Neurological Sciences

, Volume 36, Issue 5, pp 783–786 | Cite as

Reliability of administrative data for the identification of Parkinson’s disease cohorts

  • Filippo Baldacci
  • Laura Policardo
  • Simone Rossi
  • Monica Ulivelli
  • Silvia Ramat
  • Enrico Grassi
  • Pasquale Palumbo
  • Fabio Giovannelli
  • Massimo Cincotta
  • Roberto Ceravolo
  • Sandro Sorbi
  • Paolo Francesconi
  • Ubaldo Bonuccelli
Brief Communication

Abstract

Parkinson’s disease (PD) is a major worldwide public health problem with a prevalence that is expected to increase dramatically in the coming decades. Because administrative data are useful for epidemiologic and health service studies, we aimed to define procedural algorithms to identify PD patients (on a regional basis) using these data. We built two a priori algorithms, respecting privacy laws, with increasing theoretical specificity for PD including: (1) a hospital discharge diagnosis of PD; (2) PD-specific exemption; (3) a minimum of two separate prescriptions of an antiparkinsonian drug. The two algorithms differed for drugs included. Sensitivities were tested on an opportunistic sample of 319 PD patients from the databases of 5 regional movement disorders clinics. The estimated prevalence of PD in the sample population from Tuscany was 0.49 % for algorithm 1 and 0.28 % for algorithm 2. Algorithm 1 correctly identified 291 PD patients (sensitivity 91.2 %), and algorithm 2 identified 242 PD patients (sensitivity 75.9 %). We developed two reproducible algorithms demonstrating increasing theoretical specificity with good sensitivity in identifying PD patients based on an evaluation of administrative data. This may represent a low-cost strategy to reliably follow up a large number of PD patients as a whole for evaluating the effects of therapies, disease progression and prevalence.

Keywords

Administrative data Algorithm Antiparkinsonian drug Disease identification ICD-9-CM Parkinson’s disease 

Supplementary material

10072_2015_2062_MOESM1_ESM.doc (40 kb)
Supplementary material 1 (DOC 40 kb)

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Copyright information

© Springer-Verlag Italia 2015

Authors and Affiliations

  • Filippo Baldacci
    • 1
  • Laura Policardo
    • 2
  • Simone Rossi
    • 3
  • Monica Ulivelli
    • 3
  • Silvia Ramat
    • 4
  • Enrico Grassi
    • 5
  • Pasquale Palumbo
    • 5
  • Fabio Giovannelli
    • 6
  • Massimo Cincotta
    • 6
  • Roberto Ceravolo
    • 1
  • Sandro Sorbi
    • 7
  • Paolo Francesconi
    • 2
  • Ubaldo Bonuccelli
    • 1
  1. 1.Department of Clinical and Experimental Medicine, Neurology UnitUniversity of PisaPisaItaly
  2. 2.Agenzia Regionale Sanità della ToscanaFlorenceItaly
  3. 3.Department of Neuroscience, Neurology and Clinical Neurophysiology SectionUniversity of SienaSienaItaly
  4. 4.Department of NeuroscienceCareggi HospitalFlorenceItaly
  5. 5.Neurology UnitPrato HospitalPratoItaly
  6. 6.Neurology Unit, Florence Health AuthoritySan Giovanni di Dio HospitalFlorenceItaly
  7. 7.Department of Neurological and Psychiatric ScienceUniversity of FlorenceFlorenceItaly

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