Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Filters applied. Clear all
. 2016 Oct 12;8:373-380.
doi: 10.2147/CLEP.S113415. eCollection 2016.

An Algorithm for Identification and Classification of Individuals With Type 1 and Type 2 Diabetes Mellitus in a Large Primary Care Database

Affiliations
Free PMC article

An Algorithm for Identification and Classification of Individuals With Type 1 and Type 2 Diabetes Mellitus in a Large Primary Care Database

Manuj Sharma et al. Clin Epidemiol. .
Free PMC article

Abstract

Background: Research into diabetes mellitus (DM) often requires a reproducible method for identifying and distinguishing individuals with type 1 DM (T1DM) and type 2 DM (T2DM).

Objectives: To develop a method to identify individuals with T1DM and T2DM using UK primary care electronic health records.

Methods: Using data from The Health Improvement Network primary care database, we developed a two-step algorithm. The first algorithm step identified individuals with potential T1DM or T2DM based on diagnostic records, treatment, and clinical test results. We excluded individuals with records for rarer DM subtypes only. For individuals to be considered diabetic, they needed to have at least two records indicative of DM; one of which was required to be a diagnostic record. We then classified individuals with T1DM and T2DM using the second algorithm step. A combination of diagnostic codes, medication prescribed, age at diagnosis, and whether the case was incident or prevalent were used in this process. We internally validated this classification algorithm through comparison against an independent clinical examination of The Health Improvement Network electronic health records for a random sample of 500 DM individuals.

Results: Out of 9,161,866 individuals aged 0-99 years from 2000 to 2014, we classified 37,693 individuals with T1DM and 418,433 with T2DM, while 1,792 individuals remained unclassified. A small proportion were classified with some uncertainty (1,155 [3.1%] of all individuals with T1DM and 6,139 [1.5%] with T2DM) due to unclear health records. During validation, manual assignment of DM type based on clinical assessment of the entire electronic record and algorithmic assignment led to equivalent classification in all instances.

Conclusion: The majority of individuals with T1DM and T2DM can be readily identified from UK primary care electronic health records. Our approach can be adapted for use in other health care settings.

Keywords: algorithm; databases; diabetes and endocrinology; epidemiology; public health.

Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Flowchart for algorithm step 1: Identification of individuals with potential T1DM or T2DM. Note: aTwo codes must include at least one diagnostic Read code or AHD code. Abbreviations: AHD code, Additional Health Data; DM, diabetes mellitus; GP, general practitioner; LADA, latent autoimmune diabetes in adults; PCOS, polycystic ovary syndrome; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus; THIN, The Health Improvement Network.
Figure 2
Figure 2
Flowchart for algorithm step 2: Classification of individuals with T1DM and T2DM. Abbreviations: DM, diabetes mellitus; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus.

Similar articles

See all similar articles

Cited by 12 articles

See all "Cited by" articles

References

    1. World Health Organisation WHO: 10 Facts about Diabetes. 2014. [Accessed January 25, 2016]. Available from: http://www.who.int/features/factfiles/diabetes/en/
    1. World Health Organisation Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia. 2006. [Accessed May 4, 2015]. (Report of a WHO/IDF consultation). Available from: http://www.who.int/diabetes/publications/diagnosis_diabetes2006/en/
    1. American Diabetes Association Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Suppl 1):S81–S90. - PubMed
    1. Public Health England Adult Obesity and Type 2 Diabetes. 2014. [Accessed December 10, 2014]. Available from: https://www.gov.uk/government/publications/adult-obesity-and-type-2-diabetes.
    1. Sharma M, Nazareth I, Petersen I. Trends in incidence, prevalence and prescribing in type 2 diabetes mellitus between 2000 and 2013 in primary care: a retrospective cohort study. BMJ Open. 2016;6(1):e010210. - PMC - PubMed

LinkOut - more resources

Feedback