Empirical research evaluating non-traditional approaches to managing sleep problems in children with autism.

OBJECTIVE: This paper examines the efficacy of non-behavioural and non-pharmacological approaches to the treatment of sleep disturbance in individuals with autism spectrum disorder. METHODS: A systematic search of electronic databases and reference lists identified eight studies that met inclusion criteria. Studies were evaluated according to (a) treatment used, (b) participants, (c) experimental design, (d) baseline measures, (e) dependent variables, (f) follow-up measures, (g) reliability and treatment integrity, (h) results and certainty of evidence and (i) implications for treatment. RESULTS: Positive outcomes were reported for the use of massage therapy and vitamin supplements. Aromatherapy was reported to have no effect on sleep. No studies were found that examined other non-traditional treatment approaches, nor did any of the studies provide conclusive evidence. CONCLUSIONS: The limited corpus of evidence and the methodological limitations suggests that the efficacy of non-traditional approaches to treatment of sleep problems in individuals with autism is yet to be demonstrated.

DVT surveillance program in the ICU: analysis of cost-effectiveness.

BACKGROUND: Venous Thrombo-embolism (VTE--Deep venous thrombosis (DVT) and/or pulmonary embolism (PE)--in traumatized patients causes significant morbidity and mortality. The current study evaluates the effectiveness of DVT surveillance in reducing PE, and performs a cost-effectiveness analysis. METHODS: All traumatized patients admitted to the adult ICU underwent twice weekly DVT surveillance by bilateral lower extremity venous Duplex examination (48-month surveillance period--SP). The rates of DVT and PE were recorded and compared to the rates observed in the 36-month pre-surveillance period (PSP). All patients in both periods received mechanical and pharmacologic prophylaxis unless contraindicated. Total costs--diagnostic, therapeutic and surveillance--for both periods were recorded and the incremental cost for each Quality Adjusted Life Year (QALY) gained was calculated. RESULTS: 4234 patients were eligible (PSP--1422 and SP--2812). Rate of DVT in SP (2.8%) was significantly higher than in PSP (1.3%) - p<0.05, and rate of PE in SP (0.7%) was significantly lower than that in PSP (1.5%) - p<0.05. Logistic regression demonstrated that surveillance was an independent predictor of increased DVT detection (OR: 2.53 - CI: 1.462-4.378) and decreased PE incidence (OR: 0.487 - CI: 0.262-0.904). The incremental cost was $509,091/life saved in the base case, translating to $29,102/QALY gained. A sensitivity analysis over four of the parameters used in the model indicated that the incremental cost ranged from $18,661 to $48,821/QALY gained. CONCLUSIONS: Surveillance of traumatized ICU patients increases DVT detection and reduces PE incidence. Costs in terms of QALY gained compares favorably with other interventions accepted by society.

Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model.

Emergency medical services (EMS) provide life-saving care and hospital transport to patients with severe trauma or medical conditions. Severe weather events, such as snow events, may lead to adverse patient outcomes by increasing call volumes and service times. Adequate staffing levels during such weather events are critical for ensuring that patients receive timely care. To determine staffing levels that depend on weather, we propose a model that uses a discrete event simulation of a reliability model to identify minimum staffing levels that provide timely patient care, with regression used to provide the input parameters. The system is said to be reliable if there is a high degree of confidence that ambulances can immediately respond to a given proportion of patients (e.g., 99 %). Four weather scenarios capture varying levels of snow falling and snow on the ground. An innovative feature of our approach is that we evaluate the mitigating effects of different extrinsic response policies and intrinsic system adaptation. The models use data from Hanover County, Virginia to quantify how snow reduces EMS system reliability and necessitates increasing staffing levels. The model and its analysis can assist in EMS preparedness by providing a methodology to adjust staffing levels during weather events. A key observation is that when it is snowing, intrinsic system adaptation has similar effects on system reliability as one additional ambulance.

Adversarial risk analysis with incomplete information: a level-k approach.

This article proposes, develops, and illustrates the application of level-k game theory to adversarial risk analysis. Level-k reasoning, which assumes that players play strategically but have bounded rationality, is useful for operationalizing a Bayesian approach to adversarial risk analysis. It can be applied in a broad class of settings, including settings with asynchronous play and partial but incomplete revelation of early moves. Its computational and elicitation requirements are modest. We illustrate the approach with an application to a simple defend-attack model in which the defender's countermeasures are revealed with a probability less than one to the attacker before he decides on how or whether to attack.

Using simulation-optimization to construct screening strategies for cervical cancer.

Cervical cancer is the second most common cancer in women worldwide. Cervical screening is critical for preventing this type of cancer. Traditionally, screening strategies are evaluated from an economic point of view through cost-effectiveness analysis. However, cost-effectiveness analysis is typically performed on a limited number of de facto or predetermined screening policies. We develop a simulation-optimization model to determine the ages at which screening should be performed, resulting in dynamic, age-based screening policies. We consider three performance measures: cervical cancer incidence, the number of cervical cancer deaths, and the number of life years lost due to cervical cancer death. Using each performance measure, we compare our optimal, dynamic screening strategies to standard policies considered in the health screening literature that are static and predetermined. We also evaluate the anticipated impact of vaccinations for preventing cervical cancer. The strategies that are developed are compared to those used in practice or considered in the literature. The Centers for Disease Control and Prevention recommends one screening every 3 years, resulting in 14 scheduled lifetime screenings. Our dynamic screening strategies provide approximately the same health benefits as this but with four to six fewer scheduled screenings, depending on the performance measure considered. Our dynamic strategies also provide approximately the same health benefits as screening every 2 years, but with six to nine fewer scheduled screenings. The results suggest that dynamic, age-based cervical cancer screening policies offer substantial economic savings in order to offer the same health benefits as equally spaced screening strategies.

Evaluating emergency medical service performance measures.

The ultimate goal of emergency medical service systems is to save lives. However, most emergency medical service systems have performance measures for responding to 911 calls within a fixed timeframe (i.e., a response time threshold), rather than measures related to patient outcomes. These response time thresholds are used because they are easy to obtain and to understand. This paper proposes a methodology for evaluating the performance of response time thresholds in terms of resulting patient survival rates. A model that locates ambulances to optimize patient survival rates is used for base comparison. Results are illustrated using real-world data collected from Hanover County, Virginia. The results indicate that locating ambulances to maximize seven and eight min response time thresholds simultaneously maximize patient survival. Nine and 10 min response time thresholds result in more equitable patient outcomes, with improved patient survival rates in rural regions.

Efficient genetic algorithms using discretization scheduling.

In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling, or how to vary the discretization within the genetic algorithm in order to use the least amount of computation time for a solution of a desired quality. The effectiveness of discretization scheduling can be determined by comparing its computation time to the computation time of a GA using a constant discretization. There are three ingredients for the discretization scheduling: population sizing, estimated time for each function evaluation and predicted convergence time analysis. Idealized one- and two-dimensional experiments and an inverse groundwater application illustrate the computational savings to be achieved from using discretization scheduling.