Testing of Coding Algorithms for Inflammatory Bowel Disease Identification, as Indication for Use of Biological Drugs, Using a Claims Database from Southern Italy

Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-market...

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Vydané v:	Clinical epidemiology Ročník 15; s. 309 - 321
Hlavní autori:	Ingrasciotta, Ylenia, Isgrò, Valentina, Foti, Saveria Serena, Ientile, Valentina, Fontana, Andrea, L'Abbate, Luca, Benoni, Roberto, Fiore, Elena Sofia, Tari, Michele, Alibrandi, Angela, Trifirò, Gianluca
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New Zealand Dove Medical Press Limited 01.01.2023 Taylor & Francis Ltd Dove Dove Medical Press
Predmet:	Accuracy Adalimumab algorithm Algorithms Arthritis biological drugs Biological products Chronic diseases Chronic illnesses chron’s disease Clinical medicine Crohn's disease Cross-sectional studies Drug therapy Drugs Epidemiology Health aspects Health care Health care industry healthcare database Hospitals Identification Inflammatory bowel disease Inflammatory diseases Medical coding Medical diagnosis Monoclonal antibodies Original Research Patient admissions Pharmacy Quality of life Rheumatoid arthritis Steroids Tofacitinib Tumor necrosis factor-TNF Ulcerative colitis Canada Italy Europe biological drugs healthcare database Crohn's disease ulcerative colitis algorithm
ISSN:	1179-1349, 1179-1349
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Abstract	Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.
AbstractList	Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use. Background: Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received [greater than or equal to]1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use. Keywords: biological drugs, algorithm, healthcare database, ulcerative colitis, Crohn's disease Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs.BackgroundInflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs.To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database.ObjectiveTo test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database.Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score.MethodsData were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score.In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857).ResultsIn the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857).In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.ConclusionIn a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use. Ylenia Ingrasciotta,1,2 Valentina Isgrò,1 Saveria Serena Foti,2 Valentina Ientile,3 Andrea Fontana,4 Luca L’Abbate,3 Roberto Benoni,1 Elena Sofia Fiore,1 Michele Tari,5 Angela Alibrandi,6 Gianluca Trifirò1,2 1Department of Diagnostics and Public Health, University of Verona, Verona, Italy; 2Academic Spin-off “INSPIRE – Innovative Solutions for Medical Prediction and Big Data Integration in Real World Setting” – Azienda Ospedaliera Universitaria “G. Martino”, Messina, Italy; 3Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 4Unit of Biostatistics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni, Rotondo, Italy; 5Caserta-1 Local Health Service, Caserta, Italy; 6Department of Economics, University of Messina, Messina, ItalyCorrespondence: Ylenia Ingrasciotta, Department of Diagnostics and Public Health, University of Verona, P. le L.A. Scuro 10, Verona, 37134, Italy, Tel +39 045 802 7679, Email ylenia.ingrasciotta@univr.itBackground: Inflammatory bowel diseases (IBDs), Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs.Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database.Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score.Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥ 1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1– 80.5) to 98.8 (95% CI: 93.5– 100.0) for CD and from 64.7% (95% CI: 50.1– 77.6) to 94.1 (95% CI: 83.8– 98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was “Algorithm 3”, based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was “Algorithm 3”, based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857).Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.Keywords: biological drugs, algorithm, healthcare database, ulcerative colitis, Crohn’s disease Background: Inflammatory bowel diseases (IBDs), Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥ 1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1– 80.5) to 98.8 (95% CI: 93.5– 100.0) for CD and from 64.7% (95% CI: 50.1– 77.6) to 94.1 (95% CI: 83.8– 98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was “Algorithm 3”, based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was “Algorithm 3”, based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.
Audience	Academic
Author	Alibrandi, Angela Benoni, Roberto Ingrasciotta, Ylenia Isgrò, Valentina Trifirò, Gianluca Ientile, Valentina Foti, Saveria Serena Tari, Michele Fontana, Andrea Fiore, Elena Sofia L'Abbate, Luca
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BackLink	https://www.ncbi.nlm.nih.gov/pubmed/36936062$$D View this record in MEDLINE/PubMed
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Cites_doi	10.1016/j.dld.2016.12.033 10.1093/oxfordjournals.aje.a009735 10.3109/00365529609031980 10.1016/S0140-6736(17)32448-0 10.1136/gutjnl-2013-304636 10.2147/CEOR.S66338 10.1053/j.gastro.2011.01.055 10.1371/journal.pone.0089072 10.1007/s40264-018-0732-5 10.1016/j.dld.2014.04.014 10.1186/s12882-019-1554-0 10.1542/peds.2008-2306 10.1007/s40259-021-00498-3 10.1007/s40259-015-0132-7 10.1053/j.gastro.2019.01.002 10.1111/jgh.14855 10.1007/s00228-019-02654-9 10.1177/0046958019887816 10.1016/S2468-1253(19)30333-4 10.1002/ibd.21607 10.1002/pds.698 10.1038/s41598-022-20295-4 10.1016/j.jclinepi.2014.02.019 10.1111/jgh.14027 10.14309/ajg.0000000000000152 10.1016/j.cgh.2007.07.012 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3 10.1053/j.gastro.2011.10.001 10.1186/1471-2458-11-688 10.1093/ecco-jcc/jjz180 10.1155/2012/278495 10.1007/s10620-009-1074-z 10.1007/s40259-016-0175-4 10.1186/s12871-015-0165-y 10.19191/EP19.4.S2.P008.089 10.1002/pds.4950 10.1016/j.surg.2018.02.002
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Keywords	biological drugs healthcare database Crohn's disease ulcerative colitis algorithm
Language	English
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References	Thirumurthi (ref18) 2010; 55 Gunaseelan (ref40) 2019; 165 Ingrasciotta (ref25) 2019; 20 Chini (ref37) 2011; 11 Alatab (ref3) 2020; 5 Ingrasciotta (ref23) 2014; 9 Lakatos (ref7) 2011; 17 Kappelman (ref1) 2007; 5 Benchimol (ref17) 2014; 67 Youden (ref29) 1950; 3 Kim (ref38) 2018; 33 Sultana (ref26) 2019; 75 Marcianò (ref14) 2016; 30 Trifirò (ref16) 2021; 35 Lewis (ref32) 2002; 11 Ladha (ref39) 2015; 15 Degli Esposti (ref36) 2014; 18 Lee (ref28) 2020; 35 Burisch (ref6) 2014; 63 Ingrasciotta (ref13) 2015; 29 Di Domenicantonio (ref20) 2014; 46 Lee (ref19) 2020; 29 Galeone (ref9) 2017; 49 ref45 Trifirò (ref12) 2019; 42 Ingrasciotta (ref24) 2015; 29 Bernstein (ref30) 1999; 149 Rubin (ref11) 2019; 114 ref42 ref41 ref44 Cosnes (ref5) 2011; 140 ref43 Ye (ref22) 2019; 56 Romano (ref2) 2008; 122 Ng (ref8) 2017; 390 Molodecky (ref4) 2012; 142 Torres (ref10) 2020; 14 Trifirò (ref15) 2021; 35 Benchimol (ref34) 2014; vol. 67 Rezaie (ref33) 2012; 26 Coward (ref35) 2019; 156 Fonager (ref31) 1996; 31 Canova (ref21) 2019; 43 Crisafulli (ref27) 2022; 12
References_xml	– volume: 49 start-page: 459 year: 2017 ident: ref9 publication-title: Dig Liver Dis doi: 10.1016/j.dld.2016.12.033 – volume: 149 start-page: 916 year: 1999 ident: ref30 publication-title: Am J Epidemiol doi: 10.1093/oxfordjournals.aje.a009735 – volume: 31 start-page: pp. 154 year: 1996 ident: ref31 publication-title: Scand J Gastroenterol doi: 10.3109/00365529609031980 – volume: 390 start-page: 2769 year: 2017 ident: ref8 publication-title: Lancet doi: 10.1016/S0140-6736(17)32448-0 – volume: 63 start-page: 588 year: 2014 ident: ref6 publication-title: Gut doi: 10.1136/gutjnl-2013-304636 – volume: 18 start-page: 401 year: 2014 ident: ref36 publication-title: Clinico Econ Outcomes Res doi: 10.2147/CEOR.S66338 – ident: ref43 – ident: ref45 – volume: 140 start-page: 1785 year: 2011 ident: ref5 publication-title: Gastroenterology doi: 10.1053/j.gastro.2011.01.055 – ident: ref41 – volume: 9 start-page: e89072 year: 2014 ident: ref23 publication-title: PLoS One doi: 10.1371/journal.pone.0089072 – volume: 42 start-page: 347 year: 2019 ident: ref12 publication-title: Drug Saf doi: 10.1007/s40264-018-0732-5 – volume: 46 start-page: 777 year: 2014 ident: ref20 publication-title: Dig Liver Dis doi: 10.1016/j.dld.2014.04.014 – volume: 20 start-page: 359 year: 2019 ident: ref25 publication-title: BMC Nephrol doi: 10.1186/s12882-019-1554-0 – volume: 122 start-page: e1278 year: 2008 ident: ref2 publication-title: Pediatrics doi: 10.1542/peds.2008-2306 – volume: 35 start-page: 749 year: 2021 ident: ref16 publication-title: BioDrugs doi: 10.1007/s40259-021-00498-3 – volume: 29 start-page: 275 year: 2015 ident: ref24 publication-title: BioDrugs doi: 10.1007/s40259-015-0132-7 – volume: 156 start-page: 1345 year: 2019 ident: ref35 publication-title: Gastroenterology doi: 10.1053/j.gastro.2019.01.002 – volume: 35 start-page: 760 year: 2020 ident: ref28 publication-title: J Gastroenterol Hepatol doi: 10.1111/jgh.14855 – volume: 75 start-page: 1005 year: 2019 ident: ref26 publication-title: Eur J Clin Pharmacol doi: 10.1007/s00228-019-02654-9 – volume: 56 start-page: 46958019887816 year: 2019 ident: ref22 publication-title: Inquiry doi: 10.1177/0046958019887816 – volume: 5 start-page: 17 year: 2020 ident: ref3 publication-title: Lancet Gastroenterol Hepatol doi: 10.1016/S2468-1253(19)30333-4 – volume: 17 start-page: 2558 year: 2011 ident: ref7 publication-title: Inflamm Bowel Dis doi: 10.1002/ibd.21607 – volume: 11 start-page: pp. 211 year: 2002 ident: ref32 publication-title: Pharmacoepidemiol Drug Saf doi: 10.1002/pds.698 – volume: 12 start-page: 15843 year: 2022 ident: ref27 publication-title: Sci Rep doi: 10.1038/s41598-022-20295-4 – volume: vol. 67 start-page: 887 year: 2014 ident: ref34 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2014.02.019 – volume: 33 start-page: 847 year: 2018 ident: ref38 publication-title: J Gastroenterol Hepatol doi: 10.1111/jgh.14027 – volume: 114 start-page: 384 year: 2019 ident: ref11 publication-title: Am J Gastroenterol doi: 10.14309/ajg.0000000000000152 – ident: ref44 – volume: 5 start-page: 1424 year: 2007 ident: ref1 publication-title: Clin Gastroenterol Hepatol doi: 10.1016/j.cgh.2007.07.012 – volume: 3 start-page: 32 year: 1950 ident: ref29 publication-title: Cancer doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3 – volume: 142 start-page: 46 year: 2012 ident: ref4 publication-title: Gastroenterology doi: 10.1053/j.gastro.2011.10.001 – volume: 29 start-page: 275 year: 2015 ident: ref13 publication-title: BioDrugs doi: 10.1007/s40259-015-0132-7 – volume: 11 start-page: 688 year: 2011 ident: ref37 publication-title: BMC Public Health doi: 10.1186/1471-2458-11-688 – volume: 14 start-page: 4 year: 2020 ident: ref10 publication-title: J Crohns Colitis doi: 10.1093/ecco-jcc/jjz180 – ident: ref42 – volume: 26 start-page: 711 year: 2012 ident: ref33 publication-title: Can J Gastroenterol doi: 10.1155/2012/278495 – volume: 67 start-page: 887 year: 2014 ident: ref17 publication-title: J Clin Epidemiol doi: 10.1016/j.jclinepi.2014.02.019 – volume: 55 start-page: 2592 year: 2010 ident: ref18 publication-title: Dig Dis Sci doi: 10.1007/s10620-009-1074-z – volume: 30 start-page: 295 year: 2016 ident: ref14 publication-title: BioDrugs doi: 10.1007/s40259-016-0175-4 – volume: 15 start-page: 179 year: 2015 ident: ref39 publication-title: BMC Anesthesiol doi: 10.1186/s12871-015-0165-y – volume: 43 start-page: 8 year: 2019 ident: ref21 publication-title: Epidemiol Prev doi: 10.19191/EP19.4.S2.P008.089 – volume: 29 start-page: 404 year: 2020 ident: ref19 publication-title: Pharmacoepidemiol Drug Saf doi: 10.1002/pds.4950 – volume: 165 start-page: 669 year: 2019 ident: ref40 publication-title: Surgery doi: 10.1016/j.surg.2018.02.002 – volume: 35 start-page: 749 year: 2021 ident: ref15 publication-title: BioDrugs doi: 10.1007/s40259-021-00498-3
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Snippet	Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological... Background: Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with... Background: Inflammatory bowel diseases (IBDs), Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with... Ylenia Ingrasciotta,1,2 Valentina Isgrò,1 Saveria Serena Foti,2 Valentina Ientile,3 Andrea Fontana,4 Luca L’Abbate,3 Roberto Benoni,1 Elena Sofia Fiore,1...
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SubjectTerms	Accuracy Adalimumab algorithm Algorithms Arthritis biological drugs Biological products Chronic diseases Chronic illnesses chron’s disease Clinical medicine Crohn's disease Cross-sectional studies Drug therapy Drugs Epidemiology Health aspects Health care Health care industry healthcare database Hospitals Identification Inflammatory bowel disease Inflammatory diseases Medical coding Medical diagnosis Monoclonal antibodies Original Research Patient admissions Pharmacy Quality of life Rheumatoid arthritis Steroids Tofacitinib Tumor necrosis factor-TNF Ulcerative colitis
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Title	Testing of Coding Algorithms for Inflammatory Bowel Disease Identification, as Indication for Use of Biological Drugs, Using a Claims Database from Southern Italy
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