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Evaluation of a staff training programme to reimplement a comprehensive health assessment
BACKGROUND: Health information systems with applications in patient care planning and decision support depend on high-quality data. A postacute care hospital in Ontario, Canada, conducted data quality assessment and focus group interviews to guide the development of a cross-disciplinary training pro...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267310/ https://www.ncbi.nlm.nih.gov/pubmed/30555932 http://dx.doi.org/10.1136/bmjoq-2018-000353 |
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author | Turcotte, Luke A Tran, Jake Moralejo, Joshua Curtin-Telegdi, Nancy Eckel, Leslie Hirdes, John P |
author_facet | Turcotte, Luke A Tran, Jake Moralejo, Joshua Curtin-Telegdi, Nancy Eckel, Leslie Hirdes, John P |
author_sort | Turcotte, Luke A |
collection | PubMed |
description | BACKGROUND: Health information systems with applications in patient care planning and decision support depend on high-quality data. A postacute care hospital in Ontario, Canada, conducted data quality assessment and focus group interviews to guide the development of a cross-disciplinary training programme to reimplement the Resident Assessment Instrument–Minimum Data Set (RAI-MDS) 2.0 comprehensive health assessment into the hospital’s clinical workflows. METHODS: A hospital-level data quality assessment framework based on time series comparisons against an aggregate of Ontario postacute care hospitals was used to identify areas of concern. Focus groups were used to evaluate assessment practices and the use of health information in care planning and clinical decision support. The data quality assessment and focus groups were repeated to evaluate the effectiveness of the training programme. RESULTS: Initial data quality assessment and focus group indicated that knowledge, practice and cultural barriers prevented both the collection and use of high-quality clinical data. Following the implementation of the training, there was an improvement in both data quality and the culture surrounding the RAI-MDS 2.0 assessment. CONCLUSIONS: It is important for facilities to evaluate the quality of their health information to ensure that it is suitable for decision-making purposes. This study demonstrates the use of a data quality assessment framework that can be applied for quality improvement planning. |
format | Online Article Text |
id | pubmed-6267310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62673102018-12-16 Evaluation of a staff training programme to reimplement a comprehensive health assessment Turcotte, Luke A Tran, Jake Moralejo, Joshua Curtin-Telegdi, Nancy Eckel, Leslie Hirdes, John P BMJ Open Qual Original Article BACKGROUND: Health information systems with applications in patient care planning and decision support depend on high-quality data. A postacute care hospital in Ontario, Canada, conducted data quality assessment and focus group interviews to guide the development of a cross-disciplinary training programme to reimplement the Resident Assessment Instrument–Minimum Data Set (RAI-MDS) 2.0 comprehensive health assessment into the hospital’s clinical workflows. METHODS: A hospital-level data quality assessment framework based on time series comparisons against an aggregate of Ontario postacute care hospitals was used to identify areas of concern. Focus groups were used to evaluate assessment practices and the use of health information in care planning and clinical decision support. The data quality assessment and focus groups were repeated to evaluate the effectiveness of the training programme. RESULTS: Initial data quality assessment and focus group indicated that knowledge, practice and cultural barriers prevented both the collection and use of high-quality clinical data. Following the implementation of the training, there was an improvement in both data quality and the culture surrounding the RAI-MDS 2.0 assessment. CONCLUSIONS: It is important for facilities to evaluate the quality of their health information to ensure that it is suitable for decision-making purposes. This study demonstrates the use of a data quality assessment framework that can be applied for quality improvement planning. BMJ Publishing Group 2018-11-20 /pmc/articles/PMC6267310/ /pubmed/30555932 http://dx.doi.org/10.1136/bmjoq-2018-000353 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Original Article Turcotte, Luke A Tran, Jake Moralejo, Joshua Curtin-Telegdi, Nancy Eckel, Leslie Hirdes, John P Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title | Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title_full | Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title_fullStr | Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title_full_unstemmed | Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title_short | Evaluation of a staff training programme to reimplement a comprehensive health assessment |
title_sort | evaluation of a staff training programme to reimplement a comprehensive health assessment |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267310/ https://www.ncbi.nlm.nih.gov/pubmed/30555932 http://dx.doi.org/10.1136/bmjoq-2018-000353 |
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