Exploring the effects of transfers and readmissions on trends in population counts of hospital admissions for coronary heart disease: a Western Australian data linkage study

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Abstract

Objectives: To develop a method for categorising coronary heart disease (CHD) subtype in linked data accounting for different CHD diagnoses across records, and to compare hospital admission numbers and ratios of unlinked versus linked data for each CHD subtype over time, and across age groups and sex.
Design: Cohort study.
Data source: Person-linked hospital administrative data covering all admissions for CHD in Western Australia from 1988 to 2013.
Main outcome: Ratios of (1) unlinked admission counts to contiguous admission (CA) counts (accounting for transfers), and (2) 28-day episode counts (accounting for transfers and readmissions) to CA counts stratified by CHD subtype, sex and age group.

Results: In all CHD subtypes, the ratios changed in a linear or quadratic fashion over time and the coefficients of the trend term differed across CHD subtypes. Furthermore, for many CHD subtypes the ratios also differed by age group and sex. For example, in women aged 35–54 years, the ratio of unlinked to CA counts for non-ST elevation myocardial infarction admissions in 2000 was 1.10, and this increased in a linear fashion to 1.30 in 2013, representing an annual increase of 0.0148.
Conclusion: The use of unlinked counts in epidemiological estimates of CHD hospitalisations overestimates CHD counts. The CA and 28-day episode counts are more aligned with epidemiological studies of CHD. The degree of overestimation of counts using only unlinked counts varies in a complex manner with CHD subtype, time, sex and age group, and it is not possible to apply a simple correction factor to counts obtained from unlinked data.
Original languageEnglish
Article numbere019226
JournalBMJ Open
Volume7
Issue number11
DOIs
Publication statusPublished - 2017

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Information Storage and Retrieval
Coronary Disease
Population
Age Groups
Western Australia
Epidemiologic Studies
Hospitalization
Cohort Studies

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@article{b968396084d74585978690d243ff83c0,
title = "Exploring the effects of transfers and readmissions on trends in population counts of hospital admissions for coronary heart disease: a Western Australian data linkage study",
abstract = "Objectives: To develop a method for categorising coronary heart disease (CHD) subtype in linked data accounting for different CHD diagnoses across records, and to compare hospital admission numbers and ratios of unlinked versus linked data for each CHD subtype over time, and across age groups and sex.Design: Cohort study.Data source: Person-linked hospital administrative data covering all admissions for CHD in Western Australia from 1988 to 2013.Main outcome: Ratios of (1) unlinked admission counts to contiguous admission (CA) counts (accounting for transfers), and (2) 28-day episode counts (accounting for transfers and readmissions) to CA counts stratified by CHD subtype, sex and age group.Results: In all CHD subtypes, the ratios changed in a linear or quadratic fashion over time and the coefficients of the trend term differed across CHD subtypes. Furthermore, for many CHD subtypes the ratios also differed by age group and sex. For example, in women aged 35–54 years, the ratio of unlinked to CA counts for non-ST elevation myocardial infarction admissions in 2000 was 1.10, and this increased in a linear fashion to 1.30 in 2013, representing an annual increase of 0.0148.Conclusion: The use of unlinked counts in epidemiological estimates of CHD hospitalisations overestimates CHD counts. The CA and 28-day episode counts are more aligned with epidemiological studies of CHD. The degree of overestimation of counts using only unlinked counts varies in a complex manner with CHD subtype, time, sex and age group, and it is not possible to apply a simple correction factor to counts obtained from unlinked data.",
author = "Derrick Lopez and Lee Nedkoff and Matthew Knuiman and Hobbs, {Michael S.T.} and Briffa, {Thomas G.} and Preen, {David B.} and Joseph Hung and John Beilby and Sushma Mathur and Anna Reynolds and Sanfilippo, {Francesco M.}",
year = "2017",
doi = "10.1136/bmjopen-2017-019226",
language = "English",
volume = "7",
journal = "BMJ (Open)",
issn = "2044-6055",
publisher = "John Wiley & Sons",
number = "11",

}

TY - JOUR

T1 - Exploring the effects of transfers and readmissions on trends in population counts of hospital admissions for coronary heart disease: a Western Australian data linkage study

AU - Lopez, Derrick

AU - Nedkoff, Lee

AU - Knuiman, Matthew

AU - Hobbs, Michael S.T.

AU - Briffa, Thomas G.

AU - Preen, David B.

AU - Hung, Joseph

AU - Beilby, John

AU - Mathur, Sushma

AU - Reynolds, Anna

AU - Sanfilippo, Francesco M.

PY - 2017

Y1 - 2017

N2 - Objectives: To develop a method for categorising coronary heart disease (CHD) subtype in linked data accounting for different CHD diagnoses across records, and to compare hospital admission numbers and ratios of unlinked versus linked data for each CHD subtype over time, and across age groups and sex.Design: Cohort study.Data source: Person-linked hospital administrative data covering all admissions for CHD in Western Australia from 1988 to 2013.Main outcome: Ratios of (1) unlinked admission counts to contiguous admission (CA) counts (accounting for transfers), and (2) 28-day episode counts (accounting for transfers and readmissions) to CA counts stratified by CHD subtype, sex and age group.Results: In all CHD subtypes, the ratios changed in a linear or quadratic fashion over time and the coefficients of the trend term differed across CHD subtypes. Furthermore, for many CHD subtypes the ratios also differed by age group and sex. For example, in women aged 35–54 years, the ratio of unlinked to CA counts for non-ST elevation myocardial infarction admissions in 2000 was 1.10, and this increased in a linear fashion to 1.30 in 2013, representing an annual increase of 0.0148.Conclusion: The use of unlinked counts in epidemiological estimates of CHD hospitalisations overestimates CHD counts. The CA and 28-day episode counts are more aligned with epidemiological studies of CHD. The degree of overestimation of counts using only unlinked counts varies in a complex manner with CHD subtype, time, sex and age group, and it is not possible to apply a simple correction factor to counts obtained from unlinked data.

AB - Objectives: To develop a method for categorising coronary heart disease (CHD) subtype in linked data accounting for different CHD diagnoses across records, and to compare hospital admission numbers and ratios of unlinked versus linked data for each CHD subtype over time, and across age groups and sex.Design: Cohort study.Data source: Person-linked hospital administrative data covering all admissions for CHD in Western Australia from 1988 to 2013.Main outcome: Ratios of (1) unlinked admission counts to contiguous admission (CA) counts (accounting for transfers), and (2) 28-day episode counts (accounting for transfers and readmissions) to CA counts stratified by CHD subtype, sex and age group.Results: In all CHD subtypes, the ratios changed in a linear or quadratic fashion over time and the coefficients of the trend term differed across CHD subtypes. Furthermore, for many CHD subtypes the ratios also differed by age group and sex. For example, in women aged 35–54 years, the ratio of unlinked to CA counts for non-ST elevation myocardial infarction admissions in 2000 was 1.10, and this increased in a linear fashion to 1.30 in 2013, representing an annual increase of 0.0148.Conclusion: The use of unlinked counts in epidemiological estimates of CHD hospitalisations overestimates CHD counts. The CA and 28-day episode counts are more aligned with epidemiological studies of CHD. The degree of overestimation of counts using only unlinked counts varies in a complex manner with CHD subtype, time, sex and age group, and it is not possible to apply a simple correction factor to counts obtained from unlinked data.

U2 - 10.1136/bmjopen-2017-019226

DO - 10.1136/bmjopen-2017-019226

M3 - Article

VL - 7

JO - BMJ (Open)

JF - BMJ (Open)

SN - 2044-6055

IS - 11

M1 - e019226

ER -