Validation of healthcare administrative data for the diagnosis of epilepsy

C. Franchi, G. Giussani, P. Messina, M. Montesano, S. Romi, A. Nobili, I. Fortino, A. Bortolotti, L. Merlino, E. Beghi, Elio Agostoni, Francesco Basso, Andrea Rigamonti, Lorenzo Stanzani, Ottaviano Martinelli, Cristina Volpe, Marialuisa Carpanelli, Andrea Magnoni, Larissa Airoldi, Mariolina Di StefanoClaudio Zucca, Nicoletta Zanotta, Pietro Baccomo, Giancarlo Balestra, Bergamini Massimo, Marcellino Bianchi, Edoardo Giovanni Bolis, Rosalia Cavenago, Mario Crotta, Marco Coduri, Katerina Tinterova, Alberto Palazzuolo, Patrizia Daielli, Valeria Mazzoleni, Anna Villella

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

Background Administrative databases have become an important tool to monitor diseases. Patients with epilepsy could be traced using disease-specific codes and prescriptions, but formal validation is required to obtain an accurate case definition. The aim of the study was to correlate administrative data on epilepsy with an independent source of patients with epilepsy in a district of Lombardy, Northern Italy, from 2000 to 2008. Methods Data of nearly 320 600 inhabitants in the district of Lecco collected from the Drug Administrative Database of the Lombardy Region were analysed. Among them were included patients who fulfilled the International Classification of Diseases 9 (ICD-9) codes and/or the disease-specific exemption code for epilepsy and those who had at least one EEG record and took antiepileptic drugs (AEDs) as monotherapy or in variable combinations. To ascertain epilepsy cases, 11 general practitioners (GPs) with 15 728 affiliates were contacted. Multiple versions of the diagnostic algorithm were developed using different logistic regression models and all combinations of the four independent variables. Results Among the GP affiliates, 71 (4.5/1000) had a gold standard diagnosis of epilepsy. The best and most conservative algorithm included EEG and selected treatment schedules and identified 61/71 patients with epilepsy (sensitivity 85.9%, CI 76.0% to 92.2%) and 15 623/15 657 patients without epilepsy (specificity 99.8%,CI 99.7% to 99.8%). The positive and negative predictive values were 64.2% and 99.9%. Sensitivity (86.7%) and the positive predictive value (68.4%) increased only slightly when patients with single seizures were included. Conclusions A diagnostic algorithm including EEG and selected treatment schedules is only moderately sensitive for the detection of epilepsy and seizures. These findings apply only to the Northern Italian scenario.

Original languageEnglish
Pages (from-to)1019-1024
Number of pages6
JournalJournal of Epidemiology and Community Health
Volume67
Issue number12
DOIs
Publication statusPublished - 2013

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Epilepsy
Delivery of Health Care
Electroencephalography
General Practitioners
Appointments and Schedules
Logistic Models
Pharmaceutical Databases
International Classification of Diseases
Anticonvulsants
Italy
Prescriptions
Seizures
Databases
Therapeutics

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Epidemiology

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Validation of healthcare administrative data for the diagnosis of epilepsy. / Franchi, C.; Giussani, G.; Messina, P.; Montesano, M.; Romi, S.; Nobili, A.; Fortino, I.; Bortolotti, A.; Merlino, L.; Beghi, E.; Agostoni, Elio; Basso, Francesco; Rigamonti, Andrea; Stanzani, Lorenzo; Martinelli, Ottaviano; Volpe, Cristina; Carpanelli, Marialuisa; Magnoni, Andrea; Airoldi, Larissa; Stefano, Mariolina Di; Zucca, Claudio; Zanotta, Nicoletta; Baccomo, Pietro; Balestra, Giancarlo; Massimo, Bergamini; Bianchi, Marcellino; Bolis, Edoardo Giovanni; Cavenago, Rosalia; Crotta, Mario; Coduri, Marco; Tinterova, Katerina; Palazzuolo, Alberto; Daielli, Patrizia; Mazzoleni, Valeria; Villella, Anna.

In: Journal of Epidemiology and Community Health, Vol. 67, No. 12, 2013, p. 1019-1024.

Research output: Contribution to journalArticle

Franchi, C, Giussani, G, Messina, P, Montesano, M, Romi, S, Nobili, A, Fortino, I, Bortolotti, A, Merlino, L, Beghi, E, Agostoni, E, Basso, F, Rigamonti, A, Stanzani, L, Martinelli, O, Volpe, C, Carpanelli, M, Magnoni, A, Airoldi, L, Stefano, MD, Zucca, C, Zanotta, N, Baccomo, P, Balestra, G, Massimo, B, Bianchi, M, Bolis, EG, Cavenago, R, Crotta, M, Coduri, M, Tinterova, K, Palazzuolo, A, Daielli, P, Mazzoleni, V & Villella, A 2013, 'Validation of healthcare administrative data for the diagnosis of epilepsy', Journal of Epidemiology and Community Health, vol. 67, no. 12, pp. 1019-1024. https://doi.org/10.1136/jech-2013-202528
Franchi, C. ; Giussani, G. ; Messina, P. ; Montesano, M. ; Romi, S. ; Nobili, A. ; Fortino, I. ; Bortolotti, A. ; Merlino, L. ; Beghi, E. ; Agostoni, Elio ; Basso, Francesco ; Rigamonti, Andrea ; Stanzani, Lorenzo ; Martinelli, Ottaviano ; Volpe, Cristina ; Carpanelli, Marialuisa ; Magnoni, Andrea ; Airoldi, Larissa ; Stefano, Mariolina Di ; Zucca, Claudio ; Zanotta, Nicoletta ; Baccomo, Pietro ; Balestra, Giancarlo ; Massimo, Bergamini ; Bianchi, Marcellino ; Bolis, Edoardo Giovanni ; Cavenago, Rosalia ; Crotta, Mario ; Coduri, Marco ; Tinterova, Katerina ; Palazzuolo, Alberto ; Daielli, Patrizia ; Mazzoleni, Valeria ; Villella, Anna. / Validation of healthcare administrative data for the diagnosis of epilepsy. In: Journal of Epidemiology and Community Health. 2013 ; Vol. 67, No. 12. pp. 1019-1024.
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title = "Validation of healthcare administrative data for the diagnosis of epilepsy",
abstract = "Background Administrative databases have become an important tool to monitor diseases. Patients with epilepsy could be traced using disease-specific codes and prescriptions, but formal validation is required to obtain an accurate case definition. The aim of the study was to correlate administrative data on epilepsy with an independent source of patients with epilepsy in a district of Lombardy, Northern Italy, from 2000 to 2008. Methods Data of nearly 320 600 inhabitants in the district of Lecco collected from the Drug Administrative Database of the Lombardy Region were analysed. Among them were included patients who fulfilled the International Classification of Diseases 9 (ICD-9) codes and/or the disease-specific exemption code for epilepsy and those who had at least one EEG record and took antiepileptic drugs (AEDs) as monotherapy or in variable combinations. To ascertain epilepsy cases, 11 general practitioners (GPs) with 15 728 affiliates were contacted. Multiple versions of the diagnostic algorithm were developed using different logistic regression models and all combinations of the four independent variables. Results Among the GP affiliates, 71 (4.5/1000) had a gold standard diagnosis of epilepsy. The best and most conservative algorithm included EEG and selected treatment schedules and identified 61/71 patients with epilepsy (sensitivity 85.9{\%}, CI 76.0{\%} to 92.2{\%}) and 15 623/15 657 patients without epilepsy (specificity 99.8{\%},CI 99.7{\%} to 99.8{\%}). The positive and negative predictive values were 64.2{\%} and 99.9{\%}. Sensitivity (86.7{\%}) and the positive predictive value (68.4{\%}) increased only slightly when patients with single seizures were included. Conclusions A diagnostic algorithm including EEG and selected treatment schedules is only moderately sensitive for the detection of epilepsy and seizures. These findings apply only to the Northern Italian scenario.",
author = "C. Franchi and G. Giussani and P. Messina and M. Montesano and S. Romi and A. Nobili and I. Fortino and A. Bortolotti and L. Merlino and E. Beghi and Elio Agostoni and Francesco Basso and Andrea Rigamonti and Lorenzo Stanzani and Ottaviano Martinelli and Cristina Volpe and Marialuisa Carpanelli and Andrea Magnoni and Larissa Airoldi and Stefano, {Mariolina Di} and Claudio Zucca and Nicoletta Zanotta and Pietro Baccomo and Giancarlo Balestra and Bergamini Massimo and Marcellino Bianchi and Bolis, {Edoardo Giovanni} and Rosalia Cavenago and Mario Crotta and Marco Coduri and Katerina Tinterova and Alberto Palazzuolo and Patrizia Daielli and Valeria Mazzoleni and Anna Villella",
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TY - JOUR

T1 - Validation of healthcare administrative data for the diagnosis of epilepsy

AU - Franchi, C.

AU - Giussani, G.

AU - Messina, P.

AU - Montesano, M.

AU - Romi, S.

AU - Nobili, A.

AU - Fortino, I.

AU - Bortolotti, A.

AU - Merlino, L.

AU - Beghi, E.

AU - Agostoni, Elio

AU - Basso, Francesco

AU - Rigamonti, Andrea

AU - Stanzani, Lorenzo

AU - Martinelli, Ottaviano

AU - Volpe, Cristina

AU - Carpanelli, Marialuisa

AU - Magnoni, Andrea

AU - Airoldi, Larissa

AU - Stefano, Mariolina Di

AU - Zucca, Claudio

AU - Zanotta, Nicoletta

AU - Baccomo, Pietro

AU - Balestra, Giancarlo

AU - Massimo, Bergamini

AU - Bianchi, Marcellino

AU - Bolis, Edoardo Giovanni

AU - Cavenago, Rosalia

AU - Crotta, Mario

AU - Coduri, Marco

AU - Tinterova, Katerina

AU - Palazzuolo, Alberto

AU - Daielli, Patrizia

AU - Mazzoleni, Valeria

AU - Villella, Anna

PY - 2013

Y1 - 2013

N2 - Background Administrative databases have become an important tool to monitor diseases. Patients with epilepsy could be traced using disease-specific codes and prescriptions, but formal validation is required to obtain an accurate case definition. The aim of the study was to correlate administrative data on epilepsy with an independent source of patients with epilepsy in a district of Lombardy, Northern Italy, from 2000 to 2008. Methods Data of nearly 320 600 inhabitants in the district of Lecco collected from the Drug Administrative Database of the Lombardy Region were analysed. Among them were included patients who fulfilled the International Classification of Diseases 9 (ICD-9) codes and/or the disease-specific exemption code for epilepsy and those who had at least one EEG record and took antiepileptic drugs (AEDs) as monotherapy or in variable combinations. To ascertain epilepsy cases, 11 general practitioners (GPs) with 15 728 affiliates were contacted. Multiple versions of the diagnostic algorithm were developed using different logistic regression models and all combinations of the four independent variables. Results Among the GP affiliates, 71 (4.5/1000) had a gold standard diagnosis of epilepsy. The best and most conservative algorithm included EEG and selected treatment schedules and identified 61/71 patients with epilepsy (sensitivity 85.9%, CI 76.0% to 92.2%) and 15 623/15 657 patients without epilepsy (specificity 99.8%,CI 99.7% to 99.8%). The positive and negative predictive values were 64.2% and 99.9%. Sensitivity (86.7%) and the positive predictive value (68.4%) increased only slightly when patients with single seizures were included. Conclusions A diagnostic algorithm including EEG and selected treatment schedules is only moderately sensitive for the detection of epilepsy and seizures. These findings apply only to the Northern Italian scenario.

AB - Background Administrative databases have become an important tool to monitor diseases. Patients with epilepsy could be traced using disease-specific codes and prescriptions, but formal validation is required to obtain an accurate case definition. The aim of the study was to correlate administrative data on epilepsy with an independent source of patients with epilepsy in a district of Lombardy, Northern Italy, from 2000 to 2008. Methods Data of nearly 320 600 inhabitants in the district of Lecco collected from the Drug Administrative Database of the Lombardy Region were analysed. Among them were included patients who fulfilled the International Classification of Diseases 9 (ICD-9) codes and/or the disease-specific exemption code for epilepsy and those who had at least one EEG record and took antiepileptic drugs (AEDs) as monotherapy or in variable combinations. To ascertain epilepsy cases, 11 general practitioners (GPs) with 15 728 affiliates were contacted. Multiple versions of the diagnostic algorithm were developed using different logistic regression models and all combinations of the four independent variables. Results Among the GP affiliates, 71 (4.5/1000) had a gold standard diagnosis of epilepsy. The best and most conservative algorithm included EEG and selected treatment schedules and identified 61/71 patients with epilepsy (sensitivity 85.9%, CI 76.0% to 92.2%) and 15 623/15 657 patients without epilepsy (specificity 99.8%,CI 99.7% to 99.8%). The positive and negative predictive values were 64.2% and 99.9%. Sensitivity (86.7%) and the positive predictive value (68.4%) increased only slightly when patients with single seizures were included. Conclusions A diagnostic algorithm including EEG and selected treatment schedules is only moderately sensitive for the detection of epilepsy and seizures. These findings apply only to the Northern Italian scenario.

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U2 - 10.1136/jech-2013-202528

DO - 10.1136/jech-2013-202528

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