Patient characteristics associated with hospitalisations for ambulatory care sensitive conditions in Victoria, Australia

Ambulatory Care Sensitive Conditions (ACSCs) are those for which hospitalisation is thought to be avoidable with the application of preventive care and early disease management, usually delivered in an primary care setting [1‐4]. In theory, timely and effective ambulatory care can reduce the risks of hospitalisation by preventing the onset of an illness or condition; controlling an acute episodic illness or condition; or managing a chronic disease condition [1‐4]. A broad range of conditions have been identified as ambulatory care sensitive in the literature [2‐6].

ACSCs have been used extensively as an indicator of accessibility and overall effectiveness of primary health care, such that the rate of hospitalisation for ACSCs is higher in communities with poor access to ambulatory care [2, 3, 7‐9]. Used as an indicator, ACSCs are of interest to policy makers in public health and health services research as they represent the occurrence of avoidable morbidity, providing an evidence-based foundation for targeted interventions to control costs of health care provided at public expense [10‐20].

Factors that have previously been examined to explain reasons for differentials in ACSCs admission rates across geographic areas and subgroups of populations include: demographic, socio-economic status (SES), rurality, health system factors, prevalence, life style factors, environment, adherence to medication, propensity to seek care, and severity of illness [21].

ACSCs admission rates have been stratified by age and sex in several studies. Hospitalisation rates for ACSCs are steady in the age groups 19-64 years, with higher rates of admissions in younger (<=18 years) and older (>=65 years) age groups [22]. Older age groups (65+) have been studied extensively in the US, with significant increases in the rates of ACSCs admissions in this age category between 1980 and 1998 [23].

Studies examining SES and ACSCs hospitalisations have also been conducted [2, 4, 6, 8, 9, 17, 18, 20, 24‐35]. Most of these studies found that at least one SES variable (such as income, education, occupation and insurance status) was a statistically significant strong predictor of ACSCs hospitalisation, independently of other measured variables.

Many studies have analysed the effect of location of patients’ residence on ACSCs admission rates [17, 20, 26, 27, 32, 34‐39]. These studies consistently found that the highest rates of hospitalisations for ACSCs admissions occurred in the most rural areas compared to their respective counterparts residing in metropolitan areas.

Only a few studies have considered the joint impact of demographic and socioeconomic characteristics on ACSCs hospitalisations, or examined the different pattern which might pertain to paediatric and adult hospitalisations. From a policy perspective, it is important to understand the profiles of individuals experiencing access barriers to primary care as it can assist in the development of policies and programs that improve access for those individuals [27]. Victoria is the second largest state in Australia with a population of 4.8 million people in 2003. Examining the characteristics of patients may be useful in the development of policies and programs to improve access to primary health care in the state of Victoria.

The aim of this study was to examine the association between patient characteristics and hospitalisation for ACSCs in the adult and paediatric population groups in Victoria, Australia, 2003/04. More specifically, this paper reports on differentials in ASCSs admission rates among subgroups of the population included SES and rurality.

Data were obtained at both the individual- and aggregate (ecologic) level.

The study adds to knowledge of how ACSCs admission rates vary with demographic and socio-economic characteristics in several ways:

This study identified significant patient socio-demographic characteristics that were associated with higher admission rates of ACSCs, identifying potential access to primary health care problems faced by the Victorians. In the adult population, the key factors include male sex, older age, rural residence, degree of remoteness, and socio-economic disadvantage. Higher rates of ACSCs admissions in rural areas have been observed in other studies [9, 17, 20, 26, 27, 36, 38, 39]. In Victoria, significant differentials between rural and metropolitan areas have been previously described [43]. Key factors within rural areas that may be associated with higher ACSCs admission rates include degree of remoteness and accessibility to services, lower number of general practitioners per population suggesting that remote areas have fewer sources of easy to reach primary care, and socio-economic disadvantage [43]. SES has been identified in several studies as important predictor of ACSCs admission rates. This has been observed using individual level measures such as insurance status or access to Medicaid,[4, 26, 27, 50] as well as area level measures,[2, 6, 8, 17, 18, 24] which were used in this study.

The strength of the study was the analyses of characteristics of both the adult and paediatric population, highlighting potential access barriers faced in both population groups. In both the adult and paediatric groups, rural areas and areas of residence with least accessibility were associated with higher ACSCs admission rates. Male adults were more likely to be admitted with ACSCs admissions, while no significant sex differentials were observed for paediatric groups. In addition, older adults and younger children were more likely to be admitted for ACSCs than younger adults and older children, similar to the findings reported in an earlier study [27]. The findings from our study indicate that male adults, older adults, and younger children may potentially face greater access barriers than female adults and younger adults and older children.

Diabetes complications and dental conditions were the leading cause of hospital admissions in the adult and paediatric populations, respectively. Earlier studies in Victoria have also highlighted significant differentials across communities for diabetes complications, with admission rates significantly higher in rural areas compared to metropolitan [42, 51]. There are effective treatments available to prevent the progression of diabetes-related complications. Since these interventions generally achieve the best results if started in the early asymptomatic stages, and complications can progress to an advanced stage before symptoms develop, regular medical screening is essential to identify people who require treatment for their complications [52]. Strategic approaches to manage diabetes have now been developed [53]. Higher admission rates of dental conditions among children, especially in rural areas have also been reported in Victoria [54]. In Victoria, the importance of management of dental conditions in the community has been identified, and strategic approaches to improve the management of dental conditions are being implemented [55].

This study is useful in several ways:

The ACSCs in this study included conditions that can be prevented through vaccination e.g., measles, mumps, rubella, tetanus, influenza, and bacterial pneumonia (vaccine preventable ACSCs), acute conditions for which hospitalisations is commonly avoidable with medical interventions available in primary care or the use of antibiotics e.g. dehydration and gastroenteritis, kidney infection, cellulitis, perforated ulcer, ear, nose, and throat infections, pelvic inflammatory disease, and dental conditions (acute ACSCs), and selected chronic conditions that can be managed by life style factors, patient education and pharmaceuticals e.g., diabetes complications, angina, hypertension, asthma, COPD and CCF (chronic ACSCs). Most codes used in this study are available in earlier reports and papers published from the USA and England [4, 35, 44, 62, 63]. These codes of ACSCs have been validated as markers of access to primary health care in the USA and Australia [7, 8]. However, due to consistent variations in ACSCs definitions and codes, comparison across different datasets and geographic areas is a problem for informing policy and planning [44]. Caminal and Colleagues have recommended that choice of ACSCs should be country specific due to variations in health system between different countries [64].

Access barriers identified in this study are not unique to Victoria. Several international studies have identified access barriers, especially in the disadvantaged populations [7, 34, 65, 66]. For policy makers across the world, the question of access is inextricably linked with equity, one of the key performance indicators of the health system [67]. Most health systems offer inequitable access, and deliver inequitable treatment and outcomes. The goal of equity has not been achieved as seen by significant health differentials between racial, ethnic and socio-economic groups; less than adequate health care provided to vulnerable groups; and policy makers steering away rather than tackling these issues with strong policies.

A recent international survey of individuals’ views of primary health care found that a majority of Australians had been with the same doctor or place of care for more than 5 years and received appointments the same day the last time they needed medical attention [68]. On the other hand, a majority also indicated that accessing primary care after hours was difficult, although the problem in Australia was less widespread than in the United States [68]. Seventeen percent of Australians reported that they did not get medical care because of the cost of a doctor’s visit in the previous 12 months, compared with 6 percent in Canada, 28 percent in New Zealand, 4 percent in the United Kingdom, and 29 percent in the United States [68]. Similar percentages were reported for having skipped a medical test, treatment, or follow-up because of cost [68]. Australians’ reported access barriers are notably greater than those of people in the United Kingdom but also notably less than those of people in the United States. Because of universal insurance in Australia, results of this study may not directly apply to the United States. However, about 43 million Americans are beneficiaries of Medicare, a universal insurance plan of long standing. The prevalence of ACSCs is much higher in the population age 65 and older than in younger populations, as is the occurrence of ACSCs. Thus, the results from Australia may be relevant to the United States’ Medicare system.

In a system that seeks to be egalitarian, equity is the most difficult criteria to operationalise [67]. In this context, it is important to understand that access is multifaceted, not only measuring characteristics of the health system but also characteristics of individuals and the areas it serves [67]. The multiple dimensions of access reflect the need for a new research agenda that includes an expanded primary care and health services research and policy agenda, with a focus on factors that lie outside the health system [67].

Our study is subject to various caveats. The data for this study is from 2003/04. However, more recent ACSCs data from Victoria [69], as well as other jurisdictions [70] and overseas [30, 71], indicates that associations with demographic and socioeconomic factors are robust and persist across time. The findings from this study are likely to be still of relevance now, and elsewhere. As administrative database was used to identify ACSCs, the recorded diagnoses are prone to coding errors. Reliability and validity of the data in the VAED has been well documented in earlier studies, and is unlikely to have biased our results [72‐74]. The 2001 ABS Census of population and Housing was the source of aggregate level data used in this study. The ABS Census of population and Housing is a rich source of data for understanding the socio-demographic makeup, range and variation between communities, with information available down to a small aggregated level. The advantage of using Census data lies mainly in its coverage, virtually 100% complete, and sophisticated quality assurance processes aimed at minimising potential sources of errors such as undercounting, partial response, respondent error, and processing error [45]. In this study, analyses of the predictors of ACSCs were based on hospitalization data, using non-ACSCs as an approximation for those not hospitalized with an ACSCs. Future studies can be designed looking at predictors of ACSCs hospitalisation based on individual level data that includes patients that are hospitalised and those not hospitalised, although such data are hard to obtain. As the data are cross-sectional, the findings need to be interpreted with caution. The observed associations of socio-economic disadvantage, rurality and age with ACSCs admissions may not necessarily be causal. Although the Victorian ACSCs study has shown strong relationship of access with ACSCs , several other factors such as disease prevalence, co-morbidities, and physician practice patterns may also potentially explain observed differentials in this study [7, 8]. These factors can be further explored in the form of case control or prospective studies that can compare ambulatory care provided to the patients from high and low socio-economic status before admissions to hospitals. Finally, repeated hospitalisations were not excluded from the analyses due to lack of a unique identifier, which may have biased our results if the predictor variables were associated with readmission rates across population groups.

This study suggests that lack of timely and effective primary care may have significant impact on rates of admissions for ACSCs that vary by both individual- and area-level socio-demographics of the adult and paediatric population. Disadvantaged paediatric and adult population experience more need of hospital care for ACSCs. Access barriers to primary care are plausible causes for the observed disparities. These findings may have important implications for design and implementation of interventions for improving access to primary health care and reducing disparities in health.

VAED administrative database is used in this paper. No human subjects or research on human subject was conducted. The data used are de-identified and only aggregate level information is presented. In addition, we i.e. the Health Intelligence Unit (HIU) are the secondary data custodians of the VAED.