Optimality of no-fault medical liability systems

This paper considers a model of defensive medicine where doctors are imperfect agents of insured patients. A national insurer subsidises both curative and preventive medical care consumed by risk averse patients. We show that in such an environment, the optimal liability regime is similar to the no-fault systems of Sweden and New Zealand where the doctor faces zero liability. The reason is that the subsidy on preventive medicine is a better instrument to induce the optimal level of care than the malpractice regime.no-fault liability systems, malpractice liability, defensive medicine, copayment ratio

Inequality and Health: Is Housing Crowding the Link?

In this study we extend the literature (e.g. Deaton, 2002a; Kennedy and Kawachi, 1996; Wilkinson, 1996) by proposing a new mechanism through which income inequality can influence health. We argue that increased income inequality induces household crowding, which in turn leads to increased rates of infectious diseases. We use data from New Zealand that links hospital discharge rates with community-level characteristics to explore this hypothesis. Our results provide support for a differential effect of income inequality and housing crowding on rates of hospital admissions for infectious diseases among children. Importantly, we find that genetic and non-communicable diseases do not show these joint crowding and inequality effects. The effect of housing on communicable diseases provides a biological foundation for an income inequality gradient.Housing crowding, child health outcomes, income inequality

Stunting and Selection Effects of Famine: A Case Study of the Great Chinese Famine

Many developing countries experience famine. If survival is related to height, the increasingly common practice of using height as a measure of well-being may be misleading. We devise a novel method for disentangling the stunting from the selection effects of famine. Using data from the 1959-1961 Great Chinese Famine, we find that taller children were more likely to survive the famine. Controlling for selection, we estimate that children under the age of five who survived the famine grew up to be 1 to 2 cm shorter. Our results suggest that average height is potentially a biased measure of economic conditions during childhood.Famine, height, China, panel data

Parallel Private Health Insurance in Australia: A Cautionary Tale and Lessons for Canada

Canada's restrictions on the role of private health insurance for publicly insured physician and hospital services are unique among countries with universal, publicly funded health care systems. Pressure is mounting in Canada, however, to loosen these restrictions and create a parallel system of private finance. Advocates argue that creation of a parallel system of private finance will ensure the sustainability of the public system (by reducing public cost pressures), improve access to the public system (e.g., by reducing wait times), and improve quality in the public system (through competition). Opponents of parallel private finance argue that it will create "two-tiered" medicine, increase costs, compromise equity and reduce quality and access to publicly financed health care as those with the financial means (and often the strongest voice) exit to private insurance. Australia provides a particularly promising case study for Canada regarding the dynamics of parallel systems of public and private finance. This paper examines Australia's experience with parallel finance for inpatient hospital services to provide insight regarding: (a) the effectiveness of a parallel system of private finance in reducing costs and wait times in the public system; (b) risk selection between the parallel public and private insurance sectors; (c) the financial redistribution associated with the introduction and maintenance of a parallel system of finance; and (d) the dynamics of the broader political economy associated with parallel systems of finance. Australia's experience provides a number of lessons for Canada, including: (1) the potential for cost savings through introduction or expansion of a parallel private sector is very limited; (2) the introduction or expansion of a parallel private finance is unlikely to reduce wait times in the publicly financed system; (3) there is no simple way to regulate private insurers to pursue public objectives; (4) it is impossible to create an independent, isolated parallel system of private finance — interactions between the public and private insurance sectors are complex and unavoidable; (5) quality plays a key role in driving the dynamics between the public and privately financed sectors; and (6) it is essential to articulate clear policy objectives for health care financing and to design public and private roles consistent with these objectives. Our overall conclusion is that the Australian experience provides a cautionary tale regarding the risks, costs and benefits of a parallel private system of health care finance.

ドゥメイン投票法は日本の少子化対策になるか？

日本の少子化と高齢化が新たな政策を必要としていることは国民の一致した認識である。さらに、出生率と関係のある育児の応援などの必要性も広く認識されてはいるが、日本の家族援助政策は他の先進国に比べると依然として見劣りする。この問題認識と実施されている対策の不一致の理由として、少子化・高齢化にともなう有権者の年齢分布が考えられる。つまり、退職者や退職間近な高齢の有権者の数の相対的増加にともない、次世代である子供や次世代の代表である子供の親の政治的影響力の低化である。この状況を変える方策として、親が子供の代わりに票を投じるドゥメイン(Demeny)投票と呼ばれる投票法が考えられる。導入による世代間の政治的影響力の是正により、家庭に対する政策が手厚くなり、出生率が上昇すると推測できる。

High-frequency Internet survey of a probability sample of older Singaporeans: The Singapore Life Panel

Ministry of Education, Singapore under its Academic Research Funding Tier

Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study

Purpose: Whilst survival in paediatric critical care has improved, clinicians lack tools capable of predicting long-term outcomes. We developed a machine learning model to predict poor school outcomes in children surviving intensive care unit (ICU). Methods: Population-based study of children < 16 years requiring ICU admission in Queensland, Australia, between 1997 and 2019. Failure to meet the National Minimum Standard (NMS) in the National Assessment Program-Literacy and Numeracy (NAPLAN) assessment during primary and secondary school was the primary outcome. Routine ICU information was used to train machine learning classifiers. Models were trained, validated and tested using stratified nested cross-validation. Results: 13,957 childhood ICU survivors with 37,200 corresponding NAPLAN tests after a median follow-up duration of 6 years were included. 14.7%, 17%, 15.6% and 16.6% failed to meet NMS in school grades 3, 5, 7 and 9. The model demonstrated an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.8 (standard deviation SD, 0.01), with 51% specificity to reach 85% sensitivity [relative Area Under the Precision Recall Curve (rel-AUPRC) 3.42, SD 0.06]. Socio-economic status, illness severity, and neurological, congenital, and genetic disorders contributed most to the predictions. In children with no comorbidities admitted between 2009 and 2019, the model achieved a AUROC of 0.77 (SD 0.03) and a rel-AUPRC of 3.31 (SD 0.42). Conclusion: A machine learning model using data available at time of ICU discharge predicted failure to meet minimum educational requirements at school age. Implementation of this prediction tool could assist in prioritizing patients for follow-up and targeting of rehabilitative measures. Keywords: Child, Intensive care, Machine learning, Neurodevelopment, Schoo