BackgroundMultimorbidity places a substantial burden on patients and the healthcare system, but few contemporary epidemiological data are available.AimTo describe the epidemiology of multimorbidity in adults in England, and quantify associations between multimorbidity and health service utilisation.Design and settingRetrospective cohort study, undertaken in England.MethodThe study used a random sample of 403 985 adult patients (aged ≥18 years), who were registered with a general practice on 1 January 2012 and included in the Clinical Practice Research Datalink. Multimorbidity was defined as having two or more of 36 long-term conditions recorded in patients’ medical records, and associations between multimorbidity and health service utilisation (GP consultations, prescriptions, and hospitalisations) over 4 years were quantified.ResultsIn total, 27.2% of the patients involved in the study had multimorbidity. The most prevalent conditions were hypertension (18.2%), depression or anxiety (10.3%), and chronic pain (10.1%). The prevalence of multimorbidity was higher in females than males (30.0% versus 24.4% respectively) and among those with lower socioeconomic status (30.0% in the quintile with the greatest levels of deprivation versus 25.8% in that with the lowest). Physical–mental comorbidity constituted a much greater proportion of overall morbidity in both younger patients (18–44 years) and those patients with a lower socioeconomic status. Multimorbidity was strongly associated with health service utilisation. Patients with multimorbidity accounted for 52.9% of GP consultations, 78.7% of prescriptions, and 56.1% of hospital admissions.ConclusionMultimorbidity is common, socially patterned, and associated with increased health service utilisation. These findings support the need to improve the quality and efficiency of health services providing care to patients with multimorbidity at both practice and national level.
Background:This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire.Methods:External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries.Results:There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals.Conclusions:Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.
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Dates of death in primary care records often disagree with national records and should be treated with caution. There is marked variation between practices, and studies involving young patients, unexplained deaths and where precise date of death is important are particularly vulnerable to these issues.
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