scholarly journals Web Based Medical Knowledge Extraction Form to Take Out Medical Observation

Author(s):  
R. Kamalakannan
JAMIA Open ◽  
2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jana L Anderson ◽  
e Silva Lucas Oliveira J ◽  
Juan P Brito ◽  
Ian G Hargraves ◽  
Erik P Hess

Abstract Objective The overuse of antibiotics for acute otitis media (AOM) in children is a healthcare quality issue in part arising from conflicting parent and physician understanding of the risks and benefits of antibiotics for AOM. Our objective was to develop a conversation aid that supports shared decision making (SDM) with parents of children who are diagnosed with non-severe AOM in the acute care setting. Materials and Methods We developed a web-based encounter tool following a human-centered design approach that includes active collaboration with parents, clinicians, and designers using literature review, observations of clinical encounters, parental and clinician surveys, and interviews. Insights from these processes informed the iterative creation of prototypes that were reviewed and field-tested in patient encounters. Results The ear pain conversation aid includes five sections: (1) A home page that opens the discussion on the etiologies of AOM; (2) the various options available for AOM management; (3) a pictograph of the impact of antibiotic therapy on pain control; (4) a pictograph of complication rates with and without antibiotics; and (5) a summary page on management choices. This open-access, web-based tool is located at www.earpaindecisionaid.org. Conclusions We collaboratively developed an evidence-based conversation aid to facilitate SDM for AOM. This decision aid has the potential to improve parental medical knowledge of AOM, physician/parent communication, and possibly decrease the overuse of antibiotics for this condition.


2017 ◽  
Author(s):  
Andrew George Alexander ◽  
Deborah Deas ◽  
Paul Eric Lyons

BACKGROUND Imaging and its optimal use are imperative to the practice of medicine, yet many students don’t receive a formal education in radiology. Concurrently, students look for ways to take time away from medical school for residency interviewing. Web-based instruction provides an opportunity to combine these imperatives using online modalities. OBJECTIVE A largely Web-based course in radiology during the 4th year of medical school was evaluated both for its acceptance to students who needed to be away from campus for interviews, and its effectiveness on a nationally administered standardized test. METHODS All students were placed into a structured program utilizing online videos, online modules, online textbook assignments, and live interactive online lectures. Over half of the course could be completed away from campus. The Alliance of Medical Student Educators in Radiology test exam bank was used as a final exam to evaluate medical knowledge. RESULTS Positive student feedback included the freedom to travel for interviews, hands-on ultrasound training, interactive teaching sessions, and quality Web-based learning modules. Negative feedback included taking quizzes in-person, a perceived outdated online textbook, and physically shadowing hospital technicians. Most students elected to take the course during the interview months of October through January. The Alliance of Medical Student Educators in Radiology final exam results (70.5%) were not significantly different than the national cohort (70%) who took the course in-person. Test scores from students taking the course during interview travel months were not significantly different from students who took the course before (P=.30) or after (P=.34) the interview season. CONCLUSIONS Students desire to learn radiology and often choose to do so when they need to be away from campus during the fall of their 4th year of study to accomplish their residency interviews. Web-based education in radiology allows students’ interview traveling and radiology course objectives to be successfully met without adversely affecting the outcomes on a nationally normed examination in radiology. A curriculum that includes online content and live Web-based teleconference access to faculty can accomplish both imperatives.


2007 ◽  
Vol 30 (4) ◽  
pp. 69
Author(s):  
S. Glover Takahashi ◽  
D. Martin ◽  
S. Verma ◽  
S. Edwards

This paper is a retrospective study reporting on the development of remediation plans for residents who are having difficulty meeting the established program goals and objectives. Additionally, the paper describes the implementation of a consistent, competency focused approach to remediation using a standardized needs assessment and intervention planning tool has functioned to better manage difficulty. First, the paper provides a profile of the educational needs of 20 recent cases describing their specialty programs, training levels and the competency areas of difficulty. Next the paper outlines an educational inquiry tool used by residency program directors to develop, implement and evaluate the trainee’s remediation programs. The tool includes inquiry questions which the faculty answer in the development of a customized remedial educational plan in the such areas as: trainee background, trainee information, overall rationale for remediation plan, training profile, purpose of remediation, details of remediation plan, anticipated outcome of remediation plan, other factors impacting trainee success. The tool is designed to be reviewed with trainee input to ensure the desired outcomes and process for the remediation plan are transparent for both the trainee and program director. Finally three case studies are described in detail including of the types of problems that lead to remediation, examples of the remediation plans developed and the range of approaches employed to support the success of residents. The paper then summarizes the identified key issues and options in optimizing success for residents in difficulty. Christopher I, Doty CI, Lucchesi M. The Value of a Web-based Testing System to Identify Residents Who Need Early Remediation: What Were We Waiting For? Acad Emerg Med 11(3):324. Beeson MS, Jwayyed S. Development of a Specialty-wide Web-based Medical Knowledge Assessment Tool for Resident Education. Acad. Emerg. Med 2004 (Mar); 11(3):324. Boiselle PM. Remedy for Resident Evaluation and Remediation, Academic Radiology 2005(July); 12(7):894-900.


2020 ◽  
Author(s):  
Feihong Yang ◽  
Jiao Li

BACKGROUND Question answering (QA) system is widely used in web-based health-care applications. Health consumers likely asked similar questions in various natural language expression due to the lack of medical knowledge. It’s challenging to match a new question to previous similar questions for answering. In health QA system development, question matching (QM) is a task to judge whether a pair of questions express the same meaning and is used to map the answer of matched question in the given question-answering database. BERT (i.e. Bidirectional Encoder Representations from Transformers) is proved to be state-of- the-art model in natural language processing (NLP) tasks, such as binary classification and sentence matching. As a light model of BERT, ALBERT is proposed to address the huge parameters and low training speed problems of BERT. Both of BERT and ALBERT can be used to address the QM problem. OBJECTIVE In this study, we aim to develop an ALBERT based method for Chinese health related question matching. METHODS Our proposed method, named as ALBERT-QM, consists of three components. (1)Data augmenting. Similar health question pairs were augmented for training preparation. (2)ALBERT model training. Given the augmented training pairs, three ALBERT models were trained and fine-tuned. (3)Similarity combining. Health question similarity score were calculated by combining ALBRT model outputs with text similarity. To evaluate our ALBERT-QM performance on similar question identification, we used an open dataset with 20,000 labeled Chinese health question pairs. RESULTS Our ALBERT-QM is able to identify similar Chinese health questions, achieving the precision of 86.69%, recall of 86.70% and F1 of 86.69%. Comparing with baseline method (text similarity algorithm), ALBERT-QM enhanced the F1-score by 20.73%. Comparing with other BERT series models, our ALBERT-QM is much lighter with the files size of 64.8MB which is 1/6 times that other BERT models. We made our ALBERT-QM open accessible at https://github.com/trueto/albert_question_match. CONCLUSIONS In this study, we developed an open source algorithm, ALBERT-QM, contributing to similar Chinese health questions identification in a health QA system. Our ALBERT-QM achieved better performance in question matching with lower memory usage, which is beneficial to the web-based or mobile-based QA applications.


Sign in / Sign up

Export Citation Format

Share Document