The validity of the Child Health Utility instrument (CHU9D) as a routine outcome measure for use in child and adolescent mental health services

BACKGROUND: Few cost-utility studies of child and adolescent mental health services (CAMHS) use quality adjusted life years (a combination of utility weights and time in health state) as the outcome to enable comparison across disparate programs and modalities. Part of the solution to this problem involves embedding preference-based health-related quality of life (PBHRQOL) utility instruments, which generate utility weights, in clinical practice and research. The Child Health Utility (CHU9D) is a generic PBHRQOL instrument developed specifically for use in young people. The purpose of this study was to assess the suitability of the CHU9D as a routine outcome measure in CAMHS clinical practice. METHODS: Two hundred caregivers of children receiving community mental health services completed the CHU9D alongside a standardised child and adolescent mental health measure (the Strengths and Difficulties Questionnaire - SDQ) during a telephone interview. We investigated face validity, practicality, internal consistency, and convergent validity of the CHU9D. In addition, we compared the utility weights obtained in this group with utility weights from other studies of child and adolescent mental health populations. RESULTS: Participants found the CHU9D easy and quick to complete. It demonstrated acceptable internal consistency, and correlated moderately with the SDQ. It was able to discriminate between children in the abnormal range and those in the non-clinical/borderline range as measured by the SDQ. Three CHU9D items without corollaries in the SDQ (sleep, schoolwork, daily routine) were found to be significant predictors of the SDQ total score and may be useful clinical metrics. The mean utility weight of this sample was comparable with clinical subsamples from other CHU9D studies, but was significantly higher than mean utility weights noted in other child and adolescent mental health samples. CONCLUSIONS: Initial validation suggests further investigation of the CHU9D as a routine outcome measure in CAMHS is warranted. Further investigation should explore test-retest reliability, sensitivity to change, concordance between caregiver and child-completed forms, and the calibration of the utility weights. Differences between utility weights generated by the CHU9D and other utility instruments in this population should be further examined by administering a range of PBHRQOL instruments concurrently in a mental health group

A population-based model for priority setting across the care continuum and across modalities

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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

Is the value of a life or life-year saved context specific? Further evidence from a discrete choice experiment

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

An evidence-based health workforce model for primary and community care

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Discussion</p> <p>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.</p> <p>Summary</p> <p>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.</p

Market failure, policy failure and other distortions in chronic disease markets

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Discussion</p> <p>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.</p> <p>Summary</p> <p>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.</p

Review of Australian health economic evaluation – 245 interventions: what can we say about cost effectiveness?

© 2008 Dalziel et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A work force model to support the adoption of best practice care in chronic diseases – a missing piece in clinical guideline implementation

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

National Food and Nutrition Strategy: Health Systems Issues

No abstract supplie

Parsimonious and efficient assessment of health-related quality of life in osteoarthritis research: validation of the Assessment of Quality of Life (AQoL) instrument

BACKGROUND: 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. METHODS: 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. RESULTS: All instruments detected differences between groups; however no one instrument exhibited superior efficiency. The AQoL demonstrated strong psychometric properties. CONCLUSION: 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

Adverse childhood experiences, non-response and loss to follow-up: Findings from a prospective birth cohort and recommendations for addressing missing data

Adverse childhood experiences have wide-ranging impacts on population health but are inherently difficult to study. Retrospective self-report is commonly used to identify exposure but adult population samples may be biased by non-response and loss to follow-up. We explored the implications of missing data for research on child abuse and neglect, domestic violence, parental mental illness and parental substance use. Using 15 waves of data collected over 28 years in a population-based birth cohort, the Australian Temperament Project, we examined the relationship between retrospective self-reports of adverse childhood experiences and parent- and cohort-responsiveness at other time points. We then compared prevalence estimates under complete case analysis, inverse probability-weighting using baseline auxiliary variables, multiple imputation using baseline auxiliary variables, multiple imputation using auxiliary variables from all waves, and multiple imputation using additional measures of participant responsiveness. Retrospective self-reports of adverse childhood experiences were strongly associated with non-response by both parents and cohort members at all observable time points. Biases in complete case estimates appeared large and inverse probability-weighting did not reduce them. Multiple imputation increased the estimated prevalence of any adverse childhood experiences from 30.0% to 36.9% with only baseline auxiliary variables, 39.7% with a larger set of auxiliary variables and 44.0% when measures of responsiveness were added. Close attention must be paid to missing data and non-response in research on adverse childhood experiences as data are unlikely to be missing at random. Common approaches may greatly underestimate their prevalence and compromise analysis of their causes and consequences. Sophisticated techniques using a wide range of auxiliary variables are critical in this field of research, including, where possible, measures of participant responsiveness.Funding for this analysis was supported by a PhD scholarship from the University of South Australia, and the South Australian Health Economics Collaborative (funded by the South Australian Department of Health)