A Text-Mining Algorithm for Identifying Drug Pairs Potentially Involved in Prescribing Cascades: Development and Internal Validation Within the Prescribing Inappropriateness Assessment (PINA) Digital Tool - Takeaways - MDSpire
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An Algorithm for Text Mining to Detect Potential Drug Pair Interactions in Prescribing Cascades: Development and Internal Validation Using the Prescribing Inappropriateness Assessment (PINA) Tool

  • By

  • Massimo Carollo

  • Anna Forti

  • Salvatore Crisafulli

  • Luca L’Abbate

  • Irene Cristini

  • Federica Soardo

  • Marilisa Giustina Stano

  • David Bellantuono

  • Davide Benetti

  • Riccardo Lora

  • Gianluca Trifirò

  • September 19, 2026

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  • 1

    An algorithm was developed to identify drug pairs potentially representing prescribing cascades during medication review.

  • 2

    Internal validation indicated the algorithm produced few spurious matches, enhancing detection of drug pairs supported by literature.

  • 3

    The tool prioritizes candidate drug pairs for clinical assessment but does not confirm prescribing cascades or initiate deprescribing.

  • 4

    PINA software is designed to assist healthcare professionals with structured medication reviews in patients exposed to polypharmacy.

  • 5

    The algorithm analyzes adverse drug reactions and therapeutic indications to report candidate drug pairs potentially compatible with prescribing cascades.

Original Source(s)

A Text-Mining Algorithm for Identifying Drug Pairs Potentially Involved in Prescribing Cascades: Development and Internal Validation Within the Prescribing Inappropriateness Assessment (PINA) Digital Tool

  • by Massimo Carollo, Anna Forti, Salvatore Crisafulli, Luca L’Abbate, Irene Cristini, Federica Soardo, Marilisa Giustina Stano, David Bellantuono, Davide Benetti, Riccardo Lora, Gianluca Trifirò

  • September 19, 2026

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