Balancing the health workforce: breaking down overall technical change into factor technical change for labour-an empirical application to the Dutch hospital industry.

BACKGROUND: Well-trained, well-distributed and productive health workers are crucial for access to high-quality, cost-effective healthcare. Because neither a shortage nor a surplus of health workers is wanted, policymakers use workforce planning models to get information on future labour markets and adjust policies accordingly. A neglected topic of workforce planning models is productivity growth, which has an effect on future demand for labour. However, calculating productivity growth for specific types of input is not as straightforward as it seems. This study shows how to calculate factor technical change (FTC) for specific types of input. METHODS: The paper first theoretically derives FTCs from technical change in a consistent manner. FTC differs from a ratio of output and input, in that it deals with the multi-input, multi-output character of the production process in the health sector. Furthermore, it takes into account substitution effects between different inputs. An application of the calculation of FTCs is given for the Dutch hospital industry for the period 2003-2011. A translog cost function is estimated and used to calculate technical change and FTC for individual inputs, especially specific labour inputs. RESULTS: The results show that technical change increased by 2.8% per year in Dutch hospitals during 2003-2011. FTC differs amongst the various inputs. The FTC of nursing personnel increased by 3.2% per year, implying that fewer nurses were needed to let demand meet supply on the labour market. Sensitivity analyses show consistent results for the FTC of nurses. CONCLUSIONS: Productivity growth, especially of individual outputs, is a neglected topic in workforce planning models. FTC is a productivity measure that is consistent with technical change and accounts for substitution effects. An application to the Dutch hospital industry shows that the FTC of nursing personnel outpaced technical change during 2003-2011. The optimal input mix changed, resulting in fewer nurses being needed to let demand meet supply on the labour market. Policymakers should consider using more detailed and specific data on the nature of technical change when forecasting the future demand for health workers.

Concentrating Emergency Rooms: Penny-Wise and Pound-Foolish? An Empirical Research on Scale Economies and Chain Economies in Emergency Rooms in Dutch Hospitals.

In this paper, we address the issue of whether it is economically advantageous to concentrate emergency rooms (ERs) in large hospitals. Besides identifying economies of scale of ERs, we also focus on chain economies. The latter term refers to the effects on a hospital's costs of ER patients who also need follow-up inpatient or outpatient hospital care. We show that, for each service examined, product-specific economies of scale prevail indicating that it would be beneficial for hospitals to increase ER services. However, this seems to be inconsistent with the overall diseconomies of scale for the hospital as a whole. This intuitively contradictory result is indicated as the economies of scale paradox. This scale paradox also explains why, in general, hospitals are too large. There are internal (departmental) pressures to expand certain services, such as ER, in order to benefit from the product-specific economies of scale. However, the financial burden of this expansion is borne by the hospital as a whole. The policy implications of the results are that concentrating ERs seems to be advantageous from a product-specific perspective, but is far less advantageous from the hospital perspective. © 2016 The Authors. Health Economics Published by John Wiley & Sons, Ltd.

Productive innovations in hospitals: an empirical research on the relation between technology and productivity in the Dutch hospital industry.

This paper studies the relationship between technology and productivity in Dutch hospitals. In most studies technical change is measured by a proxy, namely a time trend. In practice however, innovations slowly spread over all hospitals and so different hospitals are operating under different technologies at the same point in time. In this study we explicitly inventory specific and well-known innovations in the Dutch hospital industry in the past ten years. These innovations are aggregated into a limited number of homogenous innovation clusters, which are measured by a set of technology index numbers. The index numbers are included in the cost function specification and estimation. The results indicate that technical change is non-neutral and output- biased and that some technologies affect cost in beneficial ways.