Health Expenditure Data Research Articles

Invited Commentary

Invited Commentary

Health expenditure data for policy: Health accounts, national accounts or both?

Compatibility of statistical frameworks and comparability of data are aspects of statistical quality. This paper explores comparability of data from National Accounts (NA) and Care Accounts/health accounts (CA&HA) of the Netherlands. Although based on the same sources, differences result from specificities of each framework, making data adjustments necessary. Data comparison of major aggregates and household spending is a means for verification and for triangulation of sources. Monitoring household spending on health is one of the Sustainable Development Goals. The usability of NA data for household consumption estimates is key to judge plausibility of household spending levels. However, definitions, coverage and valuation in NA and CA&HA should be understood to benefit from the use of NA data for HA. More than in the concepts used the strength of NA is the way NA are usually produced compared with HA. Key is the integrated analysis including supply and demand to verify the comprehensiveness and consistency. It is concluded that SUT data of NA on consumption of human health and social care can be used for judging plausibility of HA household spending estimates, and, in the absence of the latter, NA data can directly be used. The case of the Netherlands shows that policy measures can have a large impact on the validity of using NA for the estimation of household spending.

Have bailouts shifted the burden of paying for healthcare from the state onto individuals?

The financial crisis that enveloped Europe in 2009 created financial pressure for governments and required a number of countries to obtain a financial bailout from the IMF. The purpose of this paper is to examine the effect of the financial crisis on public health expenditure in bailout countries and if bailouts shift the burden of paying for healthcare from the state onto individuals. Quantitative health expenditure data were collected from the WHO and OECD for the period 2004-2015 and evaluated using a comparison of means Welch's t test. The majority of bailout countries recorded a decrease in public health expenditure as a percentage of total government expenditure, with Ireland recording the largest decrease with government health expenditure as a percentage of total government expenditure, falling by 22% (P < .01). In addition, the results also suggest that the burden of paying for healthcare shifted from the state onto individuals in three countries, namely Hungary, Ireland and Portugal, where public health expenditure declined and private expenditure increased significantly. The ramifications of shifting the burden of paying for healthcare from the state onto individuals at this point remain unclear with further research required to identify the long-term consequences for healthcare.

Device clinical trials: the importance of “repurposing” technology

As we all know, the US is facing a cost crisis in healthcare. As a share of the nation’s gross domestic product, healthcare accounted for 17.9% in 2016 as reported in the National Health Expenditure Data from the Centers for Medicare and Medicaid Services (1). Health care economists project that this will continue to increase on an annual basis. Cost containment is essential; but what is really driving these expenditures?

Determination of the relationship between patient satisfaction and some global economic indicators using multidimensional scaling.

The importance of labor that contributes to the economy and economic power of the country is increasing recently. There is a strong link between health and economy. People are happier, more productive, and provide more contribution to the economy in communities of healthy individuals. In countries with strong economy, serious economic investments are made in the field of health to grow healthy individuals. The purpose of this study is to determine whether patient satisfaction in primary healthcare services is related to economic strength of countries. The data of European Patients Evaluate General/Family Practice (EUROPEP) scale from 2011 at 17 Organization for Economic Co-operation and Development (OECD) countries are used. The data were compiled from OECD reports and Republic of Turkey Ministry of Health Refik Saydam Hygiene Center Presidency School of Public Health patient satisfaction with primary healthcare services reports. 17 OECD member countries in 2011 health expenditure data, some health indicators, and patient satisfaction are determined to show how grouping in two-dimensional space with the multidimensional scaling. It was observed to vary by countries and groupings that they located in terms of all three criteria. In some countries' economic and health indicators, although quite high compared to the OECD average, citizen satisfaction of healthcare services was low. In some countries, although health expenditure and health indicators are far below the OECD average, citizens' satisfaction with health services has proved to be very high. Multidimensional scaling analysis findings reveal that countries have different positions and groups in terms of each three indicators. According to these results, it cannot be said that high expenditures in the field of health will affect patients satisfaction. Having a strong economy or spending too much money on health does not increase human satisfaction in health care. Effective expenditures on the field of health will increase healthcare service satisfaction. Policy-makers should consider international criteria and take the right steps according to citizens' expectation and satisfaction of healthcare service to implement effective spending.

The economic burden of cancer care in Canada: a population-based cost study.

Resource and cost issues are a growing concern in health care. Thus, it is important to have an accurate estimate of the economic burden of care. Previous work has estimated the economic burden of cancer care for Canada; however, there is some concern this estimate is too low. The objective of this analysis was to provide a comprehensive revised estimate of this burden. We used a case-control prevalence-based approach to estimate direct annual cancer costs from 2005 to 2012. We used patient-level administrative health care data from Ontario to correctly attribute health care costs to cancer. We employed the net cost method (cost difference between patients with cancer and control subjects without cancer) to account for costs directly and indirectly related to cancer and its sequelae. Using average patient-level cost estimates from Ontario, we applied proportions from national health expenditures data to obtain the economic burden of cancer care for Canada. All costs were adjusted to 2015 Canadian dollars. Costs of cancer care rose steadily over our analysis period, from $2.9 billion in 2005 to $7.5 billion in 2012, mostly owing to the increase in costs of hospital-based care. Most expenditures for health care services increased over time, with chemotherapy and radiation therapy expenditures accounting for the largest increases over the study period. Our cost estimates were larger than those in the Economic Burden of Illness in Canada 2005-2008 report for every year except 2005 and 2006. The economic burden of cancer care in Canada is substantial. Further research is needed to understand how the economic burden of cancer compares to that of other diseases.

Data-driven screening for type 2 diabetes: Machine Learning on Belgian Health Expenditure Data

Het is uitzonderlijk dat TBV een dissertatie in Engineering Science bespreekt. Marc Claesen ging echter aan de slag met data van een mutualiteit. Mutualiteiten bieden verplichte ziekteverzekeringen aan in Belgie. Via die ziekteverzekering worden onder meer uitkeringen voor arbeidsongeschiktheden langer dan een maand gedeeltelijk vergoed en tussenkomsten voor geneesmiddelen en consultaties uitbetaald.

Cost-effectiveness of home telemonitoring in chronic kidney disease patients at different stages by a pragmatic randomized controlled trial (eNephro): rationale and study design

BackgroundHome telemonitoring has developed considerably over recent years in chronic diseases in order to improve communication between healthcare professionals and patients and to promote early detection of deteriorating health status. In the nephrology setting, home telemonitoring has been evaluated in home dialysis patients but data are scarce concerning chronic kidney disease (CKD) patients before and after renal replacement therapy. The eNephro study is designed to assess the cost effectiveness, clinical/biological impact, and patient perception of a home telemonitoring for CKD patients. Our purpose is to present the rationale, design and organisational aspects of this study.MethodseNephro is a pragmatic randomised controlled trial, comparing home telemonitoring versus usual care in three populations of CKD patients: stage 3B/4 (n = 320); stage 5D CKD on dialysis (n = 260); stage 5 T CKD treated with transplantation (n= 260). Five hospitals and three not-for-profit providers managing self-care dialysis situated in three administrative regions in France are participating. The trial began in December 2015, with a scheduled 12-month inclusion period and 12 months follow-up. Outcomes include clinical and biological data (e.g. blood pressure, haemoglobin) collected from patient records, perceived health status (e.g. health related quality of life) collected from self-administered questionnaires, and health expenditure data retrieved from the French health insurance database (SNIIRAM) using a probabilistic matching procedure.DiscussionThe hypothesis is that home telemonitoring enables better control of clinical and biological parameters as well as improved perceived health status. This better control should limit emergency consultations and hospitalisations leading to decreased healthcare expenditure, compensating for the financial investment due to the telemedicine system.Trial registrationThis study has been registered at ClinicalTrials.gov under NCT02082093 (date of registration: February 14, 2014).

Machine-Learning Algorithms to Code Public Health Spending Accounts.

Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation.

A literature-based economic evaluation of healthcare preventable adverse events in Europe.

To establish from the literature, cost of preventable adverse events (PAEs) to member states of the Joint Action European Union Network for Patient Safety and Quality of Care. We searched MEDLINE, EMBASE and CINAHL for studies in Europe estimating cost of adverse events (AEs) and PAEs (2000-March 2016). Using data from the literature, we estimated PAE costs based on national 2013 total health expenditure (THE) data reported by World Health Organization and converted to 2015 Euros. Information on type, frequency and incremental cost per episode or estimated cost of AEs was extracted. Total annual disability-adjusted life years (DALYs) resulting from PAEs in 30 EU nations were calculated using an estimate from a published study and adjusted for the percentage of AEs considered preventable. Published estimates of costs of AEs and PAEs vary based on the care setting, methodology, population and year conducted. Only one study was from primary care, the majority were conducted in acute care. Nine studies estimated percentage of THE caused by AEs, 13 studies calculated attributable length of stay. We estimated the annual cost of PAEs to the 30 nations in 2015 to be in the range of 17-38 billion Euros, total DALYs lost from AEs as 3.5 million, of which 1.5 million DALYs were likely due to PAEs. The economic burden of AEs and PAEs is substantial. However, whether patient safety interventions will be 'cost saving' depends on the effectiveness and costs of the interventions.

Modeling zero-modified count and semicontinuous data in health services research part 2: case studies.

This article is the second installment of a two-part tutorial on the analysis of zero-modified count and semicontinuous data. Part 1, which appears as a companion piece in this issue of Statistics in Medicine, provides a general background and overview of the topic, with particular emphasis on applications to health services research. Here, we present three case studies highlighting various approaches for the analysis of zero-modified data. The first case study describes methods for analyzing zero-inflated longitudinal count data. Case study 2 considers the use of hurdle models for the analysis of spatiotemporal count data. The third case study discusses an application of marginalized two-part models to the analysis of semicontinuous health expenditure data. Copyright © 2016 John Wiley & Sons, Ltd.

Impact of Income Inequality on the Nation's Health

Income inequality in the United States has been increasing in recent decades. It is unclear whether income inequality has an independent effect on health outcomes, or whether it simply correlates with increasing levels of poverty. The goal of this study was to evaluate whether income inequality is significantly associated with US county health care expenditures and health care use. Cross-sectional analysis of county health expenditure data from the Health Resources and Services Administration's Area Resources File, county income inequality measures (Gini coefficient) from the Census' American Community Survey, and estimates of potentially preventable admissions and potentially discretionary procedures from the Nationwide Inpatient Sample (1998 to 2011). Datasets were linked via county Federal Information Processing Standard codes. Multivariable linear and Poisson regression analyses were performed at the county level adjusting for county characteristics. A total of 1,237 counties (of 3,144) were included. Income inequality was associated with higher health care expenditures, with each 1 percentage-point increase in county Gini coefficient associated with a US$40,008 increase in annual county Medicare cost (p= 0.003), and an increase of 174.7 total county Medicare inpatient days per year (p < 0.001). Even after accounting for poverty level and county characteristics, counties with higher inequality had higher potentially preventable admission (eg 4.86 rate ratio for low-birth-weight hospital admissions in the top income inequality quartile compared with bottom quartile; p < 0.001) and a higher incidence of potentially discretionary procedures (eg 1.79 rate ratio for prostatectomy for benign prostatic hyperplasia in the top income inequality quartile compared with bottom quartile; p < 0.001). Income inequality is independently associated with higher health care expenditures and more health care use, with increases in both potentially discretionary procedures and in potentially preventable admissions.

An Econometric Analysis Of Health Care Utilization In Kenya

Background: Increasing access to health care has been a policy concern for many governments, Kenya included. The Kenyan government introduced and implemented a number of initiatives in a bid to address the healthcare utilization challenge. These initiatives include 10/20 policy, exemptions for user fees for some specific health services (treatment of children less than five years, maternity services in dispensaries and health centers, Tuberculosis treatment in public health facilities), and increase in the number of health facilities and health workforce. These initiatives notwithstanding, healthcare utilization in Kenya remains a challenge. The Kenya Household Health Expenditure and Utilization Survey of 2007 found that 17 percent of those who needed health care services could not access the services from both government and private health facilities largely due to financial constraints. This paper employed econometric analysis to examine what could be constraining health care utilization in Kenya despite all the efforts employed. Methods: Using the 2007 Kenya Household Health Expenditures and Utilization Survey (KHHEUS) data (n = 8414), this paper investigates the factors that affect health care utilization in Kenya by estimating a count data negative binomial model. The model was also applied to public and private health facilities to better understand the specificities of poverty in these two facility types. Common estimation problems of endogeneity, heterogeneity, multicollinearity and heteroskedasticity are addressed. Findings: The econometric analysis reveals that out-of-pocket expenditures, waiting time, distance, household size, income, chronic illness area of residence and working status of the household head are significant factors affecting health care utilization in Kenya. While income and distance are significant factors affecting public health care utilization they are not significant in explaining healthcare utilization in private facilities. In addition, working status of the household head, insurance cover and education are significant in explaining private and not public health care utilization. A striking finding is the positive relationship between distance and health care utilization implying that people will travel long distances to obtain treatment. This is perhaps associated with expectations of higher quality of care at far away higher level facilities, especially in rural areas. Conclusion: The paper confirms the existing evidence of the negative effects of Out-of-Pocket (OOP) expenditures and other determinants of health care utilization. With a better understanding of why people use or do not use health services, health care organizations can seek to improve the quality of human life. The bypassing of health facilities for higher level far away facilities implies that it is not so much about availing health facilities, but the quality of the services offered in those facilities. The government should therefore assure quality to increase utilization of the lower level facilities, especially in the rural areas.

Catastrophic Health Expenditures And Impoverishment In Kenya

Background: Out-of-pocket health expenditures leave households exposed to the risk of financial catastrophe and poverty whenever they entail significant dissaving or the sale of key household assets. Even relatively small expenditures on health can be financially disastrous for poor households and similarly, large health care expenditures can lead to financial catastrophe and bankruptcy for rich households. Objective: There is increasing evidence that out-of-pocket expenditures act as a financial barrier to accessing health care, and are a source of catastrophic expenditures and impoverishment. This paper estimates the burden of out-of-pocket payments in Kenya; the incidence and intensity of catastrophic health care expenditure and impoverishment in Kenya. Methods: Using Kenya Household Health Expenditures and Utilization Survey data of 2007, the study uses both descriptive and econometric analysis to investigate the incidence and intensity of catastrophic health expenditures and impoverishment as well as the determinants of catastrophic health expenditures. To estimate the incidence and intensity of catastrophic expenditures and impoverishment, the study used both Wagstaff and van Doorslaer, (2002) and Xu et al. (2005) and applied various thresholds to demonstrate the sensitivity of catastrophic measures. For determinants of catastrophic health expenditures, a logit model was employed. Findings: Among those who utilized health care, 11.7 percent experienced catastrophic expenditures and 4 percent were impoverished by health care payments. In addition, approximately 2.5 million individuals were pushed into poverty as a result of paying for health care. The poor experienced the highest incidence of catastrophic expenditures. Conclusion: The paper recommends that the government should establish avenues for reducing the burden of out-of-pocket expenditures borne by households. This could be through a legal requirement for everyone to belong to a health insurance and targeting the poor, the elderly and chronically ill through the devolved system of the government and devolved funds.

Is Development Assistance for Health fungible? Findings from a mixed methods case study in Tanzania

The amount of Development Assistance for Health (DAH) available to low- and middle-income countries has increased exponentially over the past decade. However, there are concerns that DAH increases have not resulted in increased spending on health at the country level. This is because DAH may be fungible, resulting from the recipient government decreasing its contribution to the health sector as a result of external funding. The aim of this research is to assess whether DAH funds in Tanzania are fungible, by exploring government substitution of its own resources across sectors and within the health sector.A database containing 28140 projects of DAH expenditure between 2000 and 2010 was compiled from the Organisation for Economic Co-operation and Development’s Creditor Reporting System (OECD-CRS) and AidData databases. Government health expenditure data for the same period were obtained from the Government of Tanzania, World Bank, public expenditure reviews and budget speeches and analysed to assess the degree of government substitution. 22 semi-structured interviews were conducted with Development Partners (DPs), government and non-government stakeholders between April and June 2012 to explore stakeholder perceptions of fungibility.We found some evidence of substitution of government funds at the health sector and sub-sector levels and two mechanisms through which it takes place: the resource allocation process and macro-economic factors. We found fungibility of external funds may not necessarily be detrimental to Tanzania’s development (as evidence suggests the funds displaced may be reallocated to education) and the mechanisms used by DPs to prevent substitution were largely ineffective.We recommend DPs engage more effectively in the priority-setting process, not just with the Ministry of Health and Social Welfare (MoHSW), but also with the Ministry of Finance, to agree on priorities and mutual funding responsibilities at a macroeconomic level. We also call for more qualitative research on fungibility.

Voluntary Health Insurance expenditure in low- and middle-income countries: Exploring trends during 1995-2012 and policy implications for progress towards universal health coverage.

BackgroundMost low- and middle-income countries (LMIC) rely significantly on private health expenditure in the form of out-of-pocket payments (OOP) and voluntary health insurance (VHI). This paper assesses VHI expenditure trends in LMIC and explores possible explanations. This illuminates challenges deriving from changes in VHI expenditure as countries aim to progress equitably towards universal health coverage (UHC).MethodsHealth expenditure data was retrieved from the WHO Global Health Expenditure Database to calculate VHI, OOP and general government health (GGHE) expenditure as a share of total health expenditure (THE) for the period of 1995–2012. A literature analysis offered potential reasons for trends in countries and regions.ResultsIn 2012, VHI as a percentage of THE (abbreviated as VHI%) was below 1 % in 49 out of 138 LMIC. Twenty-seven countries had no or more than five years of data missing. VHI% ranged from 1 to 5 % in 39 LMIC and was above 5 % in 23 LMIC. There is an upwards average trend in VHI% across all regions. However, increases in VHI% cannot be consistently linked with OOP falling or being redirected into private prepayment. There are various countries which exhibit rising VHI alongside a rise in OOP and fall in GGHE, which is a less desirable path in order to equitably progress towards UHC.Discussion and ConclusionReasons for the VHI expenditure trends across LMIC include: external influences; government policies on the role of VHI and its regulation; and willingness and ability of the population to enrol in VHI schemes. Many countries have paid insufficient attention to the potentially risky role of VHI for equitable progress towards UHC. Expanding VHI markets bear the risk of increasing fragmentation and inequities. To avoid this, health financing strategies need to be clear regarding the role given to VHI on the path towards UHC.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-016-0353-5) contains supplementary material, which is available to authorized users.

The demand for medical care services: evidence from Kuwait based on households’ out-of-pocket expenses

ABSTRACTThis article used a data set containing information on 1267 households from Kuwait to investigate the determinants of demand for medical care services by examining households’ out-of-pocket expenses. To deal with the problems associated with households’ health expenditure data, a two-part model (TPM) was estimated. Given Kuwait’s demographic composition, the model was estimated for full sample, nationals only and expatriates only. Prior to estimating the model, tests were conducted to select a transformation that reduces problems associated with heteroscedasticity and non-normality of the errors. In addition, tests were performed to determine if differences in the estimated coefficients across population groups were statistically significant.

Determinants of Out-of-Pocket and Catastrophic Health Expenditure: A Cross-sectional Study

Background: In India, Out of Pocket Health Expenditures (OOPHE) is as high as 70-80% of total health expenditures, borne by the families of ailing persons. In most cases such high OOPHE is catastrophic in nature, in the backdrop of high poverty level in the country. High OOPHE and Catastrophic Health Expenditures (CHE) have a potential to impoverish people. It is therefore important to identify the predictors of OOPHE and CHE, to formulate an equitable and efficient financial protection measure from health expenditure. Methods: The study tried to understand the factors of out-of-pocket health expenditure and catastrophic health expenditure using the cross-sectional data from 986 sampled households in Koderma district of the state of Jharkhand in India. A multi-staged sampling method was followed to select households with incidences of in-patient care in the last one and child birth in the last two years and of out-patient care in the last one month. Alongside health expenditure data of the sampled households, their socio-demographic and socio-economic information were also collected using survey questionnaire. Findings: Male headed households, families with more than five members, household head who

Nongovernment Philanthropic Spending on Public Health in the United States.

The objective of this study was to estimate the dollar amount of nongovernment philanthropic spending on public health activities in the United States. Health expenditure data were derived from the US National Health Expenditures Accounts and the US Census Bureau. Results reveal that spending on public health is not disaggregated from health spending in general. The level of philanthropic spending is estimated as, on average, 7% of overall health spending, or about $150 billion annually according to National Health Expenditures Accounts data tables. When a point estimate of charity care provided by hospitals and office-based physicians is added, the value of nongovernment philanthropic expenditures reaches approximately $203 billion, or about 10% of all health spending annually.

Share of health spending on doctors increases

After years of erosion, doctors’ share of health spending has rebounded to levels last seen in the 1980s, according to the Canadian Institute for Health Information’s (CIHI’s) annual release of [national health expenditure data][1]. But it comes from a pie that is slowly shrinking, as health