Improving surgical decision-making by measuring and predicting long-term loss of independence after surgery

手术后的生活质量对退伍军人、他们的家人和退伍军人医疗保健至关重要 系统-尤其是对于身体虚弱的患者，他们不太可能出院回家，更有可能再次入院 在30天内，并大大增加了术后死亡率和并发症。一个 当外科医生术前筛查虚弱的患者并进行调整时，虚弱的患者将获得实质性的生存好处 相应的治疗计划。虽然生存对于虚弱的患者来说是一个重要的结果，但许多人优先考虑质量 以保持独立性为基础的生命。然而，关于手术后长期独立性的数据还很缺乏。 因为手术登记关注的是30天的结果，通常不评估功能状态或其他 更多以患者为中心的质量衡量标准。大范围手术后到熟练护理机构的出院率 对于术前住在家里的虚弱患者，从30%到40%，但这并不出人意料，因为他们很可能 从短期康复中受益。然而，关于(A)这些方面是否存在关键的知识差距 患者重新获得独立或继续被收容；以及(B)如何有效地与 围手术期风险支持与患者价值观一致的手术治疗共同决定。 术后独立性丧失(LOI)是一个以患者为中心的至关重要但难以衡量的问题 结果，包括对患者重要的广泛活动。这里，我们狭义地将LOI定义为 从家里提出接受索引手术后，在其他地方居住的天数。LOI可能会解决 快速(即短期LOI)或变得持久/永久性(即长期LOI)。长期风险因素 LOI是未知的，但可能包括虚弱、紧急手术和施加高生理压力的程序 压力。对于外科医生和患者来说，关于潜在LOI的预测是至关重要的，以便更好地了解情况 关于手术治疗的决定与患者的目标和价值观保持一致。具体来说，我们的目标是： 目的1：描述术后365天内常见的LOI轨迹，以描述 医疗保健利用模式的临床有意义的异质性及其与脆弱性的关联， 紧急手术和手术压力。在一个大的老兵样本中，我们将量化背景和持续时间 对手术后一年的医疗保健利用情况进行分析，模拟LOI的轨迹和相关的风险因素。 我们假设LOI在体弱者中更常见，在紧急情况和高压力后都是如此。 做手术。 目标2：采用风险分析指数(RAI)来预测长期LOI，并探索LOI的替代模型 预测。RAI是一项由14个项目组成的外科脆弱性调查指标，需要30秒才能在 并预测术后死亡率和并发症。我们将调整RAI来建造、校准、 并验证预测长期LOI的模型，并使用以下变量探索预测LOI的替代模型 电子健康记录和现有的风险措施。我们假设来自RAI的项目反应 可以准确地预测护理点的LOI。 目标3：探讨关键利益相关者对LOI风险预测如何更好地协调共同决策的看法 关于手术治疗与患者的价值观和目标。我们将与外科医生和 与患者及其照顾者进行半结构化访谈，以探讨围手术期风险和 使共同决定与患者价值观保持一致的策略。研究将集中在外科医生的影响因素上， 患者和他们的非正式照顾者在做出手术治疗决定时会考虑亲属 在这种情况下，LOI预后的重要性，以及如何最好地传达LOI的风险和 手术实施，以告知和改进对偏好敏感的手术选择。

Quality of life following surgery is critically important to Veterans, their families, and the VA Healthcare System—especially for frail patients who are less likely to be discharged to home, more likely to be readmitted within 30 days, and have substantially increased rates of postoperative mortality and complications. A substantial survival benefit occurs for frail patients when surgeons preoperatively screen for frailty and adjust treatment plans accordingly. Although survival is an important outcome for frail patients, many prioritize quality of life based on preservation of independence. Yet data about long-term independence after surgery is lacking because surgical registries focus on 30-day outcomes and typically do not assess functional status or other more patient-centered quality measures. Discharge rates to skilled nursing facilities after major surgery range from 30% to 40% for frail patients living at home preoperatively, but this is not unexpected as they are likely to benefit from short-term rehabilitation. However, critical knowledge gaps exist regarding (a) whether these patients regain their independence or remain institutionalized; and (b) how to effectively communicate those perioperative risks to support shared decisions about surgical treatment aligned with patients' values. Postoperative Loss of Independence (LOI) is a critically important, but difficult to measure patient-centered outcome, encompassing a broad range of activities important to patients. Here we narrowly define LOI as the number of days living elsewhere than home after presenting from home for the index surgery. LOI may resolve quickly (i.e., short-term LOI) or become protracted/permanent (i.e., long-term LOI). Risk factors for long-term LOI are unknown, but likely include frailty, emergency surgery, and procedures that impose high physiological stress. Prognosis regarding potential LOI is essential for surgeons and patients to make better-informed decisions about surgical treatment that align with patients' goals and values. Specifically, we aim to: Aim 1: Characterize common trajectories of postoperative LOI in the 365 days after surgery to describe clinically meaningful heterogeneity in the patterns of healthcare utilization and their associations with frailty, emergency surgery, and operative stress. In a large Veteran sample, we will quantify the setting and duration of healthcare utilization in the year following surgery, modeling trajectories of LOI and associated risk factors. We hypothesize that LOI will be more common among the frail and after both emergency and high-stress surgery. Aim 2: Adapt the Risk Analysis Index (RAI) to predict long-term LOI and explore alternative models for LOI prediction. The RAI is a 14-item survey measure of surgical frailty that requires 30 seconds to administer at the point-of-care and predicts postoperative mortality and complications. We will adapt the RAI to build, calibrate, and validate models predicting long-term LOI and explore alternative models predicting LOI using variables in the Electronic Health Record and existing risk measures. We hypothesize that item responses from the RAI can accurately predict LOI at the point of care. Aim 3: Explore key stakeholders' perspectives on how LOI risk prognosis might better align shared decisions about surgical treatment with patients' values and goals. We will conduct focus groups with surgeons and semi-structured interviews with patients and their caregivers to explore perspectives on perioperative risks and strategies for aligning shared decisions with patients' values. Research will focus on the factors surgeons, patients, and their informal caregivers consider when making surgical treatment decisions, the relative importance of LOI prognosis in this context, and how the risk of LOI can be best communicated and operationally implemented to inform and improve preference-sensitive surgical choices.