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The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review
BACKGROUND: The Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicato...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914032/ https://www.ncbi.nlm.nih.gov/pubmed/20550719 http://dx.doi.org/10.1186/1472-6963-10-166 |
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author | Hutchinson, Alison M Milke, Doris L Maisey, Suzanne Johnson, Cynthia Squires, Janet E Teare, Gary Estabrooks, Carole A |
author_facet | Hutchinson, Alison M Milke, Doris L Maisey, Suzanne Johnson, Cynthia Squires, Janet E Teare, Gary Estabrooks, Carole A |
author_sort | Hutchinson, Alison M |
collection | PubMed |
description | BACKGROUND: The Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicators to inform quality improvement initiatives is contingent upon the validity and reliability of the indicators. The purpose of this review was to systematically examine published and grey research reports in order to assess the state of the science regarding the validity and reliability of the RAI-MDS 2.0 Quality Indicators (QIs). METHODS: We systematically reviewed the evidence for the validity and reliability of the RAI-MDS 2.0 QIs. A comprehensive literature search identified relevant original research published, in English, prior to December 2008. Fourteen articles and one report examining the validity and/or reliability of the RAI-MDS 2.0 QIs were included. RESULTS: The studies fell into two broad categories, those that examined individual quality indicators and those that examined multiple indicators. All studies were conducted in the United States and included from one to a total of 209 facilities. The number of residents included in the studies ranged from 109 to 5758. One study conducted under research conditions examined 38 chronic care QIs, of which strong evidence for the validity of 12 of the QIs was found. In response to these findings, the 12 QIs were recommended for public reporting purposes. However, a number of observational studies (n = 13), conducted in "real world" conditions, have tested the validity and/or reliability of individual QIs, with mixed results. Ten QIs have been studied in this manner, including falls, depression, depression without treatment, urinary incontinence, urinary tract infections, weight loss, bedfast, restraint, pressure ulcer, and pain. These studies have revealed the potential for systematic bias in reporting, with under-reporting of some indicators and over-reporting of others. CONCLUSION: Evidence for the reliability and validity of the RAI-MDS QIs remains inconclusive. The QIs provide a useful tool for quality monitoring and to inform quality improvement programs and initiatives. However, caution should be exercised when interpreting the QI results and other sources of evidence of the quality of care processes should be considered in conjunction with QI results. |
format | Text |
id | pubmed-2914032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29140322010-08-03 The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review Hutchinson, Alison M Milke, Doris L Maisey, Suzanne Johnson, Cynthia Squires, Janet E Teare, Gary Estabrooks, Carole A BMC Health Serv Res Research Article BACKGROUND: The Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 is designed to collect the minimum amount of data to guide care planning and monitoring for residents in long-term care settings. These data have been used to compute indicators of care quality. Use of the quality indicators to inform quality improvement initiatives is contingent upon the validity and reliability of the indicators. The purpose of this review was to systematically examine published and grey research reports in order to assess the state of the science regarding the validity and reliability of the RAI-MDS 2.0 Quality Indicators (QIs). METHODS: We systematically reviewed the evidence for the validity and reliability of the RAI-MDS 2.0 QIs. A comprehensive literature search identified relevant original research published, in English, prior to December 2008. Fourteen articles and one report examining the validity and/or reliability of the RAI-MDS 2.0 QIs were included. RESULTS: The studies fell into two broad categories, those that examined individual quality indicators and those that examined multiple indicators. All studies were conducted in the United States and included from one to a total of 209 facilities. The number of residents included in the studies ranged from 109 to 5758. One study conducted under research conditions examined 38 chronic care QIs, of which strong evidence for the validity of 12 of the QIs was found. In response to these findings, the 12 QIs were recommended for public reporting purposes. However, a number of observational studies (n = 13), conducted in "real world" conditions, have tested the validity and/or reliability of individual QIs, with mixed results. Ten QIs have been studied in this manner, including falls, depression, depression without treatment, urinary incontinence, urinary tract infections, weight loss, bedfast, restraint, pressure ulcer, and pain. These studies have revealed the potential for systematic bias in reporting, with under-reporting of some indicators and over-reporting of others. CONCLUSION: Evidence for the reliability and validity of the RAI-MDS QIs remains inconclusive. The QIs provide a useful tool for quality monitoring and to inform quality improvement programs and initiatives. However, caution should be exercised when interpreting the QI results and other sources of evidence of the quality of care processes should be considered in conjunction with QI results. BioMed Central 2010-06-16 /pmc/articles/PMC2914032/ /pubmed/20550719 http://dx.doi.org/10.1186/1472-6963-10-166 Text en Copyright ©2010 Hutchinson et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hutchinson, Alison M Milke, Doris L Maisey, Suzanne Johnson, Cynthia Squires, Janet E Teare, Gary Estabrooks, Carole A The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title | The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title_full | The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title_fullStr | The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title_full_unstemmed | The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title_short | The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review |
title_sort | resident assessment instrument-minimum data set 2.0 quality indicators: a systematic review |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914032/ https://www.ncbi.nlm.nih.gov/pubmed/20550719 http://dx.doi.org/10.1186/1472-6963-10-166 |
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