Automated Author ProfileInstitute For Global Health
Institute For Global Health
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
<br /><strong>Background:</strong> To ensure countries can effectively benefit from digital health investments, digital adaptation kits (DAKs) are designed to facilitate the accurate reflection of clinical, public health and data use guidelines within the digital systems countries are adopting. DAKs are operational, software-neutral, standardized documentation that distill clinical, public health and data use guidance into a format that can be transparently incorporated into digital systems. <br /> <br /><strong>Objectives:</strong> This DAK provides operational requirements for implementing Smart Discharges recommendations in digital systems. With a focus on discharge care, this DAK aims to provide a common language across various audiences – discharge and other programme managers, software developers, and implementers of digital systems – to ensure a common understanding of the appropriate health information content within a defined health programme area, as a mechanism to catalyse the effective use of these digital systems. The key objectives of this DAK are:<ul style=“list-style-type:square”> <li>to ensure adherence to clinical, public health and data use guidelines, and facilitate consistency of the health content that is used to inform the development of a patient-centred digital tracking and decision-support (DTDS) system;</li> <li>to enable both health programme leads and digital health teams (including software developers) to have a joint understanding of the health content within the digital system, with a transparent mechanism to review the validity and accuracy of the health content; and</li> <li>to provide a starting point of the core data elements and decision-support logic that should be included within DTDS systems for Smart Discharges.</li></ul> <br /><strong>Acknowledgements:</strong> The Institute for Global Health (IGH) is grateful for the contributions of its collaborators. This digital adaptation kit was coordinated by Peter Lewis, Charly Huxford, Jessica Trawin, Dustin Dunsmuir, Matthew Wiens, and Mark Ansermino of IGH; and Clare Komugisha of the World Alliance for Lung and Intensive Care Medicine in Uganda (WALIMU). <br />
Authors
- Institute For Global Health
<br /><strong>Objective(s):</strong> To ensure countries can effectively benefit from digital health investments, digital adaptation kits (DAKs) are designed to facilitate the accurate reflection of clinical, public health and data use guidelines within the digital systems countries are adopting. DAKs are operational, software-neutral, standardized documentation that distill clinical, public health and data use guidance into a format that can be transparently incorporated into digital systems. <br/> <br /><strong>Objective(s):</strong> This DAK provides operational requirements for implementing Smart Triage recommendations in digital systems. With a focus on triage care, this DAK aims to provide a common language across various audiences – triage and other programme managers, software developers, and implementers of digital systems – to ensure a common understanding of the appropriate health information content within a defined health programme area, as a mechanism to catalyse the effective use of these digital systems. The key objectives of this DAK are: <ul> <li> to ensure adherence to clinical, public health and data use guidelines, and facilitate consistency of the health content that is used to inform the development of a patient-centred digital tracking and decision-support (DTDS) system; <li> to enable both health programme leads and digital health teams (including software developers) to have a joint understanding of the health content within the digital system, with a transparent mechanism to review the validity and accuracy of the health content; and <li> to provide a starting point of the core data elements and decision-support logic that should be included within DTDS systems for Smart Triage. </ul> <br /><strong>Acknowledgements:</strong> The Institute for Global Health (IGH) is grateful for the contributions of its collaborators. This digital adaptation kit was coordinated by Dustin Dunsmuir, Charly Huxford, Yashodani Pillay, Justine Behan, and Mark Ansermino of IGH; and Fredson Tusingwire and Aine Ivan Aye Ashebukara of the World Alliance for Lung and Intensive Care Medicine in Uganda (WALIMU).
Authors
- Institute For Global Health