Accelerate the Creation of the cross agency Human Services Dataset.

Objective Develop a digital solution for automated data ingestion and rapid update of the large-scale Human Services Dataset (HSDS) which brings together data from across government to take a powerful view of the service usage to improve outcomes of communities. Approach The Centre for Health Reco...

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Main Authors: Pooja Nair, Michael Smith, Maria Theochari
Format: Article
Language:English
Published: Swansea University 2022-08-01
Series:International Journal of Population Data Science
Subjects:
Online Access:https://ijpds.org/article/view/1963
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author Pooja Nair
Michael Smith
Maria Theochari
author_facet Pooja Nair
Michael Smith
Maria Theochari
author_sort Pooja Nair
collection DOAJ
description Objective Develop a digital solution for automated data ingestion and rapid update of the large-scale Human Services Dataset (HSDS) which brings together data from across government to take a powerful view of the service usage to improve outcomes of communities. Approach The Centre for Health Record Linkage (CHeReL) hosts a secure, high-performing data linkage system, including a Master Linkage Key (MLK) of administrative health datasets, and generates linked data to inform policy decisions. Since 2018, CHeReL has also been annually linking over 70 frontline datasets to create a large-scale longitudinal linked dataset of over 2.5 billion records. Over the course of 2021, the CHeReL led a project to incrementally improve the currency of the HSDS in compressed timeframes. This provided opportunity to assess value and feasibility of more frequent updates to the dataset within the evaluation and investment context. Results The automated data Ingestion and validation led to a significant reduction in the data processing timeframes for the Accelerated linkage. We observed 80% reduction in Data ingestion and 75% reduction in data validation. The digital solution also allows asset owners to register and approve new data providers, monitor their data provision in real-time and report on data sourcing. This provides transparency to the Asset Owner and reduces the need for time-intensive and manual processes to jointly monitor data provision with the Data Linkage Centre. The digital solution also has the capability to support Data Providers automate their data feeds and provide on a regular basis through a secure non- touch process. This reduces on-going workload and ensures on-time provision. Conclusion The process requires a systematic change in the upstream data source, and we requested participating agencies to send us data in an agreed format. The receipt of files in standard format is pivotal for reducing the overall timeframes of HSDS creation and leverage it for policy and investment purpose.
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spelling doaj.art-53c2cebc20db428da49bd077ba1f59ae2023-12-03T07:29:38ZengSwansea UniversityInternational Journal of Population Data Science2399-49082022-08-017310.23889/ijpds.v7i3.1963Accelerate the Creation of the cross agency Human Services Dataset.Pooja Nair0Michael Smith1Maria Theochari2NSW HealthNSW HealthNSW HealthObjective Develop a digital solution for automated data ingestion and rapid update of the large-scale Human Services Dataset (HSDS) which brings together data from across government to take a powerful view of the service usage to improve outcomes of communities. Approach The Centre for Health Record Linkage (CHeReL) hosts a secure, high-performing data linkage system, including a Master Linkage Key (MLK) of administrative health datasets, and generates linked data to inform policy decisions. Since 2018, CHeReL has also been annually linking over 70 frontline datasets to create a large-scale longitudinal linked dataset of over 2.5 billion records. Over the course of 2021, the CHeReL led a project to incrementally improve the currency of the HSDS in compressed timeframes. This provided opportunity to assess value and feasibility of more frequent updates to the dataset within the evaluation and investment context. Results The automated data Ingestion and validation led to a significant reduction in the data processing timeframes for the Accelerated linkage. We observed 80% reduction in Data ingestion and 75% reduction in data validation. The digital solution also allows asset owners to register and approve new data providers, monitor their data provision in real-time and report on data sourcing. This provides transparency to the Asset Owner and reduces the need for time-intensive and manual processes to jointly monitor data provision with the Data Linkage Centre. The digital solution also has the capability to support Data Providers automate their data feeds and provide on a regular basis through a secure non- touch process. This reduces on-going workload and ensures on-time provision. Conclusion The process requires a systematic change in the upstream data source, and we requested participating agencies to send us data in an agreed format. The receipt of files in standard format is pivotal for reducing the overall timeframes of HSDS creation and leverage it for policy and investment purpose. https://ijpds.org/article/view/1963Accelerated linkageautomated data ingestionHuman Services Dataset
spellingShingle Pooja Nair
Michael Smith
Maria Theochari
Accelerate the Creation of the cross agency Human Services Dataset.
International Journal of Population Data Science
Accelerated linkage
automated data ingestion
Human Services Dataset
title Accelerate the Creation of the cross agency Human Services Dataset.
title_full Accelerate the Creation of the cross agency Human Services Dataset.
title_fullStr Accelerate the Creation of the cross agency Human Services Dataset.
title_full_unstemmed Accelerate the Creation of the cross agency Human Services Dataset.
title_short Accelerate the Creation of the cross agency Human Services Dataset.
title_sort accelerate the creation of the cross agency human services dataset
topic Accelerated linkage
automated data ingestion
Human Services Dataset
url https://ijpds.org/article/view/1963
work_keys_str_mv AT poojanair acceleratethecreationofthecrossagencyhumanservicesdataset
AT michaelsmith acceleratethecreationofthecrossagencyhumanservicesdataset
AT mariatheochari acceleratethecreationofthecrossagencyhumanservicesdataset