Article Text
Abstract
Purpose The University of Surrey-Lilly Real World Evidence (RWE) diabetes cohort has been established to provide insights into the management of type 2 diabetes mellitus (T2DM). There are 3 areas of study due to be conducted to provide insights into T2DM management: exploration of medication adherence, thresholds for changing diabetes therapies, and ethnicity-related or socioeconomic-related disparities in management. This paper describes the identification of a cohort of people with T2DM which will be used for these analyses, through a case finding algorithm, and describes the characteristics of the identified cohort.
Participants A cohort of people with T2DM was identified from the Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) data set. This data set comprises electronic patient records collected from a nationally distributed sample of 130 primary care practices across England with scope to increase the number of practices to 200.
Findings to date A cohort (N=58 717) of adults with T2DM was identified from the RCGP RSC population (N=1 260 761), a crude prevalence of diabetes of 5.8% in the adult population. High data quality within the practice network and an ontological approach to classification resulted in a high level of data completeness in the T2DM cohort; ethnicity identification (82.1%), smoking status (99.3%), alcohol use (93.3%), glycated haemoglobin (HbA1c; 97.9%), body mass index (98.0%), blood pressure (99.4%), cholesterol (87.4%) and renal function (97.8%). Data completeness compares favourably to other, similarly large, observational cohorts. The cohort comprises a distribution of ages, socioeconomic and ethnic backgrounds, diabetes complications, and comorbidities, enabling the planned analyses.
Future plans Regular data uploads from the RCGP RSC practice network will enable this cohort to be followed prospectively. We will investigate medication adherence, explore thresholds and triggers for changing diabetes therapies, and investigate any ethnicity-related or socioeconomic-related disparities in diabetes management.
- DIABETES & ENDOCRINOLOGY
- PRIMARY CARE
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Footnotes
Contributors AM led the analysis and drafting of the manuscript. AM and SdL conceived the paper. WH, AC, NM and MW supported the analysis. All the authors have contributed to the final manuscript.
Funding Eli Lilly and Company. Grant number (10.13039/100004312).
Competing interests The RCGP RSC is primarily funded by Public Health England and the development of the RCGP RSC data set is supported by surveillance work funded by Public Health England. The subcohort of people with T2DM identified from the RCGP RSC has been developed for a number of planned studies funded, as part of the University of Surrey-Lilly Real World Evidence (RWE) projects, by Eli Lilly and Company. AM, WH, MW and SdL are funded by Eli-Lilly and Company. SdL and AC have undertaken research funded by GlaxoSmithKline. NM has received fees for serving as a speaker, a consultant or an advisory board member for Allergan, Bristol-Myers Squibb-Astra-Zeneca, GlaxoSmithKline, Eli Lilly, Lifescan, MSD, Metronic, Novartis, Novo Nordisk, Pfizer, Sankio, Sanofi, Roche, Servier, Takeda. MW has received speaker fees from Astra-Zeneca.
Ethics approval Health Research Authority.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The RCGP RSC data set can be accessed by bona fide researchers on a case-by-case basis. Ethical approval by the NHS Research Ethics Committee is needed for data requests to be considered. Aggregated data tables may be created from the source data to allow specific analyses for approved research and surveillance projects. Researchers wishing to directly analyse the patient-level anonymised data will be required to complete information governance training and work on the data from the secure servers at the University of Surrey. Patient-level data cannot be taken out of the secure servers at the University of Surrey. The authors encourage interested researchers to attend the short courses on how to analyse primary care data offered by the university twice a year.