Validity of cerebrovascular ICD-9-CM codes in healthcare administrative databases. The Umbria Data-Value Project

English version

Autoři: Massimiliano Orso ^aff001; Francesco Cozzolino ^aff001; Serena Amici ^aff003; Marcello De Giorgi ^aff004; David Franchini ^aff004; Paolo Eusebi ^aff001; Anna Julia Heymann ^aff005; Guido Lombardo ^aff006; Anna Mengoni ^aff002; Alessandro Montedori ^aff001; Giuseppe Ambrosio ^aff002; Iosief Abraha ^aff001
Působiště autorů: Health Planning Service, Regional Health Authority of Umbria, Perugia, Italy ^aff001; Division of Cardiology, Santa Maria della Misericordia Hospital, University of Perugia School of Medicine, Perugia, Italy ^aff002; Cognitive Disorder and Dementia Unit, USL Umbria, Perugia, Italy ^aff003; Health ICT Service, Regional Health Authority of Umbria, Perugia, Italy ^aff004; Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche, Perugia, Italy ^aff005; Department of Surgical and Biomedical Sciences, University of Perugia, Perugia, Italy ^aff006; Centro Regionale Sangue, Servizio Immunotrasfusionale, Azienda Ospedaliera di Perugia, Perugia, Italy ^aff007
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0227653

Souhrn

Background

Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources.

Methods

We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables.

Results

We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90–99), positive predictive value (PPV) 98% (93–100), negative predictive value (NPV) 100% (95–100); intracerebral hemorrhage: SE 100% (97–100), SP 98% (91–100), PPV 98% (94–100), NPV 100% (95–100); other and unspecified intracranial hemorrhage: SE 100% (97–100), SP 96% (90–99), PPV 98% (93–100), NPV 100% (95–100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94–100), SP 66 (57–75), PPV 70% (61–77), NPV 99% (93–100); occlusion of cerebral arteries: SE 100% (97–100), SP 87% (78–93), PPV 91% (84–95), NPV 100% (95–100); acute, but ill-defined, cerebrovascular disease: SE 100% (97–100), SP 78% (69–86), PPV % 83 (75–89), NPV 100% (95–100).

Conclusions

Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.

Klíčová slova:

Diagnostic medicine – Ischemic stroke – Hemorrhagic stroke – Magnetic resonance imaging – Computed axial tomography – Hemorrhage – Cerebral arteries – Charts

Zdroje

1. Italian National Institute of Statistics. Italy Deaths and Specific Mortality Rates by Age and Year, all Geographical Areas 2015 (accessed 04/12/2018).

2. Stevens E, Emmett E, Wang Y, McKevitt C, Wolfe C. The Burden of Stroke in Europe: Stroke Alliance for Europe; 2017.

3. Sacco S, Stracci F, Cerone D, Ricci S, Carolei A. Epidemiology of stroke in Italy. Int J Stroke. 2011;6(3):219–27. doi: 10.1111/j.1747-4949.2011.00594.x 21557809.

4. Andrade SE, Harrold LR, Tjia J, Cutrona SL, Saczynski JS, Dodd KS, 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 1:100–28. doi: 10.1002/pds.2312 22262598; PubMed Central PMCID: PMC3412674.

5. McCormick N, Bhole V, Lacaille D, Avina-Zubieta JA. Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review. PLoS One. 2015;10(8):e0135834. doi: 10.1371/journal.pone.0135834 26292280; PubMed Central PMCID: PMC4546158.

6. Abraha I, Montedori A, Stracci F, Rossi M, Romagnoli C. Statin compliance in the Umbrian population. European journal of clinical pharmacology. 2003;59(8–9):659–61. doi: 10.1007/s00228-003-0675-2 14508622.

7. Menniti-Ippolito F, Maggini M, Raschetti R, Da Cas R, Traversa G, Walker AM. Ketorolac use in outpatients and gastrointestinal hospitalization: a comparison with other non-steroidal anti-inflammatory drugs in Italy. European journal of clinical pharmacology. 1998;54(5):393–7. doi: 10.1007/s002280050481 9754982.

8. Raschetti R, Maggini M, Da Cas R, Popoli P, Rossi A. Time trends in the coprescribing of cisapride and contraindicated drugs in Umbria, Italy. Jama. 2001;285(14):1840–1. Epub 2001/04/20. doi: 10.1001/jama.285.14.1840 11308395.

9. Traversa G, Bianchi C, Da Cas R, Abraha I, Menniti-Ippolito F, Venegoni M. Cohort study of hepatotoxicity associated with nimesulide and other non-steroidal anti-inflammatory drugs. Bmj. 2003;327(7405):18–22. doi: 10.1136/bmj.327.7405.18 12842950; PubMed Central PMCID: PMC164233.

10. Cozzolino F, Abraha I, Orso M, Mengoni A, Cerasa MF, Eusebi P, et al. Protocol for validating cardiovascular and cerebrovascular ICD-9-CM codes in healthcare administrative databases: the Umbria Data Value Project. BMJ Open. 2017;7(3):e013785. doi: 10.1136/bmjopen-2016-013785 28360241; PubMed Central PMCID: PMC5372118.

11. Connolly ES Jr., Rabinstein AA, Carhuapoma JR, Derdeyn CP, Dion J, Higashida RT, et al. Guidelines for the management of aneurysmal subarachnoid hemorrhage: a guideline for healthcare professionals from the American Heart Association/american Stroke Association. Stroke. 2012;43(6):1711–37. doi: 10.1161/STR.0b013e3182587839 22556195.

12. Hemphill JC 3rd, Greenberg SM, Anderson CS, Becker K, Bendok BR, Cushman M, et al. Guidelines for the Management of Spontaneous Intracerebral Hemorrhage: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke. 2015;46(7):2032–60. doi: 10.1161/STR.0000000000000069 26022637.

13. Jauch EC, Saver JL, Adams HP Jr., Bruno A, Connors JJ, Demaerschalk BM, et al. Guidelines for the early management of patients with acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2013;44(3):870–947. doi: 10.1161/STR.0b013e318284056a 23370205.

14. European Stroke Organisation Executive C, Committee ESOW. Guidelines for management of ischaemic stroke and transient ischaemic attack 2008. Cerebrovasc Dis. 2008;25(5):457–507. doi: 10.1159/000131083 18477843.

15. Wilson EB. Probable Inference, the Law of Succession, and Statistical Inference. Journal of the American Statistical Association. 1927;22(158):209–12. doi: 10.1080/01621459.1927.10502953

16. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. Bmj. 2015;351:h5527. doi: 10.1136/bmj.h5527 26511519; PubMed Central PMCID: PMC4623764.

17. West SL, Ritchey ME, Poole C. Validity of pharmacoepidemiologic drug and diagnosis data. In: Strom BL, Kimmel SE, Hennessy S, eds. Pharmacoepidemiology. Wiley-Blackwell, 2012:757–94.

18. Spolaore P, Brocco S, Fedeli U, Visentin C, Schievano E, Avossa F, et al. Measuring accuracy of discharge diagnoses for a region-wide surveillance of hospitalized strokes. Stroke. 2005;36(5):1031–4. doi: 10.1161/01.STR.0000160755.94884.4a 15790948.

19. Asplund K, Bonita R, Kuulasmaa K, Rajakangas AM, Schaedlich H, Suzuki K, et al. Multinational comparisons of stroke epidemiology. Evaluation of case ascertainment in the WHO MONICA Stroke Study. World Health Organization Monitoring Trends and Determinants in Cardiovascular Disease. Stroke. 1995;26(3):355–60. Epub 1995/03/01. doi: 10.1161/01.str.26.3.355 7886706.

20. Rinaldi R, Vignatelli L, Galeotti M, Azzimondi G, De Carolis P. Accuracy of ICD-9 codes in identifying ischemic stroke in the General Hospital of Lugo di Romagna (Italy). Neurological Sciences. 2003;24(2):65–9. doi: 10.1007/s100720300074 12827541

21. Leone MA, Capponi A, Varrasi C, Tarletti R, Monaco F. Accuracy of the ICD-9 codes for identifying TIA and stroke in an Italian automated database. Neurological Sciences. 2004;25(5):281–8. doi: 10.1007/s10072-004-0355-8 15624086.

22. Reker DM, Hamilton BB, Duncan PW, Yeh SC, Rosen A. Stroke: who's counting what? J Rehabil Res Dev. 2001;38(2):281–9. 11392661.

23. Abraha I, Giovannini G, Serraino D, Fusco M, Montedori A. Validity of breast, lung and colorectal cancer diagnoses in administrative databases: a systematic review protocol. BMJ Open. 2016;6(3):e010409. doi: 10.1136/bmjopen-2015-010409 26993624; PubMed Central PMCID: PMC4800131.

24. Montedori A, Abraha I, Chiatti C, Cozzolino F, Orso M, Luchetta ML, et al. Validity of peptic ulcer disease and upper gastrointestinal bleeding diagnoses in administrative databases: a systematic review protocol. BMJ Open. 2016;6(9):e011776. doi: 10.1136/bmjopen-2016-011776 27633635; PubMed Central PMCID: PMC5030614.

25. Rimland JM, Abraha I, Luchetta ML, Cozzolino F, Orso M, Cherubini A, et al. Validation of chronic obstructive pulmonary disease (COPD) diagnoses in healthcare databases: a systematic review protocol. BMJ Open. 2016;6(6):e011777. doi: 10.1136/bmjopen-2016-011777 27251687; PubMed Central PMCID: PMC4893853.

26. Abraha I, Serraino D, Giovannini G, Stracci F, Casucci P, Alessandrini G, et al. Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocol. BMJ Open. 2016;6(3):e010547. doi: 10.1136/bmjopen-2015-010547 27016247; PubMed Central PMCID: PMC4809074.

27. Cozzolino F, Bidoli E, Abraha I, Fusco M, Giovannini G, Casucci P, et al. Accuracy of colorectal cancer ICD-9-CM codes in Italian administrative healthcare databases: a cross-sectional diagnostic study. BMJ Open. 2018;8(7):e020630. doi: 10.1136/bmjopen-2017-020630 29980543.

28. Montedori A, Bidoli E, Serraino D, Fusco M, Giovannini G, Casucci P, et al. Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study. BMJ Open. 2018;8(5):e020628. doi: 10.1136/bmjopen-2017-020628 29773701; PubMed Central PMCID: PMC5961589.

29. Orso M, Serraino D, Abraha I, Fusco M, Giovannini G, Casucci P, et al. Validating malignant melanoma ICD-9-CM codes in Umbria, ASL Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study. BMJ Open. 2018;8(4):e020631. doi: 10.1136/bmjopen-2017-020631 29678984; PubMed Central PMCID: PMC5914898.

30. Abraha I, Serraino D, Montedori A, Fusco M, Giovannini G, Casucci P, et al. Sensitivity and specificity of breast cancer ICD-9-CM codes in three Italian administrative healthcare databases: a diagnostic accuracy study. BMJ Open. 2018;8(7):e020627. doi: 10.1136/bmjopen-2017-020627 30037866; PubMed Central PMCID: PMC6059298.