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Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study
INTRODUCTION: Rates of potentially preventable hospitalisations (PPH) are used as a proxy measure of effectiveness of, or access to community-based health services. The validity of PPH as an indicator in Australia has not been confirmed. Available evidence suggests that patient-related, clinician-re...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663419/ https://www.ncbi.nlm.nih.gov/pubmed/26597867 http://dx.doi.org/10.1136/bmjopen-2015-009879 |
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author | Passey, Megan E Longman, Jo M Johnston, Jennifer J Jorm, Louisa Ewald, Dan Morgan, Geoff G Rolfe, Margaret Chalker, Bronwyn |
author_facet | Passey, Megan E Longman, Jo M Johnston, Jennifer J Jorm, Louisa Ewald, Dan Morgan, Geoff G Rolfe, Margaret Chalker, Bronwyn |
author_sort | Passey, Megan E |
collection | PubMed |
description | INTRODUCTION: Rates of potentially preventable hospitalisations (PPH) are used as a proxy measure of effectiveness of, or access to community-based health services. The validity of PPH as an indicator in Australia has not been confirmed. Available evidence suggests that patient-related, clinician-related and systems-related factors are associated with PPH, with differences between rural and metropolitan settings. Furthermore, the proportion of PPHs which are actually preventable is unknown. The Diagnosing Potentially Preventable Hospitalisations study will determine the proportion of PPHs for chronic conditions that are deemed preventable and identify potentially modifiable factors driving these, in order to develop effective interventions to reduce admissions and improve measures of health system performance. METHODS AND ANALYSIS: This mixed methods data linkage study of approximately 1000 eligible patients with chronic PPH admissions to one metropolitan and two regional hospitals over 12 months will combine data from multiple sources to assess the: extent of preventability of chronic PPH admissions; validity of the Preventability Assessment Tool (PAT) in identifying preventable admissions; factors contributing to chronic PPH admissions. Data collected from patients (quantitative and qualitative methods), their general practitioners, hospital clinicians and hospital records, will be linked with routinely collected New South Wales (NSW) Admitted Patient Data Collection, the NSW Registry of Births, Death and Marriages death registration and Australian Bureau of Statistics mortality data. The validity of the PAT will be assessed by determining concordance between clinician assessment and that of a ‘gold standard’ panel. Multivariable logistic regression will identify the main predictor variables of admissions deemed preventable, using study-specific and linked data. ETHICS AND DISSEMINATION: The NSW Population and Health Services Research Ethics Committee granted ethical approval. Dissemination mechanisms include engagement of policy stakeholders through a project Steering Committee, and the production of summary reports for policy and clinical audiences in addition to peer-review papers. |
format | Online Article Text |
id | pubmed-4663419 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46634192015-12-03 Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study Passey, Megan E Longman, Jo M Johnston, Jennifer J Jorm, Louisa Ewald, Dan Morgan, Geoff G Rolfe, Margaret Chalker, Bronwyn BMJ Open Health Services Research INTRODUCTION: Rates of potentially preventable hospitalisations (PPH) are used as a proxy measure of effectiveness of, or access to community-based health services. The validity of PPH as an indicator in Australia has not been confirmed. Available evidence suggests that patient-related, clinician-related and systems-related factors are associated with PPH, with differences between rural and metropolitan settings. Furthermore, the proportion of PPHs which are actually preventable is unknown. The Diagnosing Potentially Preventable Hospitalisations study will determine the proportion of PPHs for chronic conditions that are deemed preventable and identify potentially modifiable factors driving these, in order to develop effective interventions to reduce admissions and improve measures of health system performance. METHODS AND ANALYSIS: This mixed methods data linkage study of approximately 1000 eligible patients with chronic PPH admissions to one metropolitan and two regional hospitals over 12 months will combine data from multiple sources to assess the: extent of preventability of chronic PPH admissions; validity of the Preventability Assessment Tool (PAT) in identifying preventable admissions; factors contributing to chronic PPH admissions. Data collected from patients (quantitative and qualitative methods), their general practitioners, hospital clinicians and hospital records, will be linked with routinely collected New South Wales (NSW) Admitted Patient Data Collection, the NSW Registry of Births, Death and Marriages death registration and Australian Bureau of Statistics mortality data. The validity of the PAT will be assessed by determining concordance between clinician assessment and that of a ‘gold standard’ panel. Multivariable logistic regression will identify the main predictor variables of admissions deemed preventable, using study-specific and linked data. ETHICS AND DISSEMINATION: The NSW Population and Health Services Research Ethics Committee granted ethical approval. Dissemination mechanisms include engagement of policy stakeholders through a project Steering Committee, and the production of summary reports for policy and clinical audiences in addition to peer-review papers. BMJ Publishing Group 2015-11-23 /pmc/articles/PMC4663419/ /pubmed/26597867 http://dx.doi.org/10.1136/bmjopen-2015-009879 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ 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 and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Health Services Research Passey, Megan E Longman, Jo M Johnston, Jennifer J Jorm, Louisa Ewald, Dan Morgan, Geoff G Rolfe, Margaret Chalker, Bronwyn Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title | Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title_full | Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title_fullStr | Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title_full_unstemmed | Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title_short | Diagnosing Potentially Preventable Hospitalisations (DaPPHne): protocol for a mixed-methods data-linkage study |
title_sort | diagnosing potentially preventable hospitalisations (dapphne): protocol for a mixed-methods data-linkage study |
topic | Health Services Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663419/ https://www.ncbi.nlm.nih.gov/pubmed/26597867 http://dx.doi.org/10.1136/bmjopen-2015-009879 |
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