ArticleBMC medical informatics and decision making2016
Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database.
Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Using natural language processing to extract information from clinical text in electronic medical records for populating clinical registries: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.Journal of biomedical informatics · 2017Pooled it
- Foundational model aided automatic high-throughput drug screening using self-controlled cohort study.medRxiv : the preprint server for health sciences · 2024Article
- "Take up to eight tablets per day": Incorporating free-text medication instructions into a transparent and reproducible process for preparing drug exposure data for pharmacoepidemiology.Pharmacoepidemiology and drug safety · 2023Article
- Opioid2MME: Standardizing opioid prescriptions to morphine milligram equivalents from electronic health records.International journal of medical informatics · 2022Article
- Evaluating the dose, indication and agreement with guidelines of antimicrobial use in companion animal practice with natural language processing.JAC-antimicrobial resistance · 2022Article
- Prediction of treatment dosage and duration from free-text prescriptions: an application to ADHD medications in the Swedish prescribed drug register.Evidence-based mental health · 2021Article
- The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology.Pharmacoepidemiology and drug safety · 2021Article
- Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study.JMIR medical informatics · 2021Article
- An Interdisciplinary Approach to Reducing Errors in Extracted Electronic Health Record Data for Research.Perspectives in health information managemen · 2021Article
- Big data analysis techniques to address polypharmacy in patients - a scoping review.BMC family practice · 2020Article
- Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper.Journal of medical Internet research · 2020Article
- Article
- A register-based approach to identifying treatment-resistant depression-Comparison with clinical definitions.PloS one · 2020Article
- Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese.Journal of biomedical semantics · 2019Article
- Identifying risks areas related to medication administrations - text mining analysis using free-text descriptions of incident reports.BMC health services research · 2019Article
- Use of text-mining methods to improve efficiency in the calculation of drug exposure to support pharmacoepidemiology studies.International journal of epidemiology · 2018Article
- A Text Structuring Method for Chinese Medical Text Based on Temporal Information.International journal of environmental research and public health · 2018Article
- Clinical Research Informatics: Supporting the Research Study Lifecycle.Yearbook of medical informatics · 2017Review
- The Challenges of Electronic Health Records and Diabetes Electronic Prescribing: Implications for Safety Net Care for Diverse Populations.Journal of diabetes research · 2017Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundFree-text medication prescriptions contain detailed instruction information that is key when preparing drug data for analysis. The objective of this study was to develop a novel model and automated text-mining method to extract detailed structured medication information from free-text prescriptions and explore their variability (e.g. optional dosages) in primary care research databases.
methodsWe introduce a prescription model that provides minimum and maximum values for dose number, frequency and interval, allowing modelling variability and flexibility within a drug prescription. We developed a text mining system that relies on rules to extract such structured information from prescription free-text dosage instructions. The system was applied to medication prescriptions from an anonymised primary care electronic record database (Clinical Practice Research Datalink, CPRD).
resultsWe have evaluated our approach on a test set of 220 CPRD prescription free-text directions. The system achieved an overall accuracy of 91 % at the prescription level, with 97 % accuracy across the attribute levels. We then further analysed over 56,000 most common free text prescriptions from CPRD records and found that 1 in 4 has inherent variability, i.e. a choice in taking medication specified by different minimum and maximum doses, duration or frequency.
conclusionsOur approach provides an accurate, automated way of coding prescription free text information, including information about flexibility and variability within a prescription. The method allows the researcher to decide how best to prepare the prescription data for drug efficacy and safety analyses in any given setting, and test various scenarios and their impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.