Sequential and Simultaneous Decision Making for Optimizing Health Care Resource Flexibilities

Health care administrators commonly employ two types of resource flexibilities (demand upgrades and staffing flexibility) to efficiently coordinate two critical internal resources, nursing staff and beds, and an external resource (contract nurses) to satisfy stochastic patient demand. Under demand upgrades, when beds are unavailable for patients in a less acute unit, patients are upgraded to a more acute unit if space is available in that unit. Under staffing flexibility, nurses cross‐trained to work in more than one unit are used in addition to dedicated and contract nurses. Resource decisions (beds and staffing) can be made at a single point in time (simultaneous decision making) or at different points in time (sequential decision making). In this article, we address the following questions: for each flexibility configuration, under sequential and simultaneous decision making, what is the optimal resource level required to meet stochastic demand at minimum cost? Is one type of flexibility (e.g., demand upgrades) better than the other type of flexibility (e.g., staffing flexibility)? We use two‐stage stochastic programming to find optimal resource levels for two nonhomogeneous hospital units that face stochastic demand following a continuous, general distribution. We conduct a full‐factorial numerical experiment and find that the benefit of using staffing flexibility on average is greater than the benefit of using demand upgrades. However, the two types of flexibilities have a positive interaction effect and they complement each other. The type of flexibility and decision timing has an independent effect on system performance (capacity and staffing costs). The benefits of cross‐training can be largely realized even if beds and staffing levels have been determined prior to the establishment of a cross‐training initiative.     

Generalized Laplacian Distributions and Autoregressive Processes

Generalized Laplacian distribution is considered. A new distribution called geometric generalized Laplacian distribution is introduced and its properties are studied. First- and higher-order autoregressive processes with these stationary marginal distributions are developed and studied. Simulation studies are conducted and trajectories of the process are obtained for selected values of the parameters. Various areas of application of these models are discussed.     

Bimodal skew-symmetric normal distribution

ABSTRACT

We introduce a new parsimonious bimodal distribution, referred to as the bimodal skew-symmetric Normal (BSSN) distribution, which is potentially effective in capturing bimodality, excess kurtosis, and skewness. Explicit expressions for the moment-generating function, mean, variance, skewness, and excess kurtosis were derived. The shape properties of the proposed distribution were investigated in regard to skewness, kurtosis, and bimodality. Maximum likelihood estimation was considered and an expression for the observed information matrix was provided. Illustrative examples using medical and financial data as well as simulated data from a mixture of normal distributions were worked.     

Financial-Firm Production of Monetary Services: A Generalized Symmetric Baroett Variable-Profit-Function Approach

An alternative monetary-production model of financial firms is employed to investigate supply-side monetary aggregation. Financial firms are conceived to produce monetary services as outputs through financial intermediation. A new method for testing the existence of consistent monetary-output aggregates in financial firms' production technology is developed in terms of a multiproduct firm's variable profit function, and the method does not require homotheticity of the aggregator function. We use a generalized symmetric Barnett flexible functional form. That specification satisfies global curvature conditions and retains its flexibility under the null hypothesis of weak separability. Neither of those properties is possessed by other flexible functional forms.     

Dynamic Savings Decisions in Agricultural Environments With Incomplete Markets

We develop a methodology for examining savings behavior in rural areas of developing countries that explicitly incorporates the sequential decision process in agriculture. The approach is used to examine the relative importance of alternative forms of savings in the presence and absence of formal financial intermediaries. Our results, based on stage-specific panel data from Pakistan, provide evidence that the presence of financial intermediaries importantly influences the use of formal savings and transfers for income smoothing. We also find that there are significant biases in evaluations of the savings-income relationship that are inattentive to the within-year dynamics of agricultural production.     

Tukey-Type Distributions in the Context of Financial Data

Abstract

In one-parameter (θ) families, we were not aware of explicit hypothesis testing scenarios where maximal invariant statistics failed to distinguish the models. We start with a concrete example (Sec. 2.2) to highlight such a hypothesis testing problem involving markedly different models. In this problem, because of the absence of a nontrivial uniformly most powerful invariant (UMPI) test, we briefly suggest two approaches to test the hypothesis. The first resolution (Sec. 3.1) is frequentist in nature. It utilizes a weight function on the parameter space and compares “average” distributions obtained under the null and alternative models in the sense of Wald (1947 Wald , A. ( 1947 ). Sequential Analysis . New York : Wiley . [Google Scholar] 1950 Wald , A. ( 1950 ). Statistical Decision Functions . New York : Wiley . [Google Scholar]). In contrast, a fully Bayesian resolution (Sec. 3.2) is also included. The note ends with a series of other interesting examples involving one-parameter families where maximal invariant statistics fail to distinguish the hypothesized models. The examples include easy-to-construct families of probability models involving only a single location or scale parameter θ.     

Regression Properties for Asymmetric Generalized Scale Mixtures of Multivariate Gaussian Variables

Analytical properties of regression and the variance–covariance matrix of asymmetric generalized scale mixture of multivariate Gaussian variables are presented. The analysis includes an in-depth analytical investigation of the first two conditional moments of the mixing variable. Exact computable expressions for the prediction and the conditional variance are presented for the generalized hyperbolic distribution using the inversion theorem for Fourier transforms. An application to financial log returns is demonstrated via the classical Euler approximation. The methodology is illustrated by analyzing the regression of intraday log returns for CISCO against the corresponding data from S&P 500.     

Developing “A Framework for Planning U.S. Federal Statistics, 1978–1989”

The Statistical Policy Division of the Office of Management and Budget has the overall responsibility for the planning and coordination of U.S. government statistics. The present staff of the Statistical Policy Division is attempting, through an integrated publication entitled “A Framework for Planning U.S. Federal Statistics, 1978–1989,” to state its perspective on necessary developments in the coming years. This article illustrates the character of the Framework materials and outlines the process for public review and comment on this undertaking.     

The Planning Stage in Statistical Reasoning

An important step in the statistical problem-solving process is the selection of the appropriate statistical procedure for the real-world situation under analysis. A decision-tree term project has been found to be an effective teaching device to help MBA students understand this step. The project requires the students to construct a decision-tree structure, which, through a series of questions and responses, will lead from the statement of a statistical question to the appropriate sampling distribution to use in addressing the question.     

From Hospital to Home with NDIS Funded Support: Examining Participant Pathway Timeframes Against Discharge Expectations

ABSTRACT

For patients with disability who require funded supports to leave hospital, the introduction of the National Disability Insurance Scheme (NDIS) represents opportunity and challenges. At a time of major reform, timely and supported discharge is reliant on overcoming interface complexities. The purpose of this study was to examine the NDIS participant pathway timeframes against discharge expectations for hospitalised adults with spinal cord injury (SCI) or acquired brain injury (ABI) and interrogate delays for the two groups. Administrative data on 54 participants (ABI?=?18 and SCI?=?36) were analysed. Both groups experienced delays to discharge and significant variability in timeframes between NDIS pathway processes and extent of delays. Group differences were identified regarding inefficiencies across the continuum, with type of support a factor to investigate further. This study has uncovered critical points in the NDIS pathway that could impact discharge of participants and where collaboration and adaptive strategies could be targeted to improve processes.

IMPLICATIONS

• Ensuring the National Disability Insurance Scheme (NDIS) pathway operates effectively in the hospital setting is critical to the timely discharge of people with complex needs who require funded supports.

• Monitoring implementation of the NDIS in the health setting is important to avert interface problems that impede timely discharge and access.