Cost of dialysis therapies in rural and remote Australia - a micro-costing analysis.

BACKGROUND: Maintenance dialysis is a costly and resource intense activity. In Australia, inadequate health infrastructure and poor access to technically skilled staff can limit service provision in remote areas where many Aboriginal dialysis patients live. With most studies based on urban service provision, there is little evidence to guide service development. However permanent relocation to an urban area for treatment can have significant social and financial impacts that are poorly quantified. This study is part of a broader project to quantify the costs and benefits of dialysis service models in urban and remote locations in Australia's Northern Territory (NT). METHODS: We undertook a micro-costing analysis of dialysis service delivery costs in urban, rural and remote areas in the NT from the payer perspective. Recurrent maintenance costs (salaries, consumables, facility management and transportation) as well as capital costs were included. Missing and centralised costs were standardised; results were inflated to 2017 values and reported in Australian dollars. RESULTS: There was little difference between the average annual cost for urban and rural services with respective median costs of $85,919 versus $84,629. However remote service costs were higher ($120,172 - $124,492), driven by higher staff costs. The inclusion of capital costs did not add substantially to annual costs. Annual home haemodialysis costs ($42,927) were similar to other jurisdictions despite the significant differences in program delivery and payment of expenses not traditionally borne by governments. Annual peritoneal dialysis costs ($58,489) were both higher than home and in-centre haemodialysis by recent national dialysis cost studies. CONCLUSION: The cost drivers for staffed services were staffing models and patient attendance rates. Staff salaries and transport costs were significantly higher in remote models of care. Opportunities to reduce expenditure exist by encouraging community supported services and employing local staff. Despite the delivery challenges of home haemodialysis including high patient attrition, the program still provides a cost benefit compared to urban staffed services. The next component of this study will examine patient health service utilisation and costs by model of care to provide a more comprehensive analysis of the overall cost of providing services in each location.

Incorporating indigenous knowledge in health services: a consumer partnership framework.

OBJECTIVES: Healthcare policy and planning should be informed by a partnership between healthcare services and healthcare users. This is critical for people who access care frequently such as indigenous Australians who have a high burden of chronic kidney disease. This study aimed to explore the most appropriate ways of enhancing services by incorporating renal patients' expectations and satisfaction of care in Australia's Northern Territory. STUDY DESIGN: This is a participatory action research. METHODS: Six aboriginal health users with end-stage kidney disease were recruited to form an Indigenous Reference Group. This group met bimonthly between April and November 2017 and meetings took the same structure as a focus group. Findings from these meetings were presented to health policy and planners in a feedback loop implemented by the study. RESULTS: This framework enabled indigenous knowledge to guide the project, indigenous priorities to be identified in this context and timely feedback of information to inform the strengths and priorities of the health service. Changes were recognised and addressed immediately. CONCLUSIONS: This qualitative research framework is a useful mechanism for providing local data to inform patient-centred health system change as expressed by health users. We recommend this consumer partnership framework be embedded into existing operational structures to support the ongoing sustainability of this group.

Miniaturized screening technologies for drug discovery.

Adaptive Profiling (APL) and other biochip companies aim to harness the power of microsystems technology together with advances in chemistry and molecular biology, to become service and technology providers to organizations involved in pharmaceutical research and development. By supplying a unique range of decision-making tools that aid an earlier identification of qualified drug candidates for clinical development, the company should gain a significant share of the 10 billion US dollar biological screening, bioavailability and toxicity assessment market.

Social disadvantage and variation in the incidence of end-stage renal disease in Australian capital cities.

OBJECTIVE: To evaluate variation in the incidence of end-stage renal disease (ESRD) within Australian capital cities. To explore the relation between the incidence of ESRD and socioeconomic disadvantage. METHODS: We obtained data from the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA) regarding 5,013 patients from capital cities who started ESRD treatment between 1 April 1993 and 31 December 1998. We used the postcode at the start of treatment to calculate the average annual incidence of ESRD for each of 51 capital city regions using 1996 Census counts based on place of usual residence. We calculated standardised incidence ratios with 95% confidence intervals for each region. The standardised incidence ratios were examined in relation to the SEIFA Index of Relative Socio-economic Disadvantage (IRSD), derived from the 1996 Census. Low IRSD values indicate more disadvantaged areas. RESULTS: There is significant variation in the standardised incidence of ESRD within capital cities. There was a significant correlation (r=-0.41, p=0.003) between the standardised incidence ratio for ESRD and the SEIFA IRSD. CONCLUSIONS AND IMPLICATIONS: Capital city areas that are more disadvantaged have a higher incidence of ESRD. Socioeconomic factors may be important determinants of the risk of developing ESRD.

Does the severity of mood and anxiety symptoms predict health care utilization?

BACKGROUND: Traditional diagnostic criteria for depression and anxiety fail to account for symptom severity. We previously evaluated a severity-based classification system of mood and anxiety symptoms. This study examines whether those severity groups are predictive of differences in health care utilization. METHODS: We used a cohort design to compare the health care utilization of 1232 subjects classified into 4 groups according to symptom severity. Health care billing data were evaluated for each subject for a 15-month period around the index visit. Multiple linear regression models were used to examine relative contributions of individual variables to differences in health care utilization. Analysis of variance procedures were used to compare charges among the severity groups after adjusting for demographic and medical comorbidity variables. RESULTS: After adjustment, significant differences in health care utilization between groups were seen in all but 3 of the 15 months studied. Also, after adjustment, the presence of a mood or anxiety disorder influenced utilization for only a 6-month period. At 9 to 12 months, subjects in the high-severity group showed a more than twofold difference in adjusted charges compared with the low-severity group ($225.36 vs $94.37). CONCLUSIONS: Our severity-based classification predicts statistically and clinically significant differences in health care utilization over most of a 15-month period. Differences in utilization persist even after adjustment for medical comorbidity and significant demographic covariates. Our work lends additional evidence that beyond screening for the presence of mood and anxiety disorders, it is important to assess symptom severity in primary care patients. Further study directed toward developing effective methods of identifying patients with high levels of mood and anxiety symptom severity could result in significant cost savings.

Health-related quality of life in primary care patients with recognized and unrecognized mood and anxiety disorders.

OBJECTIVE: Primary care providers have been criticized for underrecognizing and undertreating mental health disorders. This criticism assumes patients with recognized disorders and those with unrecognized disorders suffer the same burden of illness. This study describes differences in health-related quality of life (HRQOL) in patients with recognized and unrecognized mood and anxiety disorders in a primary care setting. METHODS: A probability sample of 500 adult ambulatory patients from a university-based, family practice clinic, completed the PRIME-MD mood and anxiety disorder modules and the SF-36 Health Survey. Computerized patient records were reviewed retrospectively to determine recognition of mood and anxiety disorders. The Mental Health (MCS) and Physical Health (PCS) Component Summary scales of the SF-36 served as the primary outcome measures. RESULTS: Sub-threshold mood and anxiety disorders were less likely to be recognized by physicians than disorders meeting DSM-III-R criteria. Recognized mood disorders were associated with a significant decrement in MCS scores (poorer HRQOL) compared with unrecognized disorders. In contrast, recognized mood disorders demonstrated slightly higher PCS scores. Recognized and unrecognized mood disorders differed significant ly in physical functioning, vitality, social functioning, role functioning related to emotional state, and mental health. Recognition of anxiety disorders was not related to HRQOL. CONCLUSIONS: Patients with mental health disorders that have been recognized by their health providers appear to suffer from poorer HRQOL than patients whose disorders have not been recognized. This relationship, though, is only apparent for mood disorders. Poorer physical functioning may mask less severe emotional symptoms in mood disorders; profound emotional symptoms make recognition easier.