Optimizing stratified cancer survivorship care through multimorbidity risk prediction

通过多发病风险预测优化分层癌症生存护理

基本信息

批准号：
10166125
负责人：
MELISSA M HUDSON
金额：
$ 15万
依托单位：
ST. JUDE CHILDREN'S RESEARCH HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-11 至 2021-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10166125
关键词：
Address Adherence Adopted Adult Age Cancer Center Cancer Survivorship Cardiomyopathies Caring Characteristics Chest Chronic Chronic Disease Clinic Clinical Practice Guideline Clinical assessments Cohort Studies Communities Community Practice Data Development Diagnosis Early identification Genetic Predisposition to Disease Geography Guidelines Health Healthcare Healthcare Systems Home environment Impaired health Incidence Individual Infrastructure Intervention Life Malignant Neoplasms Medical Modeling Morbidity - disease rate Personal Satisfaction Plant Roots Prevalence Preventive service Provider Radiation Recommendation Recording of previous events Resource Allocation Resources Risk Risk Factors Risk stratification Saint Jude Children&apos s Research Hospital Stratification Survivors Vulnerable Populations base burden of illness cancer diagnosis cancer type childhood cancer survivor cohort density disorder risk experience health care delivery health related quality of life high risk innovation medical specialties multidisciplinary multiple chronic conditions personalized risk prediction predictive modeling psychosocial risk prediction model routine care survivorship treatment services

项目摘要

There is a critical need to optimize systematic care for medically vulnerable childhood cancer survivors, the complexity of which is rooted in the significant overall multimorbidity survivors experience. Yet, depending on a variety of risk factors, subsets of survivors experience vastly different disease burdens, making access to informed, high-quality survivorship care essential to early identification and mitigation of late morbidity. Most community providers, however, see only a few survivors in their practices, each varying by cancer type, treatment era, and treatment exposures, and thus endorse discomfort managing survivors due to unfamiliarity with the guidelines' specific surveillance recommendations. Furthermore, the ability of most healthcare systems to provide preventative and treatment services in the form of a multidisciplinary, survivorship medical home to all individuals remains limited due to the complexity of implementing guidelines in non-specialized clinics. To accommodate such constraints, some have adopted basic, risk-stratified models of care to allocate the most resource-intense, survivorship specialty care to those at highest risk of chronic health conditions (CHCs). These approaches have largely stratified survivors using only basic treatment exposures and incidence and prevalence of individual CHCs, overlooking multimorbidity due to multiple CHCs and health-related quality of life (HRQoL). The ability to stratify survivor groups based on risk of multimorbidity would both simplify and optimize a) personalized survivorship care based on individual survivors' risks and needs, and b) resource allocation to those most likely to benefit from routine care in a survivorship medical home. To begin to address these needs, we propose using the SJLIFE cumulative burden personalized risk-prediction model to establish low, moderate, and high CHC burden profiles among childhood cancer survivors to identify risk-stratified groups that will inform survivorship healthcare delivery and intervention. We propose additional incorporation of HRQoL into the tiered- care selection to identify survivors likely to benefit from higher-tiered survivorship care who would otherwise be misclassified by models only considering CHCs. The proposed study will result in a stratified survivorship care approach that considers the multimorbidity of cumulative burden and HRQoL, characteristics which are key to its effective dissemination and implementation in practice.

对于医学上脆弱的儿童癌症幸存者，迫切需要优化系统的护理，其复杂性植根于重要的总体多发病幸存者经验。但是，取决于各种危险因素，幸存者的子集经历了巨大不同的疾病负担，可以进入知情的，高质量的生存护理对于早期识别和缓解后期发病至关重要。最多但是，社区提供者在实践中只看到几个幸存者，每种都因癌症类型而异 ERA和治疗暴露，因此由于不熟悉与指南的具体监视建议。此外，大多数医疗保健系统的能力以多学科的生存医疗之家的形式提供预防和治疗服务由于在非专业诊所中实施准则的复杂性，个人仍然受到限制。到适应这种约束，有些人采用了基本的，风险分层的护理模型来分配最多的资源启发，生存专业护理对患有慢性健康状况（CHC）风险最高的人。这些方法在很大程度上仅使用基本治疗暴露以及发病率和流行率分层了幸存者单个CHC，由于多个CHC和与健康相关的生活质量（HRQOL），忽视了多种疾病。根据多种多发性风险分层幸存者群体的能力既可以简化又优化a）基于个人幸存者的风险和需求的个性化生存护理，b）资源分配给那些最有可能在生存医疗之家中受益于常规护理。为了开始满足这些需求，我们建议使用SJLIFE累积负担个性化风险预测模型来建立低，中等和儿童癌症幸存者之间的高CHC负担概况，以识别将告知风险分层的群体生存医疗保健提供和干预。我们提出将HRQOL额外掺入分层护理选择以确定可能受益于高级生存护理的幸存者仅考虑CHC的模型错误分类。拟议的研究将导致分层的生存护理考虑累积负担和HRQOL的多种多发性的方法，特征是至关重要的它在实践中的有效传播和实施。