   PubMed Web of Science ®Google Scholar
• Toren K, Palmqvist M, Lowhagen O, Balder B, Tunsater A. Self-reported asthma was biased in relation to disease severity while reported year of asthma onset was accurate. J Clin Epidemiol. 2006;59(1):90–93. doi:10.1016/j.jclinepi.2005.03.019.
   PubMed Web of Science ®Google Scholar
• Perry TT, Vargas PA, McCracken A, Jones SM. Underdiagnosed and uncontrolled asthma: findings in rural schoolchildren from the Delta region of Arkansas. Ann Allergy Asthma Immunol. 2008;101(4):375–381. doi:10.1016/S1081-1206(10)60313-4.
   PubMed Web of Science ®Google Scholar
• Montnemery P, Hansson L, Lanke J, Lindholm LH, Nyberg P, Lofdahl CG, et al. Accuracy of a first diagnosis of asthma in primary health care. Fam Pract. 2002;19(4):365–368. doi:10.1093/fampra/19.4.365.
   PubMed Web of Science ®Google Scholar
• de Marco R, Cerveri I, Bugiani M, Ferrari M, Verlato G. An undetected burden of asthma in Italy: the relationship between clinical and epidemiological diagnosis of asthma. Eur. Respir. J. 1998;11(3):599–605.
   PubMed Web of Science ®Google Scholar
• Looijmans-van den Akker I, van Luijn K, Verheij T. Overdiagnosis of asthma in children in primary care: a retrospective analysis. Br J Gen Pract. 2016;66(644):e152–e157. doi:10.3399/bjgp16X683965.
   PubMed Web of Science ®Google Scholar
• Juhn Y, Kung A, Voigt R, Johnson S. Characterisation of children’s asthma status by ICD-9 code and criteria-based medical record review. Prim Care Respir J. 2010;20(1):79–83. doi:10.4104/pcrj.2010.00076.
   Google Scholar
• Activities CoPaH. H-ICDA HAoIneAA. MI: National Center for Health Statistics; 1973.
   Google Scholar
• World Health Organization. Manual of the International Classification of Diseases I, and Causes of Death, based on the recommendations of the ninth revision conference 1975, and adopted by the 29th World Health Assemby. Geneva: World Health Organization; 1977.
   Google Scholar
• Yunginger JW, Reed CE, O'Connell EJ, Melton LJ, O'Fallon WM, Silverstein MD. A community-based study of the epidemiology of asthma. Incidence rates, 1964-1983. Am Rev Respir Dis. 1992;146(4):888–894. doi:10.1164/ajrccm/146.4.888.
   PubMed Web of Science ®Google Scholar
• Sheen YH, Rolfes MC, Wi C-I, Crowson CS, Pendegraft RS, King KS, Ryu E, Juhn YJ. Association of Asthma with Rheumatoid Arthritis: A Population-Based Case-Control Study. J Allergy Clin Immunol Pract. 2018;6(1):219–226. doi:10.1016/j.jaip.2017.06.022.
   PubMed Web of Science ®Google Scholar
• Umaretiya PJ, Swanson JB, Kwon HJ, Grose C, Lohse CM, Juhn YJ. Asthma and risk of breakthrough varicella infection in children. Allergy Asthma Proc. 2016;37(3):207–215. doi:10.2500/aap.2016.37.3951.
   PubMed Web of Science ®Google Scholar
• Voge GA, Katusic SK, Qin R, Juhn YJ. Risk of Asthma in Late Preterm Infants: A Propensity Score Approach. J Allergy Clin Immunol Pract. 2015;3(6):905–10. doi:10.1016/j.jaip.2015.03.018.
   PubMed Web of Science ®Google Scholar
• Bang DW, Yang HJ, Ryoo E, Al-Hasan MN, Lahr B, Baddour LM, Yawn BP, Juhn YJ. Asthma and risk of non-respiratory tract infection: a population-based case-control study. BMJ Open. 2013;3(10):e003857. doi:10.1136/bmjopen-2013-003857.
   PubMed Web of Science ®Google Scholar
• Juhn YJ, Kita H, Yawn BP, Boyce TG, Yoo KH, McGree ME, Weaver AL, Wollan P, Jacobson RM. Increased risk of serious pneumococcal disease in patients with asthma. J Allergy Clin Immunol. 2008;122(4):719–723. doi:10.1016/j.jaci.2008.07.029.
   PubMed Web of Science ®Google Scholar
• Juhn YJ, Frey D, Li X, Jacobson R. Streptococcus pyogenes upper respiratory infection and atopic conditions other than asthma: a retrospective cohort study. Prim Care Respir J. 2012;21(2):153–158. doi:10.4104/pcrj.2011.00110.
   PubMedGoogle Scholar
• Kim B-S, Mehra S, Yawn B, Grose C, Tarrell R, Lahr B, Juhn YJ. Increased risk of herpes zoster in children with asthma: a population-based case-control study. J Pediatr. 2013;163(3):816–821. doi:10.1016/j.jpeds.2013.03.010.
   PubMed Web of Science ®Google Scholar
• Kwon HJ, Bang DW, Kim EN, Wi C-I, Yawn BP, Wollan PC, Lahr BD, Ryu E, Juhn YJ. Asthma as a risk factor for zoster in adults: A population-based case-control study. J Allergy Clin Immunol. 2016;137(5):1406–1412. doi:10.1016/j.jaci.2015.10.032.
   PubMed Web of Science ®Google Scholar
• Bang DW, Wi C-I, Kim EN, Hagan J, Roger V, Manemann S, Lahr B, Ryu E, Juhn YJ. Asthma status and risk of incident myocardial infarction: A population-based case-control study. J Allergy Clin Immunol Pract. 2016;4(5):917–923. doi:10.1016/j.jaip.2016.02.018.
   PubMed Web of Science ®Google Scholar
• Melton LJ. History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71(3):266–274. doi:10.4065/71.3.266.
   PubMed Web of Science ®Google Scholar
• St. Sauver JL, Grossardt BR, Leibson CL, Yawn BP, Melton LJ, Rocca WA. Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project. Mayo Clin Proc. 2012;87(2):151–160. doi:10.1016/j.mayocp.2011.11.009.
   PubMed Web of Science ®Google Scholar
• St Sauver JL, Grossardt BR, Yawn BP, Melton LJ, Pankratz JJ, Brue SM, Rocca WA. Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system. Int J Epidemiol. 2012;41(6):1614–1624. doi:10.1093/ije/dys195.
   PubMed Web of Science ®Google Scholar
• Bisgaard H, Szefler S. Prevalence of asthma-like symptoms in young children. Pediatr Pulmonol. 2007;42(8):723–728. doi:10.1002/ppul.20644.
   PubMed Web of Science ®Google Scholar
• Roufosse F, Weller PF. Practical approach to the patient with hypereosinophilia. J Allergy Clin Immunol. 2010;126(1):39–44. doi:10.1016/j.jaci.2010.04.011.
   PubMed Web of Science ®Google Scholar
• Smith AD, Cowan JO, Filsell S, McLachlan C, Monti-Sheehan G, Jackson P, Taylor DR. Diagnosing asthma: comparisons between exhaled nitric oxide measurements and conventional tests. Am J Respir Crit Care Med. 2004;169(4):473–478. doi:10.1164/rccm.200310-1376OC.
   PubMed Web of Science ®Google Scholar
• Sohn S, Wang Y, Wi CI, Krusemark EA, Ryu E, Ali MH. Clinical documentation variations and NLP system portability: a case study in asthma birth cohorts across institutions. J Am Med Inform Assoc. 2018;25:353–359.
   PubMed Web of Science ®Google Scholar
• Kaur H, Sohn S, Wi C-I, Ryu E, Park MA, Bachman K, Kita H, Croghan I, Castro-Rodriguez JA, Voge GA, et al. Automated chart review utilizing natural language processing algorithm for asthma predictive index. BMC Pulm Med. 2018;18(1):34. doi:10.1186/s12890-018-0593-9.
   PubMedGoogle Scholar
• Sohn S, Wi CI, Wu ST, Liu H, Ryu E, Krusemark E, Seabright A, Voge GA, Juhn YJ. Ascertainment of asthma prognosis using natural language processing from electronic medical records. J Allerg Clin Immunol. 2018;141(6):2292–2294.e3.
   Google Scholar
• Sohn S, Wi C-I, Krusemark EA, Liu H, Ryu E, Wu S, Juhn YJ. Assessment of asthma progression determined by natural language processing to improve asthma care and research in the era of electronic medical records. J Allergy Clin Immunol. 2017;139:AB100.
   Google Scholar
• Afzal Z, Engelkes M, Verhamme KMC, Janssens HM, Sturkenboom MCJM, Kors JA, Schuemie MJ. Automatic generation of case-detection algorithms to identify children with asthma from large electronic health record databases. Pharmacoepidemiol Drug Saf. 2013;22(8):826–833. doi:10.1002/pds.3438.
   PubMed Web of Science ®Google Scholar
• Center for Medicare and Medicaid Services (CMS). General Equivalence Mappings: ICD-9-CM to and from ICD-10-CM and ICD-10-PCS; 2009.
   Google Scholar