Management information systems in health systems agencies: some considerations.

Relevant considerations for the application of Management Information Systems theory (MIS) to public agencies are identified and discussed in this paper. The importance of the agency's environment, both external and internal, reporting structure and personnel makeup is examined. A specific application of these considerations in an MIS developed for the Health Systems Agency of Western New York is presented. Finally, the paper considers the importance of system implementation as well as system design.     

A goal programming model for facility location planning

The paper presents a goal programming model for facility location planning. Often the location-decision is coupled with multiple objectives, at times conflicting among themselves. Specifically the model considers the four major objectives: (i) necessary locations, (ii) maximum number of locations, (iii) capacity restrictions and (iv) transportation cost/walking distance minimization, simultaneously and proposes optimal locations in conjunction with the existing facilities in the region. The model developed has been illustrated with an example considering the location of community storage facilities in a specified region.     

Intrametropolitan planning for community-based residential care: a goals programming approach.

Small community-based residential facilities have increasingly supplanted large-scale institutions as treatment settings for mentally and physically disabled, indigent, elderly and ex-offender populations in the United States. Because the intrametropolitan assignment of these service-dependent populations and their community care facilities has not been purposively planned, most facilities and clients have clustered in inner cities, resulting in the formation of service-dependent population ghettos. This paper outlines a goals programming approach to the client/facility assignment problem. The model provides a basis for an intrametropolitan distribution of residential service facilities that balances equity and efficiency goals and that protects both client and community rights. A regional fair-share plan that incorporates negotiation and arbitration techniques is offered as an institutional mechanism for implementing the goals programming framework.     

Postal ballots—some practical considerations

This article concentrates upon some of the practical difficulties surrounding postal ballots—level of membership involvement, the problems of contacting paid up members, the drafting of questions on ballot papers and—possibly the most important issue—the degree to which the results moderate outcomes.     

Leveraging multi-tier healthcare facility network simulations for capacity planning in a pandemic

The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and downstream to district hospitals (DH). In this study, we demonstrate how a network-based modelling and simulation approach utilising generic modelling principles can (a) quantify the extent to which the existing facilities in the PHS can effectively cope with the forecasted COVID-19 caseload; and (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows. We apply the approach to an empirical study of a local PHS comprising ten PHCs, three CHCs, one DH and one makeshift CCC. Our work demonstrates how the generic modelling approach finds extensive use in the development of simulations of multi-tier facility networks that may contain multiple instances of generic simulation models of facilities at each network tier. Further, our work demonstrates how multi-tier healthcare facility network simulations can be leveraged for capacity planning in health crises.     

Posterior odds ratios for regression hypotheses: General considerations and some specific results

Much work is econometrics and statistics has been concerned with comparing Bayesian and non-Bayesian estimation results while much less has involved comparisons of Bayesian and non- Bayesian analyses of hypotheses. Some issues arising in this latter area that are mentioned and discussed in the paper are: (1) Is it meaningful to associate probabilities with hypotheses? (2) What concept of probability is to be employed in analyzing hypotheses? (3) Is a separate theory of testing needed? (4) Must a theory of testing be capable of treating both sharp and non-sharp hypotheses? (5) How is prior information incorporated in testing? (6) Does the use of power functions in practice necessitate the use of prior information? (7) How are significance levels determined when sample sizes are large and what are the interpretations of P-values and tail areas? (8) How are conflicting results provided by asymptotically equivalent testing procedures to be reconciled? (9) What is the rationale for the ‘5% accept-reject syndrome’ that afflicts econometrics and applied statistics? (10) Does it make sense to test a null hypothesis with no alternative hypothesis present? and (11) How are the results of analyses of hypotheses to be combined with estimation and prediction procedures? Brief discussions of these issues with references to the literature are provided.Since there is much controversy concerning how hypotheses are actually analyzed in applied work, the results of a small survey relating to 22 articles employing empirical data published in leading economic and econometric journals in 1978 are presented. The major results of this survey indicate that there is wide-spread use of the 1% and 5% levels of significance in non- Bayesian testing with no systematic relation between choice of significance level and sample size. Also, power considerations are not generally discussed in empirical studies. In fact there was a discussion of power in only one of the articles surveyed. Further, there was very little formal or informal use of prior information employed in testing hypotheses and practically no attention was given to the effects of tests or pre-tests on the properties of subsequent tests or estimation results. These results indicate that there is much room for improvement in applied analyses of hypotheses.Given the findings of the survey of applied studies, it is suggested that Bayesian procedures for analyzing hypotheses may be helpful in improving applied analyses. In this connection, the paper presents a review of some Bayesian procedures and results for analyzing sharp and non-sharp hypotheses with explicit use of prior information. In general, Bayesian procedures have good sampling properties and enable investigators to compute posterior probabilities and posterior odds ratios associated with alternative hypotheses quite readily. The relationships of several posterior odds ratios to usual non-Bayesian testing procedures is clearly demonstrated. Also, a relation between the P-value or tail area and a posterior odds ratio is described in detail in the important case of hypotheses about a mean of a normal distribution.Other examples covered in the paper include posterior odds ratios for the hypotheses that (1) $\text{β}{}_{\mathrm{i}}\text{>}$ and $\text{β}{}_{\mathrm{i}}\text{<0}$, where $\text{β}{}_{\mathrm{i}}$ is a regression coefficient, (2) data are drawn from either of two alternative distributions, (3) $\text{θ=0}$, $\text{θ>}$ and $\text{θ<0}$ where θ is the mean of a normal distribution, (4) $\text{β}\text{=0}$ and $\text{β}\text{≠0}$, where β is a vector of regression coefficients, (5) $\text{β}{}_2\text{=0}$ vs. $\text{β}{}_2\text{≠0}$ where $\text{β'}\text{=(}\text{β'}{}_1\text{β}{}_2\text{)}$ is a vector regression coefficients and $\text{β}{}_1$'s value is unrestricted. In several cases, is a vector of regression coefficients and $\text{β}{}_1$'s value is unrestricted. In several cases, tabulations of odds ratios are provided. Bayesian versions of the Chow-test for equality of regression coefficients and of the Goldfeld-Quandt test for equality of disturbance variances are given. Also, an application of Bayesian posterior odds ratios to a regression model selection problem utilizing the Hald data is reported.In summary, the results reported in the paper indicate that operational Bayesian procedures for analyzing many hypotheses encountered in model selection problems are available. These procedures yield posterior odds ratios and posterior probabilities for competing hypotheses. These posterior odds ratios represent the weight of the evidence supporting one model or hypothesis relative to another. Given a loss structure, as is well known one can choose among hypotheses so as to minimize expected loss. Also, with posterior probabilities available and an estimation or prediction loss function, it is possible to choose a point estimate or prediction that minimizes expected loss by averaging over alternative hypotheses or models. Thus it is seen that the Bayesian approach for analyzing competing models or hypotheses provides a unified framework that is extremely useful in solving a number of model selection problems.     

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.     

Computer-assisted planning for regional health care programs

In designing programs to improve regional health care, it is often necessary to synthesize hierarchies. Notwithstanding the fact that the health care milieu is highly complex, this process is frequently dealt with intuitively resulting in fragmented and redundant programs. It is proposed that formal procedures which relieve the individual of much of the complexity in developing programs and arranging their structure can contribute to improve understanding of the system and effectiveness of program design.This paper presents a rational approach to computer-assisted program design utilizing binary matrices and elementary Boolean operations.     

Morphological analysis for health care systems planning

Health care planners are continually challenged by the difficulty of ordering and understanding of the complexities of health care delivery systems. Methods are needed which can aid in extending thought processes into multi-dimensional solution space and rationalizing the thinking of various health care interests. This paper describes a useful approach to designing and evaluating health care systems utilizing a case study of a large metropolitan community.     

Analyzing party competition through the comparative manifesto data: some theoretical and methodological considerations

This paper deals with some of the theoretical and methodological concerns arising from an in-depth analysis of one of the most successful research groups in comparative politics: the Comparative Manifesto Project. The first part of the paper discusses its theoretical background: the dimensionality of the political space, the operationalisation of the saliency theory and whether through election manifestos it is possible to determine the actual party positions. The second part attempts to contribute to the methodological debate by focusing on generally neglected weaknesses of the CMP’s method with regard to both the classification scheme and the coding procedure. In particular, it shows that it is probably impossible to correct the major problems here identified without destroying their comparability across time and space, since they are so deeply rooted in the CMP’s approach.