Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areas

Jiménez, Mercedes Torres; García‐Alonso, Carlos R.; Salvador‐Carulla, Luis; Fernández-Rodríguez, Vicente

doi:10.1016/j.ejor.2014.10.019

Cited by 37 publications

(47 citation statements)

References 46 publications

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“…The extrapolation of our estimates to Catalonia is solely intended for the framing of scientific knowledge in an area of research where very little evidence is currently available [31]. It is noteworthy that the service availability, placement capacity and workforce capacity of the local mental health system in the catchment area were mapped before all other catchment areas in Catalonia and this information is publicly available [18]; as well as the spatial analysis of administrative prevalence of mental disorders [32] and the relative efficiency of the small mental health areas in this metropolitan area [33]. The longitudinal data on service availability, placement capacity, workforce capacity, the geographical analysis and the relative efficiency analysis of its urban mental health system make metropolitan Barcelona a unique case for evidence-informed mental health care and improve the framework for the analysis of specific issues in health care, such as local hospital costs of agitation.…”

Section: Discussionmentioning

confidence: 99%

In-patient costs of agitation and containment in a mental health catchment area

et al. 2017

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BackgroundThere is a scarce number of studies on the cost of agitation and containment interventions and their results are still inconclusive. We aimed to calculate the economic consequences of agitation events in an in-patient psychiatric facility providing care for an urban catchment area.MethodsA mixed approach combining secondary analysis of clinical databases, surveys and expert knowledge was used to model the 2013 direct costs of agitation and containment events for adult inpatients with mental disorders in an area of 640,572 adult inhabitants in South Barcelona (Spain). To calculate costs, a seven-step methodology with novel definition of agitation was used along with a staff survey, a database of containment events, and data on aggressive incidents. A micro-costing analysis of specific containment interventions was used to estimate both prevalence and direct costs from the healthcare provider perspective, by means of a mixed approach with a probabilistic model evaluated on real data. Due to the complex interaction of the multivariate covariances, a sensitivity analysis was conducted to have empirical bounds of variability.ResultsDuring 2013, 918 patients were admitted to the Acute Inpatient Unit. Of these, 52.8% were men, with a mean age of 44.6 years (SD = 15.5), 74.4% were compulsory admissions, 40.1% were diagnosed with schizophrenia or non-affective psychosis, with a mean length of stay of 24.6 days (SD = 16.9). The annual estimate of total agitation events was 508. The cost of containment interventions ranges from 282€ at the lowest level of agitation to 822€ when verbal containment plus seclusion and restraint have to be used. The annual total cost of agitation was 280,535€, representing 6.87% of the total costs of acute hospitalisation in the local area.ConclusionsAgitation events are frequent and costly. Strategies to reduce their number and severity should be implemented to reduce costs to the Health System and alleviate patient suffering.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-017-1373-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

In-patient costs of agitation and containment in a mental health catchment area

et al. 2017

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“…They defined two types of inputs/outputs including geographic information system (GIS) measures and operational measures. Other related studies may be found in Mitropoulos et al [27] (Combining DEA with location analysis for the effective services in the health sector), and Torres-Jiménez et al [28] (using the Monte Carlo DEA for evaluating small health areas).…”

Section: Literature Reviews Of Hospitals Evaluationmentioning

confidence: 97%

Do Geographical Locations Affect in Hospitals Performance? A Multi-group Data Envelopment Analysis

Rezaee

Karimdadi

2015

J Med Syst

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Hospitals are the main and the last component of the health care systems. Therefore, evaluating the performance of hospitals is vital. Several studies are done in hospitals evaluation, but almost none of them consider the geographical features. This paper proposes a new approach for evaluating hospitals. In the proposed approach, hospitals are classified into various groups and each group is equivalent to a province. It causes hospitals in each category (province) must be evaluated in homogenous environment. For this purpose, the conventional data envelopment analysis (DEA) model has been developed to this structure. The main feature of the proposed model is that it takes into consideration the geographical location. In other words, we propose a multi-group DEA model. The data on 288 Iranian hospitals grouped under 31 provinces are used to demonstrate the model. The results show that the efficiency scores are greatly changed when hospitals are evaluated in own groups.

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“…Notable stochastic DEA approaches also include Monte Carlo DEA (MC-DEA) which is based on using a Monte Carlo simulation for the input/output values of each DMU from their statistical distribution to determine the distribution of each DMU's relative technical efficiency [33]. A number of fuzzy data envelopment analysis (F-DEA) studies have also been proposed to deal with imprecision of input and output data; see the overview of Hatami-Marbini et al [26].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Mitropoulos et al [43] proposed a combined application of a CC-DEA model that is integrated with a stochastic mechanism from Bayesian techniques with an application in the Greek health system. Jimenez et al [33] used MC-DEA to evaluate the relative technical efficiency of small health care areas in probabilistic terms with respect to both mental health care, as well as the efficiency of the entire system. Lin et al [41] utilized a multi-objective simulation optimization using DEA and genetic algorithms to determine optimal resource levels in surgical services.…”

Section: Literature Reviewmentioning

confidence: 99%

Stochastic multi-objective auto-optimization for resource allocation decision-making in fixed-input health systems

Bastian

Ekin²,

Kang

et al. 2016

Health Care Manag Sci

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The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.

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Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areas

Cited by 37 publications

References 46 publications

In-patient costs of agitation and containment in a mental health catchment area

In-patient costs of agitation and containment in a mental health catchment area

Do Geographical Locations Affect in Hospitals Performance? A Multi-group Data Envelopment Analysis

Stochastic multi-objective auto-optimization for resource allocation decision-making in fixed-input health systems

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