Development and Validation of 10-Year Life Expectancy Calculators to Individualize Veterans’ Prevention Decisions

忽视预期寿命可能会导致糟糕的临床决策。健康的老年人可以受益于 筛查的筛查率很低。患有痴呆症或转移性癌症的老年人接受慢性病筛查 生长中的癌症不太可能引起症状，但可能会因假阳性结果而导致痛苦， 侵入性检查和治疗。预期寿命计算器提供了超越随意的可能性 基于年龄的截止时间，以更合理的预期寿命为基础的决策，包括年龄和其他 已知的预测死亡率的因素，如合并症、人口统计学、实验室结果和药房数据。 这项研究的目标是：(A)开发和验证使用以下技术的10年预期寿命计算器 2005年退伍军人管理局电子数据(人口统计、合并症、实验室结果和药房记录)；(B)开发 并验证增加的预期寿命计算器，该计算器添加了2009年的功能评估(活动 日常生活或日常生活能力或工具性活动或IADL评估)对其他危险因素的影响 并确定增加ADL和IADL数据是否会改善歧视；)；(C)制定和 验证VA-Medicare预期寿命计算器，该计算器将2009年的Medicare数据添加到其他风险因素和 确定增加医疗保险数据是否导致改善歧视；(D)适用预期寿命 用于确定发生的结直肠癌(CRC)筛查比例的国家VA队列计算器 对于预期寿命有限(预期寿命超过10年的可能性为25%)和延长寿命的退伍军人 两名退伍军人在推荐年龄内的预期寿命(预期寿命超过10年的可能性为75%) (50-75)用于结直肠癌筛查，以及年龄较高的退伍军人(76-85岁)，当筛查不是常规检查时 推荐的。 通过开发和验证退伍军人电子数据驱动的预期寿命计算器，该项目将 确定适龄退伍军人(50-75岁)可能不适当的结直肠癌过度筛查的比率 预期寿命有限(预期寿命10年以上的可能性为25%)。反过来，这个项目也将 确定超过推荐筛查年龄的退伍军人中可能不适当的结直肠癌筛查不足 (76-85岁)预期寿命延长(预期寿命超过10岁的可能性为75%)。这项工作将 为改善针对结直肠癌筛查的干预措施提供关键基础将估计 退伍军人个人预期寿命1)抑制对有限寿命患者的CRC筛查临床提醒 预期(50-75岁)或2岁)为延长生命的患者触发CRC筛查临床提醒 预期(76-85岁)。此外，准确的预期寿命估计也可以用来个性化 其他长期受益的预防决策，如乳腺癌筛查和强化治疗 血糖控制。因此，这项工作将是退伍军人管理局成为学习型医疗保健的另一种方式 使用临床数据使退伍军人的预防决策个人化并为全系统决策提供信息的系统 关于预防和临床警报。

Ignoring life expectancy can lead to poor clinical decisions. Healthy older adults who could benefit from screening have low screening rates. Older adults with dementia or metastatic cancer are screened for slow- growing cancers that are unlikely to cause symptoms but may lead to distress from false-positive results, invasive work-ups and treatments. Life expectancy calculators offer the possibility of moving beyond arbitrary age-based cutoffs to more rational life expectancy based decision-making, incorporating age as well as other factors known to predict mortality such as comorbidities, demographics, laboratory results and pharmacy data. The objectives of the study are to (a) develop and validate a 10-year life expectancy calculator using 2005 VA electronic data (demographics, comorbidities, laboratory results and pharmacy records); (b) develop and validate an Augmented life expectancy calculator that adds 2009 functional assessments (Activities of Daily Living or ADL and Instrumental Activities of Daily Living or IADL assessments) to the other risk factors and determine whether the addition of ADL and IADL data lead to improved discrimination; ); (c) develop and validate a VA-Medicare life expectancy calculator that adds 2009 Medicare data to the other risk factors and determine whether the addition of Medicare data lead to improved discrimination; (d) apply the life expectancy calculator to a national VA cohort to determine the proportion of colorectal cancer (CRC) screening that occurs in veterans with limited life expectancy (<25% likelihood of life expectancy of 10+ years) and extended life expectancy (>75% likelihood of life expectancy of 10+ years) in both veterans within the recommended age (50-75) for CRC screening as well as veterans at more advanced age (76-85) when screening is not routinely recommended. By developing and validating a VA electronic data driven life expectancy calculator, this project will determine the rates of potentially inappropriate CRC overscreening in age-appropriate veterans (age 50-75) with a limited life expectancy (<25% likelihood of life expectancy 10+ years). Conversely, this project will also identify potentially inappropriate CRC underscreening in veterans beyond the recommend age for screening (age 76-85) with an extended life expectancy (>75% likelihood of life expectancy of 10+ years). This work will provide the critical foundation for an intervention to improve the targeting of CRC screening will estimate an individual veterans' life expectancy to 1) suppress CRC screening clinical reminders for patients with limited life expectancy (age 50-75) or 2) trigger CRC screening clinical reminders for patients with extended life expectancy (age 76-85). Further, accurate life expectancy estimates could also be utilized to individualize other prevention decisions that have a long time to benefit, such as breast cancer screening and intensive glycemic control. Thus, this work would be another way that the VA would become a Learning Healthcare System that uses clinical data to individualize veterans' prevention decisions and inform system-wide decisions regarding prevention clinical alerts.