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. 2017 Nov 17;7(11):e019226.
doi: 10.1136/bmjopen-2017-019226.

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

Derrick Lopez  1 , Lee Nedkoff  1 , Matthew Knuiman  1 , Michael S T Hobbs  1 , Thomas G Briffa  1 , David B Preen  1 , Joseph Hung  2 , John Beilby  3 , Sushma Mathur  4 , Anna Reynolds  4 , Frank M Sanfilippo  1
Affiliations

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

Derrick Lopez et al. BMJ Open. .

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.

Keywords: cardiac epidemiology; coronary heart disease.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Comparison of CHD counts from 1988 to 2013 using four different approaches at the contiguous admission level. ACS, acute coronary syndrome; CHD, coronary heart disease; MI, myocardial infarction; NSTEMI, non-STEMI; STEMI, ST elevation myocardial infraction.
Figure 2
Figure 2
Comparison of CHD counts at the unlinked, CA (diagnosis hierarchy approach) and 28-day episode levels from 1988 to 2013. ACS, acute coronary syndrome; CA, contiguous admission; CHD, coronary heart disease; MI, myocardial infarction; NSTEMI, non-STEMI; STEMI, ST elevation myocardial infarction.
See this image and copyright information in PMC

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