scholarly journals 771 A NATIONAL US HEALTHCARE SYSTEM WEB-BASED COLONOSCOPY QUALITY REPORT CARD: ACCURATE, USABLE, AND ROBUST

2018 ◽  
Vol 87 (6) ◽  
pp. AB114-AB115
Author(s):  
Andrew J. Gawron ◽  
Yiwen Yao ◽  
William Thompson ◽  
Olga Patterson ◽  
Garrett G. Cole ◽  
...  
Keyword(s):  
Healthcare System ◽  
Report Card ◽  
Web Based ◽  
Quality Report ◽  
Colonoscopy Quality

scholarly journals Diabetes classification application with efficient missing and outliers data handling algorithms

2021 ◽  
Author(s):  
Hanaa Torkey ◽  
Elhossiny Ibrahim ◽  
EZZ El-Din Hemdan ◽  
Ayman El-Sayed ◽  
Marwa A. Shouman
Keyword(s):  
Deep Learning ◽  
Healthcare System ◽  
Wearable Sensors ◽  
Model Performance ◽  
Analysis Model ◽  
Human Errors ◽  
Web Based ◽  
Machine Learning Model ◽  
Complete Dataset ◽  
Smart Wearable

AbstractCommunication between sensors spread everywhere in healthcare systems may cause some missing in the transferred features. Repairing the data problems of sensing devices by artificial intelligence technologies have facilitated the Medical Internet of Things (MIoT) and its emerging applications in Healthcare. MIoT has great potential to affect the patient's life. Data collected from smart wearable devices size dramatically increases with data collected from millions of patients who are suffering from diseases such as diabetes. However, sensors or human errors lead to missing some values of the data. The major challenge of this problem is how to predict this value to maintain the data analysis model performance within a good range. In this paper, a complete healthcare system for diabetics has been used, as well as two new algorithms are developed to handle the crucial problem of missed data from MIoT wearable sensors. The proposed work is based on the integration of Random Forest, mean, class' mean, interquartile range (IQR), and Deep Learning to produce a clean and complete dataset. Which can enhance any machine learning model performance. Moreover, the outliers repair technique is proposed based on dataset class detection, then repair it by Deep Learning (DL). The final model accuracy with the two steps of imputation and outliers repair is 97.41% and 99.71% Area Under Curve (AUC). The used healthcare system is a web-based diabetes classification application using flask to be used in hospitals and healthcare centers for the patient diagnosed with an effective fashion.

scholarly journals Development of an automated ERCP Quality Report Card using structured data fields

2021 ◽  
Author(s):  
Gregory A. Coté ◽  
Badih Joseph Elmunzer ◽  
Erin Forster ◽  
Robert A. Moran ◽  
John G. Quiles ◽  
...  
Keyword(s):  
Report Card ◽  
Structured Data ◽  
Quality Report

636 Quantity and Quality: Web-Based Reporting of Colonoscopy Quality Metrics Throughout GI Fellowship

2015 ◽  
Vol 148 (4) ◽  
pp. S-124
Author(s):  
Rex Cheng ◽  
Bill Dewey ◽  
Carrie Silverman ◽  
Stephanie Park ◽  
Cynthia W. Ko ◽  
...  
Keyword(s):  
Quality Metrics ◽  
Web Based ◽  
Colonoscopy Quality

scholarly journals 2426 Fostering cross-disciplinary research: Lessons learned from STTEP-UP

2018 ◽  
Vol 2 (S1) ◽  
pp. 56-56 ◽  
Author(s):  
Hannibal Person ◽  
Adjoa R. Smalls-Mantey ◽  
Oluwasheyi Ayeni ◽  
Dagmar Hernandez-Saurez ◽  
Emma K. T. Benn ◽  
...  
Keyword(s):  
Healthcare System ◽  
Lessons Learned ◽  
Virtual Learning Environment ◽  
Provider Education ◽  
Research Strategies ◽  
Web Based ◽  
Protected Time ◽  
Study Population ◽  
Group Brainstorming ◽  
New Research

OBJECTIVES/SPECIFIC AIMS: N/A. METHODS/STUDY POPULATION: N/A. RESULTS/ANTICIPATED RESULTS: N/A. DISCUSSION/SIGNIFICANCE OF IMPACT: There is an increasing need to foster cross-disciplinary research to address complex problems within healthcare. The Sinai Team-based Translational Education Program: the URM Propeller (STTEP-UP) is a NCATS funded program through the Icahn School of Medicine at Mount Sinai. Its goal is to facilitate URM post-doctoral trainees becoming innovative leaders in clinical and translational research. The program includes a team-based research component, where fellows collaborate on a project. This year, disciplines represented by the four fellows include Cardiology, Psychiatry, Neurology, and Pediatrics. Identifying a clinical question and designing an investigation was facilitated by group brainstorming meetings with program mentors. Fellows designed a project to identify medical testing and prescribing that were not clinically indicated throughout the healthcare system, with the goal of exploring whether an intervention, including provider education, could reduce ordering practices. In addition to regular in-person meetings, a licensed virtual learning environment and free web-based sharing platform were used to foster collaboration. Challenges faced throughout this process, included fellows struggling to find protected time, difficulties accessing broad sets of data across the healthcare system, and overcoming administrative barriers between departments. Strengths of this approach, included fellows learning new research strategies and feeling a deeper sense of commonality with their peers. Overall, this experience supports the idea that cross-disciplinary research improves the collaboration and education of emerging researchers. However, addressing logistical and systems-based barriers may better facilitate this education and research.

Paramedic prescribing: implementation in practice

2021 ◽  
Vol 13 (1) ◽  
pp. 14-23
Author(s):  
Pete Best ◽  
Vanessa Taylor
Keyword(s):  
Healthcare System ◽  
Educational Background ◽  
Pathways To Care ◽  
Patient Access ◽  
Web Based ◽  
Convenience Sampling

Background: In April 2018, legislation was changed to allow paramedics to prescribe independently. There is limited research regarding how paramedics are implementing their prescribing qualification. Policy papers and other literature were largely written before April 2018 and therefore document expectations regarding prescribing paramedics within the healthcare system. Aim: To explore if paramedic prescribing is being practised as expected. This article reports part of a larger study that explored how paramedics are implementing their prescribing qualification in practice more broadly. Methods: A web-based survey was conducted using convenience sampling. The sample represents 14.65% of the total number of prescribing paramedics. Findings: Paramedics are working in a variety of areas of healthcare. Some paramedics do not have the required amount of experience or the educational background recommended to become a prescribing paramedic. It is unlikely that new pathways to care are being created by prescribing paramedics. It is unclear whether prescribing increases patient access to medications.

scholarly journals Quality Management System: Analisis Raport Mutu Usaha Kesehatan Sekolah (UKS)

2020 ◽  
Vol 10 (2) ◽  
pp. 112-121
Author(s):  
Sapto Irawan ◽  
Danu Prasetyo
Keyword(s):  
Quality Management ◽  
School Health ◽  
Quality Management System ◽  
Healthy Lifestyle ◽  
Report Card ◽  
Real Condition ◽  
Achievement Score ◽  
Report Analysis ◽  
Quality Report ◽  
One Year

This quality report analysis was conducted to see the quality achievement of SMK PGRI 1 Salatiga in one year for School Health Efforts (UKS) in 2018. This research describes descriptively both qualitatively and quantitatively the results of the quality report card achievement. It was shown that the achievement score in the School Health Business Report Card (UKS) was 6.6 with the category of UKS 4. Referring to the results of the analysis of the description above, it showed that the achievement report had obtained the four-star category. Validation of the achievement of the School Health Effort report card (UKS) is needed to show the real condition of the school. The achievement of the four-star category is strongly influenced by two important factors in its implementation, namely: 1) the awareness of all school members to realize a healthy lifestyle; 2) the facilities and infrastructure support in realizing healthy living behavior.

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