Best-practice diabetes care can reduce the burden of diabetes and associated health care costs. But this requires access to a multidisciplinary team with the right skill mix. We applied a needs-driven evidence-based health workforce model to describe the primary care team required to support best-practice diabetes care, paying particular attention to diverse clinic populations.
RESEARCH DESIGN AND METHODS
Care protocols, by number and duration of consultations, were derived for twenty distinct competencies based on clinical practice guidelines and structured input from a multidisciplinary clinical panel. This was combined with a previously estimated population profile of persons across 26 patient attributes (i.e., type of diabetes, complications, and threats to self-care) to estimate clinician contact hours by competency required to deliver best-practice care in the study region.
A primary care team of 22.1 full-time-equivalent (FTE) positions was needed to deliver best-practice primary care to a catchment of 1,000 persons with diabetes with the attributes of the Australian population. Competencies requiring greatest contact time were psychosocial issues and dietary advice at 3.5 and 3.3 FTE, respectively (1 FTE/∼300 persons); home (district) nursing at 3.2 FTE; and diabetes education at 2.8 FTE. The annual cost of delivering care was estimated at just over 2,000 Australian dollars (∼2,090 USD) (2012) per person with diabetes.
A needs-driven approach to primary care service planning identified a wider range of competencies in the diabetes primary and community care team than typically described. Access to psychosocial competences as well as medical management is required if clinical targets are to be met, especially in disadvantaged groups.
Type 2 diabetes (T2D) brings significant human and healthcare costs. Its progressive nature means achieving normoglycaemia is increasingly difficult, yet critical to avoiding long term vascular complications. Nearly one-half of people with T2D have glycaemic levels out of target. Insulin is effective in achieving glycaemic targets, yet initiation of insulin is often delayed, particularly in primary care. Given limited access to specialist resources and the size of the diabetes epidemic, primary care is where insulin initiation must become part of routine practice. This would also support integrated holistic care for people with diabetes. Our Stepping Up Program is based on a general practitioner (GP) and practice nurse (PN) model of care supported appropriately by endocrinologists and credentialed diabetes educator-registered nurses. Pilot work suggests the model facilitates integration of the technical work of insulin initiation within ongoing generalist care.
This protocol is for a cluster randomized controlled trial to examine the effectiveness of the Stepping Up Program to enhance the role of the GP-PN team in initiating insulin and improving glycaemic outcomes for people with T2D. 224 patients between the ages of 18 and 80 years with T2D, on two or more oral hypoglycaemic agents and with an HbA1c ≥7.5% in the last six months will be recruited from 74 general practices. The unit of randomization is the practice.
Primary outcome is change in glycated haemoglobin HbA1c (measured as a continuous variable). We hypothesize that the intervention arm will achieve an absolute HbA1c mean difference of 0.5% lower than control group at 12 months follow up. Secondary outcomes include the number of participants who successfully transfer to insulin and the proportion who achieve HbA1c measurement of <7.0%. We will also collect data on patient psychosocial outcomes and healthcare utilization and costs.
The study is a pragmatic translational study with important potential implications for people with T2D, healthcare professionals and funders of healthcare though making better use of scarce healthcare resources, improving timely access to therapy that can improve disease outcomes.
Australian and New Zealand Clinical Trials Registry ACTRN12612001028897
Type 2 diabetes; Primary care; Nursing; Randomized trial; Insulin; Implementation; Australia; Health services research
Diabetes mellitus is an increasingly prevalent metabolic disorder that is associated with substantial disease burden. Australia has an opportunity to improve ways of caring for the growing number of people with diabetes, but this may require changes to the way care is funded, organised and delivered. To inform how best to care for people with diabetes, and to identify the extent of change that is required to achieve this, the Diabetes Care Project (DCP) will evaluate the impact of two different, evidence-based models of care (compared to usual care) on clinical quality, patient and provider experience, and cost.
The DCP uses a pragmatic, cluster randomised controlled trial design. Accredited general practices that are situated within any of the seven Australian Medicare Locals/Divisions of General Practice that have agreed to take part in the study were invited to participate. Consenting practices will be randomly assigned to one of three treatment groups for approximately 18 to 22 months: (a) control group (usual care); (b) Intervention 1 (which tests improvements that could be made within the current funding model, facilitated through the use of an online chronic disease management network); or (c) Intervention 2 (which includes the same components as Intervention 1, as well as altered funding to support voluntary patient registration with their practice, incentive payments and a care facilitator). Adult patients who attend the enrolled practices and have established (≥12 month’s duration) type 1 diabetes mellitus or newly diagnosed or established type 2 diabetes mellitus are invited to participate. Multiple outcomes will be studied, including changes in glycosylated haemoglobin (primary outcome), changes in other biochemical and clinical metrics, incidence of diabetes-related complications, quality of life, clinical depression, success of tailored care, patient and practitioner satisfaction, and budget sustainability.
This project responds to a need for robust evidence of the clinical and economic effectiveness of coordinated care for the management of diabetes in the Australian primary care setting. The outcomes of the study will have implications not only for diabetes management, but also for the management of other chronic diseases, both in Australia and overseas.
Australian New Zealand Clinical Trials Registry (ACTRN12612000363886); World Health Organisation (U1111-1128-0481).
Cluster randomised controlled trial; Coordinated care; Diabetes mellitus; Economic evaluation; General practice; Primary care
Primary health care is recognised as an integral part of a country’s health care system. Measuring hospitalisations, that could potentially be avoided with high quality and accessible primary care, is one indicator of how well primary care services are performing. This review was interested in the association between chronic disease related hospitalisations and primary health care resourcing.
Studies were included if peer reviewed, written in English, published between 2002 and 2012, modelled hospitalisation as a function of PHC resourcing and identified hospitalisations for type 2 diabetes as a study outcome measure. Access and use of PHC services were used as a proxy for PHC resourcing. Studies in populations with a predominant user pay system were excluded to eliminate patient financial barriers to PHC access and utilisation. Articles were systematically excluded based on the inclusion criteria, to arrive at the final set of studies for review.
The search strategy identified 1778 potential articles using EconLit, Medline and Google Scholar databases. Ten articles met the inclusion criteria and were subject to review. PHC resources were quantified by workforce (either medical or nursing) numbers, number of primary care episodes, service availability (e.g. operating hours), primary care practice size (e.g. single or group practitioner practice—a larger practice has more care disciplines onsite), or financial incentive to improve quality of diabetes care. The association between medical workforce numbers and ACSC hospitalisations was mixed. Four of six studies found that less patients per doctor was significantly associated with a decrease in ambulatory care sensitive hospitalisations, one study found the opposite and one study did not find a significant association between the two. When results were categorised by PHC access (e.g. GPs/capita, range of services) and use (e.g. n out-patient visits), better access to quality PHC resulted in fewer ACSC hospitalisations. This finding remained when only studies that adjusted for health status were categorised. Financial incentives to improve the quality of diabetes care were associated with less ACSC hospitalisations, reported in one study.
Seven of 12 measures of the relationship between PHC resourcing and ACSC hospitalisations had a significant inverse association. As a collective body of evidence the studies provide inconclusive support that more PHC resourcing is associated with reduced hospitalisation for ACSC. Characteristics of improved or increased PHC access showed inverse significant associations with fewer ACSC hospitalisations after adjustment for health status. The varied measures of hospitalisation, PHC resourcing, and health status may contribute to inconsistent findings among studies and make it difficult to interpret findings.
Type 2 diabetes; Chronic disease; Primary health care resourcing; Ambulatory care sensitive conditions; Hospitalisation
To describe the current treatment gap in management of cardiovascular risk factors in patients with poorly controlled type 2 diabetes in general practice as well as the associated financial and therapeutic burden of pharmacological treatment.
Cross-sectional analysis of data from the Patient Engagement and Coaching for Health trial. This totalled 473 patients from 59 general practices with participants eligible if they had HbA1c > 7.5%. Main outcome measures included proportions of patients not within target risk factor levels and weighted average mean annual cost for cardiometabolic medications and factors associated with costs. Medication costs were derived from the Australian Pharmaceutical Benefits Schedule.
Average age was 63 (range 27-89). Average HbA1c was 8.1% and average duration of diabetes was 10 years. 35% of patients had at least one micro or macrovascular complication and patients were taking a mean of 4 cardio-metabolic medications. The majority of participants on treatment for cardiovascular risk factors were not achieving clinical targets, with 74% and 75% of patients out of target range for blood pressure and lipids respectively. A significant proportion of those not meeting clinical targets were not on treatment at all. The weighted mean annual cost for cardiometabolic medications was AUD$1384.20 per patient (2006-07). Independent factors associated with cost included age, duration of diabetes, history of acute myocardial infarction, proteinuria, increased waist circumference and depression.
Treatment rates for cardiovascular risk factors in patients with type 2 diabetes in our participants are higher than those identified in earlier studies. However, rates of achieving target levels remain low despite the large ‘pill burden’ and substantial associated fiscal costs to individuals and the community. The complexities of balancing the overall benefits of treatment intensification against potential disadvantages for patients and health care systems in primary care warrants further investigation.
Type 2 diabetes; Cost; Treatment gap; Treatment burden
Prevalence and incidence of diabetes and other common comorbid conditions (hypertension, coronary heart disease, renal disease and chronic lung disease) are extremely high among Indigenous Australians. Recent measures to improve quality of preventive care in Indigenous community settings, while apparently successful at increasing screening and routine check-up rates, have shown only modest or little improvements in appropriate care such as the introduction of insulin and other scaled-up drug regimens in line with evidence-based guidelines, together with support for risk factor reduction. A new strategy is required to ensure high quality integrated family-centred care is available locally, with continuity and cultural safety, by community-based care coordinators with appropriate system supports.
The trial design is open parallel cluster randomised controlled trial. The objective of this pragmatic trial is to test the effectiveness of a model of health service delivery that facilitates integrated community-based, intensive chronic condition management, compared with usual care, in rural and remote Indigenous primary health care services in north Queensland. Participants are Indigenous adults (aged 18–65 years) with poorly controlled diabetes (HbA1c>=8.5) and at least one other chronic condition. The intervention is to employ an Indigenous Health Worker to case manage the care of a maximum caseload of 30 participants. The Indigenous Health Workers receive intensive clinical training initially, and throughout the study, to ensure they are competent to coordinate care for people with chronic conditions. The Indigenous Health Workers, supported by the local primary health care (PHC) team and an Indigenous Clinical Support Team, will manage care, including coordinating access to multidisciplinary team care based on best practice standards. Allocation by cluster to the intervention and control groups is by simple randomisation after participant enrolment. Participants in the control group will receive usual care, and will be wait-listed to receive a revised model of the intervention informed by the data analysis. The primary outcome is reduction in HbA1c measured at 18 months. Implementation fidelity will be monitored and a qualitative investigation (methods to be determined) will aim to identify elements of the model which may influence health outcomes for Indigenous people with chronic conditions.
This pragmatic trial will test a culturally-sound family-centred model of care with supported case management by IHWs to improve outcomes for people with complex chronic care needs. This trial is now in the intervention phase.
Australian New Zealand Clinical Trials Registry ACTR12610000812099
Aboriginal and Torres Strait Islander; Diabetes; Indigenous Health Worker; Partnerships; HbA1c control
With rising burdens of obesity and chronic disease, the role of diet as a modifiable risk factor is of increasing public health interest. There is a growing body of evidence that low consumption of dairy products is associated with elevated risk of chronic metabolic and cardiovascular disorders. Surveys also suggest that dairy product consumption falls well below recommended targets for much of the population in many countries, including the USA, UK, and Australia. We reviewed the scientific literature on the health effects of dairy product consumption (both positive and negative) and used the best available evidence to estimate the direct healthcare expenditure and burden of disease [disability-adjusted life years (DALY)] attributable to low consumption of dairy products in Australia. We implemented a novel technique for estimating population attributable risk developed for application in nutrition and other areas in which exposure to risk is a continuous variable. We found that in the 2010–2011 financial year, AUD$2.0 billion (USD$2.1 billion, €1.6 billion, or ∼1.7% of direct healthcare expenditure) and the loss of 75,012 DALY were attributable to low dairy product consumption. In sensitivity analyses, varying core assumptions yielded corresponding estimates of AUD$1.1–3.8 billion (0.9–3.3%) and 38,299–151,061 DALY lost. The estimated healthcare cost attributable to low dairy product consumption is comparable with total spending on public health in Australia (AUD$2.0 billion in 2009–2010). These findings justify the development and evaluation of cost-effective interventions that use dairy products as a vector for reducing the costs of diet-related disease.
To develop an instrument that predicts diabetes-related vascular disease severity using routinely collected data on Australian Aboriginal and Torres Strait Islander adults with type 2 diabetes, in the absence of diabetes duration.
A complex diabetes severity classification system was simplified and adapted for use with an Australian Aboriginal and Torres Strait Islander adult population with type 2 diabetes in north Queensland. Detailed vascular health risks and morbidities were mapped to routinely collected measures. Individual–level health screening, hospital separation and mortality data were linked and used to plot mean monthly in-patient hospital cost and percent mortality by disease severity as defined by the newly developed instrument, to test construct validity.
The revised instrument consists of four combined diabetes-related microvascular and macrovascular stages that range from least severe (stage 1) to severe irreversible vascular impairment (stage 4). When applied to data of an Aboriginal and Torres Strait Islander Australian population the instrument showed good construct validity, predicting higher hospital cost and mortality as vascular disease severity increased.
This instrument discriminates between levels of diabetes-related vascular disease severity, displays good construct validity by predicting increased hospital cost and mortality with worsening severity and can be populated with routinely collected data. It may assist with future health service research and its use could be extended to practice settings for health care planning for diabetes management programs and monitoring vascular disease progression.
Diabetes vascular staging instrument; Aboriginal and Torres Strait Islander Australians
Post-traumatic stress disorder (PTSD) is diagnosed in 20% to 53% of sexually abused children and adolescents. Living with PTSD is associated with a loss of health-related quality of life. Based on the best available evidence, the NICE Guideline for PTSD in children and adolescents recommends cognitive behavioural therapy (TF-CBT) over non-directive counselling as a more efficacious treatment.
A modelled economic evaluation conducted from the Australian mental health care system perspective estimates incremental costs and Quality Adjusted Life Years (QALYs) of TF-CBT, TF-CBT combined with selective serotonin reuptake inhibitor (SSRI), and non-directive counselling. The "no treatment" alternative is included as a comparator. The first part of the model consists of a decision tree corresponding to 12 month follow-up outcomes observed in clinical trials. The second part consists of a 30 year Markov model representing the slow process of recovery in non-respondents and the untreated population yielding estimates of long-term quality-adjusted survival and costs. Data from the 2007 Australian Mental Health Survey was used to populate the decision analytic model.
In the base-case and sensitivity analyses, incremental cost-effectiveness ratios (ICERs) for all three active treatment alternatives remained less than A$7,000 per QALY gained. The base-case results indicated that non-directive counselling is dominated by TF-CBT and TF-CBT + SSRI, and that efficiency gain can be achieved by allocating more resources toward these therapies. However, this result was sensitive to variation in the clinical effectiveness parameters with non-directive counselling dominating TF-CBT and TF-CBT + SSRI under certain assumptions. The base-case results also suggest that TF-CBT + SSRI is more cost-effective than TF-CBT.
Even after accounting for uncertainty in parameter estimates, the results of the modelled economic evaluation demonstrated that all psychotherapy treatments for PTSD in sexually abused children have a favourable ICER relative to no treatment. The results also highlighted the loss of quality of life in children who do not receive any psychotherapy. Results of the base-case analysis suggest that TF-CBT + SSRI is more cost-effective than TF-CBT alone, however, considering the uncertainty associated with prescribing SSRIs to children and adolescents, clinicians and parents may exercise some caution in choosing this treatment alternative.
In order for clinical practice guidelines (CPGs) to meet their broad objective of enhancing the quality of care and supporting improved patient outcomes, they must address the needs of diverse patient populations. We set out to explore the patient attributes that are likely to demand a unique approach to the management of chronic disease, and which are crucial if evidence or services planning is to reflect clinic populations. These were incorporated into a new conceptual framework; using diabetes mellitus as an exemplar.
The patient attributes that informed the framework were identified from CPGs, the diabetes literature, an expert academic panel, and two cross-disciplinary panels; and agreed upon using a modified nominal group technique.
Full consensus was reached on twenty-four attributes. These factors fell into one of three themes: (1) type/stage of disease, (2) morbid events, and (3) factors impacting on capacity to self-care. These three themes were incorporated in a convenient way in the workforce evidence-based (WEB) model.
While biomedical factors are frequently recognised in published clinical practice guidelines, little attention is given to attributes influencing a person's capacity to self-care. Paying explicit attention to predictable threats to effective self-care in clinical practice guidelines, by drawing on the WEB model, may assist in refinements that would address observed disparities in health outcomes across socio-economic groups. The WEB model also provides a framework to inform clinical training, and health services and workforce planning and research; including the assessment of healthcare needs, and the allocation of healthcare resources.
The delivery of best practice care can markedly improve clinical outcomes in patients with chronic disease. While the provision of a skilled, multidisciplinary team is pivotal to the delivery of best practice care, the occupational or skill mix required to deliver this care is unclear; it is also uncertain whether such a team would have the capacity to adequately address the complex needs of the clinic population. This is the role of needs-based health workforce planning. The objective of this article is to describe the development of an evidence-informed, needs-based health workforce model to support the delivery of best-practice interdisciplinary chronic disease management in the primary and community care setting using diabetes as a case exemplar.
Development of the workforce model was informed by a strategic review of the literature, critical appraisal of clinical practice guidelines, and a consensus elicitation technique using expert multidisciplinary clinical panels. Twenty-four distinct patient attributes that require unique clinical competencies for the management of diabetes in the primary care setting were identified. Patient attributes were grouped into four major themes and developed into a conceptual model: the Workforce Evidence-Based (WEB) planning model. The four levels of the WEB model are (1) promotion, prevention, and screening of the general or high-risk population; (2) type or stage of disease; (3) complications; and (4) threats to self-care capacity. Given the number of potential combinations of attributes, the model can account for literally millions of individual patient types, each with a distinct clinical team need, which can be used to estimate the total health workforce requirement.
The WEB model was developed in a way that is not only reflective of the diversity in the community and clinic populations but also parsimonious and clear to present and operationalize. A key feature of the model is the classification of subpopulations, which gives attention to the particular care needs of disadvantaged groups by incorporating threats to self-care capacity. The model can be used for clinical, health services, and health workforce planning.
Preventing disability and offering effective interventions to older people during early decline in function is most likely to be effective if those most at risk of progressive disablement are able to be identified. Similarly the ability to easily identify a group with similar functional profile from disparate sectors of the community is of significant benefit to researchers. This study aimed to (1) describe the use of a pre-clinical disability screening tool to select a functionally comparable group of older men and women with early functional limitation from different settings, and (2) explore factors associated with function and disability.
Self-reported function and disability measured with the Late-Life Function and Disability Instrument along with a range of physical performance measurements were compared across residential settings and gender in a sample of 471 trial participants identified as pre-clinically disabled after being screened with the Fried pre-clinical disability tool. Factors that might lie on the pathway to progressive disablement were identified using multiple linear regression analysis.
We found that a sample population, screened for pre-clinical disability, had a functional status and disability profile reflecting early functional limitation, regardless of residential setting or gender. Statistical models identified a range of factors associated with function and disability which explained a greater degree of the variation in function, than disability.
We selected a group of people with a comparable function and disability profile, consistent with the pre-clinical stage of disability, from a sample of older Australian men and women from different residential settings using the Fried pre-clinical disability screening tool. The results suggest that the screening tool can be used with greater confidence for research, clinical and population health purposes. Further research is required to examine the validity of the tool. These findings offer insight into the type of impairment factors characterising early functional loss that could be addressed through disability prevention initiatives.
The increasing prevalence of chronic disease represents a significant burden on most health systems. This paper explores the market failures and policy failures that exist in the management of chronic diseases.
There are many sources of market failure in health care that undermine the efficiency of chronic disease management. These include incomplete information as well as information asymmetry between providers and consumers, the effect of externalities on consumer behaviour, and the divergence between social and private time preference rates. This has seen government and policy interventions to address both market failures and distributional issues resulting from the inability of private markets to reach an efficient and equitable distribution of resources. However, these have introduced a series of policy failures such as distorted re-imbursement arrangements across modalities and delivery settings.
The paper concludes that market failure resulting from a preference of individuals for 'immediate gratification' in the form of health care and disease management, rather than preventative services, where the benefits are delayed, has a major impact on achieving an efficient allocation of resources in markets for the management of chronic diseases. This distortion is compounded by government health policy that tends to favour medical and pharmaceutical interventions further contributing to distortions in the allocation of resources and inefficiencies in the management of chronic disease.
This article examines issues facing the future health care workforce in Australia in light of factors such as population ageing. It has been argued that population ageing in Australia is affecting the supply of health care professionals as the health workforce ages and at the same time increasing the demand for health care services and the health care workforce.
However, the picture is not that simple. The health workforce market in Australia is influenced by a wide range of factors; on the demand side by increasing levels of income and wealth, emergence of new technologies, changing disease profiles, changing public health priorities and a focus on the prevention of chronic disease. While a strong correlation is observed between age and use of health care services (and thus health care workforce), this is mediated through illness, as typified by the consistent finding of higher health care costs in the months preceding death.
On the supply side, the health workforce is highly influenced by policy drivers; both national policies (eg funded education and training places) and local policies (eg work place-based retention policies). Population ageing and ageing of the health workforce is not a dominant influence. In recent years, the Australian health care workforce has grown in excess of overall workforce growth, despite an ageing health workforce. We also note that current levels of workforce supply compare favourably with many OECD countries. The future of the health workforce will be shaped by a number of complex interacting factors.
Market failure, a key feature of the market for health care services which is also observed in the health care labour market – means that imbalances between demand and supply can develop and persist, and suggests a role for health workforce planning to improve efficiency in the health services sector. Current approaches to health workforce planning, especially on the demand side, tend to be highly simplistic. These include historical allocation methods, such as the personnel-to-population ratios which are essentially circular in their rationale rather than evidence-based. This article highlights the importance of evidence-based demand modelling for those seeking to plan for the future Australian health care workforce. A model based on population health status and best practice protocols for health care is briefly outlined.
Stroke-specific outcome measures and descriptive measures of health-related quality of life (HRQoL) are unsuitable for informing decision-makers of the broader consequences of increasing or decreasing funding for stroke interventions. The quality-adjusted life year (QALY) provides a common metric for comparing interventions over multiple dimensions of HRQoL and mortality differentials. There are, however, many circumstances when – because of timing, lack of foresight or cost considerations – only stroke-specific or descriptive measures of health status are available and some indirect means of obtaining QALY-weights becomes necessary. In such circumstances, the use of regression-based transformations or mappings can circumvent the failure to elicit QALY-weights by allowing predicted weights to proxy for observed weights. This regression-based approach has been dubbed 'Transfer to Utility' (TTU) regression. The purpose of the present study is to demonstrate the feasibility and value of TTU regression in stroke by deriving transformations or mappings from stroke-specific and generic but descriptive measures of health status to a generic preference-based measure of HRQoL in a sample of Australians with a diagnosis of acute stroke. Findings will quantify the additional error associated with the use of condition-specific to generic transformations in stroke.
We used TTU regression to derive empirical transformations from three commonly used descriptive measures of health status for stroke (NIHSS, Barthel and SF-36) to a preference-based measure (AQoL) suitable for attaching QALY-weights to stroke disease states; based on 2570 observations drawn from a sample of 859 patients with stroke.
Transformations from the SF-36 to the AQoL explained up to 71.5% of variation in observed AQoL scores. Differences between mean predicted and mean observed AQoL scores from the 'severity-specific' item- and subscale-based SF-36 algorithms and from the 'moderate to severe' index- and item-based Barthel algorithm were neither clinically nor statistically significant when 'low severity' SF-36 transformations were used to predict AQoL scores for patients in the NIHSS = 0 and NIHSS = 1–5 subgroups and when 'moderate to severe severity' transformations were used to predict AQoL scores for patients in the NIHSS ≥ 6 subgroup. In contrast, the difference between mean predicted and mean observed AQoL scores from the NIHSS algorithms and from the 'low severity' Barthel algorithms reached levels that could mask minimally important differences on the AQoL scale.
While our NIHSS to AQoL transformations proved unsuitable for most applications, our findings demonstrate that stroke-relevant outcome measures such as the SF-36 and Barthel Index can be adequately transformed to preference-based measures for the purposes of economic evaluation.
The development and implementation of an evidence-based approach to health workforce planning is a necessary step to achieve access to best practice chronic disease management. In its absence, the widely reported failure in implementation of clinical best practice guidelines is almost certain to continue. This paper describes a demand model to estimate the community-based primary care health workforce consistent with the delivery of best practice chronic disease management and prevention. The model takes a geographic region as the planning frame and combines data about the health status of the regional population by disease category and stage, with best practice guidelines to estimate the clinical skill requirement or competencies for the region. The translation of the skill requirement into a service requirement can then be modelled, incorporating various assumptions about the occupation group to deliver nominated competencies. The service requirement, when compared with current service delivery, defines the gap or surplus in services. The results of the model could be used to inform service delivery as well as a workforce supply strategy.
There is an increasing body of published cost-utility analyses of health interventions which we sought to draw together to inform research and policy.
To achieve consistency in costing base and policy context, study scope was limited to Australian-based cost-effectiveness analyses. Through a comprehensive literature review we identified 245 health care interventions that met our study criteria.
The median cost-effectiveness ratio was A$18,100 (~US$13,000) per QALY/DALY/LY (quality adjusted life year gained or, disability adjusted life year averted or life year gained). Some modalities tended to perform worse, such as vaccinations and diagnostics (median cost/QALY $58,000 and $68,000 respectively), than others such as allied health, lifestyle, in-patient interventions (median cost/QALY/DALY/LY all at ~A$9,000~US$6,500). Interventions addressing some diseases such as diabetes and impaired glucose tolerance or alcohol and drug dependence tended to perform well (median cost/QALY/DALY/LY < A$3,700, < US$5,000). Interventions targeting younger persons < 25 years (median cost/QALY/DALY/LY < A$41,200) tended to perform less well than those targeting adults > 25 years (median cost/QALY/DALY/LY < A$16,000). However, there was also substantial variation in the cost effectiveness of individual interventions within and across all categories.
For any given condition, modality or setting there are likely to be examples of interventions that are cost effective and cost ineffective. It will be important for decision makers to make decisions based on the individual merits of an intervention rather than rely on broad generalisations. Further evaluation is warranted to address gaps in the literature and to ensure that evaluations are performed in areas with greatest potential benefit.
A number of recent findings imply that the value of a life saved, life-year (LY) saved or quality-adjusted life year (QALY) saved varies depending on the characteristics of the life, LY or QALY under consideration. Despite these findings, budget allocations continue to be made as if all healthy life-years are equivalent. This continued focus on simple health maximisation is partly attributable to gaps in the available evidence. The present study attempts to close some of these gaps.
Discrete choice experiment to estimate the marginal rate of substitution between cost, effectiveness and various non-health arguments. Odds of selecting profile B over profile A estimated via binary logistic regression. Marginal rates of substitution between attributes (including cost) then derived from estimated regression coefficients.
Respondents were more likely to select less costly, more effective interventions with a strong evidence base where the beneficiary did not contribute to their illness. Results also suggest that respondents preferred prevention over cure. Interventions for young children were most preferred, followed by interventions for young adults, then interventions for working age adults and with interventions targeted at the elderly given lowest priority.
Results confirm that a trade-off exists between cost, effectiveness and non-health arguments when respondents prioritise health programs. That said, it is true that respondents were more likely to select less costly, more effective interventions – confirming that it is an adjustment to, rather than an outright rejection of, simple health maximisation that is required.
The PEACH study is based on an innovative 'telephone coaching' program that has been used effectively in a post cardiac event trial. This intervention will be tested in a General Practice setting in a pragmatic trial using existing Practice Nurses (PN) as coaches for people with type 2 diabetes (T2D). Actual clinical care often fails to achieve standards, that are based on evidence that self-management interventions (educational and psychological) and intensive pharmacotherapy improve diabetes control. Telephone coaching in our study focuses on both. This paper describes our study protocol, which aims to test whether goal focused telephone coaching in T2D can improve diabetes control and reduce the treatment gap between guideline based standards and actual clinical practice.
In a cluster randomised controlled trial, general practices employing Practice Nurses (PNs) are randomly allocated to an intervention or control group. We aim to recruit 546 patients with poorly controlled T2D (HbA1c >7.5%) from 42 General Practices that employ PNs in Melbourne, Australia. PNs from General Practices allocated to the intervention group will be trained in diabetes telephone coaching focusing on biochemical targets addressing both patient self-management and engaging patients to work with their General Practitioners (GPs) to intensify pharmacological treatment according to the study clinical protocol. Patients of intervention group practices will receive 8 telephone coaching sessions and one face-to-face coaching session from existing PNs over 18 months plus usual care and outcomes will be compared to the control group, who will only receive only usual care from their GPs. The primary outcome is HbA1c levels and secondary outcomes include cardiovascular disease risk factors, behavioral risk factors and process of care measures.
Understanding how to achieve comprehensive treatment of T2D in a General Practice setting is the focus of the PEACH study. This study explores the potential role for PNs to help reduce the treatment and outcomes gap in people with T2D by using telephone coaching. The intervention, if found to be effective, has potential to be sustained and embedded within real world General Practice.
The Health-sector Wide (HsW) priority setting model is designed to shift the focus of priority setting away from 'program budgets' – that are typically defined by modality or disease-stage – and towards well-defined target populations with a particular disease/health problem.
The key features of the HsW model are i) a disease/health problem framework, ii) a sequential approach to covering the entire health sector, iii) comprehensiveness of scope in identifying intervention options and iv) the use of objective evidence. The HsW model redefines the unit of analysis over which priorities are set to include all mutually exclusive and complementary interventions for the prevention and treatment of each disease/health problem under consideration. The HsW model is therefore incompatible with the fragmented approach to priority setting across multiple program budgets that currently characterises allocation in many health systems. The HsW model employs standard cost-utility analyses and decision-rules with the aim of maximising QALYs contingent upon the global budget constraint for the set of diseases/health problems under consideration. It is recognised that the objective function may include non-health arguments that would imply a departure from simple QALY maximisation and that political constraints frequently limit degrees of freedom. In addressing these broader considerations, the HsW model can be modified to maximise value-weighted QALYs contingent upon the global budget constraint and any political constraints bearing upon allocation decisions.
The HsW model has been applied in several contexts, recently to osteoarthritis, that has demonstrated both its practical application and its capacity to derive clear evidenced-based policy recommendations.
Comparisons with other approaches to priority setting, such as Programme Budgeting and Marginal Analysis (PBMA) and modality-based cost-effectiveness comparisons, as typified by Australia's Pharmaceutical Benefits Advisory Committee process for the listing of pharmaceuticals for government funding, demonstrate the value added by the HsW model notably in its greater likelihood of contributing to allocative efficiency.
The Assessment of Quality of Life (AQoL) utility instrument was psychometrically developed for the general population. This study aimed to explore its potential as an osteoarthritis (OA) outcome measure.
WOMAC, Lequesne index, SF-36, Visual analogue scales and the AQoL were administered to 222 people with OA. The ability of each questionnaire to detect differences between groups was based on (i) self-rated health (SRH) and, (ii) differences between people on an orthopedic waiting list (WL) vs people with OA in the community (C). Comparisons included effect size, relative efficiency and receiver operator characteristic curves.
All instruments detected differences between groups; however no one instrument exhibited superior efficiency. The AQoL demonstrated strong psychometric properties.
The AQoL has equivalent performance to comparator questionnaires commonly used in OA research and would be a useful adjunct to well-established disease specific scales. The AQoL has important advantages; brevity (12 items), facilitates comparisons between disease groups, and delivers a utility score that can be used in health economic evaluations.
Objective To evaluate the effectiveness of goal focused telephone coaching by practice nurses in improving glycaemic control in patients with type 2 diabetes in Australia.
Design Prospective, cluster randomised controlled trial, with general practices as the unit of randomisation.
Setting General practices in Victoria, Australia.
Participants 59 of 69 general practices that agreed to participate recruited sufficient patients and were randomised. Of 829 patients with type 2 diabetes (glycated haemoglobin (HbA1c) >7.5% in the past 12 months) who were assessed for eligibility, 473 (236 from 30 intervention practices and 237 from 29 control practices) agreed to participate.
Intervention Practice nurses from intervention practices received two days of training in a telephone coaching programme, which aimed to deliver eight telephone and one face to face coaching episodes per patient.
Main outcome measures The primary end point was mean absolute change in HbA1c between baseline and 18 months in the intervention group compared with the control group.
Results The intervention and control patients were similar at baseline. None of the practices dropped out over the study period; however, patient attrition rates were 5% in each group (11/236 and 11/237 in the intervention and control group, respectively). The median number of coaching sessions received by the 236 intervention patients was 3 (interquartile range 1-5), of which 25% (58/236) did not receive any coaching sessions. At 18 months’ follow-up the effect on glycaemic control did not differ significantly (mean difference 0.02, 95% confidence interval −0.20 to 0.24, P=0.84) between the intervention and control groups, adjusted for HbA1c measured at baseline and the clustering. Other biochemical and clinical outcomes were similar in both groups.
Conclusions A practice nurse led telephone coaching intervention implemented in the real world primary care setting produced comparable outcomes to usual primary care in Australia. The addition of a goal focused coaching role onto the ongoing generalist role of a practice nurse without prescribing rights was found to be ineffective.
Trial registration Current Controlled Trials ISRCTN50662837.