Pub Date : 2019-06-25DOI: 10.1093/acrefore/9780190625979.013.42
S. Berlinski, M. Vera-Hernandez
Socioeconomic gradients in health, cognitive, and socioemotional skills start at a very early age. Well-designed policy interventions in the early years can have a great impact in closing these gaps. Advancing this line of research requires a thorough understanding of how households make human capital investment decisions on behalf of their children, what their information set is, and how the market, the environment, and government policies affect them. A framework for this research should describe how children’s skills evolve and how parents make choices about the inputs that model child development, as well as the rationale for government interventions, including both efficiency and equity considerations.
{"title":"The Rationale for Interventions to Foster Child Development","authors":"S. Berlinski, M. Vera-Hernandez","doi":"10.1093/acrefore/9780190625979.013.42","DOIUrl":"https://doi.org/10.1093/acrefore/9780190625979.013.42","url":null,"abstract":"Socioeconomic gradients in health, cognitive, and socioemotional skills start at a very early age. Well-designed policy interventions in the early years can have a great impact in closing these gaps. Advancing this line of research requires a thorough understanding of how households make human capital investment decisions on behalf of their children, what their information set is, and how the market, the environment, and government policies affect them. A framework for this research should describe how children’s skills evolve and how parents make choices about the inputs that model child development, as well as the rationale for government interventions, including both efficiency and equity considerations.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127577881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-25DOI: 10.1093/ACREFORE/9780190625979.013.38
A. Vassall, F. Bozzani, K. Hanson
In order to secure effective service access, coverage, and impact, it is increasingly recognized that the introduction of novel health technologies such as diagnostics, drugs, and vaccines may require additional investment to address the constraints under which many health systems operate. Health-system constraints include a shortage of health workers, ineffective supply chains, or inadequate information systems, or organizational constraints such as weak incentives and poor service integration. Decision makers may be faced with the question of whether to invest in a new technology, including the specific health system strengthening needed to ensure effective implementation; or they may be seeking to optimize resource allocation across a range of interventions including investment in broad health system functions or platforms. Investment in measures to address health-system constraints therefore increasingly need to undergo economic evaluation, but this poses several methodological challenges for health economists, particularly in the context of low- and middle-income countries. Designing the appropriate analysis to inform investment decisions concerning new technologies incorporating health systems investment can be broken down into several steps. First, the analysis needs to comprehensively outline the interface between the new intervention and the system through which it is to be delivered, in order to identify the relevant constraints and the measures needed to relax them. Second, the analysis needs to be rooted in a theoretical approach to appropriately characterize constraints and consider joint investment in the health system and technology. Third, the analysis needs to consider how the overarching priority- setting process influences the scope and output of the analysis informing the way in which complex evidence is used to support the decision, including how to represent and manage system wide trade-offs. Finally, there are several ways in which decision analytical models can be structured, and parameterized, in a context of data scarcity around constraints. This article draws together current approaches to health system thinking with the emerging literature on analytical approaches to integrating health-system constraints into economic evaluation to guide economists through these four issues. It aims to contribute to a more health-system-informed approach to both appraising the cost-effectiveness of new technologies and setting priorities across a range of program activities.
{"title":"Considering Health-Systems Constraints in Economic Evaluation in Low- and Middle-Income Settings","authors":"A. Vassall, F. Bozzani, K. Hanson","doi":"10.1093/ACREFORE/9780190625979.013.38","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190625979.013.38","url":null,"abstract":"In order to secure effective service access, coverage, and impact, it is increasingly recognized that the introduction of novel health technologies such as diagnostics, drugs, and vaccines may require additional investment to address the constraints under which many health systems operate. Health-system constraints include a shortage of health workers, ineffective supply chains, or inadequate information systems, or organizational constraints such as weak incentives and poor service integration. Decision makers may be faced with the question of whether to invest in a new technology, including the specific health system strengthening needed to ensure effective implementation; or they may be seeking to optimize resource allocation across a range of interventions including investment in broad health system functions or platforms. Investment in measures to address health-system constraints therefore increasingly need to undergo economic evaluation, but this poses several methodological challenges for health economists, particularly in the context of low- and middle-income countries.\u0000 Designing the appropriate analysis to inform investment decisions concerning new technologies incorporating health systems investment can be broken down into several steps. First, the analysis needs to comprehensively outline the interface between the new intervention and the system through which it is to be delivered, in order to identify the relevant constraints and the measures needed to relax them. Second, the analysis needs to be rooted in a theoretical approach to appropriately characterize constraints and consider joint investment in the health system and technology. Third, the analysis needs to consider how the overarching priority- setting process influences the scope and output of the analysis informing the way in which complex evidence is used to support the decision, including how to represent and manage system wide trade-offs. Finally, there are several ways in which decision analytical models can be structured, and parameterized, in a context of data scarcity around constraints. This article draws together current approaches to health system thinking with the emerging literature on analytical approaches to integrating health-system constraints into economic evaluation to guide economists through these four issues. It aims to contribute to a more health-system-informed approach to both appraising the cost-effectiveness of new technologies and setting priorities across a range of program activities.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114754445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-25DOI: 10.1093/ACREFORE/9780190625979.013.377
E. Aas, E. Burger, K. Pedersen
The objective of medical screening is to prevent future disease (secondary prevention) or to improve prognosis by detecting the disease at an earlier stage (early detection). This involves examination of individuals with no symptoms of disease. Introducing a screening program is resource demanding, therefore stakeholders emphasize the need for comprehensive evaluation, where costs and health outcomes are reasonably balanced, prior to population-based implementation. Economic evaluation of population-based screening programs involves quantifying health benefits (e.g., life-years gained) and monetary costs of all relevant screening strategies. The alternative strategies can vary by starting- and stopping-age, frequency of the screening and follow-up regimens after a positive test result. Following evaluation of all strategies, the efficiency frontier displays the efficient strategies and the country-specific cost-effectiveness threshold is used to determine the optimal, i.e., most cost-effective, screening strategy. Similar to other preventive interventions, the costs of screening are immediate, while the health benefits accumulate after several years. Hence, the effect of discounting can be substantial when estimating the net present value (NPV) of each strategy. Reporting both discounting and undiscounted results is recommended. In addition, intermediate outcome measures, such as number of positive tests, cases detected, and events prevented, can be valuable supplemental outcomes to report. Estimating the cost-effectiveness of alternative screening strategies is often based on decision-analytic models, synthesizing evidence from clinical trials, literature, guidelines, and registries. Decision-analytic modeling can include evidence from trials with intermediate or surrogate endpoints and extrapolate to long-term endpoints, such as incidence and mortality, by means of sophisticated calibration methods. Furthermore, decision-analytic models are unique, as a large number of screening alternatives can be evaluated simultaneously, which is not feasible in a randomized controlled trial (RCT). Still, evaluation of screening based on RCT data are valuable as both costs and health benefits are measured for the same individual, enabling more advanced analysis of the interaction of costs and health benefits. Evaluation of screening involves multiple stakeholders and other considerations besides cost-effectiveness, such as distributional concerns, severity of the disease, and capacity influence decision-making. Analysis of harm-benefit trade-offs is a useful tool to supplement cost-effectiveness analyses. Decision-analytic models are often based on 100% participation, which is rarely the case in practice. If those participating are different from those not choosing to participate, with regard to, for instance, risk of the disease or condition, this would result in selection bias, and the result in practice could deviate from the results based on 100% par
{"title":"Economic Evaluation of Medical Screening","authors":"E. Aas, E. Burger, K. Pedersen","doi":"10.1093/ACREFORE/9780190625979.013.377","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190625979.013.377","url":null,"abstract":"The objective of medical screening is to prevent future disease (secondary prevention) or to improve prognosis by detecting the disease at an earlier stage (early detection). This involves examination of individuals with no symptoms of disease. Introducing a screening program is resource demanding, therefore stakeholders emphasize the need for comprehensive evaluation, where costs and health outcomes are reasonably balanced, prior to population-based implementation.\u0000 Economic evaluation of population-based screening programs involves quantifying health benefits (e.g., life-years gained) and monetary costs of all relevant screening strategies. The alternative strategies can vary by starting- and stopping-age, frequency of the screening and follow-up regimens after a positive test result. Following evaluation of all strategies, the efficiency frontier displays the efficient strategies and the country-specific cost-effectiveness threshold is used to determine the optimal, i.e., most cost-effective, screening strategy.\u0000 Similar to other preventive interventions, the costs of screening are immediate, while the health benefits accumulate after several years. Hence, the effect of discounting can be substantial when estimating the net present value (NPV) of each strategy. Reporting both discounting and undiscounted results is recommended. In addition, intermediate outcome measures, such as number of positive tests, cases detected, and events prevented, can be valuable supplemental outcomes to report.\u0000 Estimating the cost-effectiveness of alternative screening strategies is often based on decision-analytic models, synthesizing evidence from clinical trials, literature, guidelines, and registries. Decision-analytic modeling can include evidence from trials with intermediate or surrogate endpoints and extrapolate to long-term endpoints, such as incidence and mortality, by means of sophisticated calibration methods. Furthermore, decision-analytic models are unique, as a large number of screening alternatives can be evaluated simultaneously, which is not feasible in a randomized controlled trial (RCT). Still, evaluation of screening based on RCT data are valuable as both costs and health benefits are measured for the same individual, enabling more advanced analysis of the interaction of costs and health benefits.\u0000 Evaluation of screening involves multiple stakeholders and other considerations besides cost-effectiveness, such as distributional concerns, severity of the disease, and capacity influence decision-making. Analysis of harm-benefit trade-offs is a useful tool to supplement cost-effectiveness analyses. Decision-analytic models are often based on 100% participation, which is rarely the case in practice. If those participating are different from those not choosing to participate, with regard to, for instance, risk of the disease or condition, this would result in selection bias, and the result in practice could deviate from the results based on 100% par","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126870342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-25DOI: 10.1093/acrefore/9780190625979.013.51
J. Winter, Amelie Wuppermann
Choice of health insurance plans has become a key element of many healthcare systems around the world along with a general expansion of patient choice under the label of “Consumer-Directed Healthcare.” Allowing consumers to choose their insurance plan was commonly associated with the aim of enhancing competition between insurers and thus to contribute to the efficient delivery of healthcare. However, the evidence is accruing that consumers have difficulties in making health insurance decisions in their best interest. For example, many consumers choose plans with which they spend more in terms of premiums and out-of-pocket costs than in other available options. This has consequences for the individual consumer’s budget as well as for the functioning of the insurance market. The literature puts forward several possible reasons for consumers’ difficulties in making health insurance choices in their best interest. First, consumers may not have a sufficient level of knowledge of insurance products; for example, they might not understand insurance terminology. Second, the environment or architecture in which consumers make their decision may be too complicated. Health insurance products vary in a large number of features that consumers have to evaluate when comparing options, introducing search or hassle costs. Third, consumers may be prone to psychological biases and employ decision-making heuristics that impede good choices. For example, they might choose the plan with the cheapest premium, ignoring other important plan features that determine total cost, such as copayments. There is also evidence that consumer education programs, simplification of the choice environment, or introducing nudges such as setting smart defaults facilitate consumer decision making. Despite recent progress in our understanding of consumer choices in health insurance markets, important challenges remain. Evidence-based healthcare policy should be based on an evaluation of whether different interventions aimed at facilitating consumer choices result in welfare improvements. Ultimately, this requires measuring consumer utility, an issue that is vividly debated in the literature. Furthermore, welfare calculations necessitate an understanding of how interventions will affect the supply of health insurance, including supply reactions to changes in demand. This depends on the specific regulatory setting and characteristics of the specific market.
{"title":"Health Insurance Plan Choice and Switching","authors":"J. Winter, Amelie Wuppermann","doi":"10.1093/acrefore/9780190625979.013.51","DOIUrl":"https://doi.org/10.1093/acrefore/9780190625979.013.51","url":null,"abstract":"Choice of health insurance plans has become a key element of many healthcare systems around the world along with a general expansion of patient choice under the label of “Consumer-Directed Healthcare.” Allowing consumers to choose their insurance plan was commonly associated with the aim of enhancing competition between insurers and thus to contribute to the efficient delivery of healthcare. However, the evidence is accruing that consumers have difficulties in making health insurance decisions in their best interest. For example, many consumers choose plans with which they spend more in terms of premiums and out-of-pocket costs than in other available options. This has consequences for the individual consumer’s budget as well as for the functioning of the insurance market.\u0000 The literature puts forward several possible reasons for consumers’ difficulties in making health insurance choices in their best interest. First, consumers may not have a sufficient level of knowledge of insurance products; for example, they might not understand insurance terminology. Second, the environment or architecture in which consumers make their decision may be too complicated. Health insurance products vary in a large number of features that consumers have to evaluate when comparing options, introducing search or hassle costs. Third, consumers may be prone to psychological biases and employ decision-making heuristics that impede good choices. For example, they might choose the plan with the cheapest premium, ignoring other important plan features that determine total cost, such as copayments. There is also evidence that consumer education programs, simplification of the choice environment, or introducing nudges such as setting smart defaults facilitate consumer decision making.\u0000 Despite recent progress in our understanding of consumer choices in health insurance markets, important challenges remain. Evidence-based healthcare policy should be based on an evaluation of whether different interventions aimed at facilitating consumer choices result in welfare improvements. Ultimately, this requires measuring consumer utility, an issue that is vividly debated in the literature. Furthermore, welfare calculations necessitate an understanding of how interventions will affect the supply of health insurance, including supply reactions to changes in demand. This depends on the specific regulatory setting and characteristics of the specific market.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128548835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-25DOI: 10.1093/acrefore/9780190625979.013.77
A. Chit, P. Grootendorst
Drug companies are profit-maximizing entities, and profit is, by definition, revenue less cost. Here we review the impact of government policies that affect sales revenues earned on newly developed drugs and the impact of policies that affect the cost of drug development. The former policies include intellectual property rights, drug price controls, and the extension of public drug coverage to previously underinsured groups. The latter policies include regulations governing drug safety and efficacy, R&D tax credits, publicly funded basic research, and public funding for open drug discovery consortia. The latter policy, public funding of research consortia that seek to better understand the cellular pathways through which new drugs can ameliorate disease, appears very promising. In particular, a better understanding of human pathophysiology may be able to address the high failure rate of drugs undergoing clinical testing. Policies that expand market size by extending drug insurance to previously underinsured groups also appear to be effective at increasing drug R&D. Expansions of pharmaceutical intellectual property rights seem to be less effective, given the countervailing monopsony power of large public drug plans.
{"title":"The Effect of Government Policy on Pharmaceutical Drug Innovation","authors":"A. Chit, P. Grootendorst","doi":"10.1093/acrefore/9780190625979.013.77","DOIUrl":"https://doi.org/10.1093/acrefore/9780190625979.013.77","url":null,"abstract":"Drug companies are profit-maximizing entities, and profit is, by definition, revenue less cost. Here we review the impact of government policies that affect sales revenues earned on newly developed drugs and the impact of policies that affect the cost of drug development. The former policies include intellectual property rights, drug price controls, and the extension of public drug coverage to previously underinsured groups. The latter policies include regulations governing drug safety and efficacy, R&D tax credits, publicly funded basic research, and public funding for open drug discovery consortia.\u0000 The latter policy, public funding of research consortia that seek to better understand the cellular pathways through which new drugs can ameliorate disease, appears very promising. In particular, a better understanding of human pathophysiology may be able to address the high failure rate of drugs undergoing clinical testing. Policies that expand market size by extending drug insurance to previously underinsured groups also appear to be effective at increasing drug R&D. Expansions of pharmaceutical intellectual property rights seem to be less effective, given the countervailing monopsony power of large public drug plans.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126164999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-25DOI: 10.1093/ACREFORE/9780190625979.013.249
S. Sosa-Rubí, O. Galárraga
Conditional economic incentives are a theoretically grounded approach for eliciting behavior change. The rationale stems from present-biased preferences, by which individuals attach greater value to benefits in the present and heavily discount long-term health. A growing literature documents the use of economic incentives in the HIV field. Small and frequent conditional economic incentives offered to vulnerable populations can contribute to behavior change. Economic incentives accompanied with other strategies can help overcome obstacles to access health services and in general seem to improve linkage to HIV care, prevention interventions, and adherence to HIV treatment. Future identification of promising combinations of intervention components, modalities, and strategies may yield maximum impact.
{"title":"Economic Incentives, Risk Behaviors, and HIV","authors":"S. Sosa-Rubí, O. Galárraga","doi":"10.1093/ACREFORE/9780190625979.013.249","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190625979.013.249","url":null,"abstract":"Conditional economic incentives are a theoretically grounded approach for eliciting behavior change. The rationale stems from present-biased preferences, by which individuals attach greater value to benefits in the present and heavily discount long-term health. A growing literature documents the use of economic incentives in the HIV field. Small and frequent conditional economic incentives offered to vulnerable populations can contribute to behavior change. Economic incentives accompanied with other strategies can help overcome obstacles to access health services and in general seem to improve linkage to HIV care, prevention interventions, and adherence to HIV treatment. Future identification of promising combinations of intervention components, modalities, and strategies may yield maximum impact.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132703293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-23DOI: 10.1093/ACREFORE/9780190625979.013.265
C. V. Houtven, Fiona Carmichael, J. Jacobs, P. Coyte
Across the globe, the most common means of supporting older disabled adults in their homes is through “informal care.” An informal carer is a family member or friend, including children or adults, who help another person because of their illness, frailty, or disability. There is a rich economics literature on the direct benefits of caregiving, including allowing the care recipient to remain at home for longer than if there was no informal care provided. There is also a growing literature outlining the associated costs of care provision. Although informal care helps individuals with disabilities to remain at home and is rewarding to many carers, there are often negative effects such as depression and lost labor market earnings that may offset some of these rewards. Economists have taken several approaches to quantify the net societal benefit of informal care that consider the degree of choice in caregiving decisions and all direct and indirect benefits and costs of informal care.
{"title":"The Economics of Informal Care","authors":"C. V. Houtven, Fiona Carmichael, J. Jacobs, P. Coyte","doi":"10.1093/ACREFORE/9780190625979.013.265","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190625979.013.265","url":null,"abstract":"Across the globe, the most common means of supporting older disabled adults in their homes is through “informal care.” An informal carer is a family member or friend, including children or adults, who help another person because of their illness, frailty, or disability. There is a rich economics literature on the direct benefits of caregiving, including allowing the care recipient to remain at home for longer than if there was no informal care provided. There is also a growing literature outlining the associated costs of care provision. Although informal care helps individuals with disabilities to remain at home and is rewarding to many carers, there are often negative effects such as depression and lost labor market earnings that may offset some of these rewards. Economists have taken several approaches to quantify the net societal benefit of informal care that consider the degree of choice in caregiving decisions and all direct and indirect benefits and costs of informal care.","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125483629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-23DOI: 10.1093/ACREFORE/9780190625979.013.245
W. Yip
Important health system challenges in the east and southeast Asian countries/territories of Japan, South Korea, Taiwan, Hong Kong, Malaysia, China, Thailand, Vietnam, Indonesia, the Philippines, Laos, Myanmar, and Cambodia exist. The most commonly adopted health system among these areas is social health insurance. The high-income, aging societies of Japan, South Korea, and Taiwan have adopted single-payer/single-pipe systems with a single uniform benefit package and a single fee schedule for paying providers for services included in the benefit package. All three have achieved universal coverage with relatively equitable access to affordable care. All grapple with overutilization, aging populations, and hospital-centric and curative-focused care that is ill-suited for addressing an increasing chronic disease burden. Rising patient expectations and demand for expensive technologies contribute to rising costs. Korea also faces comparatively poorer financial risk protection. China, Thailand, Vietnam, Indonesia, and the Philippines have also adopted social health insurance, though not single-payer systems. China and Thailand have established noncontributory schemes, whereby the government heavily subsidizes poor and non-poor populations. General tax revenue is used to extend coverage to those outside formal-sector employment. Both countries use multiple, unintegrated schemes to cover their populations. Thailand has improved access to care and financial risk protection. While China has improved insurance coverage, financial risk protection gains have been limited due to low levels of service coverage, fee-for-service payment systems, poor gatekeeping, and the fee schedule that incentivizes overprescription of tests and medicine. Indonesia, Vietnam, and the Philippines use contributory schemes. Government revenue provides insurance coverage for the poor, near-poor, and selected vulnerable populations; the rest of the population must contribute to enroll. Therefore, expanding insurance coverage to the informal sector has been a significant challenge. Instead of social health insurance, Hong Kong and Malaysia have two-tiered health systems where the public sector is financed by general tax revenue and the private sector is financed primarily by out-of-pocket payments and limited private insurance. There is universal access to care; free or subsidized, good-quality public-sector services provide financial risk protection. However, Hong Kong and Malaysia have fragmented delivery systems, weak primary care, budgetary strains, and inequitable access to private care (which may offer shorter wait times and better perceived quality). Laos, Cambodia, and Myanmar’s health systems feature high out-of-pocket spending, low government investment in health, and reliance on external aid. User fees, low insurance coverage, unequal distribution of health services, and fragmented financing pose pressing challenges to achieving equitable access and adequate financial ri
{"title":"Healthcare System Challenges in Asia","authors":"W. Yip","doi":"10.1093/ACREFORE/9780190625979.013.245","DOIUrl":"https://doi.org/10.1093/ACREFORE/9780190625979.013.245","url":null,"abstract":"Important health system challenges in the east and southeast Asian countries/territories of Japan, South Korea, Taiwan, Hong Kong, Malaysia, China, Thailand, Vietnam, Indonesia, the Philippines, Laos, Myanmar, and Cambodia exist. The most commonly adopted health system among these areas is social health insurance. The high-income, aging societies of Japan, South Korea, and Taiwan have adopted single-payer/single-pipe systems with a single uniform benefit package and a single fee schedule for paying providers for services included in the benefit package. All three have achieved universal coverage with relatively equitable access to affordable care. All grapple with overutilization, aging populations, and hospital-centric and curative-focused care that is ill-suited for addressing an increasing chronic disease burden. Rising patient expectations and demand for expensive technologies contribute to rising costs. Korea also faces comparatively poorer financial risk protection.\u0000 China, Thailand, Vietnam, Indonesia, and the Philippines have also adopted social health insurance, though not single-payer systems. China and Thailand have established noncontributory schemes, whereby the government heavily subsidizes poor and non-poor populations. General tax revenue is used to extend coverage to those outside formal-sector employment. Both countries use multiple, unintegrated schemes to cover their populations. Thailand has improved access to care and financial risk protection. While China has improved insurance coverage, financial risk protection gains have been limited due to low levels of service coverage, fee-for-service payment systems, poor gatekeeping, and the fee schedule that incentivizes overprescription of tests and medicine. Indonesia, Vietnam, and the Philippines use contributory schemes. Government revenue provides insurance coverage for the poor, near-poor, and selected vulnerable populations; the rest of the population must contribute to enroll. Therefore, expanding insurance coverage to the informal sector has been a significant challenge.\u0000 Instead of social health insurance, Hong Kong and Malaysia have two-tiered health systems where the public sector is financed by general tax revenue and the private sector is financed primarily by out-of-pocket payments and limited private insurance. There is universal access to care; free or subsidized, good-quality public-sector services provide financial risk protection. However, Hong Kong and Malaysia have fragmented delivery systems, weak primary care, budgetary strains, and inequitable access to private care (which may offer shorter wait times and better perceived quality).\u0000 Laos, Cambodia, and Myanmar’s health systems feature high out-of-pocket spending, low government investment in health, and reliance on external aid. User fees, low insurance coverage, unequal distribution of health services, and fragmented financing pose pressing challenges to achieving equitable access and adequate financial ri","PeriodicalId":211658,"journal":{"name":"Oxford Research Encyclopedia of Economics and Finance","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121785567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-23DOI: 10.1093/acrefore/9780190625979.013.397
Chaocheng Gu, Han-Soo Han, Randall Wright
This article provides an introduction to New Monetarist Economics. This branch of macro and monetary theory emphasizes imperfect commitment, information problems, and sometimes spatial (endogenously) separation as key frictions in the economy to derive endogenously institutions like monetary exchange or financial intermediation. We present three generations of models in development of New Monetarism. The first model studies an environment in which agents meet bilaterally and lack commitment, which allows money to be valued endogenously as means of payment. In this setup both goods and money are indivisible to keep things tractable. Second-generation models relax the assumption of indivisible goods and use bargaining theory (or related mechanisms) to endogenize prices. Variations of these models are applied to financial asset markets and intermediation. Assets and goods are both divisible in third-generation models, which makes them better suited to policy analysis and empirical work. This framework can also be used to help understand financial markets and liquidity.
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Pub Date : 2019-05-23DOI: 10.1093/ACREFORE/9780190625979.013.303
E. Cavallo
Sudden stops in capital flows are a form of financial whiplash that creates instability and crises in the affected economies. Sudden stops in net capital flows trigger current account reversals as countries that were borrowing on net from the rest of the world before the stop can no longer finance current account deficits. Sudden stops in gross capital flows are associated with financial instability, especially when the gross flows are dominated by volatile cross-border banking flows. Sudden stops in gross and net capital flows are episodes with an external trigger. This implies that the spark that ignites sudden stops originates outside the affected country: more specifically, in the supply of foreign financing that can halt for reasons that may be unrelated to the affected country’s domestic conditions. Yet a spark cannot generate a fire unless combustible materials are around. The literature has established that a set of domestic macroeconomic fundamentals are the combustible materials that make some countries more vulnerable than others. Higher fiscal deficits, larger current account deficits, and higher levels of foreign currency debts in the domestic financial system are manifestations of weak fundamentals that increase vulnerability. Those same factors increase the costs in terms of output losses when the crisis materializes. On the flip side, international reserves provide buffers that can help countries offset the risks. Holding foreign currency reserves hedges the fiscal position of the government providing it with more resources to respond to the crisis. While it may be impossible for countries to completely insulate themselves from the volatility of capital inflows, the choice of antidotes to prevent that volatility from forcing potentially costly external adjustments is in their own hands. The global financial architecture can be improved to support those efforts if countries could agree on and fund a more powerful international lender of last resort that resembles, at the global scale, the role of the Federal Reserve Bank in promoting financial stability in the United States.
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