Information support for health management in regional Sri Lanka : health managers’ perspectives

Good management, supported by accurate, timely and reliable health information, is vital for increasing the effectiveness of Health Information Systems (HIS). When it comes to managing the under resourced health systems of developing countries, information-based decision making is particularly important. This paper reports findings of a self-report survey that investigated perceptions of local health managers (HMs) of their own regional HIS in Sri Lanka. Data were collected through a validated, pre-tested postal questionnaire, and distributed among a selected group of HMs to elicit their perceptions of the current HIS in relation to information generation, acquisition and use, required reforms to the information system and application of information and communication technology (ICT). Results based on descriptive statistics indicated that the regional HIS was poorly organised and in need of reform; that management support for the system was unsatisfactory in terms of relevance, accuracy, timeliness and accessibility; that political pressure and community and donor requests took precedence over vital health information when management decisions were made; and use of ICT was unsatisfactory. HIS strengths included user-friendly paper formats, a centralised planning system and an efficient disease notification system; weaknesses were lack of comprehensiveness, inaccuracy, and lack of a feedback system. Responses of participants indicated that HIS would be improved by adopting an internationally accepted framework and introducing ICT applications. Perceived barriers to such improvements were high initial cost of educating staff to improve computer literacy, introduction of ICTs, and HIS restructure. We concluded that the regional HIS of Central Province, Sri Lanka had failed to provide much needed information support to HMs. These findings are consistent with similar research in other developing countries and reinforce the need for further research to verify causes of poor performance and to design strategic reforms to improve HIS in regional Sri Lanka.

Utilising Reliability and Condition Monitoring Data for Asset Health Prognosis

The ability to forecast machinery health 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 which attempt to forecast machinery health based on condition data such as vibration measurements. This paper demonstrates how the population characteristics and condition monitoring data (both complete and suspended) of historical items can be integrated for training an intelligent agent to predict asset health multiple steps ahead. The model consists of a feed-forward neural network whose training targets are asset survival probabilities estimated using a variation of the Kaplan–Meier estimator and a degradation-based failure probability density function estimator. The trained network is capable of estimating the future survival probabilities when a series of asset condition readings are inputted. The output survival probabilities collectively form an estimated survival curve. Pump data from a pulp and paper mill were used for model validation and comparison. The results indicate that the proposed model can predict more accurately as well as further ahead than similar models which neglect population characteristics and suspended data. This work presents a compelling concept for longer-range fault prognosis utilising available information more fully and accurately.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

Discrimination experienced by HIV/AIDS infected persons and its associations with mental health in an Indian sample

Purpose The purpose of this study was to investigate the nature and prevalence of discrimination against people living with HIV/AIDS in West Bengal, India, and how discrimination is associated with depression, suicidal ideation and suicidal attempts. Method Semi-structured interviews and the Beck Depression Inventory were administered to 105 HIV infected persons recruited by incidental sampling, at an Integrated Counseling and Testing Center (ICTC) and through Networks of People Living with HIV/AIDS, in the West Bengal area. Results Findings showed that 40.8% of the sample has experienced discrimination at least in one social setting – such as family (29.1%), health centers (18.4%), community (17.5%) and workplace (6.8%). About two-fifths (40.8%) reported experiencing discrimination in multiple social settings. Demographic factors associated with discrimination were gender, age, occupation, education, and current residence. More than half of the sample was suffering from severe depression while 8.7% had attempted suicide. Discrimination in most areas was significantly associated with suicidal ideation and suicidal attempts. Conclusions Prevalence of discrimination associated with HIV/AIDS is high in our sample from West Bengal. While discrimination was not associated with depressive symptomatology, discrimination was associated with suicidal ideation and attempts. These findings suggest that there is an urgent need for interventions to reduce discrimination of HIV/AIDS in the West Bengal region.

Spatial modelling of population health screening : the role of accessibility in predicting expected patient flows

This paper describes a generalised linear mixed model (GLMM) approach for understanding spatial patterns of participation in population health screening, in the presence of multiple screening facilities. The models presented have dual focus, namely the prediction of expected patient flows from regions to services and relative rates of participation by region- service combination, with both outputs having meaningful implications for the monitoring of current service uptake and provision. The novelty of this paper lies with the former focus, and an approach for distributing expected participation by region based on proximity to services is proposed. The modelling of relative rates of participation is achieved through the combination of different random effects, as a means of assigning excess participation to different sources. The methodology is applied to participation data collected from a government-funded mammography program in Brisbane, Australia.

The public health challenges of mental health problems and associated difficulties

Mental health is a major global health issue. Neuropsychiatric conditions are the most significant cause of disability worldwide, and account for 14% of the global burden of disease. Depression in particular places a huge burden on society, with the Global Burden of Disease 2000 study listing it as the fourth leading cause of disease burden worldwide and the largest non-fatal disease burden. In Australia, mental disorders are startlingly common and related to significant disability. The 2007 National Survey of Mental Health and Wellbeing revealed that the lifetime prevalence of any mental disorder was 45%, and within the last 12 months 20% of Australians met criteria for a mental disorder. Many of the articles in this issue explore mental health issues in young people. Indeed, mental health issues account for a large proportion of the disease burden in young people. Across the globe, mental health disorders caused the greatest number of years lost to disability(YLDs) amongst young people aged 10 to 24 years (45% of total YLDs). Depression caused the highest number of disability-adjusted life-years (DALYs) across this age group, accounting for 8. 2% of DALYs alone.6 It is clear that mental health is a critical area of focus for researchers, practitioners, and policy makers.

Reproductive health : findings from the Australian Longitudinal Study on Women’s Health. Chapter 3: Use of contraception

Chapter 3: Use of contraception. p15-32 Key findings: This section examines trends in the use of contraception between 1996 and 2006 by women who participated in the surveys for the 1973-1978 cohort of the Australian Longitudinal Study on Women’s Health. 1. The oral contraceptive pill was the most commonly used method of contraception at each survey, but its use decreased over time. 2.Of women who consistently used contraception, 40% used the oral contraceptive pill as their only method of contraception in at least three out of four surveys. 3. The proportion of women using condoms as their only method of contraception remained steady over time (15-18%) but only 3% of all women used condoms only at every survey. 4. The proportion of women using both condoms and the oral contraceptive pill remained steady at 13-14% of all women from Survey 1 to 3, but decreased to 8% of all women at Survey 4. 5. The use of methods other than the oral contraceptive pill and/or condoms increased at Survey 4. 6. The proportion of women using an implant (e.g. Implanon) remained steady between Surveys 3 and 4, with 3% of women using an implant only. Around one third of implant users at Survey 3 continued to use this method at Survey 4. 7. The main reasons for not using contraception at Surveys 3 and 4 were pregnancy, trying to conceive, or no male sexual partners. 8. Women who used contraception were more likely to be in de facto relationships or single, be up to date with Pap tests and have had two or more births. 9. Women who did not use contraception were more likely to be non-drinkers and/or do low levels of exercise, have had one birth and have experienced miscarriage. 10. Contraception changed in expected ways according to reproductive events: women who reported only miscarriages between surveys also stopped using contraception in the same period; most women who did not report reproductive events continued to use the same method of contraception; and women who had a termination tended to switch methods.

Reproductive health: findings from the Australian Longitudinal Study on Women’s Health. Chapter 5: fertility and infertility

Chapter 5: Fertility and infertility. p52-70. This section describes patterns of fertility across Surveys 1 to 4 among the cohort of women who were born in 1973-1978. This section includes the examination of pregnancy outcomes including both live births and pregnancy losses (stillbirths, miscarriages, terminations and ectopic pregnancies). This section also examines the prevalence of self-reported problems with fertility and whether these women sought advice and/or treatment. As women age they are more likely to experience infertility and, with little other data available, the ALSWH provides an important opportunity to examine this problem and the related use of health services. 1. Pregnancy losses are common. Half of the women who report a pregnancy outcome at Survey 4 have experienced a pregnancy loss. 2. More than one third (39%) of women who have experienced a live birth by Survey 4 have also experienced a pregnancy loss. 3. For every ten women aged 28-33 years in 2006: four women had not had been pregnant, five women had a live birth (with or without a recognised pregnancy loss), and one woman had a recognised pregnancy loss only. 4. Among women who had tried to conceive or had been pregnant, one-in-six had experienced infertility. (i.e. tried unsuccessfully to get pregnant for 12 months or more) 5. The most significant factors associated with having infertility, seeking advice and using treatment were: polycystic ovary syndrome, endometriosis and miscarriage. 6. Of the women who reported infertility, two-thirds sought advice but only half used treatment. 7. Most of the women who used fertility treatment had used low cost and non-invasive methods.

Improving self care of patients with chronic disease using online personal health record

BACKGROUND: Effective management of chronic diseases such as prostate cancer is important. Research suggests a tendency to use self-care treatment options such as over-the-counter (OTC) complementary medications among prostate cancer patients. The current trend in patient-driven recording of health data in an online Personal Health Record (PHR) presents an opportunity to develop new data-driven approaches for improving prostate cancer patient care. However, the ability of current online solutions to share patients' data for better decision support is limited. An informatics approach may improve online sharing of self-care interventions among these patients. It can also provide better evidence to support decisions made during their self-managed care. AIMS: To identify requirements for an online system and describe a new case-based reasoning (CBR) method for improving self-care of advanced prostate cancer patients in an online PHR environment. METHOD: A non-identifying online survey was conducted to understand self-care patterns among prostate cancer patients and to identify requirements for an online information system. The pilot study was carried out between August 2010 and December 2010. A case-base of 52 patients was developed. RESULTS: The data analysis showed self-care patterns among the prostate cancer patients. Selenium (55%) was the common complementary supplement used by the patients. Paracetamol (about 45%) was the commonly used OTC by the patients. CONCLUSION: The results of this study specified requirements for an online case-based reasoning information system. The outcomes of this study are being incorporated in design of the proposed Artificial Intelligence (Al) driven patient journey browser system. A basic version of the proposed system is currently being considered for implementation.

Identifying competencies for Australian health professionals working in international health

A profile of the roles performed by Australian health professionals working in international health was constructed to identify the core competencies they require, and the implications for education and training of international health practitioners. The methods used included: literature review and document analysis of available training and education; an analysis of competencies required in job descriptions for international health positions; and consultations with key informants. The international health roles identified were classified in four main groups: Program Directors, Program Managers, Team Leaders and Health Specialists. Thirteen 'core' competencies were identified from the job analysis and key informant/group interviews. Contributing to international health development in resource poor countries requires high level cultural, interpersonal and team-work competencies. Technical expertise in health disciplines is required, with flexibility to adapt to new situations. International health professionals need to combine public health competencies with high level personal maturity to respond to emerging challenges.

Flexing some muscle: strategy and outcomes in the Queensland health and fitness industry

In 1993, contrary to the trend towards enterprise bargaining, and despite an employment environment favouring strong managerial prerogative, a small group of employers in the Queensland commercial health and fitness industry sought industrial regulation through an industry-specific award. A range of factors, including increased competition and unscrupulous profiteers damaging the industry’s reputation, triggered the actions as a business strategy. The strategic choices of the employer group, to approach a union to initiate a consent award, are the inverse of behaviours expected under strategic choice theory. This article argues that organizational size, collective employer action, focus on industry rather than organizational outcomes and the traditional industrial relations system providing broader impacts explain their atypical behaviour.

The effect of Tai Chi on health related quality of life in people with elevated blood glucose or diabetes : a randomized controlled trial

Purpose The aim was to assess the effects of a Tai Chi based program on health related quality of life (HR-QOL) in people with elevated blood glucose or diabetes who were not on medication for glucose control. Method 41 participants were randomly allocated to either a Tai Chi intervention group (N = 20) or a usual medical care control group (N = 21). The Tai Chi group involved 3 x 1.5 hour supervised and group-based training sessions per week for 12 weeks. Indicators of HR-QOL were assessed by self-report survey immediately prior to and after the intervention. Results There were significant improvements in favour of the Tai Chi group for the SF36 subscales of physical functioning (mean difference = 5.46, 95% CI = 1.35-9.57, P < 0.05), role physical (mean difference = 18.60, 95% CI = 2.16-35.05, P < 0.05), bodily pain (mean difference = 9.88, 95%CI = 2.06-17.69, P < 0.05) and vitality (mean difference = 9.96, 95% CI = 0.77-19.15, P < 0.05). Conclusions The findings show that this Tai Chi program improved indicators of HR-QOL including physical functioning, role physical, bodily pain and vitality in people with elevated blood glucose or diabetes who were not on diabetes medication.

Communication predicaments of older health care consumers : what can 'we' do about it?

Focuses on the importance of communication to the well-being of older people in Australia. Role of communication for the design, delivery and evaluation of health services for the elderly; Impact of aging on communication; Importance of communication between health care providers and nursing home residents.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.