This dissertation analyzes hospital efficiency using various econometric techniques. The first essay provides additional and recent evidence to the presence of contract management behavior in the U.S. hospital industry. Unlike previous studies, which focus on either an input-demand equation or the cost function of the firm, this paper estimates the two jointly using a system of nonlinear equations. Moreover, it addresses the longitudinal problem of institutions adopting contract management in different years, by creating a matched control group of non-adopters with the same longitudinal distribution as the group under study. The estimation procedure then finds that labor, and not capital, is the preferred input in U.S. hospitals regardless of managerial contract status. With institutions that adopt contract management benefiting from lower labor inefficiencies than the simulated non-contract adopters. These results suggest that while there is a propensity for expense preference behavior towards the labor input, contract managed firms are able to introduce efficiencies over conventional, owner controlled, firms. Using data for the years 1998 through 2007, the second essay investigates the production technology and cost efficiency faced by Florida hospitals. A stochastic frontier multiproduct cost function is estimated in order to test for economies of scale, economies of scope, and relative cost efficiencies. The results suggest that small-sized hospitals experience economies of scale, while large and medium sized institutions do not. The empirical findings show that Florida hospitals enjoy significant scope economies, regardless of size. Lastly, the evidence suggests that there is a link between hospital size and relative cost efficiency. The results of the study imply that state policy makers should be focused on increasing hospital scale for smaller institutions while facilitating the expansion of multiproduct production for larger hospitals. The third and final essay employs a two staged approach in analyzing the efficiency of hospitals in the state of Florida. In the first stage, the Banker, Charnes, and Cooper model of Data Envelopment Analysis is employed in order to derive overall technical efficiency scores for each non-specialty hospital in the state. Additionally, input slacks are calculated and reported in order to identify the factors of production that each hospital may be over utilizing. In the second stage, we employ a Tobit regression model in order to analyze the effects a number of structural, managerial, and environmental factors may have on a hospital's efficiency. The results indicated that most non-specialty hospitals in the state are operating away from the efficient production frontier. The results also indicate that the structural make up, managerial choices, and level of competition Florida hospitals face have an impact on their overall technical efficiency.

Thesis (M.H.S.A.)--University of Michigan, 1981.

Thesis (M.H.S.A.)--University of Michigan, 1981.

Attainment of greater efficiency in hospital operations has become a goal highly sought after as a result of several factors including skyrocketing costs. The possibility that the different incentives associated with ownership type might affect efficiency has been covered thoroughly in the literature. There are numerous studies comparing for-profit to not-for-profit hospitals or public to private hospitals. Analysis of federal ownership, however, has been less studied. In particular, comparisons involving military hospitals are non-existent, attributed to data availability and an assumption that military hospitals are too different from civilian facilities. This dissertation employs a cross-sectional Stochastic Frontier Analysis (“SFA”) of 2006 data to compare the technical efficiency of military, for-profit, not-for-profit, and other government hospitals, controlling for differences in patients, scope of work, physicianhospital working arrangements, and other structural characteristics. Four model specifications are examined, varying the method of accounting for heterogeneity of case mix. One of the specifications uses a distance function technique to allow for specific inclusion of multiple outputs, namely inpatient and outpatient workload. Results obtained using SFA are validated using Data Envelopment Analysis (“DEA”) and compared with results produced through simple ratio analysis. Estimates of overall technical efficiency ranged from 76% to 80%. The analysis found no significant correlation between ownership category and technical efficiency. Factors found to be significantly correlated with greater technical efficiency include younger average patient age, more female patients, percentage of surgical inpatient work, percentage of circulatory system-based work, accreditation, and having all credentialed physicians (i.e. no physician employees). Pooled-vs.-partitioned analysis showed that military hospitals are indeed different, but not enough to render comparisons meaningless. Data Envelopment Analysis produced comparable individual hospital efficiency scores (correlations of approximately 0.6 between like specifications using SFA and DEA) and comparable average efficiency (~87%). Ratio analysis results were sensitive to the specific ratio analyzed. This dissertation adds to the body of literature on the relationship between ownership and hospital technical efficiency. It is the first comparison of military and civilian hospital technical efficiency.

Excess inpatient length of stay (LOS) varies between hospitals and is burdensome to patients and the overall healthcare system. Variation in LOS has often been associated with hospital-level factors, such as hospital efficiency and quality. Clostridium difficile infection (CDI) is an increasingly common hospital-acquired (HA) infection. This thesis explores the connection between hospital incidence of CDI and excess LOS in patients without a CDI. It is hypothesized that HA-CDI incidence may act as a "proxy variable" to capture unobserved hospital characteristics, such as hospital quality or efficiency, associated with prolonged LOS. In addition, hospitals with longer LOS may tend to observe more HA-CDI cases prior to discharge. This thesis analyzes the ability of CDI incidence to capture excess LOS variation across hospitals, while controlling for CDI cases that occur after discharge. We use data on hospital inpatient visits, spanning the years 2005-2011, from three data sources distributed by the Healthcare Cost and Utilization Project: the Nationwide Inpatient Sample (NIS), and the State Inpatient Databases (SID) for California and New York. The NIS provides discharge records from a nationwide sampling of hospitals in a given year. The SIDs are longitudinal populations of inpatient records in each state, and patient records can be linked across stays. We compute a variety of different measures of hospital CDI incidence and identify HA-CDI cases that occur after a patient is discharged. Various multivariable regression models are analyzed to predict LOS at an individual patient level. A generalized linear modeling approach is used, and different distributions and link functions are compared using the Akaike information criterion. A multilevel modeling approach is also used to estimate the amount of between-hospital variation in LOS that can be explained by HA-CDI incidence. We find CDI incidence to be a strong predictive factor for explaining a patient's LOS and is one of the strongest predictive variables we identified. Moreover, CDI incidence appears to primarily capture between-hospital variation in excess LOS. Although we find evidence that present-on-admission indicators may underreport cases of HA CDI, our findings suggest the connection between CDI incidence and excess LOS is driven primarily by CDI cases that are HA. In addition, when we account for HA-CDI cases that occur post-discharge, the relationship between CDI incidence and LOS appears even stronger. Our results suggest that CDI incidence may be a powerful tool for making comparisons of excess LOS across hospitals.

The thesis deals with efficiency of inpatient facilities in the Czech Republic in the period 2008 to 2013. The first chapter describes the importance of inpatient facilities in the health care system and methods of evaluation of efficiency with focus on the method of DEA. Additionally it defines the necessary concepts for other parts of the work. The content of the following chapter is the analysis of the development of inpatient fund according to selected criteria. In the last chapter are first analyzed the determinants which may influence the efficiency of the hospital and the possibilities of their monitoring in the Czech Republic. This is followed by a key part of the thesis - analysis of technical and cost efficiency of hospitals, on the basis of which conclusions and recommendations are drawn into practice.

Les technologies de l’information et de la communication se sont considérablement développées dans tous les secteurs de l’économie. Dans le domaine de la santé, et tous particulièrement dans le secteur hospitalier, les investissements se sont considérablement accrus, notamment avec la mise en place de systèmes d’information clinique (SIC) intégrés. Les hypothèses derrière ces investissements sont que la mise en œuvre d’un SIC peut améliorer à la fois l’efficience d’un hôpital et la qualité des soins. Pour être validée, ces hypothèses nécessitent que soit mise au point une méthodologie de mesure du degré de mise en place d’un SIC, de l’efficience hospitalière puis de la qualité des soins. Ce travail est centré d’une part sur la méthodologie de mesure de l’utilisation d’un SIC et d’autre part sur la mesure de l’efficience hospitalière. Le cadre applicatif du travail est, dans le premier cas, le système d’information clinique de l’HEGP et dans le second les hôpitaux de court séjour de l’AP-HP dont fait partie l’HEGP. Après une étude de la littérature sur l’évaluation de l’utilisation et de de la satisfaction d’un SIC, la première partie de la thèse est organisée autour de deux études. Une première étude longitudinale de 2004 à 2014 permet d’analyser l’évolution de l’utilisation et de la satisfaction au travers d’un groupe multi professionnel d’utilisateurs et d’analyser leurs déterminants avec des méthodes d’équations structurelles. En post-adoption précoce (4 ans), l'utilisation du SIC, la qualité du SIC et l’utilité perçue (PU) expliquent 53% de la variance de la satisfaction. Dans la phase de post-adoption très tardive (>10 ans), l’effet de l’utilisation n’est plus significatif, par contre, la qualité du SIC, la confirmation des attentes et la PU sont les paramètres les plus liés à la satisfaction expliquant 86% de sa variance. Cependant, la satisfaction et la PU sont les facteurs les plus déterminants de l’intention de continuer, avec une forte influence indirecte de la qualité du système. Un modèle unifié est proposé et comparé aux modèles principaux de la littérature. La mesure de l’efficience des hôpitaux est effectuée avec un modèle économétrique dont le choix des variables a été effectué sur la base d’une revue systématique de la littérature. Trois catégories d’indicateurs d’entrée et trois catégories d’indicateurs de sorties sont utilisés. Les relations entre entrées et sorties sont analysées au travers une fonction de production (Translog) et d’un modèle paramétrique (Stochastic Frontier Analysis). Une diminution globale de l’efficience de 20 hôpitaux de court séjour de l’AP-HP sur la période 2009-2014 est observée dont les causes possibles sont discutées. La mise au point et la validation de modèles d’évaluation de l’utilisation des SIC d’une part et de mesure de l’efficience hospitalière devrait faciliter l’analyse des relations entre informatisation et efficience hospitalière, puis lorsque la même démarche aura été appliquée à la qualité des soins entre informatisation et qualité. / The information and communication technologies (ICT) have been developed in all economic sectors. In the healthcare field, and particularly in hospitals with the introduction of clinical information systems (CIS), investments have dramatically increased. The rationale for these investments is the improvement of both the hospital efficiency and the quality of the care delivered to patients after the deployment of a fully integrated CIS. In the aim to validate these relationships adapted methodologies, need to be designed and implemented. This thesis concentrates on the CIS maturity and hospital efficiency relationship. Material for testing the hypothesis come from several CIS evaluations performed at HEGP and data extracted from the decision analytics tools of Assistance Publique Hôpitaux de Paris (AP-HP). After a study of the literature on the use and satisfaction evaluation of a CIS, the first part of the thesis is organized around two main studies. A 14 years longitudinal study achieved between 2004 and 2014 analyzes the evolution of use and satisfaction and their determinants within a multi professional group of users using multiple regression techniques and structural equation methods. In early post-adoption (4 years), the CIS use, the CIS quality, and the CIS perceived usefulness (PU) explain 53% of the variance in user satisfaction. In the very late post-adoption phase (> 10 years), the effect of use on user satisfaction is no more significant. In contrast, the CIS quality, the confirmation of expectations, and the PU are the best determinants of satisfaction explaining 86% of its variance. In a second study focused on continuance intention, satisfaction and PU appear to be the best determinants of continuance intention, with a strong indirect influence of the CIS quality. A unified model is proposed and compared to the main models of the literature. The measurement of hospital efficiency was achieved with an econometric approach. Selection of indicators entered in the econometric model was performed on the basis of a systematic literature review. Three categories of input indicators and three categories of output indicators are considered. The relationship between the input and output indicators are analyzed through a Stochastic Frontier Analysis model. An overall decrease of the efficiency of the 20 short-stay hospitals of the AP-HP for the 2009-2014 period is observed and its possible causes are discussed. The development and validation of CIS use-satisfaction evaluation model combined with the analysis of the hospital efficiency evolution over time could be the first phase of a more global evaluation of the complex influence of IT introduction on hospital efficiency and the quality of care delivered to patients.

The formation of multi-hospital systems represents one of the largest structural changes in the hospital industry. As of 2008, system affiliated hospitals outnumbered stand alone hospitals 2511 to 2167 and the percentage of system affiliated rural hospitals has increased dramatically from 24.8% in 1983 to 42.2% in 2008 (based on AHA data for non-federal acute care general hospitals). The effects of system membership on hospital performance have been of great interest to health care researchers, but the majority of research on multi-hospital systems has either focused exclusively on urban facilities or pooled urban and rural facilities in the same sample, and thus failed to allow for potential differences in membership effects between urban and rural hospitals. The result is that the effect of system membership on rural hospital performance has remained largely unexplored, creating a gap in the body of health services research. The objectives of this study are both theoretical and empirical. Theoretically, this study is intended to be a deliberate empirical application of contingency theory, which is the one major organizational theory that seeks to explain variations in organizational performance as its fundamental purpose. Empirically, this study seeks to explore the relationship between rural hospital system membership and rural hospital performance, taking into account the environment of the rural hospital and the structure of the multi-hospital system to which it belongs. The study sample consists of 1010 non-federal, short-term, acute care general rural hospitals with consistent system membership and critical access hospital (CAH) status from 2004 to 2008. Hospital economic performance is represented by the dependent variables of hospital total margin and a productive efficiency score calculated using Data Envelopment Analysis (DEA). Four contingent pairs containing measures for environmental munificence, system membership, the presence of local system partners, the presence of hierarchical system partners, and CAH status, were used to measure a hospital’s fit between environment and structure. Regression analysis was used to determine the relationship between hospital performance and the fit between a hospital’s environment and its organizational/system structure. Results of the analysis indicate that hospitals with a better fit have significantly higher total margins, but results for productive efficiency were largely insignificant.