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      Eleven-year multimorbidity burden among 637 255 people with and without type 2 diabetes: a population-based study using primary care and linked hospitalisation data

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          Abstract

          Objectives

          To compare the patterns of 18 physical and mental health comorbidities between people with recently diagnosed type 2 diabetes (T2D) and people without diabetes and how these change by age, gender and deprivation over time between 2004 and 2014. Also, to develop a metric to identify most prevalent comorbidities in people with T2D.

          Design

          Population-based cohort study.

          Setting

          Primary and secondary care, England, UK.

          Participants

          108 588 people with T2D and 528 667 comparators registered in 391 English general practices. Each patient with T2D aged ≥16 years between January 2004 and December 2014 registered in Clinical Practice Research Datalink GOLD practices was matched to up to five comparators without diabetes on age, gender and general practice.

          Primary and secondary outcome measures

          Prevalence of 18 physical and mental health comorbidities in people with T2D and comparators categorised by age, gender and deprivation. Odds for association between T2D diagnosis and comorbidities versus comparators. A metric for comorbidities with prevalence of ≥5% and/or odds ≥2 in patients with T2D.

          Results

          Overall, 77% of patients with T2D had ≥1 comorbidity and all comorbidities were more prevalent in patients with T2D than in comparators. Across both groups, prevalence rates were higher in older people, women and those most socially deprived. Conditional logistic regression models fitted to estimate (OR, 95% CI) for association between T2D diagnosis and comorbidities showed that T2D diagnosis was significantly associated with higher odds for all conditions including myocardial infarction (OR 2.13, 95% CI 1.85 to 2.46); heart failure (OR 2.12, 1.84 to 2.43); depression (OR 1.75, 1.62 to 1.89), but non-significant for cancer (OR 1.12, 0.98 to 1.28). In addition to cardiovascular disease, the metric identified osteoarthritis, hypothyroidism, anxiety, schizophrenia and respiratory conditions as highly prevalent comorbidities in people with T2D.

          Conclusions

          T2D diagnosis is associated with higher likelihood of experiencing other physical and mental illnesses. People with T2D are twice as likely to have cardiovascular disease as the general population. The findings highlight highly prevalent and under-reported comorbidities in people with T2D. These findings can inform future research and clinical guidelines and can have important implications on healthcare resource allocation and highlight the need for more holistic clinical care for people with recently diagnosed T2D.

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          Most cited references30

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          Methods for identifying 30 chronic conditions: application to administrative data

          Background Multimorbidity is common and associated with poor clinical outcomes and high health care costs. Administrative data are a promising tool for studying the epidemiology of multimorbidity. Our goal was to derive and apply a new scheme for using administrative data to identify the presence of chronic conditions and multimorbidity. Methods We identified validated algorithms that use ICD-9 CM/ICD-10 data to ascertain the presence or absence of 40 morbidities. Algorithms with both positive predictive value and sensitivity ≥70% were graded as “high validity”; those with positive predictive value ≥70% and sensitivity <70% were graded as “moderate validity”. To show proof of concept, we applied identified algorithms with high to moderate validity to inpatient and outpatient claims and utilization data from 574,409 people residing in Edmonton, Canada during the 2008/2009 fiscal year. Results Of the 40 morbidities, we identified 30 that could be identified with high to moderate validity. Approximately one quarter of participants had identified multimorbidity (2 or more conditions), one quarter had a single identified morbidity and the remaining participants were not identified as having any of the 30 morbidities. Conclusions We identified a panel of 30 chronic conditions that can be identified from administrative data using validated algorithms, facilitating the study and surveillance of multimorbidity. We encourage other groups to use this scheme, to facilitate comparisons between settings and jurisdictions. Electronic supplementary material The online version of this article (doi:10.1186/s12911-015-0155-5) contains supplementary material, which is available to authorized users.
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            Recent advances in the utility and use of the General Practice Research Database as an example of a UK Primary Care Data resource.

            Since its inception in the mid-1980s, the General Practice Research Database (GPRD) has undergone many changes but remains the largest validated and most utilised primary care database in the UK. Its use in pharmacoepidemiology stretches back many years with now over 800 original research papers. Administered by the Medicines and Healthcare products Regulatory Agency since 2001, the last 5 years have seen a rebuild of the database processing system enhancing access to the data, and a concomitant push towards broadening the applications of the database. New methodologies including real-world harm-benefit assessment, pharmacogenetic studies and pragmatic randomised controlled trials within the database are being implemented. A substantive and unique linkage program (using a trusted third party) has enabled access to secondary care data and disease-specific registry data as well as socio-economic data and death registration data. The utility of anonymised free text accessed in a safe and appropriate manner is being explored using simple and more complex techniques such as natural language processing.
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              Standards of medical care in diabetes--2015: summary of revisions.

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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2020
                1 July 2020
                : 10
                : 7
                : e033866
                Affiliations
                [1 ] departmentCentre for Primary Care and Health Services Research, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health , Manchester Academic Health Science Centre (MAHSC), University of Manchester , Manchester, UK
                [2 ] departmentDepartment of Pharmaceutics, Faculty of Pharmacy , University of Tripoli , Tripoli, Libya
                [3 ] departmentCentre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health , Manchester Academic Health Sciences Centre (MAHSC), University of Manchester , Manchester, UK
                [4 ] departmentDivision of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health , Manchester Academic Health Science Centre (MAHSC), University of Manchester , Manchester, UK
                [5 ] departmentDiabetes, Endocrinology and Metabolism Centre , Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre (MAHSC) , Manchester, UK
                Author notes
                [Correspondence to ] Dr Salwa S Zghebi; salwa.zghebi@ 123456manchester.ac.uk
                Author information
                http://orcid.org/0000-0002-7978-1094
                Article
                bmjopen-2019-033866
                10.1136/bmjopen-2019-033866
                7358107
                32611677
                11bb625f-bab5-49d1-b6b6-33c817e07a65
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 25 August 2019
                : 01 May 2020
                : 05 May 2020
                Categories
                Diabetes and Endocrinology
                1506
                1843
                2474
                Original research
                Custom metadata
                unlocked

                Medicine
                multimorbidity,type 2 diabetes,epidemiology,electronic medical record,primary care,secondary care

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