Use of text-mining methods to improve efficiency in the calculation of drug exposure to support pharmacoepidemiology studies | Zendy

Stuart McTaggart | Zendy; Clifford Nangle | Zendy; Jacqueline Caldwell | Zendy; Samantha AlvarezMadrazo | Zendy; Helen M. Colhoun | Zendy; Marion Bennie | Zendy

Open Access

Use of text-mining methods to improve efficiency in the calculation of drug exposure to support pharmacoepidemiology studies

Author(s) -

Stuart McTaggart,

Clifford Nangle,

Jacqueline Caldwell,

Samantha AlvarezMadrazo,

Helen M. Colhoun,

Marion Bennie

Publication year - 2017

Publication title -

international journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.406

H-Index - 208

eISSN - 1464-3685

pISSN - 0300-5771

DOI - 10.1093/ije/dyx264

Subject(s) - computer science , pharmacoepidemiology , medical prescription , sample (material) , data mining , test (biology) , flexibility (engineering) , natural language processing , algorithm , medicine , statistics , mathematics , paleontology , chemistry , chromatography , pharmacology , biology

Efficient generation of structured dose instructions that enable researchers to calculate drug exposure is central to pharmacoepidemiology studies. Our aim was to design and test an algorithm to codify dose instructions, applied to the NHS Scotland Prescribing Information System (PIS) that records about 100 million prescriptions per annum.

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