Bv
B.L. van Hulst
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1
The chapter introduces a novel financial arrangement in healthcare services: Health Impact Bonds (HIBs). Transition aims at making healthcare services not only more affordable but also more efficient, the reason why HIBs focus on the performance (output) side of services (pay-for-success contract). The chapter describes the urgency and challenges in moving towards illness prevention, on the system (healthcare) and project levels. Next, it is explored how HIBs can improve situations of care investment that does not (fully) precipitate at the investor while preventing the rise of new problematic situations. Accordingly, a preliminary list of conditions is designed for the alignment of HIBs. Overall, it seems that HIBs provide substantial solutions by combining new contracts on paying-for-success in performance and a shared savings contract, although some questions remain regarding the involvement of investors. The concluding section includes a reflection on city involvement in HIBs.
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The chapter introduces a novel financial arrangement in healthcare services: Health Impact Bonds (HIBs). Transition aims at making healthcare services not only more affordable but also more efficient, the reason why HIBs focus on the performance (output) side of services (pay-for-success contract). The chapter describes the urgency and challenges in moving towards illness prevention, on the system (healthcare) and project levels. Next, it is explored how HIBs can improve situations of care investment that does not (fully) precipitate at the investor while preventing the rise of new problematic situations. Accordingly, a preliminary list of conditions is designed for the alignment of HIBs. Overall, it seems that HIBs provide substantial solutions by combining new contracts on paying-for-success in performance and a shared savings contract, although some questions remain regarding the involvement of investors. The concluding section includes a reflection on city involvement in HIBs.
Doelmatig huisvesten
Een empirisch onderzoek naar de relatie tussen krimp, schaal, rolverdelingen en de doelmatigheid van onderwijshuisvesting in het basisonderwijs
Dagelijks wordt in het primair onderwijs in 8.500 schoolgebouwen lesgegeven aan ruim 1,5 miljoen leerlingen. In totaal beslaan de gebouwen een oppervlakte van meer dan tien miljoen vierkante meter (Algemene Rekenkamer, 2016). Als gevolg van decentralisatie zijn gemeenten sinds 1997 grotendeels verantwoordelijk voor de onderwijshuisvesting in het primair en voortgezet onderwijs. Gemeenten dragen zorg voor onder meer de nieuwbouw en vervanging van schoolgebouwen, schoolbesturen zijn verantwoordelijk voor de exploitatie en het onderhoud. In 2014 is naar schatting 1,45 miljard euro aan onderwijshuisvesting in het basisonderwijs uitgegeven. Dit bedrag betreft ongeveer 800 miljoen euro aan uitgaven door gemeenten (CBS-Statline) en 650 miljoen euro aan uitgaven door schoolbesturen (DUO).
Dit rapport is een onderzoek naar de kostendoelmatigheid van de gemeentelijke onderwijshuisvesting in het basisonderwijs tussen 2007 en 2014. De kostendoelmatigheid is feitelijk een maat voor de kosten per leerling, waarbij rekening wordt gehouden met de leerlingsamenstelling en andere omgevingsfactoren binnen de gemeente.
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Dagelijks wordt in het primair onderwijs in 8.500 schoolgebouwen lesgegeven aan ruim 1,5 miljoen leerlingen. In totaal beslaan de gebouwen een oppervlakte van meer dan tien miljoen vierkante meter (Algemene Rekenkamer, 2016). Als gevolg van decentralisatie zijn gemeenten sinds 1997 grotendeels verantwoordelijk voor de onderwijshuisvesting in het primair en voortgezet onderwijs. Gemeenten dragen zorg voor onder meer de nieuwbouw en vervanging van schoolgebouwen, schoolbesturen zijn verantwoordelijk voor de exploitatie en het onderhoud. In 2014 is naar schatting 1,45 miljard euro aan onderwijshuisvesting in het basisonderwijs uitgegeven. Dit bedrag betreft ongeveer 800 miljoen euro aan uitgaven door gemeenten (CBS-Statline) en 650 miljoen euro aan uitgaven door schoolbesturen (DUO).
Dit rapport is een onderzoek naar de kostendoelmatigheid van de gemeentelijke onderwijshuisvesting in het basisonderwijs tussen 2007 en 2014. De kostendoelmatigheid is feitelijk een maat voor de kosten per leerling, waarbij rekening wordt gehouden met de leerlingsamenstelling en andere omgevingsfactoren binnen de gemeente.
Concentratie van de spoedeisende hulp
Een verkeerde vorm van zuinigheid
Voor de Spoedeisende Hulp gelden economische schaalvoordelen. Anders gezegd: bij een grotere SEH zijn de gemiddelde kosten per patiënt lager. Toch is dit geen reden om concentratie van de SEH ’s na te streven. Besparingen op kosten bij de SEH worden namelijk tenietgedaan door oplopende kosten in het vervolgtraject.
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Voor de Spoedeisende Hulp gelden economische schaalvoordelen. Anders gezegd: bij een grotere SEH zijn de gemiddelde kosten per patiënt lager. Toch is dit geen reden om concentratie van de SEH ’s na te streven. Besparingen op kosten bij de SEH worden namelijk tenietgedaan door oplopende kosten in het vervolgtraject.
Pomp en Heida plaatsen een aantal vraagtekens bij ons artikel 'Nederlandse ziekenhuizen te groot voor verdere schaalvoordelen'. In deze reactie laten wij zien dat de kritiek een aantal onjuistheden, denkfouten en drogredenen bevat.
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Pomp en Heida plaatsen een aantal vraagtekens bij ons artikel 'Nederlandse ziekenhuizen te groot voor verdere schaalvoordelen'. In deze reactie laten wij zien dat de kritiek een aantal onjuistheden, denkfouten en drogredenen bevat.
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.
...
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.
...
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.
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.
Door fusies zijn Nederlandse ziekenhuizen in de laatste decennia steeds groter geworden. Uit een meta-analyse van internationale studies blijkt dat de zorgkosten juist het laagst zijn in ziekenhuizen die kleiner zijn dan de meeste Nederlandse ziekenhuizen. Het is daarom onwaarschijnlijk dat verdere schaalvergroting de zorgkosten zal drukken.
...
Door fusies zijn Nederlandse ziekenhuizen in de laatste decennia steeds groter geworden. Uit een meta-analyse van internationale studies blijkt dat de zorgkosten juist het laagst zijn in ziekenhuizen die kleiner zijn dan de meeste Nederlandse ziekenhuizen. Het is daarom onwaarschijnlijk dat verdere schaalvergroting de zorgkosten zal drukken.
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.
...
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.
Healthcare expenditure in Western countries is substantial and outpaces economic growth, therefore cost containment in healthcare is high on the political agenda. One option is to increase productivity in healthcare, do more with less. This thesis uses the Dutch hospitals as a case-study and examines the three cornerstones of productivity: scale, efficiency and technical change. Based on meta-analysis it is concluded that there are no economies of scale for hospitals beyond 320 beds. Furthermore there are indications that the optimum size is significant smaller. Analysis of the efficiency of Dutch hospitals shows that there are only marginal possibilities for improvement of the efficiency. Technical change is a collective noun for productivity changes resulting from the overall process of invention, innovation, diffusion of technology and institutional changes. Although productivity consistently increased with about 2% per year as a result of technical change, it is difficult to pinpoint the innovations that contributed most to this growth. In general innovations in the field of ICT and chain care have positively contributed to productivity; productivity loss is associated with innovations aimed at improving quality. Furthermore, the thesis shows that innovations have an initial phase in which they hamper productivity; it takes time before hospitals can fully benefit from innovations.
...
Healthcare expenditure in Western countries is substantial and outpaces economic growth, therefore cost containment in healthcare is high on the political agenda. One option is to increase productivity in healthcare, do more with less. This thesis uses the Dutch hospitals as a case-study and examines the three cornerstones of productivity: scale, efficiency and technical change. Based on meta-analysis it is concluded that there are no economies of scale for hospitals beyond 320 beds. Furthermore there are indications that the optimum size is significant smaller. Analysis of the efficiency of Dutch hospitals shows that there are only marginal possibilities for improvement of the efficiency. Technical change is a collective noun for productivity changes resulting from the overall process of invention, innovation, diffusion of technology and institutional changes. Although productivity consistently increased with about 2% per year as a result of technical change, it is difficult to pinpoint the innovations that contributed most to this growth. In general innovations in the field of ICT and chain care have positively contributed to productivity; productivity loss is associated with innovations aimed at improving quality. Furthermore, the thesis shows that innovations have an initial phase in which they hamper productivity; it takes time before hospitals can fully benefit from innovations.