BioMeT and algorithm measures: A proposed standardized evaluation framework (Preprint)

2019 ◽  
Author(s):  
Alan Godfrey ◽  
Jennifer Goldsack ◽  
Pamela Tenaerts ◽  
Clara Aranda ◽  
Azad Hussain ◽  
...  
Keyword(s):  
Healthcare Professionals ◽  
Evaluation Framework ◽  
Audit Trail ◽  
Digital Medicine ◽  
Fit For Purpose ◽  
Monitoring Technologies

UNSTRUCTURED Technology is advancing at extraordinary rates with novel data being generated which could potentially revolutionary different therapeutic areas of medicine. However, adoption is medicine is hampered by a lack of trust, particularly for biometric monitoring technologies (BioMeTs) where a key question facing frontline healthcare professionals is are BioMeTs fit for purpose? Here, we discuss pragmatic barriers and guidance regarding BioMeTs, cumulating in a proposed guidance framework to better inform their development and deployment in digital medicine. Furthermore, the framework proposes a process to establish an audit trail of BioMeTs (hardware and algorithms), to instil trust amongst multidisciplinary users.

scholarly journals Verification, Analytical Validation, and Clinical Validation (V3): The Foundation of Determining Fit-for-Purpose for Biometric Monitoring Technologies (BioMeTs) (Preprint)

2019 ◽  
Author(s):  
Jennifer Goldsack ◽  
Andrea Coravos ◽  
Jessie Bakker ◽  
Brinnae Bent ◽  
Ariel V. Dowling ◽  
...  
Keyword(s):  
Best Practices ◽  
Data Science ◽  
Evidence Base ◽  
Evaluation Framework ◽  
Clinical Validation ◽  
Analytical Validation ◽  
Science Data ◽  
Interdisciplinary Field ◽  
Digital Medicine ◽  
Monitoring Technologies

UNSTRUCTURED Digital medicine is an interdisciplinary field, drawing together stakeholders with expertise in engineering, manufacturing, clinical science, data science, biostatistics, regulatory considerations, ethics, patient advocacy, and healthcare policy, to name a few. While this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes 1) verification, 2) analytical validation, and 3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.

Impact of Fit-for-Purpose Monitoring on EOR Planning

2021 ◽  
Author(s):  
Jaime Eduardo Moreno ◽  
Yunlong Liu ◽  
Oluwale Talabi ◽  
Omer Gurpinar ◽  
Morten Kristensen ◽  
...  
Keyword(s):  
Control Strategies ◽  
Time Lapse ◽  
Monitoring Strategy ◽  
Reservoir Performance ◽  
Fit For Purpose ◽  
Reduce Risk ◽  
Pilot Design ◽  
Monitoring Technologies ◽  
Performance Heterogeneity ◽  
Structured Approach

Abstract Challenges in the design of efficient EOR field pilots have been discussed and documented in the industry, particularly when it comes to optimization of monitoring plans for technical and economical perspectives. This paper explores the benefits of pilot planning where the monitoring/control strategies are included in the early stages of the design to reduce risk of measurements ambiguity and ensure good quality pilot results evaluation. It addresses the use of new and existing technology in monitoring by highlighting the advantages and challenges of each alternative including potential pairing of complementary options to achieve the pilot objectives including illustration of the use of continuous and sporadic measurements on the evaluation. The proposed approach starts with a review of reservoir performance, heterogeneity and pilot objectives to ascertain the plausible monitoring technologies/strategies to aid during the pilot de-risking, followed by the identification of adequate novel and mature monitoring options, which are specific to EOR type and measurement nature (permanent, time lapse, etc.). Advantages of incorporating the monitoring strategy as integral part of the pilot design, as well as evaluation of the effectiveness/viability in the presence of uncertainty of the selected monitoring alternatives are discussed providing a reference of suitable/plausible EOR specific technologies. The paper illustrates the importance of selecting monitoring alternatives that feed off each other and the importance of using fit-for-purpose evaluation algorithms and a digitally enabled, structured approach to analyze and democratize pilot results and enable actionable decisions in operations.

scholarly journals Developing a framework for evaluating the impact of Healthcare Improvement Science Education across Europe: a qualitative study

2017 ◽  
Vol 14 ◽  
pp. 28 ◽  
Author(s):  
Manuel Lillo-Crespo ◽  
M. Cristina Sierras-Davó ◽  
Rhoda MacRae ◽  
Kevin Rooney
Keyword(s):  
Higher Education ◽  
Qualitative Methodology ◽  
Healthcare Professionals ◽  
Evaluation Framework ◽  
European Countries ◽  
Improvement Science ◽  
Healthcare Improvement ◽  
Kirkpatrick Model ◽  
European Higher Education ◽  
The Impact

Purpose: Frontline healthcare professionals are well positioned to improve the systems in which they work. Educational curricula, however, have not always equipped healthcare professionals with the skills or knowledge to implement and evaluate improvements. It is important to have a robust and standardized framework in order to evaluate the impact of such education in terms of improvement, both within and across European countries. The results of such evaluations will enhance the further development and delivery of healthcare improvement science (HIS) education. We aimed to describe the development and piloting of a framework for prospectively evaluating the impact of HIS education and learning.Methods: The evaluation framework was designed collaboratively and piloted in 7 European countries following a qualitative methodology. The present study used mixed methods to gather data from students and educators. The framework took the Kirkpatrick model of evaluation as a theoretical reference.Results: The framework was found to be feasible and acceptable for use across differing European higher education contexts according to the pilot study and the participants’ consensus. It can be used effectively to evaluate and develop HIS education across European higher education institutions.Conclusion: We offer a new evaluation framework to capture the impact of HIS education. The implementation of this tool has the potential to facilitate the continuous development of HIS education.

Philosophical issues of artificial intelligence and “smart” algorithms’ trust in medicine

2021 ◽  
Author(s):  
TS Georgiou
Keyword(s):  
Artificial Intelligence ◽  
Disease Prevention ◽  
Healthcare Professionals ◽  
Moral Obligations ◽  
Medical Sciences ◽  
The Past ◽  
Digital Medicine ◽  
The World

In this article, the author examines the philosophical issues associated with the introduction of artificial intelligence (AI) systems in medicine. Currently, the use of AI technologies in the field of medical sciences is one of the most important trends in the world of health. ‘Smart’ AI systems are able to learn from their own experience, adapt in the environment and, according to the parameters of the assigned tasks, can make decisions that in the past belonged only to humans. These AI technologies provide an opportunity to take diagnostics, treatment and disease prevention to a higher level. Particular attention is paid to the ethics and moral obligations of AI developers and healthcare professionals in the transition to such digital medicine.

scholarly journals Illegitimate HIS access by healthcare professionals: scenarios, use cases and audit trail-based detection model

2019 ◽  
Vol 164 ◽  
pp. 629-636
Author(s):  
Liliana Sá Correia ◽  
Ricardo Cruz Correia ◽  
Pedro Pereira Rodrigues
Keyword(s):  
Healthcare Professionals ◽  
Use Cases ◽  
Audit Trail ◽  
Detection Model

scholarly journals Fit‐for‐Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience

2020 ◽  
Author(s):  
Alan Godfrey ◽  
Benjamin Vandendriessche ◽  
Jessie P. Bakker ◽  
Cheryl Fitzer‐Attas ◽  
Ninad Gujar ◽  
...  
Keyword(s):  
Fit For Purpose ◽  
Monitoring Technologies

Implementation of DIPSA evaluation framework in the Integrated Health Information Systems in public hospitals in Cyprus (Preprint)

2019 ◽  
Author(s):  
Antonis Stylianides ◽  
Jonh Mantas ◽  
Zoe Roupa ◽  
Edna Yamasaki
Keyword(s):  
Regression Analysis ◽  
Healthcare Professionals ◽  
Pearson Correlation ◽  
Health Information Systems ◽  
Healthcare Services ◽  
Demographic Characteristics ◽  
Evaluation Framework ◽  
Public Hospitals ◽  
System Quality

BACKGROUND Ministry of Health of Cyprus has implemented Integrated Health Information Systems (IHIS) in two hospitals in Cyprus. Effective use of IHIS could increase the effectiveness and quality of healthcare services. The absence of any evaluation of the existing IHIS prevents a detailed assessment of its safety, efficiency and effectiveness. OBJECTIVE The purpose of this study was to implement DIPSA evaluation framework which assessed the safety, quality of the system, collaborative interprofessional work, user satisfaction and the processes and procedures in place of the current IHIS in public hospitals in Cyprus. METHODS This project was conducted in 2017 in Cyprus. Doctors, nurses and other healthcare professionals, in total 309 subjects participated in the study. For the selection of the sample, a stratified random sampling was used based on the profession and the hospital of each participant. DIPSA evaluation framework was implemented and inferential statistics were used. Correlations were performed between the categories in the framework with the Pearson correlation method. Comparison of means (with independent samples T-test and One-way Anova) were also done between demographic characteristics and categories, the tests that were found with P -value ≤ 2 were then used in multiple regression analysis. Data analysis was done using SPSS v24. RESULTS Categories Satisfaction, Collaboration, System quality, Safety, Procedures were all rated moderately between 2.5 and 2.9. Every correlation between the categories was statistically significant with P < 0.01, but the highest Pearson correlation = 0.692 was found to be between System Quality and Satisfaction. Comparison of means between demographic characteristics and categories were performed and used in multiple regression analysis, which indicated where exactly the IHIS lacks. In addition, the open questions pointed out the 5 most common problems/needs that healthcare professionals encounter in their jobs (training, system upgrade, keep a log of data/procedures, collaboration and access). CONCLUSIONS DIPSA evaluation framework was implemented, which showed that some interventions could positively affect simultaneously one or more categories. For example, the most important need of intervention was the training of healthcare professionals, that was found that it could be affecting positively multiple categories (Satisfaction, Collaboration, Safety and Procedures). Other interventions that could affect IHIS in a positive way could be, that technical support that should be provided at all times, to upgrade the hardware where needed. To schedule daily collaboration of healthcare professionals with programmers, in order to cover their needs, by upgrading the software. To install “smart devices” within the different departments of the hospitals in order to support each other. There are also many other suggestions can help improve the healthcare services provided.

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