While involving users in healthcare decision-making has become increasingly common and important, there is a lack of knowledge about how to best design community-based health screening programs. Reviews of methods that incorporate discrete choice experiments (DCEs) are scarce, particularly for non-cancer illnesses like cardiovascular disease, diabetes and liver disease. We provide an overview of currently available applications and methods available by using DCEs in health screening programs, for chronic conditions.
Abstract Background In Australia, the overall prevalence of liver disease is increasing. Maximising uptake of community screening programmes by understanding patient preferences is integral to developing consumer-centred care models for liver disease. Discrete choice experiments (DCEs) are widely used to elicit preferences for various healthcare services. Attribute development is a vital component of a well-designed DCE and should be described in sufficient detail for others to assess the validity of outcomes. Hence, this study aimed to create a list of potential attributes and levels which can be used in a DCE study to elicit preferences for chronic liver disease screening programmes. Methods Key attributes were developed through a multi-stage, mixed methods design. Focus groups were held with consumers and health care providers on attributes of community screening programmes for liver disease. Stakeholders then prioritised attributes generated from the focus group in order of importance via an online prioritisation survey. The outcomes of the prioritisation exercise were then reviewed and refined by an expert panel to ensure clinically meaningful levels and relevance for a DCE survey. Results Fifteen attributes were generated during the focus group sessions deemed necessary to design liver disease screening services. Outcomes of the prioritisation exercise and expert panel stages recognised five attributes, with three levels each, for inclusion in a DCE survey to elicit consumer preferences for community screening for liver disease. This study also highlights broader social issues such as the stigma around liver disease that require careful consideration by policy makers when designing or implementing a liver screening programme. Conclusions The attributes and levels identified will inform future DCE surveys to understand consumer preferences for community screening programmes for liver disease. In addition, the outcomes will help inform the implementation of the LOCATE-NAFLD programme in real-world practice, and could be relevant for other liver and non-liver related chronic disease screening programmes.
Healthcare providers play a crucial role in the success of heart disease screening programs. However, screening for heart disease remains underutilized due to organizational barriers such as time constraints, user knowledge of the intervention, workforce constraints and turnover and availability of resources. Therefore, it is important to understand the preferences of healthcare providers on how to best integrate cardiac disease screening in routine practice.Five databases were systematically searched for studies that reported on healthcare providers' opinions, thoughts, and preferences on cardiac disease screening published between January 2013 and August 2023 were included. Thematic analysis was conducted to identify patterns and themes across included studies, and the quality of studies was assessed using the mixed methods appraisal tool.The initial search yielded 4624 articles, with 21 meeting the inclusion criteria. Included studies represented diverse healthcare settings and research methodologies. The identified themes were categorized into two overarching themes ‘screening preferences’ and ‘implementation of screening into practice’. Screening preferences included choice of screening device, frequency of screening, and screening population. The latter identified the crucial elements healthcare professionals prioritize when integrating screening procedures into their daily routines i.e., Change Management, Governance, Communication, Costs, and Infrastructure.Understanding their preferences and addressing organizational barriers are essential for effective implementation. By integrating their insights into practice, cardiac diseases can be detected early, optimizing patient outcomes and mitigate the burden of cardiac diseases on individuals and society.
Hand hygiene is the primary measure in hospitals to reduce the spread of infections, with nurses experiencing the greatest frequency of patient contact. The '5 critical moments' of hand hygiene initiative has been implemented in hospitals across Australia, accompanied by awareness-raising, staff training and auditing. The aim of this study was to understand the determinants of nurses' hand hygiene decisions, using an extension of a common health decision-making model, the theory of planned behaviour (TPB), to inform future health education strategies to increase compliance. Nurses from 50 Australian hospitals ( n = 2378) completed standard TPB measures (attitude, subjective norm, perceived behavioural control [PBC], intention) and the extended variables of group norm, risk perceptions (susceptibility, severity) and knowledge (subjective, objective) at Time 1, while a sub-sample ( n = 797) reported their hand hygiene behaviour 2 weeks later. Regression analyses identified subjective norm, PBC, group norm, subjective knowledge and risk susceptibility as the significant predictors of nurses' hand hygiene intentions, with intention and PBC predicting their compliance behaviour. Rather than targeting attitudes which are already very favourable among nurses, health education strategies should focus on normative influences and perceptions of control and risk in efforts to encourage hand hygiene adherence.
The effects of hepatitis C virus (HCV), such as morbidity and mortality associated with cirrhosis and liver cancer, is a major public health issue in Australia. Highly effective treatment has recently been made available to all Australians living with HCV. A decision-analytic model was developed to evaluate the cost-effectiveness of the hepatology partnership, compared to usual care. A Markov model was chosen, as it is state-based and able to include recursive events, which accurately reflects the natural history of the chronic and repetitive nature of HCV. Cost-effectiveness of the new model of care is indicated by the incremental cost-effectiveness ratio (ICER), where the mean change to costs associated with the new model of care is divided by the mean change in quality adjusted life-years (QALYs). Ten thousand iterations of the model were run, with the majority (73%) of ICERs representing cost-savings. In comparison to usual care, the intervention improves health outcomes (22.38 QALYs gained) and reduces costs by $42,122 per patient. When compared to usual care, a partnership approach to management of HCV is cost-effective and good value for money, even when key model parameters are changed in scenario analyses. Reduction in costs is driven by improved efficiency of the new model of care, where more patients are treated in a timely manner, away from the expensive tertiary setting. From an economic perspective, a reduction in hospital-based care is a positive outcome and represents a good investment for decision-makers who wish to maximise health gain per dollar spent.
Health-related quality-of-life measurements are important to understand lived experiences of patients who have cirrhosis. These measures also inform economic evaluations by modelling quality-adjusted life years (QALYs). We aimed to describe health-related quality of life, specifically multiattribute utility (scale anchors of death = 0.00 and full health = 1.00), across various stages and etiologies of cirrhosis.Face-to-face interviews were used to collect Short Form 36 (SF-36) questionnaire responses from CirCare study participants with cirrhosis (June 2017 to December 2018). The severity of cirrhosis was assessed using the Child-Pugh score classified as class A (5-6 points), B (7-9), or C (10-15) and by the absence ("compensated") versus presence ("decompensated") of cirrhosis-related complications.Patients (n = 562, average 59.8 years [SD = 11.0], male 69.9%) had a range of primary etiologies (alcohol-related 35.2%, chronic hepatitis C 25.4%, non-alcoholic fatty liver disease (NAFLD) 25.1%, chronic hepatitis B 5.9%, "other" 8.4%). Significantly lower (all P < 0.001) mean multiattribute utility was observed in the health states of patients with decompensated (mean = 0.62, SD = 0.15) versus compensated cirrhosis (mean = 0.68, SD = 0.12), Child-Pugh class C (mean = 0.59, SD = 0.15) or B (mean = 0.63, SD = 0.15) versus A (mean = 0.68, SD = 0.16), and between those of working age (18-64 years; mean = 0.64, SD = 0.16) versus those aged 65+ years (mean = 0.70, SD = 0.16). The greatest decrements in health-related quality of life relative to Australian population norms were observed across physical SF-36 domains.Persons with more advanced cirrhosis report greater life impacts. Estimates from this study are suitable for informing economic evaluations, particularly cost-utility modelling, which captures the benefits of effective prevention, surveillance, and treatments on both the quality and quantity of patients' lives.
The term 'economic determinants of health and disease' is often assumed to mean the association between increasing wealth and better health. However, examining the concept in detail provides opportunities to understand how economics can inform decisions that address inequities. Decisions need to be made about how to spend resources to address all types of inequities, not only access to healthcare, and thus maximise the welfare of society. Economics seeks to understand the choices made by people, governments and other organisations, and uses this information to predict the effect of intervention. As the focus of economics is on the welfare society, there is an inextricable link between the social and economic determinants of health...
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)