A new approach to optimal selection of services in health care organizations.

A new reimbursement policy adopted by Medicare in 1983 caused financial difficulties for many hospitals and health care organizations. Several organizations responded to these difficulties by developing systems to carefully measure their costs of providing services. The purpose of such systems was to provide relevant information about the profitability of hospital services. This paper presents a new method of making hospital service selection decisions: it is based on an optimization model that avoids arbitrary cost allocations as a basis for computing the costs of offering a given service. The new method provides more reliable information about which services are profitable or unprofitable, and it provides an accurate measure of the degree to which a service is profitable or unprofitable. The new method also provides useful information about the sensitivity of the optimal decision to changes in costs and revenues. Specialized algorithms for the optimization model lead to very efficient implementation of the method, even for the largest health care organizations.     

Predicting workload requirements for scheduled health care services, with an application to radiology departments.

A model is developed for predicting workload requirements for scheduled health care services. The model is then applied to an actual planning problem for a radiology department. The probability distribution of future workload is represented by the convolution of two families of random variables such that a compound Poisson process adequately describes workload requirements. The model developed herein can be applied to a wide assortment of capacity-expansion problems that are characterized by discrete demands (e.g. number of jobs) occurring in a given period of time, where the amount of time needed to complete each job is a continuous random variable.     

A quantitative index of access to primary medical care for health planning

The emphasis of Public Law 93–641 on numerical goals of health care, as elaborated upon by the National Health Planning Council in its guidelines, foreshadows the emergence of quantitative indices in many areas of health resources utilization and health outcomes. In the area of access to primary medical care, the guidelines spell out in detail what is considered the reasonable waiting period for an appointment, travelling time to the source of care, and in-office waiting time for individuals seeking care. An index of access is developed on the basis of these reasonable limits of waiting for health services research and planning purposes. An example of hypothesis-testing with hypothetical data is given, along with a caveat in the interpretation of the results.     

A quasi-negative binomial regression with an application to medical care data

Quality & Quantity - This paper introduced a Quasi-Negative Binomial Regression as an extension of Quasi-Negative Binomial to handle response count datasets modulated with covariates. In some...     

Efficient approach to health care industry material resource management: an empirical research

The feasibility of JIT implementation in the health care industry was examined through in-depth case studies and survey research. Specifically, this research examined two different groups in the health care industry: health care institutions that have introduced JIT philosophy into their operations and those that have not. Based on this classification, the research reveals the different impacts that the introduction of JIT philosophy has had on the health care industry's inventory management, service quality, and competitiveness. According to the research result, the introduction of the JIT philosophy in the health care industry's material management system improved that system and reduced implementation problems even though the differences between the JH and the NJH were not high. However, this research found that great potentials exist for the successful implementation of JIT philosophy for material management even though most of the JIT in the health care industry is still in its early stages. Moreover, with the maturing of the stockless material management system, differences between the JH and the NJH groups will be even more significant.     

Aggregate nursing requirement planning in a public health care delivery system.

In this paper, we present an aggregate nursing requirement planning model for inpatient services to provide inputs for preparing yearly budgets in a public health care delivery system. A forecasting system using autoregressive integrated moving average time-series models forms the basis of project demands for nursing hours by medical specialities. These projections along with the institutional constraints and patient care requirements are all incorporated in a linear programming model for assessing needs for permanent staff, overtime pay and contracting temporary help—by medical service, nursing skill level and time period (month). We also expand the model to evaluate the sizing of a pool of float nurses. The model is developed within the framework of routine managerial planning process of the system under study (vis-à vis, the data base and the organizational structure). Historical data are used to estimate input parameters for the model. The staffing needs generated from the model for 1978 are compared with the actual system performance.     

A non-linear filtering approach to stochastic volatility models with an application to daily stock returns

This paper develops a new model for the analysis of stochastic volatility (SV) models. Since volatility is a latent variable in SV models, it is difficult to evaluate the exact likelihood. In this paper, a non-linear filter which yields the exact likelihood of SV models is employed. Solving a series of integrals in this filter by piecewise linear approximations with randomly chosen nodes produces the likelihood, which is maximized to obtain estimates of the SV parameters. A smoothing algorithm for volatility estimation is also constructed. Monte Carlo experiments show that the method performs well with respect to both parameter estimates and volatility estimates. We illustrate our model by analysing daily stock returns on the Tokyo Stock Exchange. Since the method can be applied to more general models, the SV model is extended so that several characteristics of daily stock returns are allowed, and this more general model is also estimated. Copyright © 1999 John Wiley & Sons, Ltd.     

A simplified approach to M-estimation with application to two-stage estimators

This paper presents a simple version of the theory of M-estimation. It is argued that the theory is immediately applicable to almost all estimation schemes employed by econometricians. It is further argued that the great overlooked benefit of the theory is that is provides almost automatic asymptotic results, e.g., probability limits and asymptotic covariances. Thus one need not be a theoretical econometrician to invent and use specially tailored estimators. To illustrate its use the theory is applied to a variety of theoretical and applied problems. Particular attention is paid to two-stage estimators.     

A flexible parametric selection model for non‐normal data with application to health care usage

I examine the effects of insurance status and managed care on hospitalization spells, and develop a new approach for sample selection problems in parametric duration models. MLE of the Flexible Parametric Selection (FPS) model does not require numerical integration or simulation techniques. I discuss application to the exponential, Weibull, log‐logistic and gamma duration models. Applying the model to the hospitalization data indicates that the FPS model may be preferred even in cases in which other parametric approaches are available. Copyright © 2002 John Wiley & Sons, Ltd.     

A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation

This paper presents a Bayesian approach to bandwidth selection for multivariate kernel regression. A Monte Carlo study shows that under the average squared error criterion, the Bayesian bandwidth selector is comparable to the cross-validation method and clearly outperforms the bootstrapping and rule-of-thumb bandwidth selectors. The Bayesian bandwidth selector is applied to a multivariate kernel regression model that is often used to estimate the state-price density of Arrow–Debreu securities with the S&P 500 index options data and the DAX index options data. The proposed Bayesian bandwidth selector represents a data-driven solution to the problem of choosing bandwidths for the multivariate kernel regression involved in the nonparametric estimation of the state-price density pioneered by Aït-Sahalia and Lo [Aït-Sahalia, Y., Lo, A.W., 1998. Nonparametric estimation of state-price densities implicit in financial asset prices. The Journal of Finance, 53, 499, 547.]     

纽约平价房：一房难求

62岁的Jean　Mirra和丈夫申请到了纽约皇后区一幢平价楼一套一室一厅的公寓，前不久刚刚搬进去。     

A multilevel structural equation modelling approach to study segregation of deprivation: an application to Bolivia

Quality & Quantity - The study of segregation of deprivation can provide a tool to determine the economic, social and institutional factors associated with spatial unevenness in the...     

An analysis of the cost of providing ancillary services to skilled nursing facility patients in New York State

Currently, nursing homes can arrange for the provision of ancillary services either by providing the services directly, purchasing the services through contracts and fees, or by outside billings, in which the services are supplied by other providers who then bill Medicaid directly. Frequently, some combination of these three modes of provision is used for each ancillary service. The purpose of this study is to explore ancillary costs in a sample of nursing homes and to determine, to the extent possible, the most cost-efficient means of providing selected ancillary services (physical therapy, radiology and medical staff services). Prior to examining the impact of the mode of provision on cost levels, other facility and patient characteristics that might justifiably affect costs are identified and adjusted for. The results demonstrate that outside billing or purchasing services can be much less expensive than providing the services directly. It is suggested that all ancillary services (outside billings as well as services provided directly through contracts and fees) be included when facility-to-facility cost comparisons are made. This approach should serve as an incentive for nursing homes to seek the most cost-efficient means of providing ancillary services.     

Latent variable models for time series: A frequency domain approach with an application to the permanent income hypothesis

The theory of estimation and inference in a very general class of latent variable models for time series is developed by showing that the distribution theory for the finite Fourier transform of the observable variables in latent variable models for time series is isomorphic to that for the observable variables themselves in classical latent variable models. This implies that analytic work on classical latent variable models can be adapted to latent variable models for time series, an implication which is illustrated here in the context of a general canonical form. To provide an empirical example a latent variable model for permanent income is developed, its parameters are shown to be identified, and a variety of restrictions on these parameters implied by the permanent income hypothesis are tested.     

Bayesian analysis of the two‐part model with endogeneity: application to health care expenditure

This paper studies the effect of managed care on medical expenditure using a model in which the insurance status is assumed to be endogenous. Insurance plan choice is modeled through the multinomial probit model. The medical expenditure variable, the outcome of interest, has a significant proportion of zeros that are handled using the two‐part model, extended to handle endogenous insurance. The estimation approach is Bayesian, based on the Gibbs Sampler. The model is applied to a sample of 20 460 individuals obtained from the Medical Expenditure Panel Survey. The results provide substantial evidence of selectivity. Copyright © 2006 John Wiley & Sons, Ltd.     

A lemma on relative stability with an application to an economic case study

In the existing literature relative stability of trajectories is obtained under particular assumptions. In this paper a lemma is stated which provides a technique to prove relative stability in most general cases. Such a technique permits to replace the study of the stability of a balanced growth path by the study of the stability of a fixed point for an associated function. The lemma is applied to a case study, which could not be treated by means of usual techniques.