Heterogeneity in the Effect of Common Shocks on Healthcare Expenditure Growth

Health care expenditure growth is affected by important unobserved common shocks such as technological innovation, changes in sociological factors, shifts in preferences and the epidemiology of diseases. While common factors impact in principle all countries, their effect is likely to differ across countries. To allow for unobserved heterogeneity in the effects of common shocks, we estimate a panel data model of health care expenditure growth in 34 OECD countries over the years 1980 to 2012 where the usual fixed or random effects are replaced by a multifactor error structure. We address model uncertainty with Bayesian Model Averaging, to identify a small set of important expenditure drivers from 43 potential candidates. We establish 16 significant drivers of healthcare expenditure growth, including growth in GDP per capita and in insurance premiums, changes in financing arrangements and some institutional characteristics, expenditures on pharmaceuticals, population aging, costs of health administration, and inpatient care. Our approach allows us to derive estimates that are less subject to bias than in previous analyses, and provide robust evidence to policy makers on the drivers that were most strongly associated with the growth in health care expenditures over the past 32 years

Estimating healthcare demand for an aging population: a flexible and robust bayesian joint model

In this paper, we analyse two frequently used measures of the demand for health care, namely hospital visits and out-of-pocket health care expenditure, which have been analysed separately in the existing literature. Given that these two measures of healthcare demand are highly likely to be closely correlated, we propose a framework to jointly model hospital visits and out-of-pocket medical expenditure. Furthermore, the joint framework allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modelled robustly with the random effects following Dirichlet process priors with explicit cross-part correlation. The findings of our empirical analysis of the U.S. Health and Retirement Survey indicate that the demand for healthcare varies with age and gender and exhibits significant cross-part correlation that provides a rich understanding of how aging affects health care demand, which is of particular policy relevance in the context of an aging population

Heterogeneity in the Effect of Common Shocks on Health Care Expenditure Growth

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Healthcare expenditure growth is affected by important unobserved common shocks such as technological innovation, changes in sociological factors, shifts in preferences, and the epidemiology of diseases. While common factors impact in principle all countries, their effect is likely to differ across countries. To allow for unobserved heterogeneity in the effects of common shocks, we estimate a panel data model of healthcare expenditure growth in 34 OECD countries over the years 1980 to 2012, where the usual fixed or random effects are replaced by a multifactor error structure. We address model uncertainty with Bayesian model averaging, to identify a small set of robust expenditure drivers from 43 potential candidates. We establish 16 significant drivers of healthcare expenditure growth, including growth in GDP per capita and in insurance premiums, changes in financing arrangements and some institutional characteristics, expenditures on pharmaceuticals, population ageing, costs of health administration, and inpatient care. Our approach allows us to provide robust evidence to policy makers on the drivers that were most strongly associated with the growth in healthcare expenditures over the past 32 years

Estimating Health Care Costs Among Fragile and Conflict Affected States: an Elastic Net-Risk Measures Approach

Fragile and conflict affected states (FCAS) are those in which the government lacks the political will and/or capacity to provide the basic functions necessary for poverty reduction, economic development, and the security of human rights of their populations.Until recent history, unfortunately, the majority of research conducted and universal health care debates have been centered around middle income and emerging economies. As a result, FCAS have been neglected from many global discussions and decisions. Due to this neglect, many FCAS do not have proper vaccinations and antibiotics. Seemingly, well estimated health care costs are a necessary stepping stone in improving the health of citizens among FCAS. Fortunately, developments in statistical learning theory combined with data obtained by the WBG and Transparency International make it possible to accurately model health care cost among FCAS. The data used in this paper consisted of 35 countries and 89 variables. Of these 89 variables, health care expenditure (HCE) was the only response variable. With 88 predictor variables, there was expected to be multicollinearity, which occurs when multiple variables share relatively large absolute correlation. Since multicollinearity is expected and the number of variables is far greater than the number of observations, this paper adopts Zou and Hastie\u27s method of regularization via elastic net (ENET). In order to accurately estimate the maximum and expected maximum HCE among FCAS, well-known risk measures, such as Value at Risk and Conditional Value at Risk, and related quantities were obtained via Monte Carlo simulations. This paper obtained risk measures at 95 security level

PROJECTIONS OF DEMAND FOR HEALTHCARE IN IRELAND, 2015-2030: FIRST REPORT FROM THE HIPPOCRATES MODEL. ESRI RESEARCH SERIES NUMBER 67 OCTOBER 2017

This report provides baseline estimates and projections of public and private healthcare demand for Irish health and social care services for the years 2015–2030. This is the first report to be published applying the Hippocrates projection model of Irish healthcare demand and expenditure which has been developed at the ESRI in a programme of research funded by the Department of Health. Development of the model has required a very detailed analysis of the services used in Irish health and social care in 2015. This is the most comprehensive mapping of both public and private activity in the Irish healthcare system to have been published for Ireland

Heterogeneity in Longitudinal Healthcare Utilisation by Older Adults: A Latent Transition Analysis of the Irish Longitudinal Study on Ageing

BACKGROUND: Older adults likely exhibit considerable differences in healthcare need and usage. Identifying differences in healthcare utilisation both between and within individuals over time may support future service development. OBJECTIVES: To characterise temporal changes in healthcare utilisation among a nationally representative sample of community-dwelling older adults. METHODS: A latent transition analysis of the first three waves of The Irish Longitudinal Study on Ageing (TILDA) (N = 6128) was conducted. RESULTS: Three latent classes of healthcare utilisation were identified, ‘primary care only’; ‘primary care and outpatient visits’ and ‘multiple utilisation’. The classes were invariant across all three waves. Transition probabilities indicated dynamic changes over time, particularly for the ‘primary care and outpatient visits’ and ‘multiple utilisation’ statuses. DISCUSSION: Older adults exhibit temporal changes in healthcare utilisation which may reflect changes in healthcare need and disease progression. Further research is required to identify the factors which influence movement between healthcare utilisation patterns

Are the dimensions of private information more multiple than expected? Information asymmetries in the market of supplementary private health insurance in England

Our study reexamines standard econometric approaches for the detection of information asymmetries on insurance markets. We claim that evidence based on a standard framework with 2 equations, which uses potential sources of information asymmetries, should stress the importance of heterogeneity in the parameters. We argue that conclusions derived from this methodology can be misleading if the estimated coefficients in such an `unused characteristics' framework are driven by different parts of the population. We show formally that an individual's expected risk from the perspective of insurance, conditioned on certain characteristics (which are not used for calculating the risk premium), can equal the population's expectation in risk { although such characteristics are both related to risk and insurance probability, which is usually interpreted as an indicator of information asymmetries. We provide empirical evidence on the existence of information asymmetries in the market for supplementary private health insurance in the UK. Overall, we found evidence for advantageous selection into the private risk pool; ie people with lower health risk tend to insure more. The main drivers of this phenomenon seem to be characteristics such as income and wealth. Nevertheless, we also found parameter heterogeneity to be relevant, leading to possible misinterpretation if the standard `unused characteristics' approach is applied

Formal and Informal Care: An Empirical Bayesian Analysis Using the Two-Part Model

Informal care provided to the elderly by their children is proposed as a less expensive alternative to institutional long-term care. This paper explores how the elderly\u27s consumption of medical care changes in response to changes in the informal care they receive from their children. Many earlier studies have ignored both the endogeneity of informal care and the complicated nature of health care utilization data. This paper develops a two-part model with informal care treated as an endogenous regressor and imposes exclusion restrictions on the selection process. The model is fitted using the Bayesian Markov Chain Monte Carlo (MCMC) methods, in particular the Gibbs sampler and the Metropolis-Hasting algorithm. The average treatment effects and the distributions of the treatment effects are obtained via posterior simulation. The results indicate that informal care provides a substitute for nursing home care and hospital inpatient care, but it does not affect paid home health care on average. The treatment effects are heterogeneous. The largest substitution effects occur for nursing home and hospital inpatient care at the intensive margin. The policy analysis suggests that informal care policies targeting the group that incurs the largest substitution effect may help to reduce government spending on Medicaid and Medicare

Discrete event simulation model for planning Level 2 “step-down” bed needs using NEMS

In highly congested hospitals it may be common for patients to overstay at Intensive Care Units (ICU) due to blockages and imbalances in capacity. This is inadequate clinically, as patients occupy a service they no longer need; operationally, as it disrupts flow from upstream units; and financially as ICU beds are more expensive than ward beds. Step-down beds, also known as Level 2 beds, have become an increasingly popular and less expensive alternative to ICU beds to deal with this issue. We developed a discrete event simulation model that estimates Level 2 bed needs for a large university hospital. The model innovates by simulating the entirety of the hospital’s inpatient flow and most importantly, the ICU’s daily stochastic flows based on a nursing workload scoring metrics called “Nine Equivalents of Nursing Manpower Use Score” (NEMS). Using data from a large academic hospital, the model shows the benefits of Level 2 beds in improving both patient flow and costs

The cost and cost-effectiveness of alternative strategies to expand treatment to HIV-positive South Africans: scale economies and outreach costs

This repository item contains a single issue of the Health and Development Discussion Papers, an informal working paper series that began publishing in 2002 by the Boston University Center for Global Health and Development. It is intended to help the Center and individual authors to disseminate work that is being prepared for journal publication or that is not appropriate for journal publication but might still have value to readers.The South African government is currently discussing various alternative approaches to the further expansion of antiretroviral treatment (ART) in public-sector facilities. We used the EMOD-HIV model, a HIV transmission model which projects South African HIV incidence and prevalence and ARV treatment by age-group for alternative combinations of treatment eligibility criteria and testing, to generate 12 epidemiological scenarios. Using data from our own bottom-up cost analyses in South Africa, we separate outpatient cost into nonscale- dependent costs (drugs and laboratory tests) and scale-dependent cost (staff, space, equipment and overheads) and model the cost of production according to the expected future number and size of clinics. On the demand side, we include the cost of creating and sustaining the projected incremental demand for testing and treatment. Previous research with EMOD-HIV has shown that more vigorous recruitment of patients with CD4 counts less than 350 is an advantageous policy over a five-year horizon. Over 20 years, however, the model assumption that a person on treatment is 92% less infectious improves the cost-effectiveness of higher eligibility thresholds, averting HIV infections for between $1,700 and$2,800, while more vigorous expansion under the current guidelines would cost more than $7,500 per incremental HIV infection averted. Based on analysis of the sensitivity of the results to 1,728 alternative parameter combinations at each of four discount rates, we conclude that better knowledge of the behavioral elasticities could reduce the uncertainty of cost estimates by a factor of 4 to 10