Recognising potential for preventing hospitalisation
David Banham A F , Tony Woollacott A , John Gray B , Brett Humphrys C , Angel Mihnev D and Robyn McDermott EA Strategic Planning, Research and Analysis Unit, SA Health, Level 10, CitiCentre 11 Hindmarsh Square, Adelaide, SA 5000, Australia.
B Southern Adelaide Health Service, Sir Mark Oliphant Building, Lafter Drive, Science Park, Bedford Park, SA 5042, Australia.
C Country Health South Australia, Port Augusta Hospital, 36 Flinders Terrace, Port Augusta, SA 5700, Australia.
D Central Northern Adelaide Health Service, 207-255 Hampstead Road, Northfield, SA 5085, Australia.
E Division of Health Sciences, University of South Australia, City East Campus, North Terrace, Adelaide, SA 5000, Australia.
F Corresponding author. Email: david.banham@health.sa.gov.au
Australian Health Review 34(1) 116-122 https://doi.org/10.1071/AH09674
Submitted: 11 August 2008 Accepted: 1 April 2009 Published: 25 March 2010
Abstract
To identify the incidence and distribution of public hospital admissions in South Australia that could potentially be prevented with appropriate use of primary care services, analysis was completed of all public hospital separations from July 2006 to June 2008 in SA. This included those classified as potentially preventable using the Australian Institute of Health and Welfare criteria for selected potentially preventable hospitalisations (SPPH), by events and by individual, with statistical local area geocoding and allocation of relative socioeconomic disadvantage quintile. A total of 744 723 public hospital separations were recorded, of which 79 424 (10.7%) were classified as potentially preventable. Of these, 59% were for chronic conditions, and 29% were derived from the bottom socioeconomic status (SES) quintile. Individuals in the lowest SES quintile were 2.5 times more likely to be admitted for a potentially preventable condition than those from the top SES quintile. Older individuals, males, those in the most disadvantaged quintiles, non-metropolitan areas and Indigenous people were more likely to have more than one preventable admission.
People living in more disadvantaged areas in SA appear to have poorer utilisation of effective primary care, resulting in preventable hospital admissions, than those in higher SES groups. The SA Health Care Plan, 2007–2016 is aimed at investing in improved access to primary care in those areas of most disadvantage. The inclusion of SPPHs in future routine reporting should identify if this has occurred.
What is known about the topic? Ambulatory care sensitive conditions, or selected potentially preventable hospitalisation separations (SPPH), are an indicator of the availability and effectiveness of primary health care. SPPHs are increasingly reported by area level disadvantage.
What does this paper add? This paper offers analysis by individuals. It shows around three-quarters of individuals had one potentially preventable public hospital separation. The rate among those living in the most disadvantaged areas was more than twice that of lowest disadvantage areas.
What are the implications for practitioners? Realising the potential for preventing potentially avoidable hospitalisation may involve focus on particular target areas and subpopulations. Potentially preventable separations by area of disadvantage can assist with monitoring performance and evaluating policy and program initiatives. Analysis by numbers of individuals will enhance this further.
Acknowledgement
The opinions expressed here do not necessarily reflect those of the South Australian Government or SA Health.
[1] Ansari Z, Barbetti T, Carson NJ, Auckland MJ, Cicuttini F. The Victorian ambulatory care sensitive conditions study: rural and urban perspectives. Soz Praventivmed 2003; 48 33–43.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
[2] Caminal J, Starfield B, Sánchez E, Casanova C, Morales M. The role of primary care in preventing ambulatory care sensitive conditions. Eur J Public Health 2004; 14 246–51.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
[3] Gusmano MK, Rodwin VG, Weisz D. A new way to compare health systems: avoidable hospital conditions in Manhattan and Paris. Health Aff 2006; 25 510–20.
| Crossref | GoogleScholarGoogle Scholar |
[4] Shah BR, Gunraj N, Hux JE. Markers of access to and quality of primary care for Aboriginal people in Ontario, Canada. Am J Public Health 2003; 93 798–802.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
[5]
[6]
[7] DeLia D. Distributional issues in the analysis of preventable hospitalizations. Health Serv Res 2003; 38 1761–80.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
[8] Roos LL, Walld R, Uhanova J, Bond R. Physician visits, hospitalizations, and socioeconomic status: ambulatory care sensitive conditions in a Canadian setting. Health Serv Res 2005; 40 1167–85.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
[9]
[10] Stamp KM, Duckett SJ, Fisher DA. Hospital use for potentially preventable conditions in Aboriginal and Torres Strait Islander and other Australian populations. Aust N Z J Public Health 1998; 22(6): 673–8.
| Crossref | GoogleScholarGoogle Scholar | PubMed | CAS |
[11]
[12] Pappas G, Hadden WC, Kozak LJ, Fisher GF. Potentially avoidable hospitalizations: Inequalities in rates between US socioeconomic groups. Am J Public Health 1997; 87 811–6.
| Crossref | GoogleScholarGoogle Scholar | PubMed | CAS |
[13]
[14]
[15]
[16]
[17]
[18]
[19] Marascuilo LA, Slaughter RE. Statistical procedures for identifying possible sources of item bias based on χ2 statistics. J Educ Meas 1981; 18 229–48.
| Crossref | GoogleScholarGoogle Scholar |
[20]
[21]
A Throughout this report, ACSCs and SPPHs are taken to be coterminous and a full list of the relevant International Classification of Diseases, Version 10 codes applied are listed in table A1.9 at http://www.aihw.gov.au/publications/hse/ahs05-06/ahs05-06-x01.xls
B ICD-10 Principal diagnosis of renal dialysis (Z49) and any additional diagnosis in the range E10 to E14.9.
