The aim of the study was to undertake a six-year analysis from 1999/00 to 2004/05, of the demographic characteristics of hospitalisations for the surgical removal of impacted teeth in Western Australia under general anaesthesia.
Data for the current analysis was obtained from the Western Australian Hospital Morbidity Data System (HMDS). Gender, age, indigenous status, place of residence, type of hospital admitted, insurance status, and Diagnostic Related Group (DRG) cost estimates for the procedure were analysed.
A total of 37.6% of all oral health-related hospitalisations in Western Australia over the six years were for the removal of impacted teeth. Admitted patients were predominantly females (58.8%) and very few Indigenous people were hospitalised (0.2%). The average age of patients was 21.4 years (sd=9.9). Metropolitan patients were hospitalised 1.5 times more than rural patients for this condition. The majority of patients were hospitalised at a private metropolitan hospital and were insured. The total cost of hospitalisation for this condition contributes to 27% of all the oral health condition-related hospitalisation costs.
This study suggests that the hospital-based removal of impacted teeth in Western Australia is associated with factors such as indigenous status, age, gender and private hospital access along with insurance status raising interesting questions over the equity of provision of this service.
Impacted teeth; third molars; indigenous; Australia
Within the health literature, a major goal is to understand distribution of service utilisation by social location. Given equivalent access, differential incidence leads to an expectation of differential service utilisation. Cancer incidence is differentially distributed with respect to socioeconomic status. However, not all jurisdictions have incidence registries, and not all registries allow linkage with utilisation records. The British Columbia Linked Health Data resource allows such linkage. Consequently, we examine whether, in the absence of registry data, first hospitalisation can act as a proxy measure for incidence, and therefore as a measure of need for service.
Data are drawn from the British Columbia Linked Health Data resource, and represent 100% of Vancouver Island Health Authority cancer registry and hospital records, 1990–1999. Hospital separations (discharges) with principal diagnosis ICD-9 codes 140–208 are included, as are registry records with ICDO-2 codes C00-C97. Non-melanoma skin cancer (173/C44) is excluded. Lung, colorectal, female breast, and prostate cancers are examined separately. We compare registry and hospital annual counts and age-sex distributions, and whether the same individuals are represented in both datasets. Sensitivity, specificity and predictive values are calculated, as is the kappa statistic for agreement. The registry is designated the gold standard.
For all cancers combined, first hospitalisation counts consistently overestimate registry incidence counts. From 1995–1999, there is no significant difference between registry and hospital counts for lung and colorectal cancer (p = 0.42 and p = 0.56, respectively). Age-sex distribution does not differ for colorectal cancer. Ten-year period sensitivity ranges from 73.0% for prostate cancer to 84.2% for colorectal cancer; ten-year positive predictive values range from 89.5% for female breast cancer to 79.35% for prostate cancer. Kappa values are consistently high.
Claims and registry databases overlap with an appreciable proportion of the same individuals. First hospital separation may be considered a proxy for incidence with reference to colorectal cancer since 1995. However, to examine equity across cancer health services utilisation, it is optimal to have access to both hospital and registry files.
In the absence in the major Australian administrative health record collections of a direct measure of the socioeconomic status of the individual about whom the event is recorded, analysis of the association between the health status, use of health services and socioeconomic status of the population relies an area-based measure of socioeconomic status.
This paper explores the reliability of the area of address (at the levels typically available in administrative data collections) as a proxy measure for socioeconomic disadvantage. The Western Australian Data Linkage System was used to show the extent to which hospital inpatient separation rates for residents of Perth vary by socioeconomic status of area of residence, when calculated at various levels of aggregation of area, from smallest (Census Collection District) to largest (postcode areas and Statistical Local Areas). Results are also provided of the reliability, over time, of the address as a measure of socioeconomic status.
There is a strong association between the socioeconomic status of the usual address of hospital inpatients at the smallest level in Perth, and weaker associations when the data are aggregated to larger areas. The analysis also shows that a higher proportion of people from the most disadvantaged areas are admitted to hospital than from the most well-off areas (13% more), and that these areas have more separations overall (47% more), as a result of larger numbers of multiple admissions.
Of people admitted to hospital more than once in a five year period, four out of five had not moved address by the time of their second episode. Of those who moved, the most movement was within, or between, areas of similar socioeconomic status, with people from the most well off areas being the least likely to have moved.
Postcode level and SLA level data provide a reliable, although understated, indication of socioeconomic disadvantage of area. The majority of Perth residents admitted to hospital in Western Australia had the same address when admitted again within five years. Of those who moved address, the majority had moved within, or between, areas of similar socioeconomic status.
Access to data about individuals from the Western Australian Data Linkage System shows that more people from disadvantaged areas are admitted to a hospital, and that they have more episodes of hospitalisation. Were data to be available across Australia on a similar basis, it would be possible to undertake research of greater policy-relevance than is currently possible with the existing separations-based national database.
In Australia there is a socioeconomic gradient in morbidity and mortality favouring socioeconomically advantaged people, much of which is accounted for by ischaemic heart disease. This study examines if Australia's universal health care system, with its mixed public/private funding and delivery model, may actually perpetuate this inequity. We do this by quantifying and comparing socioeconomic inequalities in the receipt of coronary procedures in patients with acute myocardial infarction (AMI) and patients with angina.
Using linked hospital and mortality data, we followed patients admitted to Western Australian hospitals with a first admission for AMI (n = 5539) or angina (n = 7401) in 2001-2003. An outcome event was the receipt, within a year, of a coronary procedure—angiography, angioplasty and/or coronary artery bypass surgery (CABG). Socioeconomic status was assigned to each individual using an area-based measure, the SEIFA Index of Disadvantage. Multivariable proportional hazards regression was used to model the association between socioeconomic status and procedure rates, allowing for censoring and adjustment of multiple covariates. Mediating models examined the effect of private health insurance.
In the AMI patient cohort, socioeconomic gradients were not evident except that disadvantaged women were more likely than advantaged women to undergo CABG. In contrast, in the angina patient group there were clear socioeconomic gradients for all procedures, favouring more advantaged patients. Compared with patients in the most disadvantaged quintile of socioeconomic status, patients in the least disadvantaged quintile were 11% (1-21%) more likely to receive angiography, 52% (29-80%) more likely to undergo angioplasty and 30% (3-55%) more likely to undergo CABG. Private health insurance explained some of the socioeconomic variation in rates.
Australia's universal health care system does not guarantee equity in the receipt of high technology health care for patients with ischaemic heart disease. While such a system might ensure equity for patients with AMI, where guidelines for treatment are relatively well established, this is not the case for angina patients, where health care may be less urgent and more discretionary.
Routinely collected data such as hospital morbidity data (HMD) are increasingly used in studying clinical outcomes among patients undergoing total joint replacement (TJR). These data are readily available and cover large populations. However, since these data were not originally collected for the purpose of health research, a rigorous assessment of their quality is required. We assessed the accuracy of the diagnosis of obesity in HMD and evaluated whether the augmentation of HMD with actual weight and height of patients could improve their ability to predict major in-hospital complications following total joint replacement in men.
The electronic records of 857 participants in the Health In Men Study (HIMS) who had had TJR were linked with Western Australia HMD. HMD-recorded diagnosis of obesity was validated using the actual weight and height obtained from HIMS. In-hospital major complications were modelled using multivariable logistic regressions that either included the actual weight and height or HMD-recorded obesity. Model discrimination was calculated using area under ROC curve.
The HMD failed to detect 70% of the obese patients. Only 64 patients (7.5%) were recorded in HMD as obese although 216 (25%) were obese [BMI: ≥30kg/m2] (sensitivity: 0.2, positive predictive value: 0.7). Overall, 174 patients (20%) developed an in-hospital major complication which was significantly higher in the overweight and obese comparing with patients with normal weight. HMD-recorded obesity was not independently associated with major complications, whereas a dose–response relationship between weight and these complications was observed (P=0.004). Using the actual weight and height of the participants instead of HMD-recorded diagnosis of obesity improved model discrimination by 9%, with areas under ROC curve of: 0.69, 95% CI: 0.64-0.73 for the model with HMD-recorded obesity compared with 0.75, 95% CI: 0.70-0.79 for the model with actual weight and height, P<0.001.
Body weight is an important risk factor for in-hospital complications in patients undergoing TJR. HMD systems do not include weight and height as variables whose recording is mandatory. Augmenting HMD with patients’ weight and height may improve prediction of major complications following TJR. Our study suggests making these variables mandatory in any hospital morbidity data system.
The burden of patients with heart failure on health care systems is widely recognised, although there have been few attempts to quantify individual patterns of care and differences in health service utilisation related to age, socio-economic factors and the presence of co-morbidities. The aim of this study was to assess the typical profile, trajectory and resource use of a cohort of Australian patients with heart failure using linked population-based, patient-level data.
Using hospital separations (Admitted Patient Data Collection) with death registrations (Registry of Births, Deaths and Marriages) for the period 2000–2007 we estimated age- and gender-specific rates of index admissions and readmissions, risk factors for hospital readmission, mean length of stay (LOS), median survival and bed-days occupied by patients with heart failure in New South Wales, Australia.
We identified 29,161 index admissions for heart failure. Admission rates increased with age, and were higher for males than females for all age groups. Age-standardised rates decreased over time (256.7 to 237.7/100,000 for males and 235.3 to 217.1/100,000 for females from 2002–3 to 2006–7; p = 0.0073 adjusted for gender). Readmission rates (any cause) were 27% and 73% at 28-days and one year respectively; readmission rates for heart failure were 11% and 32% respectively. All cause mortality was 10% and 28% at 28 days and one year. Increasing age was associated with more heart failure readmissions, longer LOS and shorter median survival. Increasing age, increasing Charlson comorbidity score and male gender were risk factors for hospital readmission. Cohort members occupied 954,888 hospital bed-days during the study period (any cause); 383,646 bed-days were attributed to heart failure admissions.
The rates of index admissions for heart failure decreased significantly in both males and females over the study period. However, the impact on acute care hospital beds was substantial, with heart failure patients occupying almost 200,000 bed-days per year in NSW over the five year study period. The strong age-related trends highlight the importance of stabilising elderly patients before discharge and community-based outreach programs to better manage heart failure and reduce readmissions.
Heart failure; Hospitalization; Health services research; Australia
Potentially preventable hospitalisation (PPH) has been adopted widely by international health systems as an indicator of the accessibility and overall effectiveness of primary care. The Assessing Preventable Hospitalisation InDicators (APHID) study will validate PPH as a measure of health system performance in Australia and Scotland. APHID will be the first large-scale study internationally to explore longitudinal relationships between primary care and PPH using detailed person-level information about health risk factors, health status and health service use.
Methods and analysis
APHID will create a new longitudinal data resource by linking together data from a large-scale cohort study (the 45 and Up Study) and prospective administrative data relating to use of general practitioner (GP) services, dispensing of pharmaceuticals, emergency department presentations, hospital admissions and deaths. We will use these linked person-level data to explore relationships between frequency, volume, nature and costs of primary care services, hospital admissions for PPH diagnoses, and health outcomes, and factors that confound and mediate these relationships. Using multilevel modelling techniques, we will quantify the contributions of person-level, geographic-level and service-level factors to variation in PPH rates, including socioeconomic status, country of birth, geographic remoteness, physical and mental health status, availability of GP and other services, and hospital characteristics.
Ethics and dissemination
Participants have consented to use of their questionnaire data and to data linkage. Ethical approval has been obtained for the study. Dissemination mechanisms include engagement of policy stakeholders through a reference group and policy forum, and production of summary reports for policy audiences in parallel with the scientific papers from the study.
Epidemiology; Health Services Administration & Management; Primary Care; Public Health; Statistics & Research Methods
Measuring the real burden of cardiovascular disease in Australian Aboriginals is complicated by under-identification of Aboriginality in administrative health data collections. Accurate data is essential to measure Australia's progress in its efforts to intervene to improve health outcomes of Australian Aboriginals. We estimated the under-ascertainment of Aboriginal status in linked morbidity and mortality databases in patients hospitalised with cardiovascular disease.
Persons with public hospital admissions for cardiovascular disease in Western Australia during 2000-2005 (and their 20-year admission history) or who subsequently died were identified from linkage data. The Aboriginal status flag in all records for a given individual was variously used to determine their ethnicity (index positive, and in all records both majority positive or ever positive) and stratified by region, age and gender. The index admission was the baseline comparator.
Index cases comprised 62,692 individuals who shared a total of 778,714 hospital admissions over 20 years, of which 19,809 subsequently died. There were 3,060 (4.9%) persons identified as Aboriginal on index admission. An additional 83 (2.7%) Aboriginal cases were identified through death records, increasing to 3.7% when cases with a positive Aboriginal identifier in the majority (≥50%) of previous hospital admissions over twenty years were added and by 20.8% when those with a positive flag in any record over 20 years were incorporated. These results equated to underestimating Aboriginal status in unlinked index admission by 2.6%, 3.5% and 17.2%, respectively. Deaths classified as Aboriginal in official records would underestimate total Aboriginal deaths by 26.8% (95% Confidence Interval 24.1 to 29.6%).
Combining Aboriginal determinations in morbidity and official death records increases ascertainment of unlinked cardiovascular morbidity in Western Australian Aboriginals. Under-identification of Aboriginal status is high in death records.
The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia.
We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated.
This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity.
Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap.
One group often identified as having low socioeconomic status, those living in remote or rural areas, are often recognised as bearing an unequal burden of illness in society. This paper aims to examine equity of utilisation of general practitioner services in Australia.
Using the 2005 National Health Survey undertaken by the Australian Bureau of Statistics, a microsimulation model was developed to determine the distribution of GP services that would occur if all Australians had equal utilisation of health services relative to need.
It was estimated that those who are unemployed would experience a 19% increase in GP services. Persons residing in regional areas would receive about 5.7 million additional GP visits per year if they had the same access to care as Australians residing in major cities. This would be a 18% increase. There would be a 20% increase for inner regional residents and a 14% increase for residents of more remote regional areas. Overall there would be a 5% increase in GP visits nationally if those in regional areas had the same access to care as those in major cities.
Parity is an insufficient goal and disadvantaged persons and underserved areas require greater access to health services than the well served metropolitan areas due to their greater poverty and poorer health status. Currently underserved Australians suffer a double disadvantage: poorer health and poorer access to health services.
Although universal health care aims for equity in service delivery, socioeconomic status still affects death rates from ischemic heart disease and stroke as well as access to revascularization procedures. We investigated whether psychiatric status is associated with a similar pattern of increased mortality but reduced access to procedures. We measured the associations between mental illness, death, hospital admissions and specialized or revascularization procedures for circulatory disease (including ischemic heart disease and stroke) for all patients in contact with psychiatric services and primary care across Nova Scotia.
We carried out a population-based record-linkage analysis of related data from 1995 through 2001 using an inception cohort to calculate rate ratios compared with the general public for each outcome (n = 215 889). Data came from Nova Scotia's Mental Health Outpatient Information System, physician billings, hospital discharge abstracts and vital statistics. We estimated patients' income levels from the median incomes of their residential neighbourhoods, as determined in Canada's 1996 census.
The rate ratio for death of psychiatric patients was significantly increased (1.34), even after adjusting for potential confounders, including income and comorbidity (95% confidence interval [CI] 1.29–1.40), which was reflected in the adjusted rate ratio for first admissions (1.70, 95% CI 1.67–1.72). Their chances of receiving a procedure, however, did not match this increased risk. In some cases, psychiatric patients were significantly less likely to undergo specialized or revascularization procedures, especially those who had ever been psychiatric inpatients. In the latter case, adjusted rate ratios for cardiac catheterization, percutaneous transluminal coronary angioplasty and coronary artery bypass grafts were 0.41, 0.22 and 0.34, respectively, in spite of psychiatric inpatients' increased risk of death.
Psychiatric status affects survival with and access to some procedures for circulatory disease, even in a universal health care system that is free at the point of delivery. Understanding how these disparities come about and how to reduce them should be a priority for future research.
To demonstrate the use of end-quintile comparisons in assessing the effect of socio-economic status on hospital utilisation and outcomes in Western Australia.
Hospital morbidity records were extracted from the WA Data Linkage System for the period 1994–99, with follow-up to the end of 2000. Multivariate modelling was used to estimate the effect of socio-economic status on hospital admission rates, average and total length of stay (LOS), cumulative incidence of readmission at 30 days and one year, and case fatality at one year.
The study demonstrated higher rate ratios of hospital admission in the more disadvantaged quintiles: rate ratios were 1.31 (95% CI 1.25–1.37) and 1.32 (1.26–1.38) in the first quintile (most disadvantaged) and the second quintile respectively, compared with the fifth quintile (most advantaged). There was a longer total LOS in the most disadvantaged quintile compared with quintile 5 (LOS ratio 1.24; 1.23–1.26). The risk of readmission at 30 days and one year and the risk of death at one year were also greater in those with greater disadvantage: the hazard ratios for quintiles 1:quintile 5 were 1.07 (1.05–1.09), 1.17 (1.16–1.18) and 1.10 (1.07–1.13) respectively. In contradiction to the trends towards higher hospital utilisation and poorer outcomes with increasing social disadvantage, in some MDC's the rate ratio of quintile 1:quintile 2 was less than 1, and quintile 4:quintile 5 was greater than 1. For all surgical admissions the most disadvantaged had a significantly lower admission rate than the second quintile.
This study has shown that the disadvantaged within Western Australia are more intensive users of hospital services but their outcomes following hospitalisation are worse, consistent with their health status. Instances of overuse in the least disadvantaged and under use in the most disadvantaged have also been identified.
Australia is a wealthy developed country. However, there are significant disparities in health outcomes for Aboriginal infants compared with other Australian infants. Health outcomes tend to be worse for those living in remote areas. Little is known about the health service utilisation patterns of remote dwelling Aboriginal infants. This study describes health service utilisation patterns at the primary and referral level by remote dwelling Aboriginal infants from northern Australia.
Data on 413 infants were analysed. Following birth, one third of infants were admitted to the regional hospital neonatal nursery, primarily for preterm birth. Once home, most (98%) health service utilisation occurred at the remote primary health centre, infants presented to the centre about once a fortnight (mean 28 presentations per year, 95%CI 26.4-30.0). Half of the presentations were for new problems, most commonly for respiratory, skin and gastrointestinal symptoms. Remaining presentations were for reviews or routine health service provision. By one year of age 59% of infants were admitted to hospital at least once, the rate of hospitalisation per infant year was 1.1 (95%CI 0.9-1.2).
The hospitalisation rate is high and admissions commence early in life, visits to the remote primary health centre are frequent. Half of all presentations are for new problems. These findings have important implications for health service planning and delivery to remote dwelling Aboriginal families.
Socioeconomic status appears to be an important predictor of coronary angiography use after acute myocardial infarction. One potential explanation for this is that patients with lower socioeconomic status live in neighbourhoods near nonteaching hospitals that have no catheterization capacity, few specialists and lower volumes of patients with acute myocardial infarction. This study was conducted to determine whether the impact of socioeconomic status on angiography use would be lessened by considering variations in the supply of services.
We examined payment claims for physician services, hospital discharge abstracts and vital status data for 47 036 patients with acute myocardial infarction admitted to hospitals in Ontario between April 1994 and March 1997. Neighbourhood income of each patient was obtained from Canada's 1996 census. Using multivariate hierarchical logistic regression and adjusting for baseline patient and physician factors, we examined the interaction among hospital and regional characteristics, socioeconomic status and angiography use in the first 90 days after admission to hospital for acute myocardial infarction.
Within each hospital and geographic subgroup, crude rates of angiography rose progressively with increases in neighbourhood income. After adjusting for sociodemographic, clinical and physician characteristics, hospitals with on-site angiography capacity (adjusted odds ratio [OR] 1.88, 95% confidence interval [CI] 1.52–2.33), those with university affiliations (adjusted OR 1.60, 95% CI 1.27–2.01) and those closest to tertiary institutions (adjusted OR 1.57, 95% CI 1.32–1.87) were all associated with higher 90-day angiography use after acute myocardial infarction. However, the relative impact of socioeconomic status on 90-day angiography use was similar whether or not hospitals had on-site procedural capacity (interaction term p = 0.68), had university affiliations (interaction term p = 0.99), were near tertiary facilities (interaction term p = 0.67) or were in rural or urban regions (interaction term p = 0.90).
Socioeconomic status was as important a predictor of angiography use in hospitals with ready access to cardiac catheterization facilities as it was in those without. The socioeconomic gradient in the use of angiography after acute myocardial infarction cannot be explained by the distribution of specialists or tertiary hospitals.
In 2001, Thailand implemented the Universal Coverage Scheme (UCS), a public insurance system that aimed to achieve universal access to healthcare, including essential medicines, and to influence primary care centres and hospitals to use resources efficiently, via capitated payment for outpatient services and other payment policies for inpatient care. Our objective was to evaluate the impact of the UCS on utilisation of medicines in Thailand for three non-communicable diseases: cancer, cardiovascular disease and diabetes.
Interrupted time-series design, with a non-equivalent comparison group.
Quarterly purchases of medicines from hospital and retail pharmacies collected by IMS Health between 1998 and 2006.
UCS implementation, April–October 2001.
Total pharmaceutical sales volume and percent market share by licensing status and National Essential Medicine List status.
The UCS was associated with long-term increases in sales of medicines for conditions that are typically treated in outpatient primary care settings, such as diabetes, high cholesterol and high blood pressure, but not for medicines for diseases that are typically treated in secondary or tertiary care settings, such as heart failure, arrhythmias and cancer. Although the majority of increases in sales were for essential medicines, there were also postpolicy increases in sales of non-essential medicines. Immediately following the reform, there was a significant shift in hospital sector market share by licensing status for most classes of medicines. Government-produced products often replaced branded generic or generic competitors.
Our results suggest that expanding health insurance coverage with a medicine benefit to the entire Thai population increased access to medicines in primary care. However, our study also suggests that the UCS may have had potentially undesirable effects. Evaluations of the long-term impacts of universal health coverage on medicine utilisation are urgently needed.
Essential Medicines; Cardiology; Diabetes & Endocrinology; Oncology
Although the Canadian health care system provides essential services to all residents, evidence suggests that socioeconomic gradients in disease outcomes still persist. The main objective of our study was to investigate whether mortality, from cardiovascular disease or other causes, varies by neighbourhood socioeconomic gradients in patients accessing the healthcare system for cardiovascular disease management.
Methods and Findings
A cohort of 485 patients with angiographic evidence of coronary artery disease (CAD) and neighbourhood socioeconomic status information was followed for 13.3 years. Survival analyses were completed with adjustment for potentially confounding risk factors. There were 64 cases of cardiovascular mortality and 66 deaths from non-cardiovascular chronic diseases. No socioeconomic differentials in cardiovascular mortality were observed. However, lower neighbourhood employment, education, and median family income did predict an increased risk of mortality from non-cardiovascular chronic diseases. For each quintile decrease in neighbourhood socioeconomic status, non-cardiovascular mortality risk rose by 21–30%. Covariate-adjusted hazard ratios (95% confidence interval) for non-cardiovascular mortality were 1.21 (1.02–1.42), 1.21 (1.01–1.46), and 1.30 (1.06–1.60), for each quintile decrease in neighbourhood education, employment, and income, respectively. These patterns were primarily attributable to mortality from cancer. Estimated risks for mortality from cancer rose by 42% and 62% for each one quintile decrease in neighbourhood median income and employment rate, respectively. Although only baseline clinical information was collected and patient-level socioeconomic data were not available, our results suggest that environmental socioeconomic factors have a significant impact on CAD patient survival.
Despite public health care access, CAD patients who reside in lower-socioeconomic neighbourhoods show increased vulnerability to non-cardiovascular chronic disease mortality, particularly in the domain of cancer. These findings prompt further research exploring mechanisms of neighbourhood effects on health, and ways they may be ameliorated.
STUDY OBJECTIVE: To measure the trend, pattern, and cost of time spent in hospital during the last year of life in Western Australia and to identify trends in the place of death. The results were compared with those reported from the Oxford Record Linkage Study. DESIGN: Mortality records for those aged 65 years and over were linked to inpatient hospital morbidity records with a date of separation within one year before death. Comparative inpatient resource utilisation was estimated using ANDRG 3.0 cost weights for Australian public hospitals. SETTING: Western Australia. PARTICIPANTS: All 68,875 persons aged 65 years and over who died between 1 January 1985 and 31 December 1994. MAIN RESULTS: Increasing proportions of all age groups (65-74, 75-84, and 85+ years) were admitted to hospital at least once in the year before death during 1985-94, but the chance of admission decreased with age. There was a trend towards a greater number of shorter admissions per person. Total bed days per person showed no significant increase, except at ages 65-74 years. Total inpatient resource utilisation during the last year of life was lowest and remained constant in those aged 85 years and over, while increasing gradually (3.7% per annum) in the younger elderly. The Western Australian population spent more time in hospital in the last year of life at ages 65-74 years, but the advanced elderly spent less time in hospital, when compared with the Oxford Region. CONCLUSIONS: Recent gains in life expectancy and higher per capita health expenditure have not been accompanied by more time spent in hospital during the last year of life at ages 75+ years. International differences between Western Australia and Oxford can be explained by differences in aged care provision.
The inverse association between socioeconomic position (SEP) and health has been extensively explored in Italy; however few studies have been carried out on the relationship between income inequalities and health status or health services utilisation, particularly at a local level.
The objective of this study is to test the association between the demand for hospital care and a small area indicator based on income in four Italian cities, over a four-year period (1997-2000), in the adult population.
Census Block (median 260 residents) Median per capita Income (CBMI) was computed through record linkage between 1998 national tax and local population registries in the cities of Rome, Turin, Milan and Bologna (total population approximately 5.5 million). CBMI was linked to acute hospital discharges among residents, based on patient's residence.
Age-standardized gender-specific hospitalisation rates were computed by CBMI quintiles (first quintile indicating lowest income), overall, and by city and year. Heterogeneity of the association between income level and hospitalisation was analysed through a Poisson model.
We found an inverse association between small area income level and hospitalisation rates, which decreased continuously from 153 per 1000 inhabitants in the first quintile to 107 per 1000 inhabitants in the fifth quintile. Income differences in hospitalisation were confirmed in each city and year. However, the magnitude of the association and the absolute level of hospitalisation rates were quite different in each city and tended to slightly decrease over time in all cities considered, except Bologna.
Our study confirms an inverse association between income level and the use of hospitalization in four Italian cities, using a small area economic indicator, based on population tax data. Further analysis of the association between income and cause-specific hospitalization rates will allow to better understand the capability of the Italian National Health System to compel with socio-economic inequalities in health needs.
Furthermore the SEP indicator we propose can represent a contribution to the improvement of tools for monitoring inequalities in health and in health services utilization.
This project is a community-level study of equity of access to eye health services for Indigenous Australians.
The project used data on eye health services from multiple sources including Medicare Australia, inpatient and outpatient data and the National Indigenous Eye Health Survey.
The analysis focused on the extent to which access to eye health services varied at an area level according to the proportion of the population that was Indigenous (very low = 0-1.0%, low = 1.1-3.0%, low medium = 3.1-6.0%, high medium = 6.1-10.0%, high = 10.1-20.0%, very high = 20 + %). The analysis of health service utilisation also took into account age, remoteness and the Socioeconomic Indices for Areas (SEIFA).
The rate of eye exams provided in areas with very high Indigenous populations was two-thirds of the rate of eye exams for areas with very low indigenous populations. The cataract surgery rates in areas with high medium to very high Indigenous populations were less than half that reference areas. In over a third of communities with very high Indigenous populations the cataract surgery rate fell below the World Health Organization (WHO) guidelines compared to a cataract surgery rate of 3% in areas with very low Indigenous populations.
There remain serious disparities in access to eye health service in areas with high Indigenous populations. Addressing disparities requires a co-ordinated approach to improving Indigenous people’s access to eye health services. More extensive take-up of existing Medicare provisions is an important step in this process. Along with improving access to health services, community education concerning the importance of eye health and the effectiveness of treatment might reduce reluctance to seek help.
Aboriginal and Torres Strait Islander; Indigenous; Eye; Cataract; Equity
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 a primary care setting. ACSCs are used extensively as indicators of accessibility and effectiveness of primary health care. We examined the association between patient characteristics and hospitalisation for ACSCs in the adult and paediatric population in Victoria, Australia, 2003/04.
Hospital admissions data were merged with two area-level socioeconomic indexes: Index of Socio-Economic Disadvantage (IRSED) and Accessibility/Remoteness Index of Australia (ARIA). Univariate and multiple logistic regressions were performed for both adult (age 18+ years) and paediatric (age <18 years) groups, reporting odds ratios (OR) and 95% confidence intervals (CI) for a number of predictors of ACSCs admissions compared to non-ACSCs admissions.
Predictors were much more strongly associated with ACSCs admissions compared to non-ACSCs admissions in the adult group than for the paediatric group with the exception of rurality. Significant adjusted ORs in the adult group were 1.06, 1.15, 1.13, 1.06 and 1.11 for sex, rurality, age, IRSED and ARIA variables, and 1.34, 1.04 and 1.09 in the paediatric group for rurality, IRSED and ARIA, respectively.
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. Understanding the characteristics of individuals experiencing access barriers to primary care will be useful for developing targeted interventions meeting the unique ambulatory needs of the population.
Ambulatory care; Primary care; Socio-demographic; Access barriers
The problem of accessibility and affordability of health care is reported to be a major social concern in modern China. It is pronounced in rural households which represent 60% of China's population. There are a few large scale studies which have been conducted into socioeconomic inequalities in health care utilisation for rural populations. Those studies that exist are mainly bivariate analyses. The aim of this study is to examine the relationship between socioeconomic characteristics and health service utilisation among rural counties, using aggregated data from a nationally representative dataset, within a multivariate regression analysis framework.
Secondary data analysis was conducted on China's National Health Services Survey (NHSS) 2003. Aggregated data on health care utilisation, socioeconomic position, demographic characteristics and health status were used. The samples included 67 rural counties. Multivariate linear regression analyses were performed.
The results of the ecological multivariate analyses showed a positive relationship between private insurance coverage and the use of outpatient care (p-value < 0.05, standardised coefficient = 0.22). Annual income was positively correlated with annual medical expenditure (p-value < 0.01, standardised coefficient = 0.56). A rural county's area socioeconomic stratum, a composite measure frequently used in bivariate studies including the NHSS analysis report, could not explain any association with the use of health care.
This study highlights that richer rural households with a greater ability to pay are more able to use health services in China. The findings suggest that the scope of medical insurance might be restrictive, or the protection provided might be limited, and the health care costs might still be too high. Additional efforts are required to ensure that poorer Chinese rural households are able to utilise health care according to their needs, regardless of their income levels or private insurance coverage. This would require targeted strategies to assist low income families and a broad spectrum of interventions to address the social determinants of health.
Design: A process evaluation of a specialist outreach service, using health service utilisation data and interviews with health professionals and patients.
Setting: The Top End of Australia's Northern Territory, where Darwin is the capital city and the major base for hospital and specialist services. In the rural and remote areas outside Darwin there are many small, predominantly indigenous communities, which are greatly disadvantaged by a severe burden of disease and limited access to medical care.
Participants: Seventeen remote health practitioners, five specialists undertaking outreach, five regional health administrators, and three patients from remote communities.
Main results: The barriers faced by many remote indigenous people in accessing specialist and hospital care are substantial. Outreach delivery of specialist services has overcome some of the barriers relating to distance, communication, and cultural inappropriateness of services and has enabled an over fourfold increase in the number of consultations with people from remote communities. Key issues affecting sustainability include: an adequate specialist base; an unmet demand from primary care; integration with, accountability to and capacity building for a multidisciplinary framework centred in primary care; good communication; visits that are regular and predictable; funding and coordination that recognises responsibilities to both hospitals and the primary care sector; and regular evaluation.
Conclusions: In a setting where there is a disadvantaged population with inadequate access to medical care, specialist outreach from a regional centre can provide a more equitable means of service delivery than hospital based services alone. A sustainable outreach service that is organised appropriately, responsive to local community needs, and has an adequate regional specialist base can effectively integrate with and support primary health care processes. Poorly planned and conducted outreach, however, can draw resources away and detract from primary health care.
Secondary prevention for established ischaemic heart disease (IHD) involves medication therapy and a healthier lifestyle, but adherence is suboptimal. Simply having scheduled regular appointments with a primary care physician could confer a benefit for IHD patients possibly through increased motivation and awareness, but this has not previously been investigated in the literature.
To estimate the association between regular general practitioner (GP) visitation and rates of all-cause death, IHD death or repeat hospitalisation for IHD in older patients in Western Australia (WA).
A retrospective cohort design.
Patients aged ≥ 65 years (n = 31,841) with a history of hospitalisation for IHD from 1992–2006 were ascertained through routine health data collected on the entire WA population and included in the analysis.
Frequency and regularity of GP visits was determined during a three-year exposure period at commencement of follow-up. A regularity score (range 0–1) measured the regularity of intervals between the GP visits and was divided into quartiles. Patients were then followed for a maximum of 11.5 years for outcome determination. Hazard ratios and 95% confidence intervals were calculated using Cox proportional hazards models.
Compared with the least regular quartile, patients with greater GP visit regularity had significantly decreased risks of all-cause death (2nd least, 2nd most and most regular: HR = 0.76, 0.71 and 0.71); and IHD death (2nd least, 2nd most and most regular: HR = 0.70, 0.68 and 0.65). Patients in the 2nd least regular quartile also appeared to experience decreased risk of any repeat IHD hospitalisation (HR = 0.83, 95%CI 0.71–0.96) as well as emergency hospitalisation (HR = 0.81, 95%CI 0.67–0.98), compared with the least regular quartile.
Some degree of regular GP visitation offers a small but significant protection against morbidity and mortality in older people with established IHD. The findings indicate the importance of scheduled, regular GP visits for the secondary prevention of IHD.
ischemic heart disease; hospitalisations; GP visits; record linkage; primary care
Statistical time series derived from administrative data sets form key indicators in measuring progress in addressing disadvantage in Aboriginal and Torres Strait Islander populations in Australia. However, inconsistencies in the reporting of Indigenous status can cause difficulties in producing reliable indicators. External data sources, such as survey data, provide a means of assessing the consistency of administrative data and may be used to adjust statistics based on administrative data sources.
We used record linkage between a large-scale survey (the Western Australian Aboriginal Child Health Survey), and two administrative data sources (the Western Australia (WA) Register of Births and the WA Midwives’ Notification System) to compare the degree of consistency in determining Indigenous status of children between the two sources. We then used a logistic regression model predicting probability of consistency between the two sources to estimate the probability of each record on the two administrative data sources being identified as being of Aboriginal and/or Torres Strait Islander origin in a survey. By summing these probabilities we produced model-adjusted time series of neonatal outcomes for Aboriginal and/or Torres Strait Islander births.
Compared to survey data, information based only on the two administrative data sources identified substantially fewer Aboriginal and/or Torres Strait Islander births. However, these births were not randomly distributed. Births of children identified as being of Aboriginal and/or Torres Strait Islander origin in the survey only were more likely to be living in urban areas, in less disadvantaged areas, and to have only one parent who identifies as being of Aboriginal and/or Torres Strait Islander origin, particularly the father. They were also more likely to have better health and wellbeing outcomes. Applying an adjustment model based on the linked survey data increased the estimated number of Aboriginal and/or Torres Strait Islander births in WA by around 25%, however this increase was accompanied by lower overall proportions of low birth weight and low gestational age babies.
Record linkage of survey data to administrative data sets is useful to validate the quality of recording of demographic information in administrative data sources, and such information can be used to adjust for differential identification in administrative data.
Background—Fires are a leading cause of death, but non-fatal injuries from residential fires have not been well characterised.
Methods—To identify residential fire injuries that resulted in an emergency department visit, hospitalisation, or death, computerised databases from emergency departments, hospitals, ambulance and helicopter services, the fire department, and the health department, and paper records from the local coroner and fire stations were screened in a deprived urban area between June 1996 and May 1997.
Result—There were 131 fire related injuries, primarily smoke inhalation (76%), an incidence of 36 (95% confidence interval (CI) 30 to 42)/100 000 person years. Forty one patients (32%) were hospitalised (11 (95% CI 8 to 15)/100 000 person years) and three people (2%) died (0.8 (95% CI 0.2 to 2.4)/100 000 person years). Injury rates were highest in those 0–4 (68 (95% CI 39 to 112)/100 000 person years) and ≥85 years (90 (95% CI 29 to 213)/100 000 person years). Rates did not vary by sex. Leading causes of injury were unintentional house fires (63%), assault (8%), clothing and nightwear ignition (6%), and controlled fires (for example, gas burners) (4%). Cooking (31%) and smoker's materials (18%) were leading fire sources.
Conclusions—Because of the varied causes of fire and flame injuries, it is likely that diverse interventions, targeted to those at highest risk, that is, the elderly, young children, and the poor, may be required to address this important public health problem.