Yauheniya Varabyova

International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches ☆☆

There is a growing interest in the cross-country comparisons of the performance of national health care systems. The present work provides a comparison of the technical efficiency of the hospital sector using unbalanced panel data from OECD countries over the period 2000-2009. The estimation of the technical efficiency of the hospital sector is performed using nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Internal and external validity of findings is assessed by estimating the Spearman rank correlations between the results obtained in different model specifications. The panel-data analyses using two-step DEA and one-stage SFA show that countries, which have higher health care expenditure per capita, tend to have a more technically efficient hospital sector. Whether the expenditure is financed through private or public sources is not related to the technical efficiency of the hospital sector. On the other hand, the hospital sector in countries with higher income inequality and longer average hospital length of stay is less technically efficient.

Health technology assessment of medical devices: a survey of non-European union agencies.

Objectives: The aim of this study was to review and compare current health technology assessment (HTA) activities for medical devices across non-European Union HTA agencies. Methods: HTA activities for medical devices were evaluated from three perspectives: organizational structure, processes, and methods. Agencies were primarily selected upon membership of existing HTA networks. The data collection was performed in two stages: stage 1–agency Web-site assessment using a standardized questionnaire, followed by review and validation of the collected data by a representative of the agency; and stage 2–semi-structured telephone interviews with key informants of a sub-sample of agencies. Results: In total, thirty-six HTA agencies across twenty non-EU countries assessing medical devices were included. Twenty-seven of thirty-six (75 percent) agencies were judged at stage 1 to have adopted HTA-specific approaches for medical devices (MD-specific agencies) that were largely organizational or procedural. There appeared to be few differences in the organization, process and methods between MD-specific and non–MD-specific agencies. Although the majority (69 percent) of both categories of agency had specific methods guidance or policy for evidence submission, only one MD-specific agency had developed methodological guidelines specific to medical devices. In stage 2, many MD-specific agencies cited insufficient resources (budget, skilled employees), lack of coordination (between regulator and reimbursement bodies), and the inability to generalize findings from evidence synthesis to be key challenges in the HTA of medical devices. Conclusions: The lack of evidence for differentiation in scientific methods for HTA of devices raises the question of whether HTA needs to develop new methods for medical devices but rather adapt existing methodological approaches. In contrast, organizational and/or procedural adaptation of existing HTA agency frameworks to accommodate medical devices appear relatively commonplace.

The efficiency of health care production in OECD countries: A systematic review and meta-analysis of cross-country comparisons

There has been an ongoing interest in the analysis and comparison of the efficiency of health care systems using nonparametric and parametric applications. The objective of this study was to review the current state of the literature and to synthesize the findings on health system efficiency in OECD countries. We systematically searched five electronic databases through August 2014 and identified 22 studies that analyzed the efficiency of health care production at the country level. We summarized these studies with view on their sample, methods, and utilized variables. We developed and applied a checklist of 14 items to assess the quality of the reviewed studies along four dimensions: reporting, external validity, bias, and power. Moreover, to examine the internal validity of findings we meta-analyzed the efficiency estimates reported in 35 models from ten studies. The qualitative synthesis of the literature indicated large differences in study designs and methods. The meta-analysis revealed low correlations between country rankings suggesting a lack of internal validity of the efficiency estimates. In conclusion, methodological problems of existing cross-country comparisons of the efficiency of health care systems draw into question the ability of these comparisons to provide meaningful guidance to policy-makers.

The Role of Learning in Health Technology Assessments: An Empirical Assessment of Endovascular Aneurysm Repairs in German Hospitals

Changes in performance due to learning may dynamically influence the results of a technology evaluation through the change in effectiveness and costs. In this study, we estimate the effect of learning using the example of two minimally invasive treatments of abdominal aortic aneurysms: endovascular aneurysm repair (EVAR) and fenestrated EVAR (fEVAR). The analysis is based on the administrative data of over 40,000 patients admitted with unruptured abdominal aortic aneurysm to more than 500 different hospitals over the years 2006 to 2013. We examine two patient outcomes, namely, in-hospital mortality and length of stay using hierarchical regression models with random effects at the hospital level. The estimated models control for patient and hospital characteristics and take learning interdependency between EVAR and fEVAR into account. In case of EVAR, we observe a significant decrease both in the in-hospital mortality and length of stay with experience accumulated at the hospital level; however, the learning curve for fEVAR in both outcomes is effectively flat. To foster the consideration of learning in health technology assessments of medical devices, a general framework for estimating learning effects is derived from the analysis.

Using nonparametric conditional approach to integrate quality into efficiency analysis: empirical evidence from cardiology departments

Health care providers are under pressure to improve both efficiency and quality. The two objectives are not always mutually consistent, because achieving higher levels of quality may require additional resources. The aim of this study is to demonstrate how the nonparametric conditional approach can be used to integrate quality into the analysis of efficiency and to investigate the mechanisms through which quality enters the production process. Additionally, we explain how the conditional approach relates to other nonparametric methods that allow integrating quality into efficiency analysis and provide guidance on the selection of an appropriate methodology. We use data from 178 departments of interventional cardiology and consider three different measures of quality: patient satisfaction, standardized mortality ratio, and patient radiation exposure. Our results refute the existence of a clear trade-off between efficiency and quality. In fact, the impact of quality on the production process differs according to the utilized quality measure. Patient satisfaction does not affect the attainable frontier but does have an inverted U-shaped effect on the distribution of inefficiencies; mortality ratio negatively impacts the attainable frontier when the observed mortality more than doubles the predicted mortality; and patient radiation exposure is not associated with the production process.

Comparing the Efficiency of Hospitals in Italy and Germany: Nonparametric Conditional Approach Based on Partial Frontier

Traditional nonparametric frontier techniques to measure hospital efficiency have been criticized for their deterministic nature and the inability to incorporate external factors into the analysis. Moreover, efficiency estimates represent a relative measure meaning that the implications from a hospital efficiency analysis based on a single-country dataset are limited by the availability of suitable benchmarks. Our first objective is to demonstrate the application of advanced nonparametric methods that overcome the limitations of the traditional nonparametric frontier techniques. Our second objective is to provide guidance on how an international comparison of hospital efficiency can be conducted using the example of two countries: Italy and Germany. We rely on a partial frontier of order-m to obtain efficiency estimates robust to outliers and extreme values. We use the conditional approach to incorporate hospital and regional characteristics into the estimation of efficiency. The obtained conditional efficiency estimates may deviate from the traditional unconditional efficiency estimates, which do not account for the potential influence of operational environment on the production possibilities. We nonparametrically regress the ratios of conditional to unconditional efficiency estimates to examine the relation of hospital and regional characteristics with the efficiency performance. We show that the two countries can be compared against a common frontier when the challenges of international data compatibility are successfully overcome. The results indicate that there are significant differences in the production possibilities of Italian and German hospitals. Moreover, hospital characteristics, particularly bed-size category, ownership status, and specialization, are significantly related to differences in efficiency performance across the analyzed hospitals.

Integrating quality into the nonparametric analysis of efficiency: a simulation comparison of popular methods

Measuring efficiency in service-producing industries is challenging, because output quality may have to be considered in addition to output quantity. Previous studies have relied on different nonparametric methods to model the relationship between efficiency and quality; however, limited work has been done so far to compare and integrate these methods. Our literature search identified the following popular methods: a one-stage approach, a congestion analysis, and a two-stage approach. The first two methods treat quality as an additional output (or input) of the production process, whereas the two-stage approach first estimates efficiency without considering quality and then regresses the efficiency estimates on quality in the second stage. In this study, we compare the performance of these three conventional methods to a fairly novel method, the so-called conditional approach, that can also be used to incorporate quality into the analysis of efficiency. We simulate data using eight data generating processes that reflect potential relationships between efficiency and quality in empirical settings. Our simulation exercise illustrates the dominance of the conditional approach over the conventional methods in terms of both predicting the true efficiency scores and capturing the original relationship between efficiency and quality. The conditional approach represents a powerful and flexible tool that can be used when the theoretical link between efficiency and quality is unclear.