Diabetes (Diagnostic Code)

Ellie Paige, Jessica Barret, David Stevens, Ruth H Keogh, Michael J Sweeting, Irwin Nazareth, Irene Peterson, Angela M Wood

PH895 / 1869 Clinical-Coded Phenotype

  1. Overview

    Phenotype Type
    Disease or syndrome
    Sex
    Both
    Valid Event Date Range
    01/01/1997 - 18/01/2016
    Coding System
    Read codes v2
    Data Sources
    Collections
    ClinicalCodes RepositoryPhenotype Library
    Tags
    No data
  2. Definition

    The benefits of using electronic health records (EHRs) for disease risk screening and personalized health-care decisions are being increasingly recognized. Here we present a computationally feasible statistical approach with which to address the methodological challenges involved in utilizing historical repeat measures of multiple risk factors recorded in EHRs to systematically identify patients at high risk of future disease. The approach is principally based on a 2-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements via landmark-age–specific multivariate linear mixed-effects models with correlated random intercepts, which account for sporadically recorded repeat measures, unobserved data, and measurement errors. The second stage predicts future disease risk from a sex-stratified Cox proportional hazardsmodel, with estimated current risk factor values from the first stage.We exemplify thesemethods by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using primary-care EHRs for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol in 41,373 persons from 10 primary-care practices in England andWales contributing to The Health Improvement Network (1997–2016). Using cross-validation, the model was well-calibrated (Brier score = 0.041, 95% confidence interval: 0.039, 0.042) and had good discrimination (C-index = 0.768, 95%confidence interval: 0.759, 0.777).

  3. Implementation

    Implementation

    No data
  4. Clinical Code List

  5. Publication

    • Ellie Paige, Jessica Barret, David Stevens, Ruth H Keogh, Michael J Sweeting, Irwin Nazareth, Irene Peterson, Angela M Wood, Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk. American Journal of Epidemiology, 187(7): 1530-1538, 2018.

    Citation Example

    Ellie Paige, Jessica Barret, David Stevens, Ruth H Keogh, Michael J Sweeting, Irwin Nazareth, Irene Peterson, Angela M Wood. PH895 / 1869 - Diabetes (Diagnostic Code). Phenotype Library [Online]. 04 April 2022. Available from: http://phenotypes.healthdatagateway.org/phenotypes/PH895/version/1869/detail/. [Accessed 15 June 2024]

  6. API

    To Export Phenotype Details:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH895/version/1869/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(
     'PH895',
     version_id=1869
    )

    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(
     'PH895',
     version_id=1869
    )

    To Export Phenotype Code List:

    FormatAPI
    JSON site_root/api/v1/phenotypes/PH895/version/1869/export/codes/?format=json
    CSV site_root/phenotypes/PH895/version/1869/export/codes/
    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(
     'PH895',
     version_id=1869
    )

    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(
     'PH895',
     version_id=1869
    )

  7. Version History

    Version IDNameOwnerPublish date
    1869 Diabetes (Diagnostic Code) ieuan.scanlon2022-04-04currently shown