Development of a digital dashboard to address population-level obesity using electronic medical record data.
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| Titel: | Development of a digital dashboard to address population-level obesity using electronic medical record data. |
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| Autoren: | Canfell OJ; Department of Nutritional Sciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 9NH, UK.; School of Public Health, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Burton-Jones A; UQ Business School, Faculty of Business, Economics, and Law, The University of Queensland, St Lucia, Qld, Australia., Eakin E; School of Public Health, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Woods L; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Macklin S; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Austin J; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Philip R; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Lim HC; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Ahmed KR; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia., Slade C; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia.; Institute of Teaching and Learning Innovation, The University of Queensland, St Lucia, Qld, Australia., Francis D; Metro North Hospital and Health Service, Department of Health, Queensland Government, Herston, Qld, Australia., Sullivan C; Queensland Digital Health Centre, Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia.; Metro North Hospital and Health Service, Department of Health, Queensland Government, Herston, Qld, Australia. |
| Quelle: | Public health research & practice [Public Health Res Pract] 2025 Dec 10; Vol. 35 (4). |
| Publikationsart: | Journal Article |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: CSIRO Publishing on behalf of the Sax Institute Country of Publication: Australia NLM ID: 101648133 Publication Model: Print Cited Medium: Internet ISSN: 2204-2091 (Electronic) Linking ISSN: 22042091 NLM ISO Abbreviation: Public Health Res Pract Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2025- : Clayton, Victoria, Australia : CSIRO Publishing on behalf of the Sax Institute Original Publication: Ultimo, NSW : Sax Institute, [2014]- |
| MeSH-Schlagworte: | Electronic Health Records* , Obesity*/epidemiology , Obesity*/prevention & control, Humans ; Queensland/epidemiology ; Male ; Female ; Adult ; Middle Aged ; Body Mass Index ; Adolescent ; Aged ; Young Adult |
| Abstract: | Objectives: (1) To safely extract electronic medical record data to co-produce a population health informatics dashboard for obesity. (2) To explore how a population health informatics dashboard for obesity might be translated into routine public health practice. Methods: This mixed methods study was conducted in Queensland, Australia, with stakeholders (n = 27) according to the Three Horizons Framework for Digital Health Transformation. Horizon 1 established the digital infrastructure necessary for accessing routine electronic medical record data from inpatient, outpatient, emergency, and community encounters. Horizon 2 co-produced user requirements for a population health informatics dashboard and developed a proof of concept. Horizon 3 conducted usability testing to explore the theoretical feasibility of integrating the dashboard into practice. Results: The Queensland Healthy Weight Dashboard is an interactive visualisation platform for obesity surveillance capable of using near-real-time electronic medical record data. We developed a proof of concept using a synthetic sample of 726,561 patients. Once commissioned, the dashboard will display aggregate, non-identifiable data from a total sample of >1 million patients with a measured body mass index across 71 facilities in Queensland, including 19 health services and at least 71 individual facilities that use the integrated electronic Medical Record. The dashboard can display near real-time (quarterly) data via descriptive analytics to (1) identify total raw counts and normalised values, (2) longitudinally track data, and (3) geographically heatmap obesity, overweight, and healthy weight rates, and stratify by time (2016-2022), gender, age (2-99 years), and location (geographical area, facility). Usability testing with public health practitioner end-users (n = 4) revealed above-average overall usability but mixed task-based usability. Practitioners were optimistic about integrating the dashboard into routine practice. Conclusion: We co-produced a population health informatics tool for obesity that can display hospital electronic medical record data in near real-time. With further validation and usability improvements, this tool can be translated into public health practice to guide obesity interventions. (© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing.) |
| Contributed Indexing: | Keywords: clinical dashboard; digital health; electronic medical records; health care professionals; obesity; population surveillance; public health informatics; routinely collected health data |
| Entry Date(s): | Date Created: 20251024 Date Completed: 20251024 Latest Revision: 20251024 |
| Update Code: | 20251024 |
| DOI: | 10.1071/PU24029 |
| PMID: | 41134114 |
| Datenbank: | MEDLINE |
Nájsť tento článok vo Web of Science | Abstract: | Objectives: (1) To safely extract electronic medical record data to co-produce a population health informatics dashboard for obesity. (2) To explore how a population health informatics dashboard for obesity might be translated into routine public health practice.<br />Methods: This mixed methods study was conducted in Queensland, Australia, with stakeholders (n = 27) according to the Three Horizons Framework for Digital Health Transformation. Horizon 1 established the digital infrastructure necessary for accessing routine electronic medical record data from inpatient, outpatient, emergency, and community encounters. Horizon 2 co-produced user requirements for a population health informatics dashboard and developed a proof of concept. Horizon 3 conducted usability testing to explore the theoretical feasibility of integrating the dashboard into practice.<br />Results: The Queensland Healthy Weight Dashboard is an interactive visualisation platform for obesity surveillance capable of using near-real-time electronic medical record data. We developed a proof of concept using a synthetic sample of 726,561 patients. Once commissioned, the dashboard will display aggregate, non-identifiable data from a total sample of >1 million patients with a measured body mass index across 71 facilities in Queensland, including 19 health services and at least 71 individual facilities that use the integrated electronic Medical Record. The dashboard can display near real-time (quarterly) data via descriptive analytics to (1) identify total raw counts and normalised values, (2) longitudinally track data, and (3) geographically heatmap obesity, overweight, and healthy weight rates, and stratify by time (2016-2022), gender, age (2-99 years), and location (geographical area, facility). Usability testing with public health practitioner end-users (n = 4) revealed above-average overall usability but mixed task-based usability. Practitioners were optimistic about integrating the dashboard into routine practice.<br />Conclusion: We co-produced a population health informatics tool for obesity that can display hospital electronic medical record data in near real-time. With further validation and usability improvements, this tool can be translated into public health practice to guide obesity interventions.<br /> (© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing.) |
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| ISSN: | 2204-2091 |
| DOI: | 10.1071/PU24029 |