TY - JOUR
T1 - Identifying Relapses in Multiple Sclerosis Patients through Administrative Data
T2 - A Validation Study in the Lazio Region, Italy
AU - Colais, Paola
AU - Agabiti, Nera
AU - Davoli, Marina
AU - Buttari, Fabio
AU - Centonze, Diego
AU - De Fino, Chiara
AU - Di Folco, Marta
AU - Filippini, Graziella
AU - Francia, Ada
AU - Galgani, Simonetta
AU - Gasperini, Claudio
AU - Giuliani, Manuela
AU - Mirabella, Massimiliano
AU - Nociti, Viviana
AU - Pozzilli, Carlo
AU - Bargagli, Anna Maria
PY - 2017/8
Y1 - 2017/8
N2 - Background: Relapse is frequently considered an outcome measure of disease activity in relapsing-remitting multiple sclerosis (MS). The objectives of this study were to identify relapse episodes in patients with MS in the Lazio region using health administrative databases and to evaluate the validity of the algorithm using patients enrolled at MS treatment centers. Methods: MS cases were identified in the period between January 1, 2006 and December 31, 2009 using data from regional Health Information Systems (HIS). An algorithm based on HIS was used to identify relapse episodes, and patients recruited at MS centers were used to validate the algorithm. Positive and negative predictive values (PPV, NPV) and the Cohen's kappa coefficient were calculated. Results: The overall MS population identified through HIS consisted of 6,094 patients, of whom 67.1% were female and the mean age was 41.5. Among the MS patients identified by the algorithm, 2,242 attended the centers and 3,852 did not. The PPV was 58.9%, the NPV was 76.3%, and the kappa was 0.36. Conclusions: The proposed algorithm based on health administrative databases does not seem to be able to reliably detect relapses; however, it may be a helpful tool to detect healthcare utilization, and therefore to identify the worsening condition of a patient's health.
AB - Background: Relapse is frequently considered an outcome measure of disease activity in relapsing-remitting multiple sclerosis (MS). The objectives of this study were to identify relapse episodes in patients with MS in the Lazio region using health administrative databases and to evaluate the validity of the algorithm using patients enrolled at MS treatment centers. Methods: MS cases were identified in the period between January 1, 2006 and December 31, 2009 using data from regional Health Information Systems (HIS). An algorithm based on HIS was used to identify relapse episodes, and patients recruited at MS centers were used to validate the algorithm. Positive and negative predictive values (PPV, NPV) and the Cohen's kappa coefficient were calculated. Results: The overall MS population identified through HIS consisted of 6,094 patients, of whom 67.1% were female and the mean age was 41.5. Among the MS patients identified by the algorithm, 2,242 attended the centers and 3,852 did not. The PPV was 58.9%, the NPV was 76.3%, and the kappa was 0.36. Conclusions: The proposed algorithm based on health administrative databases does not seem to be able to reliably detect relapses; however, it may be a helpful tool to detect healthcare utilization, and therefore to identify the worsening condition of a patient's health.
KW - Administrative data
KW - Algorithm
KW - Health information systems
KW - Multiple sclerosis
KW - Relapse
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U2 - 10.1159/000479515
DO - 10.1159/000479515
M3 - Article
AN - SCOPUS:85027099040
SP - 171
EP - 178
JO - Neuroepidemiology
JF - Neuroepidemiology
SN - 0251-5350
ER -