Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia.
To explore patterns of health service use in the lead-up to, and following, admission for a 'preventable' hospitalisation.



266 950 participants in the 45 and Up Study, New South Wales (NSW) Australia



Linked data on hospital admissions, general practitioner (GP) visits and other health events were used to create visual representations of health service use. For each participant, health events were plotted against time, with different events juxtaposed using different markers and panels of data. Various visualisations were explored by patient characteristics, and compared with a cohort of non-admitted participants matched on sociodemographic and health characteristics. Health events were displayed over calendar year and in the 90 days surrounding first preventable hospitalisation.



The visualisations revealed patterns of clustering of GP consultations in the lead-up to, and following, preventable hospitalisation, with 14% of patients having a consultation on the day of admission and 27% in the prior week. There was a clustering of deaths and other hospitalisations following discharge, particularly for patients with a long length of stay, suggesting patients may have been in a state of health deterioration. Specialist consultations were primarily clustered during the period of hospitalisation. Rates of all health events were higher in patients admitted for a preventable hospitalisation than the matched non-admitted cohort.



We did not find evidence of limited use of primary care services in the lead-up to a preventable hospitalisation, rather people with preventable hospitalisations tended to have high levels of engagement with multiple elements of the healthcare system. As such, preventable hospitalisations might be better used as a tool for identifying sicker patients for managed care programmes. Visualising longitudinal health data was found to be a powerful strategy for uncovering patterns of health service use, and such visualisations have potential to be more widely adopted in health services research.
Centre for Big Data Research in Health, University of New South Wales Australia, Sydney, Australia.
Michael O
0000-0001-6444-7272
MO
Falster
Centre for Big Data Research in Health, University of New South Wales Australia, Sydney, Australia.
Louisa R
LR
Jorm
MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
Alastair H
AH
Leyland
D000368:Aged; D015331:Cohort Studies; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D005260:Female; D006302:Health Services Research / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009517:New South Wales; D011320:Primary Health Care / Q000706:statistics & numerical data*; D011446:Prospective Studies
PRIMARY CARE; Preventable hospitalisations; data visualisations; longitudinal health data