The accessibility of healthcare resources is closely related to the well-being of residents. How to measure residents' access to healthcare services, how to delineate healthcare service divisions, and how to optimize the layout of service facilities are important contents of healthcare service planning? Mastering the theories, models and tools of healthcare service accessibility analysis, and accurately judging, analyzing and planning the temporal and spatial allocation of healthcare services, will effectively improve public healthcare policies and improve residents' well-being.
To advance this goal and encourage more researchers and students to participate in the spatial study of public health, the Spatial Data Lab* will organize an online Spatiotemporal Innovation Workshop for public health with a focus on the new methodology, technology and applications in assessing the spatial inequality of healthcare accessibility.
Requirement: The hands-on training workshop is free to apply and the number of participants is limited to 15 people. It is desirable that those applicants have some background in geographic analysis and public health. Each participant is expected to complete a homework project. Those who complete the course will receive a certificate, and outstanding students will be invited to join the research team of the Spatial Data Lab for Healthcare Study.
Agenda:
8:30pm - 11:00pm, October 12 - 15, October 2022 (U.S. Eastern Time)
October 12 (Day One): Introduction to KNIME Analytics Platform
Contents: (1) KNIME download and installation; (2) Environment configuration for script nodes; (3) Software interface and main functions; (4) Sample workflows; (5) Deployment of workflows on Knime Webportal (or KNIME Hub).
Assignment: (1) Install KNIME software on local PC; (2) load and execute KNIME workflows on local PC; (3) run the sample workflows on the KNIME Webportal.
October 13 (Day Two): Introduction to healthcare accessibility models and case study on healthcare inequality assessment
Contents: (1) Recent development of accessibility model of generalized two-step floating catchment area method (G2SFCA); (2) Case study on healthcare inequality assessment; (3) The workflow design for accessibility model; (4) The reproduction and expansion of the workflow, including data replacement, model modification, and analytical functions.
Assignment: Reproduce and expand the case study by replacing data, methods, or improve the visualization by groups.
October 15 (Day There): Presentation and discussion on the group report
Contents: Participants present their group work on expanded workflow with new data.
Application: To apply, please send your research interests and CV to spatialdatalab@lists.fas.harvard.edu before September 30, 2022 at 11:59pm (U.S. Eastern Time).
*The Spatial Data Lab is a joint project supported by the Center for Geographical Analysis at Harvard University, Future Data Lab, KNIME, and the NSF Spatiotemporal Innovation Center, which is designed to promote repeatable, replicable, and scalable spatiotemporal innovation research and global collaboration in related fields.
LOCATION: STATUS:CONFIRMED DTSTART:20221013T003000Z DTEND:20221016T030000Z END:VEVENT END:VCALENDAR