Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

Objectives: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The objective is to showcase a big data approach that takes advantage of large electronic medical record (EMR) data to emulate clinical trials. To overcome the limitations of regression analysis, a deep learning-based analysis pipeline was developed. Study Design and Setting: Lumpectomy (breast-conserving surgery) and mastectomy are the two most commonly used surgical procedures for early-stage female breast cancer patients. An emulation trial was designed using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data to evaluate their relative effectiveness in overall survival. The analysis pipeline consisted of a propensity score step, a weighted survival analysis step, and a bootstrap inference step. Results: A total of 65,997 subjects were enrolled in the emulated trial, with 50,704 and 15,293 in the lumpectomy and mastectomy arms, respectively. The two surgery procedures had comparable effects in terms of overall survival (survival year change = 0.08, 95% confidence interval (CI): -0.08, 0.25) for the elderly SEER-Medicare early-stage female breast cancer patients. Conclusion: This study demonstrated the power of "mining large EMR data + deep learning-based analysis," and the proposed analysis strategy and technique can be potentially broadly applicable. It provided convincing evidence of the comparative effectiveness of lumpectomy and mastectomy.

Two-level Bayesian interaction analysis for survival data incorporating pathway information.

Genetic interactions play an important role in the progression of complex diseases, providing explanation of variations in disease phenotype missed by main genetic effects. Comparatively, there are fewer studies on survival time, given its challenging characteristics such as censoring. In recent biomedical research, two-level analysis of both genes and their involved pathways has received much attention and been demonstrated as more effective than single-level analysis. However, such analysis is usually limited to main effects. Pathways are not isolated, and their interactions have also been suggested to have important contributions to the prognosis of complex diseases. In this paper, we develop a novel two-level Bayesian interaction analysis approach for survival data. This approach is the first to conduct the analysis of lower-level gene-gene interactions and higher-level pathway-pathway interactions simultaneously. Significantly advancing from the existing Bayesian studies based on the Markov Chain Monte Carlo (MCMC) technique, we propose a variational inference framework based on the accelerated failure time model with effective priors to accommodate two-level selection as well as censoring. Its computational efficiency is much desirable for high-dimensional interaction analysis. We examine performance of the proposed approach using extensive simulation. The application to TCGA melanoma and lung adenocarcinoma data leads to biologically sensible findings with satisfactory prediction accuracy and selection stability.

Human disease clinical treatment network for the elderly: analysis of the medicare inpatient length of stay and readmission data.

Clinical treatment outcomes are the quality and cost targets that health-care providers aim to improve. Most existing outcome analysis focuses on a single disease or all diseases combined. Motivated by the success of molecular and phenotypic human disease networks (HDNs), this article develops a clinical treatment network that describes the interconnections among diseases in terms of inpatient length of stay (LOS) and readmission. Here one node represents one disease, and two nodes are linked with an edge if their LOS and number of readmissions are conditionally dependent. This is the very first HDN that jointly analyzes multiple clinical treatment outcomes at the pan-disease level. To accommodate the unique data characteristics, we propose a modeling approach based on two-part generalized linear models and estimation based on penalized integrative analysis. Analysis is conducted on the Medicare inpatient data of 100,000 randomly selected subjects for the period of January 2010 to December 2018. The resulted network has 1008 edges for 106 nodes. We analyze key network properties including connectivity, module/hub, and temporal variation. The findings are biomedically sensible. For example, high connectivity and hub conditions, such as disorders of lipid metabolism and essential hypertension, are identified. There are also findings that are less/not investigated in the literature. Overall, this study can provide additional insight into diseases' properties and their interconnections and assist more efficient disease management and health-care resources allocation.

A Linguistic Analysis of News Coverage of E-Healthcare in China with a Heterogeneous Graphical Model.

E-healthcare has been envisaged as a major component of the infrastructure of modern healthcare, and has been developing rapidly in China. For healthcare, news media can play an important role in raising public interest and utilization of a particular service and complicating (and, perhaps clouding) debate on public health policy issues. We conducted a linguistic analysis of news reports from January 2015 to June 2021 related to E-healthcare in mainland China, using a heterogeneous graphical modeling approach. This approach can simultaneously cluster the datasets and estimate the conditional dependence relationships of keywords. It was found that there were eight phases of media coverage. The focuses and main topics of media coverage were extracted based on the network hub and module detection. The temporal patterns of media reports were found to be mostly consistent with the policy trend. Specifically, in the policy embryonic period (2015-2016), two phases were obtained, industry management was the main topic, and policy and regulation were the focuses of media coverage. In the policy development period (2017-2019), four phases were discovered. All the four main topics, namely industry development, health care, financial market, and industry management, were present. In 2017 Q3-2017 Q4, the major focuses of media coverage included social security, healthcare and reform, and others. In 2018 Q1, industry regulation and finance became the focuses. In the policy outbreak period (2020-), two phases were discovered. Financial market and industry management were the main topics. Medical insurance and healthcare for the elderly became the focuses. This analysis can offer insights into how the media responds to public policy for E-healthcare, which can be valuable for the government, public health practitioners, health care industry investors, and others.

An emulated target trial analysis based on Medicare data suggested non-inferiority of Dabigatran versus Rivaroxaban.

OBJECTIVES: Rivaroxaban and Dabigatran were the first two non-vitamin K antagonist oral anticoagulants (NOACs) for preventing stroke among non-valvular Atrial Fibrillation patients. This article aimed to evaluate the relative efficacy and safety of Rivaroxaban versus Dabigatran. STUDY DESIGN AND SETTING: An emulated target trial analysis was conducted based on Medicare, in which we constructed three "randomized clinical trials" with well-defined inclusion/exclusion criteria, treatment regimens, and analysis procedures. We analyzed the individual trials, examined temporal variations, and generated unified results via pooled analysis. RESULTS: With a two-year data collection window (2012-2013), 70,129 subjects were enrolled in the three emulated trials, with 36,269 and 34,089 in the Rivaroxaban and Dabigatran arms, respectively. Dabigatran (the reference group for hazard ratio - HR) was superior regarding time to any primary event (including ischemic stroke, other thromboembolic events, major bleeding, and death; HR 1.232, P-value 0.0025), major bleeding (HR 1.187, P-value <0.0001), and mortality (HR 1.488, P-value <0.0001). Differences regarding stroke and other thromboembolic events were not significant. CONCLUSION: Dabigatran was found as superior for the Medicare patients with multiple chronic conditions. Temporal variations, which had been largely neglected in the literature, were observed. This study may provide new insight into treating AF with NOACs.

Human disease clinical treatment network for the elderly: The analysis of medicare inpatient length of stay data.

Disease clinical treatment measures, such as inpatient length of stay (LOS), have been examined for most if not all diseases. Such analysis has important implications for the management and planning of health care, financial, and human resources. In addition, clinical treatment measures can also informatively reflect intrinsic disease properties such as severity. The existing studies mostly focus on either a single disease (or a few pre-selected and closely related diseases) or all diseases combined. In this study, we take a new and innovative perspective, examine the interconnections in length of stay (LOS) among diseases, and construct the very first disease clinical treatment network on LOS. To accommodate uniquely challenging data distributions, a new conditional network construction approach is developed. Based on the constructed network, the analysis of important network properties is conducted. The Medicare data on 100 000 randomly selected subjects for the period of January 2008 to December 2018 is analyzed. The network structure and key properties are found to have sensible biomedical interpretations. Being the very first of its kind, this study can be informative to disease clinical management, advance our understanding of disease interconnections, and foster complex network analysis.

Regional Adoption of Commercial Gene Expression Testing for Prostate Cancer.

IMPORTANCE: Although tissue-based genomic tests can aid in treatment decision-making for patients with prostate cancer, little is known about their clinical adoption. OBJECTIVE: To evaluate regional adoption of genomic testing for prostate cancer and understand common trajectories of uptake shared by regions. DESIGN, SETTING, AND PARTICIPANTS: This dynamic cohort study of patients diagnosed with prostate cancer used administrative claims from Blue Cross Blue Shield Axis, the largest source of commercial health insurance in the US, to characterize temporal trends in the use of commercial, tissue-based genomic testing and calculate the proportion of tested patients at the hospital referral region (HRR) level. Eligible patients from July 1, 2012, through June 30, 2018, were those aged 40 to 89 years with prostate cancer diagnosed from July 1, 2012, through June 30, 2018. MAIN OUTCOMES AND MEASURES: Group-based trajectory modeling was used to classify regions according to discrete trajectories of adoption of commercial, tissue-based genomic testing for prostate cancer. Across regions with distinct trajectories, HRR-level sociodemographic and health care contextual characteristics were compared, using data previously calculated among Medicare beneficiaries. RESULTS: A total of 92 418 men with prostate cancer who met inclusion criteria were identified; the median (interquartile range) age at diagnosis was 60 (56-63) years. Overall, the proportion of patients who received genomic testing increased from 0.8% in July 2012 to June 2013 to 11.3% in July 2017 to June 2018. Trajectory modeling identified 5 distinct regional trajectories of genomic testing adoption. Although less than 1% of patients in each group were tested at baseline, group 1 (lowest adoption) increased to 4.0%. Groups 2 (7.8%), 3 (14.6%), and 4 (17.3%) experienced more modest growth, while in group 5 (highest adoption), use increased to 33.8% of patients tested from June 2017 to July 2018. Compared with regions that more slowly adopted testing, HRRs with the highest rate of adoption (group 5) had higher HRR-level education measures (percentage [SD] with college education: group 1, 25.6% [4.8%]; vs group 2, 27.5% [7.3%]; vs group 3, 30.3% [9.1%]; vs group 4, 29.8% [8.2%]; vs group 5, 30.4% [11.4%]; P for trend = .03), median (SD) household income (group 1, $50 412.8 [$6907.4]; vs group 2, $54 419.6 [$11 324.5]; vs group 3, $61 424.0 [$17 723.8]; vs group 4, $58 508.3 [$15 174.6]; vs group 5, $58 367.0 [$13 180.5]; P for trend = .005), and prostate cancer resources, including clinician density (No. [SD] of clinicians per 100 000: group 1, 2.5 [0.3]; vs group 2, 2.5 [0.5]; vs group 3, 2.6 [0.5]; vs group 4, 2.7 [0.7]; vs group 5, 2.6 [0.5]; P for trend = .04) and prostate cancer screening (percentage [SD] of prostate-specific antigen testing among patients aged 68-74 y: group 1, 29.4% [11.8%]; vs group 2, 32.4% [11.2%]; vs group 3, 33.1% [12.7%]; vs group 4, 36.1% [9.7%]; vs group 5, 28.8% [11.8%]; P for trend = .05). CONCLUSIONS AND RELEVANCE: In this cohort study of patients with prostate cancer, the adoption of commercial tissue-based genomic testing for prostate cancer was highly variable in the US at the regional level and may be associated with contextual measures related to socioeconomic status and patterns of prostate cancer care. These findings highlight factors underlying differential adoption of prognostic technologies for patients with cancer.

Healthcare, Insurance, and Medical Expenditure of the Floating Population in Beijing, China.

Background: China has a large floating population created by the fast urbanization and unique hukou system. With low socioeconomic status, labor-intensive jobs, and the lack of portability of health insurance, the floating population are often disadvantageous in healthcare. However, there is often insufficient attention to healthcare of the floating population. Method: To provide an informative description of certain aspects of the floating population under healthcare, particularly including demographic characteristics, illness conditions, insurance utilization, and medical expenditure, a survey study was conducted in Beijing, China, collecting data on 437 subjects. Characteristics of the floating population and treatments of their illness conditions are examined using univariate and multivariate regression analysis. Results: Personal characteristics and healthcare of the floating population are examined in detail. It is found that the floating population has low insurance coverage and utilization rates. Multiple personal characteristics are identified as significantly associated with insurance utilization and medical expenditure. Conclusions: This study suggests the necessity of further improving healthcare and health insurance protection for the floating population. The identified significant characteristics may assist healthcare providers and other stakeholders identifying the less advantaged.

Racial differences in testicular cancer in the United States: descriptive epidemiology.

BACKGROUND: Testicular cancer (TC) is the most common malignancy in young adult men, and in many countries the incidence rates of testicular cancer have been increasing since the middle of the twentieth century. Since disease presentation and tumor progression patterns are often heterogeneous across racial groups, there may be important racial differences in recent TC trends. METHODS: In this study, Surveillance, Epidemiology, and End Results (SEER) data on TC patients diagnosed between 1973 and 2015 were analyzed, including the following racial/ethnic groups: non-Hispanic whites (NHW), Hispanic whites (HW), blacks, and Asians and Pacific Islanders (API). Patient characteristics, age-adjusted incidence rates, and survival were compared across racial groups. A multivariate Cox model was used to analyze the survival data of TC patients, in order to evaluate racial differences across several relevant factors, including marital status, age group, histologic type, treatment, stage, and tumor location. RESULTS: NHWs had the highest incidence rates, followed by blacks, HWs, and APIs. There were significant survival differences among the racial groups, with NHWs having the highest survival rates and blacks having the lowest. CONCLUSION: An analysis of SEER data showed that racial differences existed among TC patients in the United States with respect to patient characteristics, incidence, and survival. The results can be useful to stakeholders interested in reducing the burden of TC morbidity and mortality.

Human disease cost network analysis.

Diseases can be interconnected. In the recent years, there has been a surge of multidisease studies. Among them, HDN (human disease network) analysis takes a system perspective, examines the interconnections among diseases along with their individual properties, and has demonstrated great potential. Most of the existing HDN analyses are based on either molecular information (which may be unreliable and have limited clinical relevance) or phenotypic measures (which may have limited implications for disease management and not directly reflect disease severity). In this study, we take advantage of the uniquely valuable Taiwan NHIRD (National Health Insurance Research Database) data and conduct an HDN analysis of disease treatment cost. Complementing the existing literature, treatment cost can serve as a surrogate of disease severity (and hence be clinically highly relevant) and also directly describe the financial burden of illness (and hence be uniquely informative for disease management). With inpatient and outpatient treatment data on close to 1 million randomly selected subjects and collected during the period of 2000 to 2013, the human disease cost network is constructed using a novel copula-based approach and the weighted correlation-based network construction technique. Extensive analysis is conducted, and the results are found to be biomedically sensible.

Medical expenditure for middle-aged and elderly in Beijing.

BACKGROUND: High medical expenditures serve as a major obstacle for many people trying to access healthcare. Our goals are to provide an updated and comprehensive description of each category of medical expenditure in inpatient and outpatient treatment, and to identify factors associated with medical expenditures. METHODS: A survey of the middle-aged and elderly was conducted in August 2016 in Beijing, China. Data were collected from 808 random samples. Each participant had reported at least one inpatient or outpatient treatment episode and was 45 years old or older, were collected. Chi-squared tests, t-tests, multivariate analysis, and a linear regression were conducted in the data analysis. RESULTS: A total of 452 and 734 subjects had at least one inpatient and outpatient treatment, respectively. Even though insurance covered a significant amount of the total cost, the remaining out-of-pocket cost was still high, possibly resulting in financial difficulties for a number of the subjects. Demographic and socioeconomic factors were found to be associated with various costs. CONCLUSIONS: Our findings suggest that the government may need to further adjust health care and health insurance systems to alleviate financial burdens caused by illness and improve the effective utilization of healthcare services.

Descriptions of self-treatment for the middle-aged and elderly in Shanxi, China.

OBJECTIVES: Self-treatment is a widespread practice among patients with common symptoms and ailments; it is necessary to explore multiple aspects of it. Notably, there is little research into self-treatment among middle-aged and elderly people, who are more likely to fall ill. Our goals are to provide a comprehensive description of self-treatment and explore associated factors with insurance utilization and expenditures among the middle-aged and elderly populations in China. METHODS: A survey was conducted in July 2016 in Shanxi, China. A stratified sampling scheme was applied to achieve representativeness. A total of 972 subjects were surveyed. Descriptive statistics, t- and Chi-squared tests, multivariate logistic regression, and multivariate linear regression were utilized. RESULTS: In our study, 772 (79.4%) of the surveyed subjects self-treated during the previous twelve months. Among them, 253 (32.8%) used health insurance. Subjects' characteristics were associated with insurance utilization and expenditures for self-treatment. Total cost was positively associated with insurance utilization. The subjects with a junior high education (p-value < 0.001, aOR = 0.049) and senior high education (p-value = 0.020, aOR = 0.146) had a lower probability of using insurance. For both total costs and out-of-pocket costs, subjects who were 51 to 60 years old had lower costs. The subjects who were seriously sick and had a primary school education, as well as enterprise occupations, had higher costs. Self-treatment times were also positively associated with costs. Finally, it was found that subjects who didn't use insurance had lower total costs. CONCLUSIONS: The prevalence of self-treatment was high (79.4%). Some characteristics were associated with insurance utilization and expenditures in self-treatment. Our results may be helpful for policy interventions, which are needed to further improve the effectiveness of health insurance in China.

Differences exist across insurance schemes in China post-consolidation.

BACKGROUND: In China, the basic insurance system consists of three schemes: the UEBMI (Urban Employee Basic Medical Insurance), URBMI (Urban Resident Basic Medical Insurance), and NCMS (New Cooperative Medical Scheme), across which significant differences have been observed. Since 2009, the central government has been experimenting with consolidating these schemes in selected areas. This study examines whether differences still exist across schemes after the consolidation. METHODS: A survey was conducted in the city of Suzhou, collecting data on subjects 45 years old and above with at least one inpatient or outpatient treatment during a period of twelve months. Analysis on 583 subjects was performed comparing subjects' characteristics across insurance schemes. A resampling-based method was applied to compute the predicted gross medical cost, OOP (out-of-pocket) cost, and insurance reimbursement rate. RESULTS: Subjects under different insurance schemes differ in multiple aspects. For inpatient treatments, subjects under the URBMI have the highest observed and predicted gross and OOP costs, while those under the UEBMI have the lowest. For outpatient treatments, subjects under the UEBMI and URBMI have comparable costs, while those under the NCMS have much lower costs. Subjects under the NCMS also have a much lower reimbursement rate. CONCLUSIONS: Differences still exist across schemes in medical costs and insurance reimbursement rate post-consolidation. Further investigations are needed to identify the causes, and interventions are needed to eliminate such differences.

Disease-related costs of care and survival among Medicare-enrolled patients with myelodysplastic syndromes.

BACKGROUND: Although newer treatments for myelodysplastic syndromes (MDS), particularly hypomethylating agents (HMAs), are expensive, it is unclear whether MDS-related costs of care are associated with overall survival. This study evaluated the relation between MDS-related costs and survival among Medicare beneficiaries with MDS. METHODS: Eligible patients were identified from the Surveillance, Epidemiology, and End Results-Medicare database with codes for MDS from International Classification of Diseases for Oncology, 3rd edition. The patients were diagnosed between January 1, 2005 and December 31, 2011, were 66 years old or older, and were followed through death or the end of study (December 31, 2012). Medicare payments were used to estimate costs. Cumulative costs in a propensity score-matched group of cancer-free Medicare beneficiaries were subtracted from costs in the MDS cohort in each registry to estimate MDS-related costs. Hazard ratios (HRs) and 95% confidence intervals (CIs) were derived from multivariate Cox proportional hazards models adjusted for patient and disease characteristics. RESULTS: There were 8580 eligible patients, and 1,267 (14.7%) received HMAs. The overall 2-year survival rate was 48.7%, and the 2-year registry-specific MDS-related cost per patient ranged from $40,793 to $78,156 across 16 registries. The 2-year MDS-related cost was not associated with survival in the overall study population (first tertile, reference; second tertile, HR, 0.96; 95% CI, 0.89-1.04; P = .29; third tertile, HR, 0.98; 95% CI, 0.91-1.06; P = .64) or in subgroups of patients who did or did not receive HMAs. CONCLUSIONS: Medicare expenditures for elderly patients with MDS varied across registries but were not associated with survival. A lack of an association between costs and outcomes warrants additional research because it may help to identify potential areas for cost-saving interventions without compromising patient outcomes. Cancer 2016;122:1598-607. © 2016 American Cancer Society.

Race, Socioeconomic Status, and Life Expectancy After Acute Myocardial Infarction.

BACKGROUND: Previous studies have been unable to disentangle the negative associations of black race and low socioeconomic status (SES) with long-term outcomes of patients after acute myocardial infarction (AMI). Such information could assist in efforts to address both racial and socioeconomic disparities. METHODS AND RESULTS: We used data from the Cooperative Cardiovascular Project, a prospective cohort study of Medicare beneficiaries hospitalized with AMI with 17 years of follow-up, to evaluate the relationship between race, area-level SES (measured by zip code-level median household income), and life expectancy after AMI. Life expectancy was estimated by using Cox proportional hazards regression with extrapolation using exponential models. Of the 141 095 patients with AMI, 6.3% were black and 6.8% resided in low-SES areas; 26% of black patients lived in low-SES areas in comparison with 5.7% of white patients. Post-myocardial infarction life expectancy estimates were shorter for black patients than for white patients across all socioeconomic levels in patients ≤ 75 years of age. After adjustment for patient and treatment characteristics, the association between race and life expectancy persisted but was attenuated. Younger black patients (<68 years) had shorter life expectancies than white patients, whereas older black patients had longer life expectancies. The largest white-black gap in life expectancy occurred in patients residing in high- and medium-SES areas (P=0.02 interaction). CONCLUSIONS: Black and white patients residing in low-SES areas have similar life expectancies after AMI, which are lower than those living in higher-SES areas. Racial disparities were most prominent among patients living in high-SES areas.

Life Expectancy and Years of Potential Life Lost After Acute Myocardial Infarction by Sex and Race: A Cohort-Based Study of Medicare Beneficiaries.

BACKGROUND: Most studies of sex and race differences after acute myocardial infarction (AMI) have not taken into account differences in life expectancy in the general population. Years of potential life lost (YPLL) is a metric that takes into account the burden of disease and can be compared by sex and race. OBJECTIVES: This study sought to determine sex and race differences in long-term survival after AMI using life expectancy and YPLL to account for differences in population-based life expectancy. METHODS: Using data from the Cooperative Cardiovascular Project, a prospective cohort study of Medicare beneficiaries hospitalized for AMI between 1994 and 1995 (N = 146,743), we calculated life expectancy and YPLL using Cox proportional hazards regression with extrapolation using exponential models. RESULTS: Of the 146,743 patients with AMI, 48.1% were women and 6.4% were black; the average age was 75.9 years. Post-AMI life expectancy estimates were similar for men and women of the same race but lower for black patients than white patients. On average, women lost 10.5% (SE 0.3%) more of their expected life than men, and black patients lost 6.2% (SE 0.6%) more of their expected life than white patients. After adjustment, women still lost an average of 7.8% (0.3%) more of their expected life than men, but black race became associated with a survival advantage, suggesting that racial differences in YPLL were largely explained by differences in clinical presentation and treatment between black and white patients. CONCLUSIONS: Women and black patients lost more years of life after AMI, on average, than men and white patients, an effect that was not explained in women by clinical or treatment differences.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath.

Illness and medical and other expenditures: observations from western and eastern China.

BACKGROUND: Illness and the medical expenditure that follows have a profound impact on the well-being of individuals and households. China is a huge country with significant regional differences. The goal of this study is to investigate the associations of illness and medical expenditure with other categories of household expenditures, with special attention paid to the differences in observations between the western and eastern regions. METHODS: A survey was conducted in six major cities in China, three in the east and three in the west, in 2011. Data on demographics, illness conditions, and medical and other expenditures were collected from 12,515 households. RESULTS: In the analysis of the associations of illness conditions and medical expenditure with demographics, multiple significant associations were observed, and there are differences between the eastern and western regions. In univariate analyses, illness conditions and medical expenditure were found as having significant associations with other categories of expenditures. In multivariate analyses adjusting for household and household head characteristics, few associations were observed, and there exist differences between the regions. CONCLUSIONS: This study has provided empirical evidence on the associations of illness/medical expenditure with demographics and with other categories of expenditures. Differences across regions were observed in multiple aspects. The reasons underlying such differences are worth investigating further.

Health insurance utilization and its impact: observations from the middle-aged and elderly in China.

OBJECTIVE: In China, despite a high coverage rate, health insurance is not used for all illness episodes. Our goal is to identify subjects' characteristics associated with insurance utilization and the association between utilization and medical expenditure. METHODS: A survey was conducted in January and February of 2012. 2093 middle-aged and elderly subjects (45 years old and above) were surveyed. RESULTS: Heath insurance was not utilized for 12.6% (inpatient), 53.3% (outpatient), and 72.6% (self-treatment) of disease episodes. Subjects' characteristics were associated with insurance utilization. Inpatient and outpatient treatments were expensive. In the multivariate analysis of outpatient treatment expenditure, insurance utilization was significantly associated with higher treatment cost, lost income, and gross total cost. CONCLUSION: Utilization of health insurance may need to be improved. Insurance utilization can reduce out-of-pocket medical expenditure. However, the amount paid by the insured is still high. Policy intervention is needed to further improve the effectiveness of health insurance.

Illness, medical expenditure and household consumption: observations from Taiwan.

BACKGROUND: Illness conditions lead to medical expenditure. Even with various types of medical insurance, there can still be considerable out-of-pocket costs. Medical expenditure can affect other categories of household consumptions. The goal of this study is to provide an updated empirical description of the distributions of illness conditions and medical expenditure and their associations with other categories of household consumptions. METHODS: A phone-call survey was conducted in June and July of 2012. The study was approved by ethics review committees at Xiamen University and FuJen Catholic University. Data was collected using a Computer-Assisted Telephone Survey System (CATSS). "Household" was the unit for data collection and analysis. Univariate and multivariate analyses were conducted, examining the distributions of illness conditions and the associations of illness and medical expenditure with other household consumptions. RESULTS: The presence of chronic disease and inpatient treatment was not significantly associated with household characteristics. The level of per capita medical expenditure was significantly associated with household size, income, and household head occupation. The presence of chronic disease was significantly associated with levels of education, insurance and durable goods consumption. After adjusting for confounders, the associations with education and durable goods consumption remained significant. The presence of inpatient treatment was not associated with consumption levels. In the univariate analysis, medical expenditure was significantly associated with all other consumption categories. After adjusting for confounding effects, the associations between medical expenditure and the actual amount of entertainment expenses and percentages of basic consumption, savings, and insurance (as of total consumption) remained significant. CONCLUSION: This study provided an updated description of the distributions of illness conditions and medical expenditure in Taiwan. The findings were mostly positive in that illness and medical expenditure were not observed to be significantly associated with other consumption categories. This observation differed from those made in some other Asian countries and could be explained by the higher economic status and universal basic health insurance coverage of Taiwan.