Efficiency in hospitals owned by the Iranian Social Security Organisation: measurement, determinants, and remedial actions.

Given the need to ensure the best use of scarce resources, increasing emphasis is being placed on hospital efficiency measurement. In the literature about hospital efficiency measurement, there is an absence of a well-defined framework to select the most appropriate set of input and output variables. Variables used in hospital efficiency studies predominantly reflect a narrow view of hospital functions with a little attention to quality variables. This implies that the hospital goal and its full range of functions in efficiency measurement are poorly understood. While numerous studies have been undertaken in developed countries, there have been only a few attempts at measuring hospital efficiency in developing countries. However, there has so far been no systematic attempt, using frontier-based techniques, to measure the efficiency of Iranian hospitals, and to identify factors affecting efficiency and remedial actions to improve efficiency. By focusing on the above two issues, this thesis makes three arguments. First, by undertaking an in-depth investigation regarding the multi-product nature of hospitals, considering a fuller range of hospital functions, and the values of various stakeholders including patient, staff, and community, this study has proposed a health-oriented framework with a focus on the Iranian hospitals to select the most appropriate variables for measuring hospital efficiency. I argue that both variables (existing in the literature, and discussed for addition) should be taken into account in order to enhance the validity of hospital efficiency studies. Second, two types of techniques (simple ratio analysis and data envelopment analysis) were used for measuring the technical efficiency of hospitals owned by the Iranian Social Security Organization (SSO). The benefits and shortcomings of each method were discussed. For example, considering major surgery rates, which implicitly provide information about the case-mix, has revealed that all high-turnover, high-occupancy outlying hospitals as well as the majority of hospitals falling in the relatively well-performing quadrant in the Lasso diagram had a low major surgery rate. This suggests that simple ratio analysis can only measure the performance of hospitals over a single dimension ignoring their multi-input and multi-output nature of hospitals. Using Data Envelopment Analysis (DEA), I measured technical efficiency, scale efficiency, and types of returns to scale for the SSO hospitals. In addition to studying their overall and relative efficiency, I analysed the magnitude of the inefficiency for each individual hospital. The results revealed that 22 of the 53 hospitals were deemed to be efficient. Inefficient hospitals had an average score of 78%, implying a potential reduction in all inputs on average by about 22% with no impact on output levels. The comparison of DEA results and simple ratio analysis has revealed that hospitals with an exceptional performance on individual variable even though less valuable compared with other variables can gain a full efficiency score. This critical analysis of the study strongly suggests that the findings obtained from unconstrained DEA should be interpreted with caution. Finally, in addition to simply measuring efficiency, it was felt that a better understanding of the factors affecting hospital efficiency and remedial actions to improve efficiency is needed. Using qualitative methods, a complex mix of organisational factors such as hospital financing, political influences such as political pressures in determining hospital location, and the training and experience of the managers were argued to be influential factors in hospital efficiency. The interviews also provided a great insight into remedial actions such as reforms in the regulatory framework and corporatization.Thesis (Ph.D) -- University of Adelaide, School of Population Health and Clinical Practice, 200

Model structuring for economic evaluations of new health technologies

In countries such as Australia, the UK and Canada, decisions on whether to fund new health technologies are commonly informed by decision analytic models. While the impact of making inappropriate structural choices/assumptions on model predictions is well noted, there is a lack of clarity about the definition of key structural aspects, the process of developing model structure (including the development of conceptual models) and uncertainty associated with the structuring process (structural uncertainty) in guidelines developed by national funding bodies. This forms the focus of this paper. Building on the reports of good modelling practice, and recognising the fundamental role of model structuring within the model development process, we specified key structural choices and provided ideas about the model structuring process for the future direction. This will help to further standardise guidelines developed by national funding bodies, with potential impact on transparency, comprehensiveness and consistency of model structuring. We argue that the process of model structuring and structural sensitivity analysis should be documented in a more systematic and transparent way in submissions to national funding bodies. Within the decision-making process, the development of conceptual models and presentation of all key structural choices would mean that national funding bodies could be more confident of maximising value for money when making public funding decision

Development and validation of an individual-based state-transition model for the prediction of frailty and frailty-related events

Frailty is a biological syndrome that is associated with increased risks of morbidity and mortality. To assess the value of interventions to prevent or manage frailty, all important impacts on costs and outcomes should be estimated. The aim of this study is to describe the development and validation of an individual-based state transition model that predicts the incidence and progression of frailty and frailty-related events over the remaining lifetime of older Australians. An individual-based state transition simulation model comprising integrated sub models that represent the occurrence of seven events (mortality, hip fracture, falls, admission to hospital, delirium, physical disability, and transitioning to residential care) was developed. The initial parameterisation used data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The model was then calibrated for an Australian population using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The simulation model established internal validity with respect to predicting outcomes at 24 months for the SHARE population. Calibration was required to predict longer terms outcomes at 48 months in the SHARE and HILDA data. Using probabilistic calibration methods, over 1,000 sampled sets of input parameter met the convergence criteria across six external calibration targets. The developed model provides a tool for predicting frailty and frailty-related events in a representative community dwelling Australian population aged over 65 years and provides the basis for economic evaluation of frailty-focussed interventions. Calibration to outcomes observed over an extended time horizon would improve model validity

Adolescent values for immunisation programs in Australia: A discrete choice experiment.

The importance of adolescent engagement in health decisions and public health programs such as immunisation is becoming increasingly recognised. Understanding adolescent preferences and further identifying barriers and facilitators for immunisation acceptance is critical to the success of adolescent immunisation programs. This study applied a discrete choice experiment (DCE) to assess vaccination preferences in adolescents.This study was conducted as a cross-sectional, national online survey in Australian adolescents. The DCE survey evaluated adolescent vaccination preferences. Six attributes were assessed including disease severity, target for protection, price, location of vaccination provision, potential side effects and vaccine delivery method. A mixed logit model was used to analyse DCE data.This survey was conducted between December 2014 and January 2015. Of 800 adolescents aged 15 to 19 years, stronger preferences were observed overall for: vaccination in the case of a life threatening illness (p<0.001), lower price vaccinations (p<0.001), mild but common side effects (p = 0.004), delivery via a skin patch (p<0.001) and being administered by a family practitioner (p<0.001). Participants suggested that they and their families would be willing to pay AU$394.28 (95$348.40 to AU$446.92) more for a vaccine targeting a life threatening illness than a mild-moderate illness, AU$37.94 (95%CI: AU$19.22 to AU$57.39) more for being vaccinated at a family practitioner clinic than a council immunisation clinic, AU$23.01 (95$7.12 to AU$39.24) more for common but mild and resolving side effects compared to rare but serious side effects, and AU$51.80 (95%CI: AU$30.42 to AU$73.70) more for delivery via a skin patch than injection.Consideration of adolescent preferences may result in improved acceptance of, engagement in and uptake of immunisation programs targeted for this age group