Jodi Gray

A critical review of model-based economic studies of depression: modelling techniques, model structure and data sources.

Depression is the most common mental health disorder and is recognized as a chronic disease characterized by multiple acute episodes/relapses. Although modelling techniques play an increasingly important role in the economic evaluation of depression interventions, comparatively little attention has been paid to issues around modelling studies with a focus on potential biases. This, however, is important as different modelling approaches, variations in model structure and input parameters may produce different results, and hence different policy decisions.This paper presents a critical review of literature on recently published model-based cost-utility studies of depression. Taking depression as an illustrative example, through this review, we discuss a number of specific issues in relation to the use of decision-analytic models including the type of modelling techniques, structure of models and data sources.The potential benefits and limitations of each modelling technique are discussed and factors influencing the choice of modelling techniques are addressed. This review found that model-based studies of depression used various simulation techniques. We note that a discrete-event simulation may be the preferred technique for the economic evaluation of depression due to the greater flexibility with respect to handling time compared with other individual-based modelling techniques.Considering prognosis and management of depression, the structure of the reviewed models are discussed. We argue that a few reviewed models did not include some important structural aspects such as the possibility of relapse or the increased risk of suicide in patients with depression. Finally, the appropriateness of data sources used to estimate input parameters with a focus on transition probabilities is addressed. We argue that the above issues can potentially bias results and reduce the comparability of economic evaluations.

Photoreceptor processing improves salience facilitating small target detection in cluttered scenes.

Target detection amidst clutter is a challenging task for both natural and artificial vision, yet one solved at the level of neurons in the 3rd optic ganglion of insects. These neurons are capable of responding to the motion of small objects, even against complex moving backgrounds. While the basic physiology has been investigated, little is known about how these cells are able to reject background motion while robustly responding to such small stimuli. By recording intracellularly from fly photoreceptors stimulated with natural image sequences containing a target viewed against a complex moving background, we show that the process of target detection begins at the earliest stages of vision. The temporal processing by photoreceptors alone, in the absence of any spatial interactions, improved the discrimination of targets (essentially a spatial task) by around 70%. This enhancement of target salience can be explained by elaborate models of photoreceptor temporal non-linear dynamics. The application of the functional principals outlined in this work could be utilized in areas such as robotics and surveillance, medical imaging, or astronomy, anywhere it is necessary to detect a small item from a cluttered surround.

A proposed model for economic evaluations of major depressive disorder

In countries like UK and Australia, the comparability of model-based analyses is an essential aspect of reimbursement decisions for new pharmaceuticals, medical services and technologies. Within disease areas, the use of models with alternative structures, type of modelling techniques and/or data sources for common parameters reduces the comparability of evaluations of alternative technologies for the same condition. The aim of this paper is to propose a decision analytic model to evaluate long-term costs and benefits of alternative management options in patients with depression. The structure of the proposed model is based on the natural history of depression and includes clinical events that are important from both clinical and economic perspectives. Considering its greater flexibility with respect to handling time, discrete event simulation (DES) is an appropriate simulation platform for modelling studies of depression. We argue that the proposed model can be used as a reference model in model-based studies of depression improving the quality and comparability of studies.

Practice nurse involvement in general practice clinical care: policy and funding issues need resolution

In Australia, primary care-based funding initiatives have been implemented to encourage general practices to employ practice nurses. The aim of this paper is to discuss limitations of the current funding and policy arrangements in enhancing the clinical role of practice nurses in the management of chronic conditions. This paper draws on the results of a real-world economic evaluation, the Primary Care Services Improvement Project (PCSIP). The PCSIP linked routinely collected clinical and resource use data to undertake a risk-adjusted cost-effectiveness analysis of increased practice nurse involvement in clinical-based activities for the management of diabetes and obesity. The findings of the PCSIP suggested that the active involvement of practice nurses in collaborative clinical-based activities is cost-effective, as well as addressing general practice workforce issues. Although primary healthcare organisations (e.g. Medicare Locals) can play a key role in supporting enhanced practice nurse roles, improvements to practice nurse funding models could further encourage more efficient use of an important resource.

A risk adjusted cost-effectiveness analysis of alternative models of nurse involvement in obesity management in primary care.

Controlled evaluations are subject to uncertainty regarding their replication in the real world, particularly around systems of service provision. Using routinely collected data, we undertook a risk adjusted cost‐effectiveness (RAC‐E) analysis of alternative applied models of primary health care for the management of obese adult patients. Models were based on the reported level of involvement of practice nurses (registered or enrolled nurses working in general practice) in the provision of clinical‐based activities.

A risk-adjusted economic evaluation of alternative models of involvement of practice nurses in management of type 2 diabetes.

To determine the cost‐effectiveness of alternative models of practice nurse involvement in the management of type 2 diabetes within the primary care setting.

A model-based evaluation of collaborative care in management of patients with type 2 diabetes in Australia: an initial report

OBJECTIVES To analyse the short- and long-term costs and benefits of alternative models of primary care for the management of patients with type 2 diabetes in Australia. The models of care reflect differential uptake of primary care-based incentive programs, including reminder systems and involvement of practice nurses in management. This paper describes our study protocol and its progress. METHODS We are undertaking an observational study using a cluster sample design that links retrospective patient data from a range of sources to estimate costs and intermediate outcomes (such as the level of glycosylated haemoglobin (HbA1c)) over a 3-year time horizon. We use the short-term data as a basis to estimate lifetime costs and benefits of alternative models of care using a decision analytic model. INITIAL REPORT: We recruited 15 practices from a metropolitan area (Adelaide) and allocated them to three models of care. Three hundred and ninety-nine patients agreed to participate. We use multilevel analysis to evaluate the association between different models of care and patient-level outcomes, while controlling for several covariates. DISCUSSION/CONCLUSIONS Given the large amount of funding currently used to maintain primary care-based incentives in general practices in Australia, the results of this study generate the knowledge required to promote investment in the most cost-effective incentives.

A long-term evaluation of the stage of change approach and compensable injury outcomes – a cluster-randomised trial

Abstract This study investigated the long-term injury outcomes for workers in companies from a range of industries which had been randomly allocated to receive ergonomics interventions tailored according to the stage of change (SOC) approach or standard ergonomics advice. Differences in compensable injury outcomes between the groups were analysed using logistic regression models. Questionnaire results from face-to-face interviews to assess musculoskeletal pain and discomfort (MSPD), job satisfaction and other factors were also analysed. Although not significant at the 0.05 level, after adjusting for workgroup clustering, workers in receipt of tailored advice were 55% (OR = 0.45, 95% CI = 0.19–1.08) less likely to report a compensable injury than those in receipt of standard ergonomics advice. Workload, job satisfaction and MSPD were significantly correlated with injury outcomes. The observed outcomes support the potential value of the SOC approach, as well as highlighting the need to consider workload, job satisfaction and MSPD when planning injury prevention programmes. Practitioner Summary: This study investigated compensable injury outcomes for workers who had received ergonomics advice tailored according to the stage of change (SOC) approach compared with standard ergonomics advice. The results support the potential value of the SOC approach and highlight the need to consider workload, job satisfaction and musculoskeletal pain and discomfort when planning injury prevention interventions.

Practice nurse involvement in primary care depression management: an observational cost-effectiveness analysis

BackgroundMost evidence on the effect of collaborative care for depression is derived in the selective environment of randomised controlled trials. In collaborative care, practice nurses may act as case managers. The Primary Care Services Improvement Project (PCSIP) aimed to assess the cost-effectiveness of alternative models of practice nurse involvement in a real world Australian setting. Previous analyses have demonstrated the value of high level practice nurse involvement in the management of diabetes and obesity. This paper reports on their value in the management of depression.MethodsGeneral practices were assigned to a low or high model of care based on observed levels of practice nurse involvement in clinical-based activities for the management of depression (i.e. percentage of depression patients seen, percentage of consultation time spent on clinical-based activities). Linked, routinely collected data was used to determine patient level depression outcomes (proportion of depression-free days) and health service usage costs. Standardised depression assessment tools were not routinely used, therefore a classification framework to determine the patient’s depressive state was developed using proxy measures (e.g. symptoms, medications, referrals, hospitalisations and suicide attempts). Regression analyses of costs and depression outcomes were conducted, using propensity weighting to control for potential confounders.ResultsCapacity to determine depressive state using the classification framework was dependent upon the level of detail provided in medical records. While antidepressant medication prescriptions were a strong indicator of depressive state, they could not be relied upon as the sole measure. Propensity score weighted analyses of total depression-related costs and depression outcomes, found that the high level model of care cost more (95% CI: -

Managing high‐risk surgical patients: modifiable co‐morbidities matter

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