Objective To examine the daily bed requirements arising from the flow of emergency admissions to an acute hospital, to identify the implications of fluctuating and unpredictable demands for emergency admission for the management of hospital bed capacity, and to quantify the daily risk of insufficient capacity for patients requiring immediate admission. Design Modelling of the dynamics of the hospital system, using a discrete-event stochastic simulation model, which reflects the relation between demand and available bed capacity. Setting Hypothetical acute hospital in England. Subjects Simulated emergency admissions of all types except mental disorder. Main outcome measures The risk of having no bed available for any patient requiring immediate admission; the daily risk that there is no bed available for at least one patient requiring immediate admission; the mean bed occupancy rate. Results Risks are discernible when average bed occupancy rates exceed about 85%, and an acute hospital can expect regular bed shortages and periodic bed crises if average bed occupancy rises to 90% or more. Conclusions There are limits to the occupancy rates that can be achieved safely without considerable risk to patients and to the efficient delivery of emergency care. Spare bed capacity is therefore essential for the effective management of emergency admissions, and its cost should be borne by purchasers as an essential element of an acute hospital service.

Recent research has employed different analytical techniques to estimate the impact of the various long-term complications of type 2 diabetes on health-related utility and health status. However, limited patient numbers or lack of variety of patient experience has limited their power to discriminate between separate complications and grades of severity. In this study alternative statistical model forms were compared to investigate the influence of various factors on self-assessed health status and calculated utility scores, including the presence and severity of complications, and type of diabetes therapy. Responses to the EuroQol EQ-5D questionnaire from 4641 patients with type 2 diabetes in 5 European countries were analysed. Simple multiple regression analysis was used to model both visual analogue scale (VAS) scores and time trade-off index scores (TTO). Also, two complex models were developed for TTO analysis using a structure suggested by the EuroQol calculation algorithm. Both VAS and TTO models achieved greater explanatory power than in earlier studies. Relative weightings for individual complications differed between VAS and TTO scales, reflecting the strong influence of loss of mobility and severe pain in the EuroQol algorithm. Insulin-based therapy was uniformly associated with a detrimental effect equivalent to an additional moderate complication. Evidence was found that TTO values are not responsive in cases where 3 or more multiple complications are present, and therefore may underestimate utility loss for patients most adversely affected by complex chronic diseases like diabetes.

The majority of chemotherapy drugs are dosed based on body surface area (BSA). No standard BSA values for patients being treated in the United Kingdom are available on which to base dose and cost calculations. We therefore retrospectively assessed the BSA of patients receiving chemotherapy treatment at three oncology centres in the UK between 1st January 2005 and 31st December 2005.A total of 3613 patients receiving chemotherapy for head and neck, ovarian, lung, upper GI/pancreas, breast or colorectal cancers were included. The overall mean BSA was 1.79 m2 (95% CI 1.78–1.80) with a mean BSA for men of 1.91 m2 (1.90–1.92) and 1.71 m2 (1.70–1.72) for women. Results were consistent across the three centres. No significant differences were noted between treatment in the adjuvant or palliative setting in patients with breast or colorectal cancer. However, statistically significant, albeit small, differences were detected between some tumour groups.In view of the consistency of results between three geographically distinct UK cancer centres, we believe the results of this study may be generalised and used in future costings and budgeting for new chemotherapy agents in the UK.

The review of clinical data related to the three drugs (including conventional treatment) compared with conventional treatment plus placebo indicates that in the short term (12-24 weeks), the three treatments are clinically effective in relation to assessment of ASAS, BASDAI and BASFI. Indirect comparisons of treatments were limited and did not show a significant difference in effectiveness between the three agents. The short-term economic assessment indicates that none of the three anti-TNF-alpha agents is likely to be considered cost-effective at current acceptability thresholds, with infliximab consistently the least favourable option. There is an absence of evidence concerning a number of limiting factors related to patients suffering from AS, the disease itself and its treatment. In order to obtain robust estimates of the longer term clinical effectiveness and cost-effectiveness of anti-TNF-alpha agents for AS, clinical trials that aim to address these limiting factors need to be conducted.

Non-compliance with drug therapies not only limits their effectiveness, but in some instances, is associated with grave clinical sequelae and substantial economic burden. It is important, therefore, to consider non-compliance in economic evaluations. A review of pharmacoeconomic evaluations, which have applied sensitivity analysis to non-compliance rates, was undertaken to evaluate the impact of non-compliance on the cost-effectiveness of different drug therapies. Although 22 evaluations satisfied the inclusion criteria, additional information was obtained from the authors of most studies, as the published details were inadequate. The majority of evaluations assumed altered effectiveness owing to reduced compliance in the absence of supportive clinical evidence. Because of the disparity in the nature of the outcomes, the measures of non-compliance and the time horizon of the studies evaluated, it was not possible to compare the magnitude of the impact of non-compliance among different drug-disease combinations. However, it was evident that non-compliance always results in a reduction in efficacy, but its impact on costs varied substantially. The importance of incorporating measures of compliance is highlighted, as failing to account for 'real world' compliance rates in pharmacoeconomic evaluations may lead to selection of sub-optimal treatment strategies.

A recent publication includes a review of survival extrapolation methods used in technology appraisals of treatments for advanced cancers. The author of the article also noted shortcomings and inconsistencies in the analytical methods used in appraisals. He then proposed a survival model selection process algorithm to guide modelers' choice of projective models for use in future appraisals. This article examines the proposed algorithm and highlights various shortcomings that involve questionable assumptions, including researchers' access to patient-level data, the relevance of proportional hazards modeling, and the appropriateness of standard probability functions for characterizing risk, which may mislead practitioners into employing biased structures for projecting limited data in decision models. An alternative paradigm is outlined. This paradigm is based on the primacy of the experimental data and adherence to the scientific method through hypothesis formulation and validation. Drawing on extensive experience of survival modeling and extrapolation in the United Kingdom, practical advice is presented on issues of importance when using data from clinical trials terminated without complete follow-up as a basis for survival extrapolation.

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Type II (non-insulin-dependent) diabetes mellitus is a common chronic illness with a prevalence as high as 8 % in many countries [1]. In Europe approximately 27 million people suffer from diabetes, 80±90 % of whom have Type II diabetes [2]. Due to increased life expectancy, increased frequency of diagnosis and lifestyle changes, the prevalence of this disease in Europe is expected to increase by 50 % over the next 15 years. Approximately 50 % of people with Type II diabetes are thought to be undiagnosed [3] because its onset is gradual and could precede diagnosis by up to 7 years [4].Diabetes imposes a substantial burden on both individuals [5] and health-care budgets. In the UK, annual diabetes costs were estimated at £ 547 million in 1995, with 64 % of these costs resulting from hospital in-patient care [6]. This large hospital care burden is a result of the treatment of retinal, renal, neuropath-