Market failure in long-term private health insurance markets: a proposed solution

Recently, private health insurance rates have declined in many countries. In places requiring community rating in their health insurance premiums, a major cause is age-based adverse selection. However, even in countries without community rating, a de facto type of partial community rating tends to occur. In this note, a modified version of Pauly et al.'s guaranteed renewability model, which addresses the problem of age-based adverse selection (Pauly et al., 1995) is presented. Their model is extended from three to 35 periods. Also, probabilities are allowed to increase by age for low-risk types using actual age-based probabilities. This extension of their work shows that private health insurance contracts available stray far from optimal contracts that deal with age-based adverse selection. This suggests that government actions to affect private insurance options are warranted.

Heart failure following cancer therapy in patients with hematological malignancies aged 18 years and under : a linked health data analysis (1996-2009)

Introduction: The causal link between chemotherapy treatments and subsequent cardiotoxicity is well established, particularly for children with hematological malignancies. Little information exists on the characteristics and outcomes for patients with heart failure (HF) after chemotherapy. This study aimed to describe the characteristics, survival and mortality of patients who received chemotherapy for hematological cancer (leukemias, lymphomas and related disorders) before 18 years old and subsequently developed HF compared to those who did not.

Methods: Linked health data (1996-2009) from the Queensland Cancer Registry, Death Registry and Hospital Administration records for HF and chemotherapy admissions were reviewed. From all breast and hematological cancers patients (n=73,158), 15,987 received chemotherapy, including 819 patients aged ≤18 years at time of cancer diagnosis. Patients were categorized as those with an index HF admission (occurred after cancer diagnosis) and those without an index HF admission (non HF).

Results: Of the 819 patients, 3.7% (n=30) had an index HF admission. Median age of HF patients at time of cancer diagnosis was 5 years (IQR 3-12) compared to 7 years (IQR 3-14) in the non HF group (p=0.503). Median follow up from cancer diagnosis was 2.5 years in the HF group compared to 5.42 years in the non HF group (p<0.01). Of those who developed HF, 70% (n=21) had the index admission within 12 months of their cancer diagnosis. Of those with HF, 53.3% (n=16) died (all cause) compared to 14.6% (n=115) with no HF. On adjustment for age, sex and chemotherapy admissions, HF patients had an almost 5 fold increased mortality risk compared to non HF patients (HR 4.91 [95% CI, 2.88-8.36]) (Figure 1).

Conclusions: This study demonstrated that in children with hematological cancers the onset of HF occurred soon after chemotherapy and mortality risk is almost 5 times that of children who do not develop HF. Innovative strategies are still needed for the prevention and management of cardiotoxicity in this population.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

There is nothing that 'identifies me to that place' : Aboriginal Women's perceptions of health spaces and places

There is a growing body of literature within social and cultural geography that explores notions of place, space, culture, race and identity. The more recent works suggest that places are experienced and understood in multiple ways and are embedded within an array of politics. Memmott and Long, who have undertaken place-based research with Australian Indigenous people, present the theoretical position that ‘place is made and takes on meaning through an interaction process involving mutual accommodation between people and the environment’. They outline that places and their cultural meanings are generated through one or a combination of three types of people–environment interactions. These include: a place that is created by altering the physical characteristics of a piece of environment and which might encompass a feature or features which are natural or made; a place that is created totally through behaviour that is carried out within a specific area, therefore that specific behaviour becomes connected to that specific place; and a place created by people moving or being moved from one environment to another and establishing a new place where boundaries are created and activities carried out. All these ideas of places are challenged and confirmed by what Indigenous women have said about their particular use of, and relationship with, space within several health services in Rockhampton, Central Queensland. As my title suggests, Indigenous women do not see themselves as ‘neutral’ or ‘non-racialised’ citizens who enter and ‘use’ a supposedly neutral health service. Instead, Aboriginal women demonstrate they are active recognisers of places that would identify them within the particular health place. That is, they as Aboriginal women didn’t just ‘make’ place, the places and spaces ‘make’ them. The health services were identified as sites within which spatial relations could begin to grow with recognition of themselves as Aboriginal women in place, or instead create a sense of marginality in the failure of the spaces to identify them. The women’s voices within this paper are drawn from interviews undertaken with twenty Aboriginal women in Rockhampton, Central Queensland, Australia, who participated in a research project exploring ‘how the relationship between health services and Aboriginal women can be more empowering from the viewpoints of Aboriginal women’. The assumption underpinning this study was that empowering and re-empowering practices for Aboriginal women can lead to improved health outcomes. Throughout the interviews women shared some of their lived realities including some of their thoughts on identity, the body, employment in the health sector, service delivery and their notions of health service spaces and places. Their thoughts on health service spaces and places provide an understanding of the lived reality for Aboriginal women and are explored and incorporated within this paper.

Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur

Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm− 1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. This ex-vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Structural health monitoring of bridges using acoustic emission technology

Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

The intra-aortic balloon pump in heart failure management : implications for nursing practice

Management of acute heart failure is an important consideration in critical care. Mechanical support of the failing heart is crucial for improving health outcomes. The most common Australasian application of intraaortic balloon counterpulsation (IABP) is in the setting of cardiogenic shock. High end users of IABP (>37/annum) demonstrate significantly lower mortality for cardiogenic shock managed with IABP (p <0.001) in contrast to hospitals which employ limited IABP (<4/annum). This underscores the importance of proficiency in managing patient receiving IABP support. Nurses play a crucial role in carding for patients with acute heart failure. This paper summarises care considerations for management of the IABP.

Anger and depression predict hospital use among chronic heart failure patients

Costly hospital readmissions among chronic heart failure (CHF) patients are expected to increase dramatically with the ageing population. This study investigated the prognostic ability of depression, anger and anxiety, prospectively, and after adjusting for illness severity, on the number of readmissions to hospital and the total length of stay over one year. Participants comprised 175 inpatients with CHF. Depression, anger, anxiety, and illness severity were measured at baseline. One year later, the number of readmissions and length of stay for each patient were obtained from medical records. Depression and anger play a detrimental role in the health profile of CHF patients.

Privacy and trust management for electronic health records

Establishing a nationwide Electronic Health Record system has become a primary objective for many countries around the world, including Australia, in order to improve the quality of healthcare while at the same time decreasing its cost. Doing so will require federating the large number of patient data repositories currently in use throughout the country. However, implementation of EHR systems is being hindered by several obstacles, among them concerns about data privacy and trustworthiness. Current IT solutions fail to satisfy patients’ privacy desires and do not provide a trustworthiness measure for medical data. This thesis starts with the observation that existing EHR system proposals suer from six serious shortcomings that aect patients’ privacy and safety, and medical practitioners’ trust in EHR data: accuracy and privacy concerns over linking patients’ existing medical records; the inability of patients to have control over who accesses their private data; the inability to protect against inferences about patients’ sensitive data; the lack of a mechanism for evaluating the trustworthiness of medical data; and the failure of current healthcare workflow processes to capture and enforce patient’s privacy desires. Following an action research method, this thesis addresses the above shortcomings by firstly proposing an architecture for linking electronic medical records in an accurate and private way where patients are given control over what information can be revealed about them. This is accomplished by extending the structure and protocols introduced in federated identity management to link a patient’s EHR to his existing medical records by using pseudonym identifiers. Secondly, a privacy-aware access control model is developed to satisfy patients’ privacy requirements. The model is developed by integrating three standard access control models in a way that gives patients access control over their private data and ensures that legitimate uses of EHRs are not hindered. Thirdly, a probabilistic approach for detecting and restricting inference channels resulting from publicly-available medical data is developed to guard against indirect accesses to a patient’s private data. This approach is based upon a Bayesian network and the causal probabilistic relations that exist between medical data fields. The resulting definitions and algorithms show how an inference channel can be detected and restricted to satisfy patients’ expressed privacy goals. Fourthly, a medical data trustworthiness assessment model is developed to evaluate the quality of medical data by assessing the trustworthiness of its sources (e.g. a healthcare provider or medical practitioner). In this model, Beta and Dirichlet reputation systems are used to collect reputation scores about medical data sources and these are used to compute the trustworthiness of medical data via subjective logic. Finally, an extension is made to healthcare workflow management processes to capture and enforce patients’ privacy policies. This is accomplished by developing a conceptual model that introduces new workflow notions to make the workflow management system aware of a patient’s privacy requirements. These extensions are then implemented in the YAWL workflow management system.

Developing a model of care to improve the health and well-being for Indigenous people receiving renal dialysis treatment

The high levels of end-stage renal disease among Indigenous Australians, particularly in remote areas of the country, are a serious public health concern. The magnitude of the problem is reflected in figures from the Australian and New Zealand Transplant and Dialysis Registry that show that Indigenous Australians experience end-stage renal disease at a rate almost 9–10 times higher than other non-Indigenous Australians. A majority of Indigenous Australians have to relocate to receive appropriate renal dialysis treatment. In some Australian states, renal treatment is based on self-care dialysis which allows those Indigenous Australians to be treated back in their community. Evidence clearly shows that reuniting renal patients with community and family improves overall health and well-being for those Indigenous Australians. With the appropriate resources, training, and support, self-care management of renal dialysis treatment is an effective way for Indigenous people with end-stage renal failure to be treated at home. In this context, the study was used to gain insight and further understanding of the impact that end-stage renal disease and renal dialysis treatment has had on the lives of Indigenous community members. The study findings are from 14 individually interviewed people from South East Queensland. Data from the interviews were analysed using a combination of thematic and content analysis. The study methodology was based on qualitative data principles where the Indigenous community members were able to share their experiences and journeys living with end-stage renal disease. Many of the experiences and understanding closely relate to the renal disease pattern and the treatment with other outside influences, such as social, cultural, and environmental influences, all having an equal impact. Each community member’s experience with end-stage renal disease is unique; some manage with family and medical support, while others try to manage independently. From the study, community members who managed their renal dialysis treatment independently were much more aware of their renal health status. The study provides recommendations towards a model of care to improve the health and well-being is based on self-care and self-determination principles.

Caveat Anicula! Beware of the Quiet Little Old Ladies : Demographics, Pharmacotherapy, Survival and Readmissions in a 10 Year Cohort of Heart Failure Patients with Preserved Systolic Function

Objective--To determine whether heart failure with preserved systolic function (HFPSF) has different natural history from left ventricular systolic dysfunction (LVSD). Design and setting--A retrospective analysis of 10 years of data (for patients admitted between 1 July 1994 and 30 June 2004, and with a study census date of 30 June 2005) routinely collected as part of clinical practice in a large tertiary referral hospital.Main outcome measures-- Sociodemographic characteristics, diagnostic features, comorbid conditions, pharmacotherapies, readmission rates and survival.Results--Of the 2961 patients admitted with chronic heart failure, 753 had echocardiograms available for this analysis. Of these, 189 (25%) had normal left ventricular size and systolic function. In comparison to patients with LVSD, those with HFPSF were more often female (62.4% v 38.5%; P = 0.001), had less social support, and were more likely to live in nursing homes (17.9% v 7.6%; P < 0.001), and had a greater prevalence of renal impairment (86.7% v 6.2%; P = 0.004), anaemia (34.3% v 6.3%; P = 0.013) and atrial fibrillation (51.3% v 47.1%; P = 0.008), but significantly less ischaemic heart disease (53.4% v 81.2%; P = 0.001). Patients with HFPSF were less likely to be prescribed an angiotensin-converting enzyme inhibitor (61.9% v 72.5%; P = 0.008); carvedilol was used more frequently in LVSD (1.5% v 8.8%; P < 0.001). Readmission rates were higher in the HFPSF group (median, 2 v 1.5 admissions; P = 0.032), particularly for malignancy (4.2% v 1.8%; P < 0.001) and anaemia (3.9% v 2.3%; P < 0.001). Both groups had the same poor survival rate (P = 0.912). Conclusions--Patients with HFPSF were predominantly older women with less social support and higher readmission rates for associated comorbid illnesses. We therefore propose that reduced survival in HFPSF may relate more to comorbid conditions than suboptimal cardiac management.