Ines Basso PhD , Silvia Gonella RN, PhD , Erika Bassi PhD , Silvia Caristia PhD , Sara Campagna PhD , Alberto Dal Molin PhD
{"title":"质量改进干预措施对养老院入院率的影响:系统回顾与元分析》。","authors":"Ines Basso PhD , Silvia Gonella RN, PhD , Erika Bassi PhD , Silvia Caristia PhD , Sara Campagna PhD , Alberto Dal Molin PhD","doi":"10.1016/j.jamda.2024.105261","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To synthesize evidence assessing the effectiveness of quality improvement (QI) interventions in reducing hospital service use from nursing homes (NHs).</div></div><div><h3>Design</h3><div>Systematic review and meta-analysis of randomized controlled trials (RCTs), controlled before-after (CBA), uncontrolled before-after (UBA), and interrupted time series studies. Searches were conducted in MEDLINE, CINAHL, The Cochrane Library, Embase, and Web of Science from 2000 to August 2023 (PROSPERO: CRD42022364195).</div></div><div><h3>Setting and Participants</h3><div>Long-stay NH residents (>30 days).</div></div><div><h3>Methods</h3><div>Included QI interventions using a continuous and data-driven approach to assess solutions aimed at reducing hospital service use. Risk of bias was assessed using JBI tools. Delivery arrangements and implementation strategies were categorized through EPOC taxonomy.</div></div><div><h3>Results</h3><div>Screening of 14,076 records led to the inclusion of 22 studies describing 29 QI interventions from 6 countries across 964 NHs. Ten studies, comprising 4 of 5 RCTs, 3 of 4 CBAs, and 1 of 12 UBAs were deemed to have a low risk of bias. All but 3 QI interventions used multiple component delivery arrangements (median 6; IQR 3-8), focusing on the “coordination of care and management of care processes” alone or combined with “changes in how, when, where, and by whom health care is delivered.” The most frequently used implementation strategies were educational meetings (n = 25) and materials (n = 20). The meta-analysis of 11 studies showed a significant reduction in “all-cause hospital admissions” for QI interventions compared with standard care (rate ratio, 0.60; 95% CI, 0.41-0.87; <em>I</em><sup>2</sup> = 99.3%), with heterogeneity due to study design, QI intervention duration, type of delivery arrangements, and number of implementation strategies. No significant effects were found for emergency department (ED) visits or potentially avoidable hospitalizations.</div></div><div><h3>Conclusions and Implications</h3><div>The study provides preliminary evidence supporting the implementation of QI interventions seeking to reduce hospital admissions from NHs. However, these findings require confirmation through future experimental research.</div></div>","PeriodicalId":17180,"journal":{"name":"Journal of the American Medical Directors Association","volume":"25 11","pages":"Article 105261"},"PeriodicalIF":4.2000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of Quality Improvement Interventions on Hospital Admissions from Nursing Homes: A Systematic Review and Meta-Analysis\",\"authors\":\"Ines Basso PhD , Silvia Gonella RN, PhD , Erika Bassi PhD , Silvia Caristia PhD , Sara Campagna PhD , Alberto Dal Molin PhD\",\"doi\":\"10.1016/j.jamda.2024.105261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>To synthesize evidence assessing the effectiveness of quality improvement (QI) interventions in reducing hospital service use from nursing homes (NHs).</div></div><div><h3>Design</h3><div>Systematic review and meta-analysis of randomized controlled trials (RCTs), controlled before-after (CBA), uncontrolled before-after (UBA), and interrupted time series studies. Searches were conducted in MEDLINE, CINAHL, The Cochrane Library, Embase, and Web of Science from 2000 to August 2023 (PROSPERO: CRD42022364195).</div></div><div><h3>Setting and Participants</h3><div>Long-stay NH residents (>30 days).</div></div><div><h3>Methods</h3><div>Included QI interventions using a continuous and data-driven approach to assess solutions aimed at reducing hospital service use. Risk of bias was assessed using JBI tools. Delivery arrangements and implementation strategies were categorized through EPOC taxonomy.</div></div><div><h3>Results</h3><div>Screening of 14,076 records led to the inclusion of 22 studies describing 29 QI interventions from 6 countries across 964 NHs. Ten studies, comprising 4 of 5 RCTs, 3 of 4 CBAs, and 1 of 12 UBAs were deemed to have a low risk of bias. All but 3 QI interventions used multiple component delivery arrangements (median 6; IQR 3-8), focusing on the “coordination of care and management of care processes” alone or combined with “changes in how, when, where, and by whom health care is delivered.” The most frequently used implementation strategies were educational meetings (n = 25) and materials (n = 20). The meta-analysis of 11 studies showed a significant reduction in “all-cause hospital admissions” for QI interventions compared with standard care (rate ratio, 0.60; 95% CI, 0.41-0.87; <em>I</em><sup>2</sup> = 99.3%), with heterogeneity due to study design, QI intervention duration, type of delivery arrangements, and number of implementation strategies. 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Impact of Quality Improvement Interventions on Hospital Admissions from Nursing Homes: A Systematic Review and Meta-Analysis
Objective
To synthesize evidence assessing the effectiveness of quality improvement (QI) interventions in reducing hospital service use from nursing homes (NHs).
Design
Systematic review and meta-analysis of randomized controlled trials (RCTs), controlled before-after (CBA), uncontrolled before-after (UBA), and interrupted time series studies. Searches were conducted in MEDLINE, CINAHL, The Cochrane Library, Embase, and Web of Science from 2000 to August 2023 (PROSPERO: CRD42022364195).
Setting and Participants
Long-stay NH residents (>30 days).
Methods
Included QI interventions using a continuous and data-driven approach to assess solutions aimed at reducing hospital service use. Risk of bias was assessed using JBI tools. Delivery arrangements and implementation strategies were categorized through EPOC taxonomy.
Results
Screening of 14,076 records led to the inclusion of 22 studies describing 29 QI interventions from 6 countries across 964 NHs. Ten studies, comprising 4 of 5 RCTs, 3 of 4 CBAs, and 1 of 12 UBAs were deemed to have a low risk of bias. All but 3 QI interventions used multiple component delivery arrangements (median 6; IQR 3-8), focusing on the “coordination of care and management of care processes” alone or combined with “changes in how, when, where, and by whom health care is delivered.” The most frequently used implementation strategies were educational meetings (n = 25) and materials (n = 20). The meta-analysis of 11 studies showed a significant reduction in “all-cause hospital admissions” for QI interventions compared with standard care (rate ratio, 0.60; 95% CI, 0.41-0.87; I2 = 99.3%), with heterogeneity due to study design, QI intervention duration, type of delivery arrangements, and number of implementation strategies. No significant effects were found for emergency department (ED) visits or potentially avoidable hospitalizations.
Conclusions and Implications
The study provides preliminary evidence supporting the implementation of QI interventions seeking to reduce hospital admissions from NHs. However, these findings require confirmation through future experimental research.
期刊介绍:
JAMDA, the official journal of AMDA - The Society for Post-Acute and Long-Term Care Medicine, is a leading peer-reviewed publication that offers practical information and research geared towards healthcare professionals in the post-acute and long-term care fields. It is also a valuable resource for policy-makers, organizational leaders, educators, and advocates.
The journal provides essential information for various healthcare professionals such as medical directors, attending physicians, nurses, consultant pharmacists, geriatric psychiatrists, nurse practitioners, physician assistants, physical and occupational therapists, social workers, and others involved in providing, overseeing, and promoting quality