{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/125167"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/125167","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Application of Visualization-based Analytic Methods in Population Health and Health Services Research to Rehabilitation Sciences","abstract":"Visualization-based analytic methods have evolved rapidly over the last two decades, allowing knowledge generation from large healthcare datasets. However, their application in the rehabilitation sciences, particularly related to population health and health services research is limited. This research is divided into two main parts. The first presents two systematic literature syntheses of two information visualization methods, visual analytics and interactive visualization, both applied in these areas of healthcare. The second part presents two use cases illustrating the application of these methods. The first use case is an interactive visualization dashboard prototype for the Canadian Institute for Health Information's Population Grouping Methodology, where the candidate was placed as an embedded fellow. The second use case presents a proof-of-principle dashboard exploring data on rehospitalizations from a multicenter practice-based evidence study on outcomes of persons with spinal cord injury. Rehabilitation health services' research can benefit from the use of visualization-based methods alone or combined with exploratory visual and confirmatory statistical analysis to advance the field. In addition, this thesis highlights the opportunity for organizations to leverage embedded research for advancing and improving healthcare through integrated knowledge translation initiatives and building Learning Health Systems inclusive of rehabilitation services.","abstract_html":"Visualization-based analytic methods have evolved rapidly over the last two decades, allowing knowledge generation from large healthcare datasets. However, their application in the rehabilitation sciences, particularly related to population health and health services research is limited. This research is divided into two main parts. The first presents two systematic literature syntheses of two information visualization methods, visual analytics and interactive visualization, both applied in these areas of healthcare. The second part presents two use cases illustrating the application of these methods. The first use case is an interactive visualization dashboard prototype for the Canadian Institute for Health Information's Population Grouping Methodology, where the candidate was placed as an embedded fellow. The second use case presents a proof-of-principle dashboard exploring data on rehospitalizations from a multicenter practice-based evidence study on outcomes of persons with spinal cord injury. Rehabilitation health services' research can benefit from the use of visualization-based methods alone or combined with exploratory visual and confirmatory statistical analysis to advance the field. In addition, this thesis highlights the opportunity for organizations to leverage embedded research for advancing and improving healthcare through integrated knowledge translation initiatives and building Learning Health Systems inclusive of rehabilitation services.","abstract_has_math":false,"creators":["Chishtie, Jawad Ahmed"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Rehabilitation Science","school":null,"contributors":[],"advisors":["Jaglal, Susan B."],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-11","date_published":"2022-11","updated_at":"2026-07-27T21:28:20Z","subjects":["data visualization","health services research","population health","rehabilitation","visual analytics"],"languages":[],"rights":["Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/125167","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Jaglal, Susan B."]},{"key":"dc:contributor.department","label":"Department","values":["Rehabilitation Science"]},{"key":"dc:creator","label":"Author","values":["Chishtie, Jawad Ahmed"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-11"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-11-11T17:08:14Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-11-11T17:08:14Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-11"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["data visualization","health services research","population health","rehabilitation","visual analytics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/125167"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Visualization-based analytic methods have evolved rapidly over the last two decades, allowing knowledge generation from large healthcare datasets. However, their application in the rehabilitation sciences, particularly related to population health and health services research is limited. This research is divided into two main parts. The first presents two systematic literature syntheses of two information visualization methods, visual analytics and interactive visualization, both applied in these areas of healthcare. The second part presents two use cases illustrating the application of these methods. The first use case is an interactive visualization dashboard prototype for the Canadian Institute for Health Information's Population Grouping Methodology, where the candidate was placed as an embedded fellow. The second use case presents a proof-of-principle dashboard exploring data on rehospitalizations from a multicenter practice-based evidence study on outcomes of persons with spinal cord injury. Rehabilitation health services' research can benefit from the use of visualization-based methods alone or combined with exploratory visual and confirmatory statistical analysis to advance the field. In addition, this thesis highlights the opportunity for organizations to leverage embedded research for advancing and improving healthcare through integrated knowledge translation initiatives and building Learning Health Systems inclusive of rehabilitation services."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Application of Visualization-based Analytic Methods in Population Health and Health Services Research to Rehabilitation Sciences"]}]}],"canonical_facts":{"dc:contributor.advisor":["Jaglal, Susan B."],"dc:contributor.department":["Rehabilitation Science"],"dc:creator":["Chishtie, Jawad Ahmed"],"dc:date":["2022-11"],"dc:date.accessioned":["2022-11-11T17:08:14Z"],"dc:date.available":["2022-11-11T17:08:14Z"],"dc:date.issued":["2022-11"],"dc:description.abstract":["Visualization-based analytic methods have evolved rapidly over the last two decades, allowing knowledge generation from large healthcare datasets. However, their application in the rehabilitation sciences, particularly related to population health and health services research is limited. This research is divided into two main parts. The first presents two systematic literature syntheses of two information visualization methods, visual analytics and interactive visualization, both applied in these areas of healthcare. The second part presents two use cases illustrating the application of these methods. The first use case is an interactive visualization dashboard prototype for the Canadian Institute for Health Information's Population Grouping Methodology, where the candidate was placed as an embedded fellow. The second use case presents a proof-of-principle dashboard exploring data on rehospitalizations from a multicenter practice-based evidence study on outcomes of persons with spinal cord injury. Rehabilitation health services' research can benefit from the use of visualization-based methods alone or combined with exploratory visual and confirmatory statistical analysis to advance the field. In addition, this thesis highlights the opportunity for organizations to leverage embedded research for advancing and improving healthcare through integrated knowledge translation initiatives and building Learning Health Systems inclusive of rehabilitation services."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/125167"],"dc:rights":["Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["data visualization","health services research","population health","rehabilitation","visual analytics"],"dc:title":["Application of Visualization-based Analytic Methods in Population Health and Health Services Research to Rehabilitation Sciences"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:20Z"}