Making consent for electronic health and social care data research fit for purpose in the 21st century [0.03%]
面向二十一世纪的电子健康和社会护理数据研究的知情同意框架改革
Philip Anthony Heslop,Karen Davies,Avan Sayer et al.
Philip Anthony Heslop et al.
Niels Peek,Mark Sujan,Philip Scott
Niels Peek
Developing the infrastructure to support the optimisation of antibiotic prescribing using the learning healthcare system to improve healthcare services in the provision of primary care in England [0.03%]
利用学习型医疗卫生体系优化英格兰初级保健中抗生素处方的基础设施建设以改进医疗服务
Victoria Palin,Edward Tempest,Chirag Mistry et al.
Victoria Palin et al.
Introduction: The learning healthcare system (LHS) underpinned by data analysis and feedback to clinical care providers is thought to improve quality of care. The work aimed to implement an LHS for antibiotic prescribing ...
Development and validation of prediction rules to target care intensification in veteran patients with diabetes [0.03%]
糖尿病退伍军人患者护理加强干预预测规则的制定与验证
Heather M Campbell,Allison Murata,Gerald A Charlton et al.
Heather M Campbell et al.
Background: Diabetes affects 30.3 million people in the USA. Among these people, a major risk factor for microvascular complications is having a glycated haemoglobin (HbA1c) value of ≥75 mmol/mol; therefore, it would be ...
Limited evidence of benefits of patient operated intelligent primary care triage tools: findings of a literature review [0.03%]
智能初级诊疗甄别工具的效益证据不足：文献综述结果
Kristian Gottliebsen,Göran Petersson
Kristian Gottliebsen
Introduction: There is consistent evidence that the workload in general practices is substantially increasing. The digitalisation of healthcare including the use of artificial intelligence has been suggested as a solution...
Kathryn Moyse,Pamela Enderby,Katie Chadd et al.
Kathryn Moyse et al.
Background: Evidencing the impact of speech and language therapy interventions is challenging. The UK's professional body for speech and language therapists (SLTs) is supporting a consistent approach to outcome measuremen...
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals [0.03%]
一项预测脓毒症算法对患者死亡率、住院时长和再入院率影响的前瞻性多中心临床结果评估：来自美国医院实际患者的资料
Hoyt Burdick,Eduardo Pino,Denise Gabel-Comeau et al.
Hoyt Burdick et al.
Background: Severe sepsis and septic shock are among the leading causes of death in the USA. While early prediction of severe sepsis can reduce adverse patient outcomes, sepsis remains one of the most expensive conditions...
Multicenter Study
BMJ health & care informatics. 2020 Apr;27(1):e100109. DOI:10.1136/bmjhci-2019-100109 2020
Extending an open-source tool to measure data quality: case report on Observational Health Data Science and Informatics (OHDSI) [0.03%]
利用OHDSI系统测量大数据环境中的数据质量研究报告
Brian E Dixon,Chen Wen,Tony French et al.
Brian E Dixon et al.
Introduction: As the health system seeks to leverage large-scale data to inform population outcomes, the informatics community is developing tools for analysing these data. To support data quality assessment within such a...
Joey A Robaina,Tracey P Bastrom,Andrew C Richardson et al.
Joey A Robaina et al.
Background: Clinic 'no shows' (NS) can be a burden on the healthcare system, and efforts to minimise them can reduce lost revenue and improve patient care. Leveraging a large data set via the electronic health record (EHR...
Digital health interventions for chronic diseases: a scoping review of evaluation frameworks [0.03%]
针对慢性疾病的数字卫生干预措施评价框架的系统回顾
Nazli Bashi,Farhad Fatehi,Mahsa Mosadeghi-Nik et al.
Nazli Bashi et al.
Background: Monitoring and evaluations of digital health (DH) solutions for the management of chronic diseases are quite heterogeneous and evidences around evaluating frameworks are inconsistent. An evidenced-based framew...