Lft Fbc (M3)

S Jill Stocks, Evangelos Kontopantelis, Artur Akbarov, Sarah Rodgers, Anthony J Avery, Darren M Aschroft

PH665 / 1330 Clinical-Coded Phenotype

  1. Overview

    Phenotype Type
    Biomarker
    Sex
    Both
    Valid Event Date Range
    Start - 01/02/2013
    Coding System
    Read codes v2
    Data Sources
    CPRD GOLD
    Collections
    ClinicalCodes RepositoryPhenotype Library
    Tags
    No data
    Ontology
    No data

  2. Definition

    Study question:

    What is the prevalence of different types of potentially hazardous prescribing in general practice in the United Kingdom, and what is the variation between practices?

    Methods:

    A cross sectional study included all adult patients potentially at risk of a prescribing or monitoring error defined by a combination of diagnoses and prescriptions in 526 general practices contributing to the Clinical Practice Research Datalink (CPRD) up to 1 April 2013. Primary outcomes were the prevalence of potentially hazardous prescriptions of anticoagulants, anti-platelets, NSAIDs, β blockers, glitazones, metformin, digoxin, antipsychotics, combined hormonal contraceptives, and oestrogens and monitoring by blood test less frequently than recommended for patients with repeated prescriptions of angiotensin converting enzyme inhibitors and loop diuretics, amiodarone, methotrexate, lithium, or warfarin.

    Study answer and limitations:

    49 927 of 949 552 patients at risk triggered at least one prescribing indicator (5.26%, 95% confidence interval 5.21% to 5.30%) and 21 501 of 182 721 (11.8%, 11.6% to 11.9%) triggered at least one monitoring indicator. The prevalence of different types of potentially hazardous prescribing ranged from almost zero to 10.2%, and for inadequate monitoring ranged from 10.4% to 41.9%. Older patients and those prescribed multiple repeat medications had significantly higher risks of triggering a prescribing indicator whereas younger patients with fewer repeat prescriptions had significantly higher risk of triggering a monitoring indicator. There was high variation between practices for some indicators. Though prescribing safety indicators describe prescribing patterns that can increase the risk of harm to the patient and should generally be avoided, there will always be exceptions where the indicator is clinically justified. Furthermore there is the possibility that some information is not captured by CPRD for some practices—for example, INR results in patients receiving warfarin.

    What this study adds:

    The high prevalence for certain indicators emphasises existing prescribing risks and the need for their appropriate consideration within primary care, particularly for older patients and those taking multiple medications. The high variation between practices indicates potential for improvement through targeted practice level intervention.

  3. Implementation

    Implementation

    No data

  4. Clinical Code List

  5. Publication

    Related publications

    • S Jill Stocks, Evangelos Kontopantelis, Artur Akbarov, Sarah Rodgers, Anthony J Avery, Darren M Ashcroft, Examining variations in prescribing safety in UK general practice cross sectional study using the Clinical Practice Research Datalink. BMJ, 351(h5501), 2015.

    Citation Example

    S Jill Stocks, Evangelos Kontopantelis, Artur Akbarov, Sarah Rodgers, Anthony J Avery, Darren M Aschroft. PH665 / 1330 - Lft Fbc (M3). Phenotype Library [Online]. 06 October 2021. Available from: http://phenotypes.healthdatagateway.org/phenotypes/PH665/version/1330/detail/. [Accessed 25 April 2025]

  6. API

    To Export Phenotype Details:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH665/version/1330/detail/?format=json
    R Package

    # Download here

    library(ConceptLibraryClient)


    # Connect to API

    client = ConceptLibraryClient::Connection$new(public=TRUE)


    # Get details of phenotype

    phenotype_details = client$phenotypes$get_detail(
     'PH665',
     version_id=1330
    )

    Py Package

    # Download here

    from pyconceptlibraryclient import Client


    # Connect to API

    client = Client(public=True)


    # Get codelist of phenotype

    phenotype_codelist = client.phenotypes.get_detail(
     'PH665',
     version_id=1330
    )

    To Export Phenotype Code List:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH665/version/1330/export/codes/?format=json
    R Package

    # Download here

    library(ConceptLibraryClient)


    # Connect to API

    client = ConceptLibraryClient::Connection$new(public=TRUE)


    # Get codelist of phenotype

    phenotype_codelist = client$phenotypes$get_codelist(
     'PH665',
     version_id=1330
    )

    Py Package

    # Download here

    from pyconceptlibraryclient import Client


    # Connect to API

    client = Client(public=True)


    # Get codelist of phenotype

    phenotype_codelist = client.phenotypes.get_codelist(
     'PH665',
     version_id=1330
    )

  7. Version History

    Version IDNameOwnerPublish date
    Lft Fbc (M3) ieuan.scanlon2021-10-06 16:29