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Successful operational integration of healthcare analytics at Seattle Children's

INTRODUCTION: As the quantity and complexity of health data grows, it is critical for healthcare organizations to devise analytic strategies that power data innovation so they can take advantage of new opportunities and improve outcomes. Seattle Children's Healthcare System (Seattle Children�...

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Autores principales: Frisbee, Kathleen L., Sousa, Ryan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10091203/
https://www.ncbi.nlm.nih.gov/pubmed/37066101
http://dx.doi.org/10.1002/lrh2.10331
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author Frisbee, Kathleen L.
Sousa, Ryan
author_facet Frisbee, Kathleen L.
Sousa, Ryan
author_sort Frisbee, Kathleen L.
collection PubMed
description INTRODUCTION: As the quantity and complexity of health data grows, it is critical for healthcare organizations to devise analytic strategies that power data innovation so they can take advantage of new opportunities and improve outcomes. Seattle Children's Healthcare System (Seattle Children's) is an example of an organization that has built an operating model that integrates analytics into their business and daily operations. We present a roadmap for how Seattle Children's consolidated its fragmented analytics operations into a unified cohesive ecosystem capable of supporting advanced analytics capabilities and operational integration to transform care and accelerate research. METHODS: In‐depth interviews were conducted with ten leaders at Seattle Children's who have been instrumental in developing their enterprise analytics program. Interviews included the following leadership roles: Chief Data & Analytics Officer, Director of Research Informatics, Principal Systems Architect, Manager of Bioinformatics and High Throughput Analytics, Director of Neurocritical Care, Strategic Program Manager & Neuron Product Development Lead, Director of Dev Ops,Director of Clinical Analytics, Data Science Manager, and Advance Analytics Product Engineer. The interviews were unstructured and consisted of conversations intended to gather information from leadership about their experiences in building out Enterprise Analytics at Seattle Children's. RESULTS: Seattle Children's has built an advanced enterprise analytics ecosystem that is integrated into its daily operations by applying an entrepreneurial mindset and agile development practices that are common in a startup environment. Analytics efforts were approached iteratively by selecting high‐value projects that were delivered through Multidisciplinary Delivery Teams that were integrated into service lines. Service line leadership, in partnership with the Delivery Team leads, were responsible for the success of the team by setting project priorities, determining project budgets, and maintaining overall governance of their analytics endeavors. This organizational structure has led to the development of a wide range of analytic products that have been used to improve both operations and clinical care at Seattle Children's. CONCLUSIONS: Seattle Children's has demonstrated how a leading healthcare system can successfully create a robust, scalable, near real‐time analytics ecosystem‐ one that delivers significant value to the organization from the ever‐expanding volume of health data we see today.
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spelling pubmed-100912032023-04-13 Successful operational integration of healthcare analytics at Seattle Children's Frisbee, Kathleen L. Sousa, Ryan Learn Health Syst Experience Reports INTRODUCTION: As the quantity and complexity of health data grows, it is critical for healthcare organizations to devise analytic strategies that power data innovation so they can take advantage of new opportunities and improve outcomes. Seattle Children's Healthcare System (Seattle Children's) is an example of an organization that has built an operating model that integrates analytics into their business and daily operations. We present a roadmap for how Seattle Children's consolidated its fragmented analytics operations into a unified cohesive ecosystem capable of supporting advanced analytics capabilities and operational integration to transform care and accelerate research. METHODS: In‐depth interviews were conducted with ten leaders at Seattle Children's who have been instrumental in developing their enterprise analytics program. Interviews included the following leadership roles: Chief Data & Analytics Officer, Director of Research Informatics, Principal Systems Architect, Manager of Bioinformatics and High Throughput Analytics, Director of Neurocritical Care, Strategic Program Manager & Neuron Product Development Lead, Director of Dev Ops,Director of Clinical Analytics, Data Science Manager, and Advance Analytics Product Engineer. The interviews were unstructured and consisted of conversations intended to gather information from leadership about their experiences in building out Enterprise Analytics at Seattle Children's. RESULTS: Seattle Children's has built an advanced enterprise analytics ecosystem that is integrated into its daily operations by applying an entrepreneurial mindset and agile development practices that are common in a startup environment. Analytics efforts were approached iteratively by selecting high‐value projects that were delivered through Multidisciplinary Delivery Teams that were integrated into service lines. Service line leadership, in partnership with the Delivery Team leads, were responsible for the success of the team by setting project priorities, determining project budgets, and maintaining overall governance of their analytics endeavors. This organizational structure has led to the development of a wide range of analytic products that have been used to improve both operations and clinical care at Seattle Children's. CONCLUSIONS: Seattle Children's has demonstrated how a leading healthcare system can successfully create a robust, scalable, near real‐time analytics ecosystem‐ one that delivers significant value to the organization from the ever‐expanding volume of health data we see today. John Wiley and Sons Inc. 2022-08-19 /pmc/articles/PMC10091203/ /pubmed/37066101 http://dx.doi.org/10.1002/lrh2.10331 Text en © 2022 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Experience Reports
Frisbee, Kathleen L.
Sousa, Ryan
Successful operational integration of healthcare analytics at Seattle Children's
title Successful operational integration of healthcare analytics at Seattle Children's
title_full Successful operational integration of healthcare analytics at Seattle Children's
title_fullStr Successful operational integration of healthcare analytics at Seattle Children's
title_full_unstemmed Successful operational integration of healthcare analytics at Seattle Children's
title_short Successful operational integration of healthcare analytics at Seattle Children's
title_sort successful operational integration of healthcare analytics at seattle children's
topic Experience Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10091203/
https://www.ncbi.nlm.nih.gov/pubmed/37066101
http://dx.doi.org/10.1002/lrh2.10331
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