权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

SCH: INT Re-envisioned Chat-assessment for Real-time Investigating of Nursing and Guidance

SCH：INT 重新设想的用于护理和指导实时调查的聊天评估

基本信息

批准号：
10453755
负责人：
VICKI Stover HERTZBERG
金额：
$ 22.2万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-13 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10453755
关键词：
Academy Address Adopted Adoption Algorithms American Area Big Data Big Data Methods Care given by nurses Caring Clinical Clinical Pathways Coupled Data Data Science Decision Making Developed Countries Development Dimensions Discipline of Nursing Documentation Electronic Health Record Equilibrium Event Evolution Family Caregiver Feedback Fees Goals Guidelines Health Health Personnel Healthcare Healthcare Systems Hospitals Informatics Infrastructure Institute of Medicine (U.S.)Institution International Investigation Knowledge Label Lead Learning Limes Machine Learning Measures Medical Medicine Methods Mining Mission Modeling Nurse Administrator Nurses Nurses Performance Evaluations Nursing Informatics Outcome Patient-Focused Outcomes Patients Pattern Physicians Process Publications Quality Indicator Recovery Reporting Research Risk Safety School Nursing Seminal Source Structure System Text Time Training Uncertainty United States Centers for Medicare and Medicaid Services United States National Library of Medicine Weight Work acute care arm base clinical practice computer science data mining data modeling data standards design flexibility graduate student health care quality heterogenous data improved indexing individual patient industry partner innovation learning algorithm machine learning prediction massive open online courses multimodality nursing care quality open source patient population patient safety phrases predictive modeling supervised learning tool vector

项目摘要

Two decades have lapsed since the seminal publications of the National Academy of Medicine (formerly the Institute of Medicine), To Err Is Human and Crossing the Quality Chasm, cast a national spotlight on health-care safety and quality, yet US patient outcome indices continue to lag behind those in other industrialized countries. The 2009 American Recovery and Reinvestment Act mandated health-care providers adopt electronic health record (EHR) systems, leading to widespread EHR adoption, albeit primarily for billing purposes rather than research or quality improvement efforts. Thus EHR impact on health-care quality has tended to be in the domains of physician efficiency and guideline compliance. Despite a large body of evidence that nursing quality is directly related to patient outcomes in the acute care selling, nurses often lack timely information to use in improving individual patient outcomes, and indices of outcomes across patient populations are slow to budge over lime. Widespread adoption of EHRs in U.S. hospitals now allows determination of outcome quality indicators for all patients in a hospital for real-time feedback to nurses. Quality indicators are often only determined by piecing together other information to determine occurrence of an incident, e.g., exhuming information buried in nursing notes. The goal is to develop Chart-assessment for Real-lime Investigation of Nursing and Guidance (CARING), an automated machine learning system to report and predict nursing quality indicators in real-time for hospitalized patients to assist nurses in care planning. CARI NG will reflect algorithmic innovations to mine sequential patterns from multi-sourced, heterogeneous data including nursing narratives, yielding robust predictive models that are insensitive to uncertain labels and evolve with changes in health-care practices. CARING will represent EHR data using inter-connected tensors, capturing higher-order relations, temporal weighting, i.e., more recent data receives more weight, and incorporating domain expert feedback in development. Although CARING will be developed initially for the ten hospitals of our industry partner Emory Healthcare, its flexible refinement will enable adaptation at other health-care institutions. Outcomes of this project will give nurses actionable data in real time to improve nursing care quality that they do not receive now. Moreover, this system can be implemented into the health information infrastructure at an institutional level, integrating multi-scale and multi-level clinical, contextual, and organizational data surrounding each patient for real-time reporting and incorporation into predictive models.

自美国国家医学科学院（National Academy of Medicine）发表开创性出版物以来，已经过去了20年

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Comprehensive and Improved Definition for Hospital-Acquired Pressure Injury Classification Based on Electronic Health Records: Comparative Study.

DOI：
10.2196/40672
发表时间：
2023-02-23
期刊：
JMIR MEDICAL INFORMATICS
影响因子：
3.2
作者：
Sotoodeh, Mani;Zhang, Wenhui;Simpson, Roy L.;Hertzberg, Vicki Stover;Ho, Joyce C.
通讯作者：
Ho, Joyce C.

Pressure Ulcer Injury in Unstructured Clinical Notes: Detection and Interpretation

DOI：
发表时间：
2020
期刊：
AMIA ... Annual Symposium proceedings. AMIA Symposium
影响因子：
0
作者：
Mani Sotoodeh;Zelalem Gero;Wenhui Zhang;L. Roy;Simpson;V. Hertzberg;Joyce Ho
通讯作者：
Mani Sotoodeh;Zelalem Gero;Wenhui Zhang;L. Roy;Simpson;V. Hertzberg;Joyce Ho

Examining the Concordance in the Documented Pressure Injury Site, Stage, and Count in Medical Information Mart for Intensive Care-III.

检查重症监护医疗信息市场中记录的压力性损伤部位、阶段和计数的一致性 - III。