■对于医疗保健获得的第1阶段和第2阶段压力伤害知之甚少。我们报告了医疗保健获得性1期和2期压力性损伤的发生率,and,使用四种相互竞争的分析方法估计超额停留时间。我们讨论不同方法的优点。
■我们计算了在新加坡一家大型急性护理医院发生的1期和2期医疗保健获得性压力伤的月发病率。要估计超额停留时间,我们与对照组进行了未经调整的比较,进行线性回归,然后用伽马分布进行广义线性回归。最后,我们拟合了一个简单的基于状态的模型。成本归因工作的设计是一项回顾性匹配的队列研究。
■2016年的发病率为0.553%(95%置信区间[CI]0.55,0.557)和2017年的0.469%(95%CI0.466,0.472)。对于在最长停留时间60天审查的数据,未经调整的比较显示,超额住院时间最高,为17.68(16.43~18.93)天,多态模型显示最低,为1.22(0.19,2.23)天.
■将停留时间过长归因于压力伤害的低质量方法会产生夸大的估计,从而可能误导决策者。来自多状态模型的发现,这是一种适当的方法,是合理的,并说明了降低这些事件风险可能节省的卧床天数。第1阶段和第2阶段压力伤是常见的,并通过延长住院时间来增加成本。将有经济价值投资于预防。使用对停留时间过长的有偏差的估计会夸大预防的潜在价值。
UNASSIGNED: Little is known about stage 1 and 2 pressure injuries that are health care-acquired. We report incidence rates of health care-acquired stage 1 and stage 2 pressure injuries, and, estimate the excess length of stay using four competing analytic methods. We discuss the merits of the different approaches.
UNASSIGNED: We calculated monthly incidence rates for stage 1 and 2 health care-acquired pressure injuries occurring in a large Singapore acute care hospital. To estimate excess stay, we conducted unadjusted comparisons with a control cohort, performed linear regression and then generalized linear regression with a gamma distribution. Finally, we fitted a simple state-based model. The design for the cost attribution work was a retrospective matched cohort study.
UNASSIGNED: Incidence rates in 2016 were 0.553% (95% confidence interval [CI] 0.55, 0.557) and 0.469% (95% CI 0.466, 0.472) in 2017. For data censored at 60 days\' maximum stay, the unadjusted comparisons showed the highest excess stay at 17.68 (16.43-18.93) days and multi-state models showed the lowest at 1.22 (0.19, 2.23) days.
UNASSIGNED: Poor-quality methods for attribution of excess length of stay to pressure injury generate inflated estimates that could mislead decision makers. The findings from the multi-state model, which is an appropriate method, are plausible and illustrate the likely bed-days saved from lowering the risk of these events. Stage 1 and 2 pressure injuries are common and increase costs by prolonging the length of stay. There will be economic value investing in prevention. Using biased estimates of excess length of stay will overstate the potential value of prevention.