Polypharmacy is common in UK primary care. The main factor associated with this is multimorbidity, although considerable variation exists between different conditions. The impact of clinical conditions on the number of medicines is generally less in the presence of co-existing concordant conditions.

Background:Appreciating variation in the length of pre- or post-presentation diagnostic intervals can help prioritise early diagnosis interventions with either a community or a primary care focus.Methods:We analysed data from the first English National Audit of Cancer Diagnosis in Primary Care on 10 953 patients with any of 28 cancers. We calculated summary statistics for the length of the patient and the primary care interval and their ratio, by cancer site.Results:Interval lengths varied greatly by cancer. Laryngeal and oropharyngeal cancers had the longest median patient intervals, whereas renal and bladder cancer had the shortest (34.5 and 30 compared with 3 and 2 days, respectively). Multiple myeloma and gallbladder cancer had the longest median primary care intervals, and melanoma and breast cancer had the shortest (20.5 and 20 compared with 0 and 0 days, respectively). Mean patient intervals were longer than primary care intervals for most (18 of 28) cancers, and notably so (two- to five-fold greater) for 10 cancers (breast, melanoma, testicular, vulval, cervical, endometrial, oropharyngeal, laryngeal, ovarian and thyroid).Conclusions:The findings support the continuing development and evaluation of public health interventions aimed at shortening patient intervals, particularly for cancers with long patient interval and/or high patient interval over primary care interval ratio.

BACKGROUND: Health services have failed to respond to the pressures of multimorbidity. Improved measures of multimorbidity are needed for conducting research, planning services and allocating resources. METHODS: We modelled the association between 37 morbidities and 3 key outcomes (primary care consultations, unplanned hospital admission, death) at 1 and 5 years. We extracted development (n = 300 000) and validation (n = 150 000) samples from the UK Clinical Practice Research Datalink. We constructed a general-outcome multimorbidity score by averaging the standardized weights of the separate outcome scores. We compared performance with the Charlson Comorbidity Index. RESULTS: Models that included all 37 conditions were acceptable predictors of general practitioner consultations (C-index 0.732, 95% confidence interval [CI] 0.731-0.734), unplanned hospital admission (C-index 0.742, 95% CI 0.737-0.747) and death at 1 year (C-index 0.912, 95% CI 0.905-0.918). Models reduced to the 20 conditions with the greatest combined prevalence/weight showed similar predictive ability (C-indices 0.727, 95% CI 0.725-0.728; 0.738, 95% CI 0.732-0.743; and 0.910, 95% CI 0.904-0.917, respectively). They also predicted 5-year outcomes similarly for consultations and death (C-indices 0.735, 95% CI 0.734-0.736, and 0.889, 95% CI 0.885-0.892, respectively) but performed less well for admissions (C-index 0.708, 95% CI 0.705-Disclaimer: This study is based in part on data from the Clinical Practice Research Datalink obtained under licence from the UK Medicines and Healthcare Products Regulatory Agency. The data are provided by patients and collected by the NHS as part of their care and support. Linked mortality data were provided by the UK Office for National Statistics through NHS Digital. The interpretation and conclusions contained in this study are those of the authors alone.