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Evaluating Digital Health Capability at Scale Using the Digital Health Indicator
Background Health service providers must understand their digital health capability if they are to drive digital transformation in a strategic and informed manner. Little is known about the assessment and benchmarking of digital maturity or capability at scale across an entire jurisdiction. The pub...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581585/ https://www.ncbi.nlm.nih.gov/pubmed/36261114 http://dx.doi.org/10.1055/s-0042-1757554 |
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author | Woods, Leanna Eden, Rebekah Pearce, Andrew Wong, Yu Ching Ides Jayan, Lakshmi Green, Damian McNeil, Keith Sullivan, Clair |
author_facet | Woods, Leanna Eden, Rebekah Pearce, Andrew Wong, Yu Ching Ides Jayan, Lakshmi Green, Damian McNeil, Keith Sullivan, Clair |
author_sort | Woods, Leanna |
collection | PubMed |
description | Background Health service providers must understand their digital health capability if they are to drive digital transformation in a strategic and informed manner. Little is known about the assessment and benchmarking of digital maturity or capability at scale across an entire jurisdiction. The public health care system across the state of Queensland, Australia has an ambitious 10-year digital transformation strategy. Objective The aim of this research was to evaluate the digital health capability in Queensland to inform digital health strategy and investment. Methods The Healthcare Information and Management Systems Society Digital Health Indicator (DHI) was used via a cross-sectional survey design to assess four core dimensions of digital health transformation: governance and workforce; interoperability; person-enabled health; and predictive analytics across an entire jurisdiction simultaneously. The DHI questionnaire was completed by each health care system ( n = 16) within Queensland in February to July 2021. DHI is scored 0 to 400 and dimension score is 0 to 100. Results The results reveal a variation in DHI scores reflecting the diverse stages of health care digitization across the state. The average DHI score across sites was 143 (range 78–193; SD35.3) which is similar to other systems in the Oceania region and global public systems but below the global private average. Governance and workforce was on average the highest scoring dimension (x̅= 54), followed by interoperability (x̅ = 46), person-enabled health (x̅ = 36), and predictive analytics (x̅ = 30). Conclusion The findings were incorporated into the new digital health strategy for the jurisdiction. As one of the largest single simultaneous assessments of digital health capability globally, the findings and lessons learnt offer insights for policy makers and organizational managers. |
format | Online Article Text |
id | pubmed-9581585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-95815852022-10-20 Evaluating Digital Health Capability at Scale Using the Digital Health Indicator Woods, Leanna Eden, Rebekah Pearce, Andrew Wong, Yu Ching Ides Jayan, Lakshmi Green, Damian McNeil, Keith Sullivan, Clair Appl Clin Inform Background Health service providers must understand their digital health capability if they are to drive digital transformation in a strategic and informed manner. Little is known about the assessment and benchmarking of digital maturity or capability at scale across an entire jurisdiction. The public health care system across the state of Queensland, Australia has an ambitious 10-year digital transformation strategy. Objective The aim of this research was to evaluate the digital health capability in Queensland to inform digital health strategy and investment. Methods The Healthcare Information and Management Systems Society Digital Health Indicator (DHI) was used via a cross-sectional survey design to assess four core dimensions of digital health transformation: governance and workforce; interoperability; person-enabled health; and predictive analytics across an entire jurisdiction simultaneously. The DHI questionnaire was completed by each health care system ( n = 16) within Queensland in February to July 2021. DHI is scored 0 to 400 and dimension score is 0 to 100. Results The results reveal a variation in DHI scores reflecting the diverse stages of health care digitization across the state. The average DHI score across sites was 143 (range 78–193; SD35.3) which is similar to other systems in the Oceania region and global public systems but below the global private average. Governance and workforce was on average the highest scoring dimension (x̅= 54), followed by interoperability (x̅ = 46), person-enabled health (x̅ = 36), and predictive analytics (x̅ = 30). Conclusion The findings were incorporated into the new digital health strategy for the jurisdiction. As one of the largest single simultaneous assessments of digital health capability globally, the findings and lessons learnt offer insights for policy makers and organizational managers. Georg Thieme Verlag KG 2022-10-19 /pmc/articles/PMC9581585/ /pubmed/36261114 http://dx.doi.org/10.1055/s-0042-1757554 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Woods, Leanna Eden, Rebekah Pearce, Andrew Wong, Yu Ching Ides Jayan, Lakshmi Green, Damian McNeil, Keith Sullivan, Clair Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title | Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title_full | Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title_fullStr | Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title_full_unstemmed | Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title_short | Evaluating Digital Health Capability at Scale Using the Digital Health Indicator |
title_sort | evaluating digital health capability at scale using the digital health indicator |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581585/ https://www.ncbi.nlm.nih.gov/pubmed/36261114 http://dx.doi.org/10.1055/s-0042-1757554 |
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