倾向得分匹配
医学
队列
结果(博弈论)
队列研究
前瞻性队列研究
匹配(统计)
内科学
重症监护医学
数学
病理
数理经济学
作者
Hui Zhang,Yang Wang,Zhu-Ming Jiang,Jens Kondrup,Hai Fang,Martha Andrews,Marie T. Nolan,Shao-Yu Mu,Jun Zhang,Kang Yu,Qian Lü,Weiming Kang
出处
期刊:Nutrition
[Elsevier]
日期:2016-12-20
卷期号:37: 53-59
被引量:44
标识
DOI:10.1016/j.nut.2016.12.004
摘要
There is a lack of evidence regarding the economic effects of nutrition support in patients at nutritional risk. The aim of this study was to perform a cost-effectiveness analysis by comparing an adequate nutrition support cohort with a no-support cohort. A prospective observational study was performed in the surgical and medical gastroenterology wards. We identified patients at nutritional risk and the provision of nutrition support by the staff, unaware of the risk status, was recorded. Cost data were obtained from each patient's statement of accounts, and effectiveness was measured by the rate of infectious complication. To control for potential confounding variables, the propensity score method with matching was carried out. The incremental cost-effectiveness ratio was calculated based on the matched population. We screened 3791 patients, and 440 were recruited for the analysis. Patients in the nutrition support cohort had a lower incidence of infectious complications than those in the no-support cohort (9.1 versus 18.1%; P = 0.007). This result was similar in the 149 propensity matched pairs (9.4 versus 24.2%; P < 0.001). The median hospital length of stay was significantly reduced among the matched nutrition support patients (13 versus 15 d; P < 0.001). The total costs were similar among the matched pairs (US $6219 versus $6161). The incremental cost-effectiveness analysis suggested that nutrition support cost US $392 per patient prevented from having infectious complications. Nutrition support was associated with fewer infectious complications and shorter length of stay in patients at nutritional risk. The incremental cost-effectiveness ratio indicated that nutrition support had not increased costs significantly.
科研通智能强力驱动
Strongly Powered by AbleSci AI