Presence of DR and ME, visual acuity impairment and patient co-morbidities lead to significant impairment of both the physical and mental components of HRQOL.
Sepsis is a systemic response to severe infection in critically ill patients and is among the most frequent causes of death in intensive care medicine. Every year between 44,000 and 95,000 persons suffer from this illness in Germany. With the help of a retrospective electronic chart analysis in three adult ICUs of three university hospitals we calculated by a bottom-up approach the direct costs of these patients yielding per patient costs of 23,297 euros on average. Linking the direct costs per patient with the incidence data, the total direct costs for severe sepsis in Germany per year were estimated to range from 1,025 to 2,214 million euros. Direct costs, however, were found to make up only about 28% of the burden of disease of severe sepsis. The indirect costs range between 2,622 and 5,660 million euros. Productivity loss due to premature death does account for the largest part of the indirect costs. In conclusion, severe sepsis imposes annual costs between 3,647 and 7,874 million euros to the German society.
BackgroundEvidence-based medicine, the Institute of Medicine (IOM) and the German Institute for Quality and Efficiency in Health Care (IQWiG), support the inclusion of patients' preferences in health care decisions. In fact there are not many trials which include an assessment of patient's preferences. The aim of this study is to demonstrate that preferences of physicians and of patients can be assessed and that this information may be helpful for medical decision making.MethodOne of the established methods for assessment of preferences is the conjoint analysis. Conjoint analysis, in combination with a computer assisted telephone interview (CATI), was used to collect data from 827 diabetes patients and 60 physicians, which describe the preferences expressed as levels of four factors in the management and outcome of the disease. The first factor described the main treatment effect (reduction of elevated HbA1c, improved well-being, absence of side effects, and no limitations of daily life). The second factor described the effect on the body weight (gain, no change, reduction). The third factor analyzed the mode of application (linked to meals or flexible application). The fourth factor addressed the type of product (original brand or generic product). Utility values were scaled and normalized in a way that the sum of utility points across all levels is equal to the number of attributes (factors) times 100.ResultsThe preference weights confirm that the reduction of body weight is at least as important for patients - especially obese patients - and physicians as the reduction of an elevated HbA1c. Original products were preferred by patients while general practitioners preferred generic products.ConclusionUsing the example of diabetes, the difference between patients' and physicians' preferences can be assessed. The use of a conjoint analysis in combination with CATI seems to be an effective approach for generation of data which are needed for policy and medical decision making in health care.
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