scholarly journals Comments on: involving service users in the qualitative analysis of patient narratives to support healthcare quality improvement

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Marney Williams ◽  
Mike Etkind ◽  
Fran Husson ◽  
Della Ogunleye ◽  
John Norton
Keyword(s):  
Quality Improvement ◽  
Data Analysis ◽  
Healthcare Quality ◽  
English Summary ◽  
Service Users ◽  
Research Projects ◽  
Period Analysis ◽  
Patient Narratives ◽  
Time Period ◽  
Alternative Approach

Plain English summary Some previous researchers (Locock et al) have written about what may be the best way for public contributors to be involved in data analysis in research projects. Their experience has been that giving public contributors large amounts of text to read is not the best use of their time and experience. They have recommended that a better approach would be for a researcher to meet with a group of users at the start of analysis, to discuss what to look out for. However, as another patient group that has been involved in analysis, we think differently. The approach we used was to be more fully involved in the project over a longer time period. Analysis tasks were broken down into stages to make it easier for those taking part. We found that this allowed us to take part fully without placing too much burden on us. We found that our approach was workable and successful and see no reason why it could not be applied in other circumstances. Abstract In this journal, Locock et al. have suggested that service users should not be overburdened with large amounts of data, and that eliciting users’ reflections on their experience at the start of analysis and using this as a guide to direct researcher attention during the remainder of the process may work better. As public contributors that have been involved in analysis we suggest an alternative approach in this brief letter, based on our own experiences.

scholarly journals Enhancing the healthcare quality improvement storyboard using photovoice

2020 ◽  
Vol 9 (4) ◽  
pp. e001104
Author(s):  
Pamela Mathura ◽  
Miriam Li ◽  
Natalie McMurtry ◽  
Narmin Kassam
Keyword(s):  
Quality Improvement ◽  
Healthcare Quality ◽  
Healthcare Quality Improvement

Finding the best examples of healthcare quality improvement in Sub-Saharan Africa

2010 ◽  
Vol 19 (5) ◽  
pp. 416-419 ◽  
Author(s):  
C. Liu ◽  
J. Babigumira ◽  
A. Chiunda ◽  
A. Katamba ◽  
I. Litvak ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Healthcare Quality ◽  
Sub Saharan Africa ◽  
Healthcare Quality Improvement ◽  
Sub Saharan

261 Using Technology to Improve Inpatient Surgical Lists

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
A Gowda ◽  
Z Chia ◽  
T Fonseka ◽  
K Smith ◽  
S Williams
Keyword(s):  
Quality Improvement ◽  
Patient Care ◽  
Junior Doctors ◽  
Research Projects ◽  
Point Scale ◽  
Improvement Project ◽  
Surgical Department ◽  
Team Meetings ◽  
And Training ◽  
Multi Disciplinary Team

Abstract Introduction Every day in our surgical department; prior to our quality improvement project, Junior Doctors spent on average 3.26 clinical hours maintaining 5 surgical inpatient lists of different specialities with accessibility of lists rated as “neutral” based on a 5-point scale from difficult to easy. Our hospital previously had lists stored locally on designated computers causing recurrent difficulties in accessing and editing these lists. Method We used surveys sent to clinicians to collect data. Cycle 1: Surgical Assessment Units list on Microsoft Teams Cycle 2: Addition of surgical specialities and wards lists onto Microsoft Teams. Cycle 3 (current): expand the use of Microsoft Teams to other specialities. Results Utilising technology led to a 25% reduction in time spent on maintaining inpatient lists, to 2.46 hours a day, and an improvement in the accessibility of lists to “easy”. Across a year, this saves over 220 hours clinician hours which can be used towards patient care and training. Furthermore, use of Microsoft Teams has improved communication and patient care, in the form of virtual regional Multi-Disciplinary Team meetings and research projects. Conclusions Microsoft Teams is currently free to all NHS organisations in England so there is potential for these efficiency savings to be replicated nationwide.

Pengaruh Kualitas Layanan, Nilai Nasabah, Kepercayaan dan Kepuasan Terhadap Loyalitas Nasabah Pengguna Layanan Mobile Banking Syariah

2020 ◽  
Vol 19 (3) ◽  
pp. 134-158
Author(s):  
Yulia Widi Astuti ◽  
Ratno Agriyanto ◽  
Ahmad Turmudzi
Keyword(s):  
Data Analysis ◽  
Service Quality ◽  
Customer Loyalty ◽  
Customer Value ◽  
Service Users ◽  
Mobile Banking ◽  
Banking Services ◽  
Insignificant Effect ◽  
Banking Service ◽  
The City

This study analyzes the effect of service quality, customer value, trust and satisfaction on customer loyalty at Bank Syariah Mandiri. The problem in this research is: how to increase customer loyalty of mobile banking service users at BSM. This study used 100 respondents using mobile banking services at BSM in the city of Semarang. Data analysis using SEM with the Smart PLS 3 computer program. The results showed that, among other things, service quality had a positive and insignificant effect on loyalty. Customer value has a positive and significant effect on loyalty. The effect of trust on customer loyalty has a positive and insignificant effect. Meanwhile, satisfaction has a positive and significant effect on loyalty.

Drilling Data Quality Management: Case Study With a Laboratory Scale Drilling Rig

2018 ◽  
Author(s):  
Suranga C. H. Geekiyanage ◽  
Dan Sui ◽  
Bernt S. Aadnoy
Keyword(s):  
Decision Making ◽  
Quality Improvement ◽  
Control System ◽  
Data Analysis ◽  
Quality Management ◽  
Data Quality ◽  
Incomplete Data ◽  
Laboratory Scale ◽  
Data Quality Management ◽  
Drilling Rig

Drilling industry operations heavily depend on digital information. Data analysis is a process of acquiring, transforming, interpreting, modelling, displaying and storing data with an aim of extracting useful information, so that the decision-making, actions executing, events detecting and incident managing of a system can be handled in an efficient and certain manner. This paper aims to provide an approach to understand, cleanse, improve and interpret the post-well or realtime data to preserve or enhance data features, like accuracy, consistency, reliability and validity. Data quality management is a process with three major phases. Phase I is an evaluation of pre-data quality to identify data issues such as missing or incomplete data, non-standard or invalid data and redundant data etc. Phase II is an implementation of different data quality managing practices such as filtering, data assimilation, and data reconciliation to improve data accuracy and discover useful information. The third and final phase is a post-data quality evaluation, which is conducted to assure data quality and enhance the system performance. In this study, a laboratory-scale drilling rig with a control system capable of drilling is utilized for data acquisition and quality improvement. Safe and efficient performance of such control system heavily relies on quality of the data obtained while drilling and its sufficient availability. Pump pressure, top-drive rotational speed, weight on bit, drill string torque and bit depth are available measurements. The data analysis is challenged by issues such as corruption of data due to noises, time delays, missing or incomplete data and external disturbances. In order to solve such issues, different data quality improvement practices are applied for the testing. These techniques help the intelligent system to achieve better decision-making and quicker fault detection. The study from the laboratory-scale drilling rig clearly demonstrates the need for a proper data quality management process and clear understanding of signal processing methods to carry out an intelligent digitalization in oil and gas industry.

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