Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method.

The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them

An evaluation of the quality of evidence underpinning diabetes management models: a review of the literature

OBJECTIVE: There is a paucity of research on the quality of evidence relating to primary care workforce models. Thus, the aim of the present study was to evaluate the quality of evidence on diabetes primary care workforce models in Australia. METHODS: The National Health and Medical Research Council of Australia's (National Health and Medical Reseach Council; 2000, 2001) frameworks for evaluating scientific evidence and economic evaluations were used to assess the quality of studies involving primary care workforce models for diabetes care involving Australian adults. A search of medical databases (MEDLINE, AMED, RURAL, Australian Indigenous HealthInfoNet and The Cochrane Institute), journals for diabetes care (Diabetes Research and Clinical Practice, Diabetes Care, Diabetic Medicine, Population Health Management, Rural and Remote Health, Australian Journal of Primary Health, PLoS Medicine, Medical Journal of Australia, BMC Health Services Research, BMC Public Health, BMC Family Practice) and Commonwealth and state government health websites was undertaken to acquire Australian studies of diabetes workforce models published 2005-13. Various diabetes workforce models were examined, including 'one-stop shops', pharmacy care, Aboriginal services and telephone-delivered interventions. The quality of evidence was evaluated against several criteria, including relevance and replication, strength of evidence, effect size, transferability and representativeness, and value for money. RESULTS: Of the 14 studies found, four were randomised controlled trials and one was a systematic review (i.e. Level II and I (best) evidence). Only three provided a replicable protocol or detailed intervention delivery. Eleven lacked a theoretical framework. Twelve reported significant improvements in clinical (patient) outcomes, commonly HbA1c, cholesterol and blood pressure; only four reported changes in short- and long-term outcomes (e.g. quality of life). Most studies used a small or targeted population. Only two studies assessed both benefits and costs of their intervention compared with usual care and cost effectiveness. CONCLUSIONS: More rigorous studies of diabetes workforce models are needed to determine whether these interventions improve patient outcomes and, if they do, represent value for money. WHAT IS KNOWN ABOUT THE TOPIC?: Although health systems with strong primary care orientations have been associated with enhanced access, equity and population health, the primary care workforce is facing several challenges. These include a mal-distribution of resources (supply side) and health outcomes (demand side), inconsistent support for teamwork care models, and a lack of enhanced clinical inter-professional education and/or training opportunities. These challenges are exacerbated by an ageing health workforce and general population, as well as a population that has increased prevalence of chronic conditions and multi-morbidity. Although several policy directions have been advocated to address these challenges, there is a lack of high-quality evidence about which primary care workforce models are best (and which models represent better value for money than current practice) and what the health effects are for patients. WHAT DOES THIS PAPER ADD?: This study demonstrated several strengths and weaknesses of Australian diabetes models of care studies. In particular, only five of the 14 studies assessed were designed in a way that enabled them to achieve a Level II or I rating (and hence the 'best' level of evidence), based on the NHMRC's (2000, 2001) frameworks for assessing scientific evidence. The majority of studies risked the introduction of bias and thus may have incorrect conclusions. Only a few studies described clearly what the intervention and the comparator were and thus could be easily replicated. Only two studies included cost-effectiveness studies of their interventions compared with usual care. WHAT ARE THE IMPLICATIONS FOR PRACTITIONERS?: Although there has been an increase in the number of primary care workforce models implemented in Australia, there is a need for more rigorous research to assess whether these interventions are effective in producing improved health outcomes and represent better value for money than current practice. Researchers and policymakers need to make decisions based on high-quality evidence; it is not obvious what effect the evidence is having on primary care workforce reform

Care&WorkMOD: An Australian Microsimulation Model Projecting the Economic Impacts of Early Retirement in Informal Carers

We developed a microsimulation model, Care&WorkMOD, to estimate the economic costs of early exit from the labour force, both for informal carers and the government, from 2015 to 2030. In this paper, we describe the methods used to create the model Care&WorkMOD, and the sources of data and model assumptions. Care&WorkMOD is based on the unit record data of people aged 15-64 years in the three Australian Bureau of Statistics (ABS) Surveys of Disability, Ageing and Carers (SDAC) 2003, 2009 and 2012. Population and the labour force projections from the 2015 Intergenerational Report and the outputs of an Australian microsimulation model APPSIM were used for the static aging of the base data to every five years from 2015 to 2030. The 2015 output dataset of another microsimulation model STINMOD was linked with Care&WorkMOD base data using synthetic matching. The matching process has added data on further economic variables from STINMOD into Care&WorkMOD, which are not available in SDACs. Economic data were indexed based on long-term trends on economic variables to capture the projected economic growth from 2015 to 2030. Care&WorkMOD can provide the long-term estimates of the lost labour productivity due to informal caring responsibilities and the related economic burden both at the individual and national level, and has the potential to “fill the gaps” in the current body of evidence on the costs of chronic diseases, particularly related to informal carers