ABSTRACT
Using a discrete-event simulation (DES) model, the current disaster plan regarding the allocation of multiple injured patients from a mass casualty incident was evaluated for an acute specialty hospital in Vienna, Austria. With the current resources available, the results showed that the number of severely injured patients currently assigned might have to wait longer than the medically justifiable limit for lifesaving surgery. Furthermore, policy scenarios of increasing staff and/or equipment did not lead to a sufficient improvement of this outcome measure. However, the mean target waiting time for critical treatment of moderately injured patients could be met under all policy scenarios. Using simulation-optimization, an optimal staff-mix could be found for an illustrative policy scenario. In addition, a multiple regression model of simulated staff-mix policy scenarios identified staff categories (number of radiologists and rotation physicians) with the highest impact on waiting time and survival. In the short term, the current hospital disaster plan should consider reducing the number of severely injured patients to be treated. In the long term, we would recommend expanding hospital capacity-in terms of both structural and human resources as well as improving regional disaster planning. Policymakers should also consider the limitations of this study when applying these insights to different areas or circumstances.
ABSTRACT
Health care systems need to be resilient to deal with disasters like the global spread of the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) on top of serving the changing needs of a multi-morbid, ageing and often dispersed population. This paper identifies, discusses and augments critical dimensions of resilience retrieved from the academic literature. It pulls together an integrated concept of resilience characterised by organisational capabilities. Our concept does not focus on the micro-level like most resilience literature in health care but addresses the system level with many stakeholders involved. Distinguishing exogenous shocks to the health care system into adverse events and planned innovations provides the basis for our conclusions and insights. It becomes apparent only when dealing with planned interventions that transformative capabilities are indispensable to cope with sudden increases in health care pressures. Due to the current focus on absorptive and adaptive resilience, organisations over-rely on management capabilities that cannot generate a lasting increase in functionality. Therefore, reducing the resilience discussion to bouncing back from adverse events could deceive organisations into cultivating a suboptimal mix of organisational capabilities lacking transformative capabilities, which pave the way for a structural change that aims at a sustainably higher functionality.
ABSTRACT
We investigated the benefit of a 6-week ambulant psychiatric rehabilitation program in an ambulant psychiatric rehabilitation clinic in Vienna, Austria, from January 2014 to December 2016 by an uncontrolled repeated measures study. The potential of this intervention program was assessed by effectiveness and cost measures using suitable statistical analyses. We compared the effectiveness and cost measures of this ambulant psychiatric rehabilitation program on patients for the period of up to 12 months after discharge to the period of 12 months before admission to the intervention program based on self-reported catamnesis questionnaires. For the program's effectiveness measures, we accounted for both psychological indices for measuring depression severity, symptom burden, and functioning to document the health improvement of patients and economy-related indices such as the number of sick leave days for patients. For the program's cost measures, both direct tangible treatment and medication costs and indirect tangible costs based on the productivity loss measured in non-working days of the patients were considered. The results significantly demonstrated that all psychological effectiveness measures for the patients highly improved by the 6-weeks rehabilitation program and remained rather stable 12 months after discharge. We found that costs for the 6-week ambulant psychiatric rehabilitation program could be easily covered within 12 months after discharge once a total societal cost perspective was considered. Even additional total cost savings of up to over 5000 Euro could be achieved which were highest for employed patients, followed by unemployed patients receiving rehabilitation allowance due to both their high direct medication and treatment costs as well as high indirect costs for productivity loss. The most important finding was that this treatment program was especially beneficial for rehabilitation patients in earlier stages of psychiatric diseases who were still employed, indicating the need for early intervention in mental disorder.
ABSTRACT
This articles provides a short summary of the research topics and latest research results of the European Working Group "Operations Research Applied to Health Services" (ORAHS) organized as an e-conference in Juli 2020 at the University of Vienna, Austria (https://orahs2020.univie.ac.at/). Furthermore, challenges for OR in health care including application areas, decision support systems, general trends, and modelling techniques are briefly illustrated from an European and international perspective by providing selected essential literature reviews.
Subject(s)
COVID-19/therapy , Delivery of Health Care , Disease Management , Health Planning , Pneumonia, Viral/therapy , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Testing , Comorbidity , Humans , Mental Disorders/therapy , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/virology , SARS-CoV-2 , TelemedicineABSTRACT
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.
Subject(s)
Ambulances/organization & administration , Decision Making , Disaster Planning/organization & administration , Mass Casualty Incidents , Ambulances/supply & distribution , Computer Simulation , Decision Support Techniques , Disaster Planning/methods , Health Care Rationing/organization & administration , Health Status , Humans , Triage/organization & administrationABSTRACT
Diabetes mellitus affects approximately 171 million individuals worldwide. The costs of the adult form of diabetic mellitus account for up to 6% of total health care expenditures in industrialized countries. About 25% of these diabetics develop disabling and most painful foot complications accounting for about 17% of the direct lifetime costs. Diabetic foot prevention programs have been recently introduced in some Austrian federal states to meet the diabetic health targets of the Austrian Health Plan and the St. Vincent Declaration. We developed a new age-group specific Markov model combined with a Monte Carlo simulation model to help policymakers analyze the cost-effectiveness of such programs compared to the status quo in terms of incremental costs per quality-adjusted life years gained (QALY). The Markov model revealed that diabetic foot prevention programs were cost saving when targeted at patients at high risk and mainly cost-effective when targeted at patients with mild symptoms. The Monte Carlo simulation showed that only large scope prevention programs would fulfill the specified reductions in the number of diabetic foot complications as defined in the Austrian Health Plan and the St. Vincent Declaration. Our results clearly indicate the enormous impact of diabetic foot prevention programs.
Subject(s)
Cost-Benefit Analysis , Diabetes Mellitus/epidemiology , Diabetic Foot/prevention & control , Adult , Aged , Austria/epidemiology , Diabetes Complications , Diabetes Mellitus/economics , Female , Health Care Costs/statistics & numerical data , Humans , Male , Markov Chains , Middle Aged , Monte Carlo Method , Quality-Adjusted Life YearsABSTRACT
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.
Subject(s)
Length of Stay/statistics & numerical data , National Health Programs/economics , Patient Admission/economics , Patient Discharge/economics , Austria , Budgets , Canada , Economics, Hospital , Financing, Government , Health Policy , Length of Stay/economics , Organizational Policy , Time FactorsABSTRACT
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.