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Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data

INTRODUCTION: Potentially preventable hospitalisation (PPH) has been adopted widely by international health systems as an indicator of the accessibility and overall effectiveness of primary care. The Assessing Preventable Hospitalisation InDicators (APHID) study will validate PPH as a measure of hea...

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Autores principales: Jorm, Louisa R, Leyland, Alastair H, Blyth, Fiona M, Elliott, Robert F, Douglas, Kirsty M A, Redman, Sally
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533070/
https://www.ncbi.nlm.nih.gov/pubmed/23242247
http://dx.doi.org/10.1136/bmjopen-2012-002344
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author Jorm, Louisa R
Leyland, Alastair H
Blyth, Fiona M
Elliott, Robert F
Douglas, Kirsty M A
Redman, Sally
author_facet Jorm, Louisa R
Leyland, Alastair H
Blyth, Fiona M
Elliott, Robert F
Douglas, Kirsty M A
Redman, Sally
author_sort Jorm, Louisa R
collection PubMed
description INTRODUCTION: Potentially preventable hospitalisation (PPH) has been adopted widely by international health systems as an indicator of the accessibility and overall effectiveness of primary care. The Assessing Preventable Hospitalisation InDicators (APHID) study will validate PPH as a measure of health system performance in Australia and Scotland. APHID will be the first large-scale study internationally to explore longitudinal relationships between primary care and PPH using detailed person-level information about health risk factors, health status and health service use. METHODS AND ANALYSIS: APHID will create a new longitudinal data resource by linking together data from a large-scale cohort study (the 45 and Up Study) and prospective administrative data relating to use of general practitioner (GP) services, dispensing of pharmaceuticals, emergency department presentations, hospital admissions and deaths. We will use these linked person-level data to explore relationships between frequency, volume, nature and costs of primary care services, hospital admissions for PPH diagnoses, and health outcomes, and factors that confound and mediate these relationships. Using multilevel modelling techniques, we will quantify the contributions of person-level, geographic-level and service-level factors to variation in PPH rates, including socioeconomic status, country of birth, geographic remoteness, physical and mental health status, availability of GP and other services, and hospital characteristics. ETHICS AND DISSEMINATION: Participants have consented to use of their questionnaire data and to data linkage. Ethical approval has been obtained for the study. Dissemination mechanisms include engagement of policy stakeholders through a reference group and policy forum, and production of summary reports for policy audiences in parallel with the scientific papers from the study.
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spelling pubmed-35330702013-01-04 Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data Jorm, Louisa R Leyland, Alastair H Blyth, Fiona M Elliott, Robert F Douglas, Kirsty M A Redman, Sally BMJ Open Health Services Research INTRODUCTION: Potentially preventable hospitalisation (PPH) has been adopted widely by international health systems as an indicator of the accessibility and overall effectiveness of primary care. The Assessing Preventable Hospitalisation InDicators (APHID) study will validate PPH as a measure of health system performance in Australia and Scotland. APHID will be the first large-scale study internationally to explore longitudinal relationships between primary care and PPH using detailed person-level information about health risk factors, health status and health service use. METHODS AND ANALYSIS: APHID will create a new longitudinal data resource by linking together data from a large-scale cohort study (the 45 and Up Study) and prospective administrative data relating to use of general practitioner (GP) services, dispensing of pharmaceuticals, emergency department presentations, hospital admissions and deaths. We will use these linked person-level data to explore relationships between frequency, volume, nature and costs of primary care services, hospital admissions for PPH diagnoses, and health outcomes, and factors that confound and mediate these relationships. Using multilevel modelling techniques, we will quantify the contributions of person-level, geographic-level and service-level factors to variation in PPH rates, including socioeconomic status, country of birth, geographic remoteness, physical and mental health status, availability of GP and other services, and hospital characteristics. ETHICS AND DISSEMINATION: Participants have consented to use of their questionnaire data and to data linkage. Ethical approval has been obtained for the study. Dissemination mechanisms include engagement of policy stakeholders through a reference group and policy forum, and production of summary reports for policy audiences in parallel with the scientific papers from the study. BMJ Publishing Group 2012-12-13 /pmc/articles/PMC3533070/ /pubmed/23242247 http://dx.doi.org/10.1136/bmjopen-2012-002344 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
spellingShingle Health Services Research
Jorm, Louisa R
Leyland, Alastair H
Blyth, Fiona M
Elliott, Robert F
Douglas, Kirsty M A
Redman, Sally
Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title_full Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title_fullStr Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title_full_unstemmed Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title_short Assessing Preventable Hospitalisation InDicators (APHID): protocol for a data-linkage study using cohort study and administrative data
title_sort assessing preventable hospitalisation indicators (aphid): protocol for a data-linkage study using cohort study and administrative data
topic Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533070/
https://www.ncbi.nlm.nih.gov/pubmed/23242247
http://dx.doi.org/10.1136/bmjopen-2012-002344
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