scholarly journals Informal carer's knowledge of traumatic brain injury questionnaire: Initial development and validation

Nursing Open ◽  
2021 ◽  
Author(s):  
Amena Awadh Bamatraf ◽  
Mei Chan Chong ◽  
Mazlina Mazlan ◽  
Chong Chin Che ◽  
Rista Fauziningtyas ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Initial Development ◽  
Development And Validation

Predicting Outcome after Traumatic Brain Injury: Development and Validation of a Prognostic Score Based on Admission Characteristics

2005 ◽  
Vol 22 (10) ◽  
pp. 1025-1039 ◽  
Author(s):  
Chantal W.P.M. Hukkelhoven ◽  
Ewout W. Steyerberg ◽  
J. Dik F. Habbema ◽  
Elana Farace ◽  
Anthony Marmarou ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Prognostic Score ◽  
Predicting Outcome ◽  
Development And Validation

scholarly journals tbiExtractor: A framework for extracting traumatic brain injury common data elements from radiology reports

2019 ◽  
Author(s):  
Margaret Mahan ◽  
Daniel Rafter ◽  
Hannah Casey ◽  
Marta Engelking ◽  
Tessneem Abdallah ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Gold Standard ◽  
High Sensitivity ◽  
Clinical Findings ◽  
Common Data Elements ◽  
Radiology Reports ◽  
Data Elements ◽  
Clinical Conditions ◽  
Development And Validation

ABSTRACTObjectiveThe manual extraction of valuable data from electronic medical records is cumbersome, error-prone, and inconsistent. By automating extraction in conjunction with standardized terminology, the quality and consistency of data utilized for research and clinical purposes would be substantially improved. Here, we set out to develop and validate a framework to extract pertinent clinical conditions for traumatic brain injury (TBI) from computed tomography (CT) reports.Materials and MethodsWe developed tbiExtractor, which extends pyConTextNLP, a regular expression algorithm using negation detection and contextual features, to create a framework for extracting TBI common data elements from radiology reports. The algorithm inputs radiology reports and outputs a structured summary containing 27 clinical findings with their respective annotations. Development and validation of the algorithm was completed using two physician annotators as the gold standard.ResultstbiExtractor displayed high sensitivity (0.92-0.94) and specificity (0.99) when compared to the gold standard. The algorithm also demonstrated a high equivalence (94.6%) with the annotators. A majority of clinical findings (85%) had minimal errors (F1 Score ≥ 0.80). When compared to annotators, tbiExtractor extracted information in significantly less time (0.3 sec vs 1.7 min per report).Discussion and ConclusiontbiExtractor is a validated algorithm for extraction of TBI common data elements from radiology reports. This automation reduces the time spent to extract structured data and improves the consistency of data extracted. Lastly, tbiExtractor can be used to stratify subjects into groups based on visible damage by partitioning the annotations of the pertinent clinical conditions on a radiology report.

scholarly journals Screening for Lifetime History of Traumatic Brain Injury Among Older American and Irish Adults at Risk for Dementia: Development and Validation of a Web-Based Survey

2020 ◽  
Vol 74 (2) ◽  
pp. 699-711
Author(s):  
Raquel C. Gardner ◽  
Ernesto Rivera ◽  
Megan O’Grady ◽  
Colin Doherty ◽  
Kristine Yaffe ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
At Risk ◽  
Brain Injury ◽  
Web Based ◽  
Lifetime History ◽  
History Of ◽  
Development And Validation

Development and validation of the Caregiver Empowerment Scale: A resource for working with family caregivers of persons with traumatic brain injury.

2011 ◽  
Vol 56 (3) ◽  
pp. 243-250 ◽  
Author(s):  
Charles Edmund Degeneffe ◽  
Fong Chan ◽  
Laura Dunlap ◽  
David Man ◽  
Connie Sung
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Family Caregivers ◽  
Development And Validation
Sign in / Sign up

Export Citation Format

Share Document