Marion S. Rauner

An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria

Abstract To the best of our knowledge, this paper describes the first ant colony optimization (ACO) approach applied to nurse scheduling, analyzing a dynamic regional problem which is currently under discussion at the Vienna hospital compound. Each day, pool nurses have to be assigned for the following days to public hospitals while taking into account a variety of soft and hard constraints regarding working date and time, working patterns, nurses qualifications, nurses’ and hospitals’ preferences, as well as costs. Extensive computational experiments based on a four week simulation period were used to evaluate three different scenarios varying the number of nurses and hospitals for six different hospitals’ demand intensities. The results of our simulations and optimizations reveal that the proposed ACO algorithm achieves highly significant improvements compared to a greedy assignment algorithm.

Use of discrete-event simulation to evaluate strategies for the prevention of mother-to-child transmission of HIV in developing countries

HIV/AIDS affects over 40 million people worldwide, and more than 70% of these people live in Africa. Mother-to-child transmission of HIV accounts for over 90% of all HIV infections in children under the age of 15 years. However, implementing HIV prevention policies in Africa is extremely difficult because of the poor medical and socio-economic infrastructure. In this paper, we present a discrete-event simulation model that evaluates the relative benefits of two potentially affordable interventions aimed at preventing mother-to-child transmission of HIV, namely anti-retroviral treatment at childbirth and/or bottlefeeding strategies. The model uses rural Tanzanian data and compares different treatment policies. Our results demonstrate that strategic guidelines about breastfeeding are highly dependent on the assumed increase in infant mortality due to bottlefeeding, the efficacy of anti-retroviral treatment at childbirth, and the maternal health stage. The cost of averted infections, though low by Western standards, may represent significant obstacles to policy implementation in developing countries.

Combined Discrete-event Simulation and Ant Colony Optimisation Approach for Selecting Optimal Screening Policies for Diabetic Retinopathy

In this paper we present the first application to a healthcare problem of discrete-event simulation (DES) embedded in an ant colony optimisation (ACO) model. We are concerned with choosing optimal screening policies for retinopathy, a sight-threatening complication of diabetes. The early signs of retinopathy can be detected by screening before the patient is aware of symptoms, and blindness prevented by laser treatment. In this paper we describe the methodology used to combine the purpose-written DES model with the ACO algorithm. We simulate the effects of different screening strategies on a population of diabetic patients, and compare them in terms of two objective functions: Min C/E, cost-effectiveness (minimum incremental cost per year of sight saved, compared with a no-screening baseline) and Max E, maximum effectiveness (years of sight saved). We describe how ACO is used to optimise these two objectives, and discuss the issues involved in optimising stochastic variables. We present results for a range of different assumptions and scenarios about the format of screening programmes, using realistic data, and make policy recommendations on the basis of our findings.

The effect of funding policy on day of week admissions and discharges in hospitals: the cases of Austria and Canada.

This paper compares two different funding policies for inpatients, the case-based approach in Austria versus the global budgeting approach in Canada. It examines the impact of these funding policies on length of stay of inpatients as one key measure of health outcome. In our study, six major clinical categories for inpatients are selected in which the day of the week for admission is matched to the particular day of the week of discharge for each individual case. The strategic statistical analysis proves that funding policies have a significant impact on the expected length of stay of inpatients. For all six clinical categories, Austrian inpatients stayed longer in hospitals compared to Canadian inpatients. Moreover, inpatients were not admitted and discharged equally throughout the week. We also statistically prove for certain clinical categories that more inpatients are discharged on certain days such as Mondays or Fridays depending on the funding policy. Our study is unique in the literature and our conclusions indicate that, with the right incentives in place, the length of stay can be decreased and discharge anomalies can be eliminated, which ultimately leads to a decrease in healthcare expenditures and an increase in healthcare effectiveness.

Using Simulation for AIDS Policy Modeling: Benefits for HIV/AIDS Prevention Policy Makers in Vienna, Austria

In spite of advanced therapies and the success of additional prevention programs, the HIV/AIDS epidemic still remains a challenge. Our paper refers academics, health care managers, and policy makers to the relevance of AIDS policy simulators in better decision-making. By highlighting the types of decisions AIDS policy models can support, we demonstrate the strategic role of AIDS policy simulators for the efficient and effective planning of scarce resources to fight the epidemic. For each type of decision, we then review exemplary AIDS policy simulators that have helped policy makers make better decisions. Finally, we present the benefits of an AIDS policy simulator for HIV/AIDS prevention policy makers in Vienna, Austria.

AIDS policy modeling for the 21st century: an overview of key issues.

Decisions about HIV prevention and treatment programs are based on factors such as program costs and health benefits, social and ethical issues, and political considerations. AIDS policy models – that is, models that evaluate the monetary and non-monetary consequences of decisions about HIV/AIDS interventions – can play a role in helping policy makers make better decisions. This paper provides an overview of the key issues related to developing useful AIDS policy models. We highlight issues of importance for researchers in the field of AIDS policy modeling as well as for policy makers. These include geographic area, setting, target groups, interventions, affordability and effectiveness of interventions, type and time horizon of policy model, and type of economic analysis. This paper is not intended to be an exhaustive review of the AIDS policy modeling literature, although many papers from the literature are discussed as examples; rather, we aim to convey the composition, achievements, and challenges of AIDS policy modeling.

Resource planning for ambulance services in mass casualty incidents: a DES-based policy model

Due to an increasing number of mass casualty incidents, which are generally complex and unique in nature, we suggest that decision makers consider operations research-based policy models to help prepare emergency staff for improved planning and scheduling at the emergency site. We thus develop a discrete-event simulation policy model, which is currently being applied by disaster-responsive ambulance services in Austria. By evaluating realistic scenarios, our policy model is shown to enhance the scheduling and outcomes at operative and online levels. The proposed scenarios range from small, simple, and urban to rather large, complex, remote mass casualty emergencies. Furthermore, the organization of an advanced medical post can be improved on a strategic level to increase rescue quality, including enhanced survival of injured victims. In particular, we consider a realistic mass casualty incident at a brewery relative to other exemplary disasters. Based on a variety of such situations, we derive general policy implications at both the macro (e.g., strategic rescue policy) and micro (e.g., operative and online scheduling strategies at the emergency site) levels.

Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies

We present a risk-group oriented chronic disease progression model embedded within a metaheuristic-based optimization of the policy variables. Policy-makers are provided with Pareto-optimal screening schedules for risk groups by considering cost and effectiveness outcomes as well as budget constraints. The quality of the screening technology depends on risk group, disease stage, and time. As the metaheuristic solution technique, we use the Pareto ant colony optimization (P-ACO) algorithm for multiobjective combinatorial optimization problems, which is based on the ant colony optimization paradigm. Our approach is illustrated by a numerical example for breast cancer. For a 10-year time horizon, we provide cost-effective screening schedules for selected annual and total budgets. We then discuss policy implications of 16 mammography screening scenarios varying the screening schedule (annual, biennial, triennial, quadrennial) and the rate of women tested (25%, 50%, 75%, 100%). Due to the models flexible structure, interventions for multiple chronic diseases can be considered simultaneously.

How many AEDs in which region? An economic decision model for the Austrian Red Cross

Abstract We developed an innovative decision model combined with an integer programming model to analyse the cost-effectiveness of semi-automated early defibrillators (AEDs) for the Austrian Red Cross. To estimate the costs of this intervention per quality-adjusted life-year (QALY) gained, we calculated the acquisition and maintenance costs of defibrillators, training costs for emergency medical technicians, hospitalisation costs for patients with sudden cardiac arrest and future health care costs for surviving patients discharged from a hospital as well as the improved survival and quality-of-life benefits from the use of AEDs. AED programmes produced cost-effectiveness ratios of less than 55,000 Euro per QALY over a wide range of assumptions regarding uncertain parameters in the analysis. The AED costs for a full AED programme would amount to a maximum of approximately 10.3 million Euro for the Red Cross. The first step would be to equip ambulances in rural areas, then in urban areas and finally in Vienna.

Impact of the new Austrian inpatient payment strategy on hospital behavior: a system-dynamics model

Abstract In Austria, a new performance-oriented reimbursement system for inpatients was introduced in 1997. The system is aimed at implementing a more effective and efficient health care payment strategy that will contain costs. It reverses reimbursement on a per inpatient per day basis resulting in a cost explosion that has exceeded the limits of the overall health care budget. This paper presents a strategic system-dynamics model that analyzes the impact of the new payment system on hospitals’ reimbursement maximization behavior. Empirical findings support the results of our models ability to determine future adaptations of the system.