Kjartan Sarheim Anthun

Measuring cost efficiency in the Nordic Hospitals—a cross-sectional comparison of public hospitals in 2002

The aim of this study was to compare the performance of hospital care in four Nordic countries: Norway, Finland, Sweden and Denmark. Using national discharge registries and cost data from hospitals, cost efficiency in the production of somatic hospital care was calculated for public hospitals. Data were collected using harmonised definitions of inputs and outputs for 184 hospitals and data envelopment analysis was used to calculate Farrell efficiency estimates for the year 2002. Results suggest that there were marked differences in the average hospital efficiency between Nordic countries. In 2002, average efficiency was markedly higher in Finland compared to Norway and Sweden. This study found differences in cost efficiency that cannot be explained by input prices or differences in coding practices. More analysis is needed to reveal the causes of large efficiency disparities between Nordic hospitals.

Cost efficiency of university hospitals in the Nordic countries: a cross-country analysis

This paper estimates cost efficiency scores using the bootstrap bias-corrected procedure, including variables for teaching and research, for the performance of university hospitals in the Nordic countries. Previous research has shown that hospital provision of research and education interferes with patient care routines and inflates the costs of health care services, turning university hospitals into outliers in comparative productivity and efficiency analyses. The organisation of patient care, medical education and clinical research as well as available data at the university hospital level are highly similar in the Nordic countries, creating a data set of comparable decision-making units suitable for a cross-country cost efficiency analysis. The results demonstrate significant differences in university hospital cost efficiency when variables for teaching and research are entered into the analysis, both between and within the Nordic countries. The results of a second-stage analysis show that the most important explanatory variables are geographical location of the hospital and the share of discharges with a high case weight. However, a substantial amount of the variation in cost efficiency at the university hospital level remains unexplained.

International hospital productivity comparison: Experiences from the Nordic countries

This article focuses on describing the methodological challenges intrinsic in international comparative studies of hospital productivity and how these challenges have been addressed within the context of hospital comparisons in the Nordic countries. The hospital sectors in the Nordic countries are suitable for international comparison as they exhibit similar structures in the organisation for hospital care, hold administrative data of good quality at the hospital level, apply a similar secondary patient classification system, and use similar definitions of operating costs. The results of a number of studies have suggested marked differences in hospital cost efficiency and hospital productivity across the Nordic countries and the Finnish hospitals have the highest estimates in all the analyses. Explanatory factors that were tested and seemed to be of limited importance included institutional, structural and technical. A factor that is yet to be included in the Nordic hospital productivity comparison is the quality of care. Patient-level data available from linkable national registers in each country enable the development of quality indicators and will be included in the forthcoming hospital productivity studies within the context of the EuroHOPE (European health care outcomes, performance and efficiency) project.

Costs and Quality at the Hospital Level in the Nordic Countries

This article develops and analyzes patient register-based measures of quality for the major Nordic countries. Previous studies show that Finnish hospitals have significantly higher average productivity than hospitals in Sweden, Denmark, and Norway and also a substantial variation within each country. This paper examines whether quality differences can form part of the explanation and attempts to uncover quality-cost trade-offs. Data on costs and discharges in each diagnosis-related group for 160 acute hospitals in 2008-2009 were collected. Patient register-based measures of quality such as readmissions, mortality (in hospital or outside), and patient safety indices were developed and case-mix adjusted. Productivity is estimated using bootstrapped data envelopment analysis. Results indicate that case-mix adjustment is important, and there are significant differences in the case-mix adjusted performance measures as well as in productivity both at the national and hospital levels. For most quality indicators, the performance measures reveal room for improvement. There is a weak but statistical significant trade-off between productivity and inpatient readmissions within 30 days but a tendency that hospitals with high 30-day mortality also have higher costs. Hence, no clear cost-quality trade-off pattern was discovered. Patient registers can be used and developed to improve future quality and cost comparisons.

Costs and Quality at the Hospital Level in the Nordic Countries.

This article develops and analyzes patient register-based measures of quality for the major Nordic countries. Previous studies show that Finnish hospitals have significantly higher average productivity than hospitals in Sweden, Denmark, and Norway and also a substantial variation within each country. This paper examines whether quality differences can form part of the explanation and attempts to uncover quality-cost trade-offs. Data on costs and discharges in each diagnosis-related group for 160 acute hospitals in 2008-2009 were collected. Patient register-based measures of quality such as readmissions, mortality (in hospital or outside), and patient safety indices were developed and case-mix adjusted. Productivity is estimated using bootstrapped data envelopment analysis. Results indicate that case-mix adjustment is important, and there are significant differences in the case-mix adjusted performance measures as well as in productivity both at the national and hospital levels. For most quality indicators, the performance measures reveal room for improvement. There is a weak but statistical significant trade-off between productivity and inpatient readmissions within 30 days but a tendency that hospitals with high 30-day mortality also have higher costs. Hence, no clear cost-quality trade-off pattern was discovered. Patient registers can be used and developed to improve future quality and cost comparisons.

Cross-country comparisons of health-care costs: The case of cancer treatment in the Nordic countries

The objective of this study is to perform a cross-country comparison of cancer treatment costs in the Nordic countries, and to demonstrate the added value of decomposing documented costs in interpreting national differences. The study is based on individual-level data from national patient and prescription drug registers, and data on cancer prevalence from the NORDCAN database. Hospital costs were estimated on the basis of information on diagnosis-related groups (DRG) cost weights and national unit costs. Differences in per capita costs were decomposed into two stages: stage one separated the price and volume components, and stage two decomposed the volume component, relating the level of activity to service needs and availability. Differences in the per capita costs of cancer treatment between the Nordic countries may be as much as 30 per cent. National differences in the costs of treatment mirror observed differences in total health care costs. Differences in health care costs between countries may relate to different sources of variation with different policy implications. Comparisons of per capita spending alone can be misleading if the purpose is to evaluate, for example, differences in service provision and utilisation. The decomposition analysis helps to identify the relative influence of differences in the prevalence of cancer, service utilisation and productivity.

Productivity growth, case mix and optimal size of hospitals. A 16-year study of the Norwegian hospital sector

BACKGROUND AND OBJECTIVES This paper analyses productivity growth in the Norwegian hospital sector over a period of 16 years, 1999-2014. This period was characterized by a large ownership reform with subsequent hospital reorganizations and mergers. We describe how technological change, technical productivity, scale efficiency and the estimated optimal size of hospitals have evolved during this period. MATERIAL AND METHODS Hospital admissions were grouped into diagnosis-related groups using a fixed-grouper logic. Four composite outputs were defined and inputs were measured as operating costs. Productivity and efficiency were estimated with bootstrapped data envelopment analyses. RESULTS Mean productivity increased by 24.6% points from 1999 to 2014, an average annual change of 1.5%. There was a substantial growth in productivity and hospital size following the ownership reform. After the reform (2003-2014), average annual growth was <0.5%. There was no evidence of technical change. Estimated optimal size was smaller than the actual size of most hospitals, yet scale efficiency was high even after hospital mergers. However, the later hospital mergers have not been followed by similar productivity growth as around time of the reform. CONCLUSIONS This study addresses the issues of both cross-sectional and longitudinal comparability of case mix between hospitals, and thus provides a framework for future studies. The study adds to the discussion on optimal hospital size.

Statistics as a technology of governance: the Norwegian need for numbers & numbers for need

Purpose – This study aims to explore the development in Norway from an awareness of the need for numbers to govern in the 70s to a statistical information system launched in 2006, called IPLOS, to respond to this need. The article seeks to discuss how this system was developed, what the Norwegian authorities attempted to achieve with the development, which goals they desired and how the statistics were intended to contribute to reach them.Design/methodology/approach – This study has a multisite approach inspired by situational analysis, and draws on “governing by numbers” among other theoretical debates. It is based on original data (qualitative interviews) and secondary sources (policy and statistics development documents). The sources represent both top down and bottom up perspectives: authorities, municipalities, expertise involved in the development and disability activists.Findings – The statistics development expresses three challenges in Norwegian health and care service policy: planning and govern...