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[Use of the PMSI for the detection of adverse drug reactions]

Marie-Noëlle Osmont1, Marc Cuggia, Elisabeth Polard

  • 1Centre régional de Pharmacovigilance, CHU Pontchaillou, Rennes, France.

Therapie
|August 29, 2013
PubMed
Abstract

Insights

International Classification of Diseases 10th version (ICD10) codes in French hospital discharge data can identify serious adverse drug reactions (ADR). This method complements spontaneous reporting for enhanced patient safety.

Area of Science:

  • Pharmacovigilance
  • Health Informatics
  • Drug Safety

Background:

  • Serious adverse drug reactions (ADR) pose a significant public health challenge.
  • Effective methods for detecting ADR are crucial for patient safety and regulatory oversight.
  • Current pharmacovigilance relies heavily on spontaneous reporting, which has limitations.

Purpose of the Study:

  • To assess the utility of International Classification of Diseases 10th version (ICD10) codes within the French hospital discharge database (Programme de médicalisation des systèmes d'information, PMSI) for identifying serious ADR.
  • To evaluate the performance of specific ICD10 codes in detecting ADR.

Main Methods:

  • A query was designed using specific ICD10 codes.
  • The query targeted hospital discharge records from the French University Hospital of Rennes for the year 2009.
  • Hospitalization summaries containing selected ICD10 codes were analyzed to validate potential ADR.

Main Results:

  • Out of 383 identified cases, 142 (37.1%) were validated as serious ADR.
  • Five specific ICD10 codes (T88.6, L27.0, J70.4, G62.0, N14.1) demonstrated performance above 40% and collectively detected 79.5% of the ADR.
  • The ICD10 query identified 22 ADR that were also spontaneously reported during the study period.

Conclusions:

  • The Programme de médicalisation des systèmes d'information (PMSI) database, utilizing ICD10 codes, shows promise as a tool for detecting serious ADR signals.
  • This data-driven approach can serve as a valuable supplement to traditional spontaneous reporting systems for pharmacovigilance.

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