scholarly journals Data, Information, Evidence, and Knowledge: A Proposal for Health Informatics and Data Science

2019 ◽  
Vol 10 (3) ◽  
Author(s):  
Olaf Dammann
Keyword(s):  
Health Informatics ◽  
Data Science ◽  
The Status ◽  
Repeatability And Reproducibility ◽  
Dikw Hierarchy

In this commentary , I revisit and modify Ackoff’s data-information-knowledge-wisdom (DIKW) hierarchy. I suggest to de-emphasize the wisdom part and to insert evidence between information and knowledge (DIEK). This framework defines data as raw symbols, which become information when they are contextualized. Information achieves the status of evidence in comparison to relevant standards. Evidence is used to test hypotheses and is transformed into knowledge by success and consensus. As checkpoints for the transition from evidence to knowledge I suggest relevance, robustness, repeatability, and reproducibility.

scholarly journals Evaluation Considerations for Secondary Uses of Clinical Data: Principles for an Evidence-based Approach to Policy and Implementation of Secondary Analysis

2017 ◽  
Vol 26 (01) ◽  
pp. 59-67 ◽  
Author(s):  
P. J. Scott ◽  
M. Rigby ◽  
E. Ammenwerth ◽  
J. McNair ◽  
A. Georgiou ◽  
...  
Keyword(s):  
Clinical Data ◽  
Health Informatics ◽  
Best Practice ◽  
Data Science ◽  
Clinical Performance ◽  
Secondary Analysis ◽  
Health Data ◽  
Evidence Based ◽  
Great Expectations ◽  
Scientific Context

Summary Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon “Big Data” and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics.

Data Science in Health Informatics

2021 ◽  
pp. 299-340
Author(s):  
Behzad Soleimani Neysiani ◽  
Nasim Soltani ◽  
Saeed Doostali ◽  
Mohammad Shiralizadeh Dezfoli ◽  
Zahra Aminoroaya ◽  
...  
Keyword(s):  
Health Informatics ◽  
Data Science

Kaitiakitanga and Health Informatics

2011 ◽  
pp. 1342-1350
Author(s):  
Robyn Kamira
Keyword(s):  
New Zealand ◽  
Health Informatics ◽  
Health Sector ◽  
Collective Ownership ◽  
Cultural Concepts ◽  
Aotearoa New Zealand ◽  
The Status

Indigenous contributions to governance in health informatics can be drawn from cultural concepts such as Kaitiakitanga, which implies guardianship, stewardship, governance and responsibility roles. This chapter explores Kaitiakitanga, its potential implementation in the Aotearoa (New Zealand) health sector, and its contributions to our thinking. After decades of unsuccessful attempts to positively shift the status of health for Maori, we must ask whether more control by Maori over information about Maori will make a difference. Kaitiakitanga enables us to explore Maori perspectives and insights about health and information and calls for stronger inclusion of Maori in decisions. It acts as a guideline to address ongoing and complex issues such as collective ownership, the responsible publication of data and whether benefits in health for Maori can be explicitly declared and met.

scholarly journals Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

2020 ◽  
Vol 12 (22) ◽  
pp. 3690 ◽  
Author(s):  
Angela Lausch ◽  
Michael E. Schaepman ◽  
Andrew K. Skidmore ◽  
Sina C. Truckenbrodt ◽  
Jörg M. Hacker ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Science ◽  
Cost Effective ◽  
Trait Variation ◽  
The Past ◽  
Objective Monitoring ◽  
The Status ◽  
Close Range ◽  
Hyperspectral Sensor

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

scholarly journals Evaluation Considerations for Secondary Uses of Clinical Data: Principles for an Evidence-based Approach to Policy and Implementation of Secondary Analysis

2017 ◽  
Vol 26 (01) ◽  
pp. 59-67 ◽  
Author(s):  
P. J. Scott ◽  
M. Rigby ◽  
E. Ammenwerth ◽  
J. McNair ◽  
A. Georgiou ◽  
...  
Keyword(s):  
Clinical Data ◽  
Health Informatics ◽  
Best Practice ◽  
Data Science ◽  
Clinical Performance ◽  
Secondary Analysis ◽  
Health Data ◽  
Evidence Based ◽  
Great Expectations ◽  
Scientific Context

Summary Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon “Big Data” and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics.

scholarly journals Future Direction of IMIA Standardization

2014 ◽  
Vol 23 (01) ◽  
pp. 105-109 ◽  
Author(s):  
M. Kimura ◽  
S. Ogishima ◽  
A. Shabo ◽  
I. K. Kim ◽  
C. Parisot ◽  
...  
Keyword(s):  
Health Care ◽  
Health Informatics ◽  
Global Alliance ◽  
Development Organizations ◽  
Health Care Informatics ◽  
Integrating The Healthcare Enterprise ◽  
The Status ◽  
Future Direction ◽  
Care Informatics ◽  
Standard Development

Summary Objectives: Standardization in the field of health informatics has increased its importance and global alliance for establishing interoperability and compatibility internationally. Standardization has been organized by standard development organizations (SDOs) such as ISO (International Organization for Standardization), CEN (European Committee for Standardization), IHE (Integrating the Healthcare Enterprise), and HL7 (Health Level 7), etc. This paper reports the status of these SDOs’ activities. Methods: In this workshop, we reviewed the past activities and the current situation of standardization in health care informatics with the standard development organizations such as ISO, CEN, IHE, and HL7. Then we discussed the future direction of standardization in health informatics toward “future medicine” based on standardized technologies. Results: We could share the status of each SDO through exchange of opinions in the workshop. Some WHO members joined our discussion to support this constructive activity. Conclusion: At this meeting, the workshop speakers have been appointed as new members of the IMIA working groups of Standards in Health Care Informatics (WG16). We could reach to the conclusion that we collaborate for the international standardization in health informatics toward “future medicine”.

scholarly journals Informatics for Health 2017: Advancing both science and practice

2017 ◽  
Vol 24 (1) ◽  
pp. 1 ◽  
Author(s):  
Philip J. Scott ◽  
Ronald Cornet ◽  
Colin McCowan ◽  
Niels Peek ◽  
Paolo Fraccaro ◽  
...  
Keyword(s):  
Big Data ◽  
Medical Informatics ◽  
Health Informatics ◽  
Data Science ◽  
Digital Health ◽  
Health It ◽  
Special Issue ◽  
Organizational Intervention ◽  
Policy Makers ◽  
Multi Level

Introduction: The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress.Discussion: The twin programmes of “Big Data” and “Digital Health” are not always joined up by coherent policy and investment priorities. Substantial global investment in health IT and data science has led to sound progress but highly variable outcomes. Society needs an approach that brings together the science and the practice of health informatics. The goal is multi-level Learning Health Systems that consume and intelligently act upon both patient data and organizational intervention outcomes.Conclusions: Informatics for Health demonstrated the art of the possible, seen in the breadth and depth of our contributions. We call upon policy makers, research funders and programme leaders to learn from this joined-up approach.

Digital continuous healthcare and disruptive medical technologies: m-Health and telemedicine skills training for data-driven healthcare

2018 ◽  
Vol 25 (10) ◽  
pp. 623-635 ◽  
Author(s):  
A Hasan Sapci ◽  
H Aylin Sapci
Keyword(s):  
Health Informatics ◽  
Data Science ◽  
Medical Information ◽  
Training Session ◽  
Skills Training ◽  
Application Development ◽  
Healthcare Applications ◽  
Wireless Monitoring ◽  
Medical Technologies ◽  
Monitoring Devices

Introduction Disruptive medical technologies, wearable devices and new diagnostic solutions have been shaping the future of healthcare, and the health informatics skills gap has become a major problem for technology-centric healthcare applications. This study evaluated the relationships between a specific practical skills training method and students' confidence in using wireless monitoring devices along with the attitude towards technology adoption. Methods Six practical exercises were developed to provide health informatics technical skills to transfer medical information and display multi-channel biological signals. Two hundred and six undergraduate nursing students received a telemedicine and homecare training course. Their familiarity with various data formats and likelihood to recommend telemedicine and remote monitoring applications were measured. Results The skills training session changed students' attitudes towards remote patient monitoring, and the majority of students provided positive feedback about their confidence in using wireless monitoring devices after the training session. Students stated their plans to use the technology when they start practising and to educate their patients to promote the use of telemedicine. Conclusion We propose a skills training framework that covers (a) telemedicine, (b) m-Health and connected health, (c) health informatics application development, (d) health informatics device innovation, and (e) data science.

scholarly journals #Datasaveslives: mixed methods analysis of a social media campaign to promote the benefits of using health data for research purposes (Preprint)

2019 ◽  
Author(s):  
Lamiece Hassan ◽  
Goran Nenadic ◽  
Mary Patricia Tully
Keyword(s):  
Social Media ◽  
Health Informatics ◽  
Data Science ◽  
Health Data ◽  
Media Campaign ◽  
Wide Audience ◽  
Personal Support ◽  
Twitter Users ◽  
The Uk ◽  
The Impact

BACKGROUND Social media provides the potential to engage a wide audience about scientific research, including the public. However little empirical research exists to guide health scientists regarding what works and how to optimize impact. We examined the social media campaign #datasaveslives, which was established in 2014 to highlight positive examples of the use and reuse of health data in research. OBJECTIVE The study aimed to examine how the #datasaveslives hashtag was used on social media, how often and by whom; thus, the study aimed to provide insights into the impact of a major social media campaign in the UK health informatics research community and further afield. METHODS We analyzed all publicly available posts (tweets) between 1 September 2016 and 31 August 2017 on the microblogging platform Twitter that included the hashtag #datasaveslives (n=13,895). Using a combination of qualitative and quantitative analyses, we determined the frequency and purpose of tweets. Social network analysis was used to analyze and visualize tweet sharing (‘retweet’) networks among hashtag users. RESULTS Overall, we found 4,175 original tweets and 9,720 retweets featuring #datasaveslives by 3,649 unique Twitter users. In total, 2,756 (66.0%) of original posts were retweeted at least once. Higher frequencies of tweets were observed during the weeks of prominent policy publications, popular conferences and public engagement events. Cluster analysis based on retweet relationships revealed an interconnected series of groups of #datasaveslives users in academia, health services and policy, and charities and patient networks. Thematic analysis of tweets showed that #datasaveslives was used for a broader range of purposes than indexing information, including event reporting, encouraging participation and action, and showing personal support for data sharing. CONCLUSIONS This study shows that a hashtag-based social media campaign was effective in encouraging a wide audience of stakeholders to disseminate positive examples of health research. Furthermore, the findings suggest the campaign supported community-building and bridging practices within and between the interdisciplinary sectors related to the field of health data science and encouraged individuals to demonstrate personal support for sharing health data. CLINICALTRIAL

Sign in / Sign up

Export Citation Format

Share Document