| BackgroundWith the rapid development of society and economy, the improvement of living standard, change of lifestyle and rapid aging of population, the global prevalence and patients of diabetes are rising at an alarming pace. As diabetes and its complications not only cause serious injury to physical and mental health of patients, but also make a heavy burden to patients, families and society. It’s one the most popular and most challenging public health problems. In China, the prevalence of diabetes increased by10times in recent20years, and the economic burden of diabetes had been increasing rapidly. Predicted by the Word Bank’s Asia-Pacific reports, diabetes will become the most prevalent disease of next decade in China. The rapid growth of diabetes patients calls for more health services and resources, and it brings new challenges for national health planning and resource allocation. Health policy is usually made based on previous or existing data, however, the estimate of existing demand is supposed to underestimate the actual situation in the future. Therefore, making scientific prediction on diabetes’economic burden by historical trends analysis is worthy of further exploration, and it’s also a problem policy makers eager to solve.Researches of diabetes’economic burden in China started late. Many scholars were conducting such kind of researches, but these studies were fragmented with variety of study areas, contents, methods and findings. The imperfect of national health information systems and missing or unreleased of related basic data lead to so less national researches of diabetes’economic burden. Literatures on forecasting research of diabetes’ economic burden are few. What’s worth, rough prediction methods, too early study time and poor timeliness made previous researches difficult to contribute in policy making. Therefore, it’s urgent to draw on the experience and research methods of developed countries and to explore the theoretical basis and research ideas of diabetes’economic burden prediction, to build prediction model in China, to apply in health research and planning practice, and to service for health policy making and resource allocation in China. This paper will systematically summarize related theories and models on diabetes’ economic burden prediction, in order to build forecast model of this study, to predict diabetes’ economic burden in future years, to explore factors driving the growth of diabetes’ economic burden, to provide a scientific basis for health planning and resources allocation, to achieve "needs-based" health services planning and provision and to ensure the investment of resources match future requirements.Based on the above, this paper proposes the following research questions:1) How many prediction models for diabetes’ economic burden are there in domestic and foreign countries? What’s the theoretical basis, advantages and disadvantages of each model?2) How to build prediction models for diabetes’economic burden? What are available data?3) How is the historical trend of diabetes’economic burden in China? Which are motivating factors of its growth?4) What the future development of diabetes’economic burden will be? Which are driving factors?ObjectivesThe overall objective of this thesis is to explore how to build diabetes’ economic burden forecasting model by researches of theoretical models and empirical analysis, to predict future development of diabetes’ economic burden by analyzing its historical trend and to provide data and scientific evidence for health planning and resources allocation by its motivating factors. Specific objectives including:1) to systematically summarize the related theories and models on diabetes’economic burden prediction in domestic and foreign countries;2) to build forecast models of diabetes’ prevalence and economic burden;3) to analyze the historical trend and its movitating factors of diabetes’economic burden during1997-2009;4) to forecast the future development of diabetes’economic burden and its motivating factors;5) to provide the scientific suggestions for national health planning and resources allocation.MethodsThe strategy of this study of prediction study of economic burden of Diabetes, is to predict the future population, diabetes prevalence and the average of disease economic burden per capita respectively based on historical trend, and then generate the final grossdisease economic burden of diabetes for some year by multiplying the results above together. The prediction study is conducted based on group model by age. The disease economic burdens of diabetes include disease burden, direct economic burden and indirect burden.Firstly, generate group prediction model of diabetes prevalence and individual prediction model of diabetes at the basis of summarial analized the existing prediction model of the forein country.Trend extrapolation and function model are applied to predict diabetes prevalence, while the influencing factors of the disease occurrence rate are analyzed with panel data regression model; secondly, generate the prediction model of disease economic burden per capita, medical service utilization and cost prediction model. The trend extrapolationand annual growth rate method is used for the former one, while sample selection model is applied to the later model. The evaluation and measurement of disease economic burden of diabetes focuse on disease economic burden caused by all the diseases and additional economic burden caused by diabetes, which is based on measurement method of direct economic burden of diabetes recommended by WHO; The disease burden is evaluated by patient numbers and labor-days lost and the economic burden is evaluated by cost of illness approach, while direct economic burden is evaluated by medical fees and indirect economic burden is evaluated by human capital approach. Finally, Logarithmic Mean Divisia Index is applied to decompose impacting factors’contribution to the economic burden growth.The study is based on the data of China Health and Nutrition Survey (CHNS) which was a long term time-series international cooperation program conducted by North Carolina University and China Center for Disease Control. Given various economic development level and dietary pattern, the study covered9provinces including Liaoning, Heilongjiang, Jiangsu, Shandong, Henan, Hubei, Hunan, Guangxi, and Guizhou. The cross-sectional analysis was conducted every2-4years on4400households selected randomly, involving19000subjects. As the diabetes investigation started from1997, therefore, we only use data from investigations in1997,2000,2004,2006and2009. Adults age20and above from the five investigations are included. The records of one subject ranged from1to5, and there are48696records in all. All the diabetic patients involved were diagnosed patients. The demographic data is based on predicted database from US Bureau of the Census. The study describe the demographic characters of subjects, investigated the factors influencing diabetes prevalence and medical fees, analyze the historical trend of disease economic burden of diagnosed diabetes in China from1997to2009, and predicte the future trend of the burden from2010to2020. The indexes involve physical condition, health related factor, social demography economic characteristics, medical service utilization and disease economic burden. Different index variables are analyzed with different statistical analysis methods. Chi-square test and variance analysis are applied to the divergence analysis.Results1. Basic characteristics of research subjectThe subject of this research was the populations who were20+years old. The percent of female was about52%over the period from1997to2009; the percent of the group (20-39ages) decreased about10%, while for the group (45-59ages) and group (60+ages), the percent increased about10%respectively from1997to2009. For the group whose education level was no higher than primary school, its percent decreased about8%, while for the groups who attended junior middle school, senior middle school and the university, the percents of these three groups increased about3%respectively. The percent for the unemployed increased17%, and the retirees raised about5%from1997to2009. There were about33.3%people who owned town registered permanent residence. The percent of the population with medical insurance raised about64%, and household incomes per capital increased from4013yuan to11487yuan. Compared with people without diabetes, the age structure of diabetic patients was more ageing; and the overall education level was lower, the proportion of unemployed and retirees was higher, and the proportion of town census register was higher.The four-week prevalence rate increased by about8%of total population, the prevalence of chronic diseases increased by about9%, obesity rate had increased about5%, the rate of overweight increased by about14%, hypertension rate increased by about7%, excessive physical activity rate fell by nearly15%, smoking and drinking rate decreased about4%, respectively. According to the comparison, for the diabetic population, its four-week prevalence rate, obesity rates, the rates of overweight and high blood pressure were significantly higher than people without diabetes; however, the rate of excessive physical activity, drinking and smoking among diabetic population was lower than people without diabetes.2. Influence factors of diabetes prevalence and medical expensesDiabetes prevalence between different characteristics of grouping people analysis results showed that the diabetes prevalence was different among different groups divided by ages, education, occupation, income and household registration (P<0.05). The diabetes prevalence was higher among those groups (aged60+, lowest education level and highest education level, the retirees and the unemployed, low-income and high-income). The differences on the diabetes prevalence among different groups which were divided by different characteristics, such as different body mass index, blood pressure, physical activity, smoking, drinking and so on, were statistically significant (P<0.05). The diabetes prevalence of overweight group was2times more than the normal and lighter groups, the obese group was four times more than the normal and lighter groups, hypertension group was about3times of the group without hypertension, and it was3times for group without excessive physical compared with group with excessive physical activity. Diabetes prevalence of multi-factor analysis showed that age, obesity, high blood pressure, excessive physical activity and other factors had significant influence on the diabetes prevalence (P<0.05). Results of analysis on the medical expenses per case among groups divided by different characteristics showed that there were statistically differences between different groups which were divided by gender, age, education, occupation, income, household registration kinds of medical insurance. Male was about1.37times than that of women, and group (aged60+) was about1.53times than that of group (aged20-39). Groups (high education level, the retirees and the unemployed) had higher medical expenses per case than other corresponding groups. However there were no significant differences between different groups which divided by gender, age, education, occupation, income, household registration and kinds of medical insurance on the medical expenses per case (P>0.05).Medical expenses of multi-factor analysis results showed that age, marital status, educational level, occupation, medical insurance, family annual per capita income, household registration and whether in hospital onthe influence of medical expenses were statistically significant (P<0.05).3. Historical trend of disease and economic burden for diagnosed diabetes in China From1997to2009, the diagnosed diabetes prevalence rate increased from0.95%to2.24%among people aged20+years old, and that rose0.07%,1.11%and4.15%respectively in the group aged20-39,40-59and60+. The diagnosed diabetes patients rose from7.7017million to21.5959million, which included0.3058million (aged20-39),5.6993million (aged40-59) and7.8691million (aged60+). There were2.6530million increased diagnosed diabetes patients resulted from demographic changes, and8.0741million increased patients resulted from the rise of prevalence rate. There were3.1471million increased patients under the unit effect of demographic changes and the rise of prevalence rate. The total days due to illness among diagnosed diabetes patients in China rose from97.08million days to97.08million days, and the total growth rate was283.94%, while the growth rate caused by the increase number of patients was199.94%, and the growth rate of28.94%caused by the increased days due to illness per capita, and the growth rate was55.06%which was affected by those two. Extra days due to illness rose from41.91million days to41.91million days. The total growth rate was457.14%, and the growth rate of179.20%was caused by the increase of the number of patients and the growth rate of93.38%was caused by the increased extra days due to illness per capita. A combination caused the growth rate of184.56%. Total medical costs of diagnosed diabetes patients in China increased from24.719billion yuan to97.893billion yuan. The total growth rate was296.02%. The growth rate of190.79%was resulted from the increased number of patients, and the medical expense per capita led to the growth rate of36.64%. The growth rate of68.59%was made by the combine effect of those two aspects. Additional medical costs increased from19.719billion yuan to68.295billion yuan, the total growth rate of246.34%. The growth rate of180.73%caused by the increase number of patients and the increase of additional medical expense per capita led to the growth rate of25.16%, and the combination of those caused the growth rate of40.45%. The total indirect economic burden to diagnosed diabetes patients in China increased from2.007billion yuan to26.117billion yuan, and the total growth rate was1201.53%.The growth rate of199.47%was caused by the increase number of patients and the increased indirect economic burden per capita led to the growth rate of340.49%, and a661.57%growth rate resulted from the combination cause; Additional indirect economic burden was from866million yuan to16.363billion yuan, and the total growth rate was1498.90%. The growth rate of179.26%was caused by the increase of the number of patients, and the extra indirect economic burden increase per capita led to the growth rate of563.73%.The growth rate of1045.91%was built by a combination effort.4. Projection of disease and economic burden for diagnosed diabetes in China From2010to2020, the diagnosed diabetes morbidity of people over20will rise from2.313%to4.664%, of which the aged20-39group, the aged40-59group and the aged60+group will rise0.018percentages,1.673percentages and5.815percentages respectively. The number of diagnosed diabetes patients will rise from22.8555 million to50.1356million, of which the20-39group will decrease33.6thousand, the40-59group will increase8.0266million and the60+group will increase19.2841million, and the total growth rate of diagnosed diabetes patients will be119.35%, of which caused by demographic change is25.86%, morbidity rise is71.97%and the combined effect of both is21.70%. The total number of absence days from work of diabetes patients will rise from403.63million to1084.51million and the total growth rate will be168.69%, of which caused by the rise of patients number is128.63%, the rise of absence day from work per capita is19.74%, and the combined effect of both is22.12%. The total number of extra absence day from work will rise from256.27million to773.79million, and the total growth rate will be201.95%, of which caused by the rise of patients number is123.51%, the rise of extra absence day from work per capita is33.96%and the combined effect of both is44.48%. The total medical expense of diagnosed diabetes patient is predicted to rise from109.415billion to402.053billion, and the growth rate will be267.46%, of which caused by the rise of patients number is125.11%, the rise of medical expense per capita is63.47%and the combined effect of both is78.88%. The total extra medical expense will rise from75.707billion to254.165billion, and the total growth rate will be235.72%, of which caused by the rise of number of diagnosed patients is117.39%, the rise of medical expense per capita is55.34%and the combined effect of both is62.99%. The total indirect financial burden of diagnosed diabetes patients will rise from30.544billion to169.127billion, and the total growth rate will be453.71%, of which caused by the rise of number of patients is128.63%, the rise of indirect financial burden per capita is143.06%and the combined effect of both is182.02%. The total extra financial burden will rise from19.393billion to120.672billion, and the total growth rate will be522.25%, of which caused by the rise of number of patients is123.45%, the rise of extra financial burden per capita is176.02%and combined effect of both is222.78%.Conclusions and RecommendationsForecasting studies of diabetes’economic burden in China has a crucial importance for health planning and resources allocation to meet the demand of future. The key point and difficulty of predicting studies is the build of prediction model and the acquisition of data, which is the main reason for so few researches in domestic. Based on systematically summarize related theories and models on diabetes’ economic burden prediction in domestic and foreign countries, this thesis carries out quantitative predictions of China’s future economic burden of diabetes. China is in the economic and social transition that diabetes’prevalence is rapidly growing. The higher level of province’s economic development, the higher prevalence of diabetes, prevalence in urban area is higher than the one in rural area, the same in one area. Prevalence of diabetes in different populations is different, and there is higher prevalence in the old, low-educated, informal workers, the low-income and other vulnerable populations. Medical expenses in different populations also different, the old and informal workers and other vulnerable populations also have higher prevalence. However, the cost differences among different populations are small, which indicates heavy burden for all diabetes patients. Compared with non-diabetes patients, the utilization rates of healthcare and costs per time of diabetes patients are higher, which lead to higher average annual per capita cost and larger individual economic burden and family economic burden. The prevalence of diabetes has brought heavy burden to population health and social economy, even heavier in the future. As the rapid growth of factors, healthcare expenditure, social development and aging population, the prevalence rate, patients and economic burden of diabetes in China will increasing dramatically. The increase of prevalence plays a more important role to increased patients than population changes. The contribution of diabetes patients’ increase to disease economic burden increase is greater than the one of increase cost of per patient. While, the contribution of per patient’s cost also can’t be ignored. Only with effective measures, can we avoid the "blowout" phenomenon of diabetes’ economic burdea.This study has the following policy implications:1) In order to make better predictions of future health problems, relevant department should strengthen the collection of data and improve electronic information system of all levels health institutions.2) According to the trend and motivating factors of national diabetes’ economic burden, we can carry out health planning and resources allocations to meet the demand of future.3) In order to control and delay the economic burden of diabetes, it’s necessary to take effective health economic policy and preventive interventions, such as diet control, reduce obesity and high blood pressure, etc., to strengthen diabetes prevention interventions and disease management for reducing diabetes’ economic burden from the source.4) For those suffer heavy economic burden, specific health policy and assistance should be adopted, such as covering diabetes outpatient services into medical insurance payments, expanding medial insurance reimbursement for diabetes patients. So, it’s possible to reduce economic burden of diabetes patients and improve the life quality of them.Innovations and LimitationsThe innovations including:1) There has not been systematically study of burden and economic burden of diabetes. Different studies using different prediction models got quite different results. Based on literature review, this thesis systematically summarizes related theories and models on diabetes’economic burden prediction in domestic and foreign countries, compare and evaluate their strengths and weaknesses, and come up with suggestions for improvements and future development direction by ideas and methods of mathematical statistics and econometrics.2) There is a lack of domestic economic burden prediction studies of dabetes. Based on study of theoretical models, this paper carries out prediction study of national diabetes’future economic burden, explores answers to the questions we may encounter on the progress, in order to not only to provide data and scientific evidence for health planning and resources allocation but also open a new frontier for forecasting studies of other health problems.3) Panel data model and sample selection model are used to analyze the factors of diabetes and healthcare expenditure. Advantages of both models make research findings more reliable, at the same time, it’s helpful to predict the future development of diabetes’economic burden by analyzing the trend of influencing factors. By calculation method reference of diabetes’direct economic burden, recommended by WHO, and estimating patients’additional economic burden of diabetes by comparing analysis, it’s possible to evaluate diabetes’economic burden and show heavier economic burden of diabetes patients than non-diabetes patients, even though it’s impossible to separate health losses and economic losses of patients. The limitations and prospects including:1) In this thesis, only trend extrapolation is used, the prevalence of diabetes prediction using mathematical functions, per capital economic burden prediction using the annual growth rate, both of which attribute the role of all factors to time variable and make factors of prevalence and healthcare expenditure two separate parts. This is the limitation of methodology in this study. The subsequent research can contribute to macroeconomic panel data regression model, microscopic simulation model and long-term costs model of disease.2) We only utilized a few years’data, mainly because historical data don’t available in a short time by survey and domestic related data are not published, which may affect the accuracy of long-time prediction results to a certain extent. It’s better to track and collect long-term relevant data in the future, and as time goes on list the latest information into time series data to re-fitting the model. In addition, there are many complex factors influencing the prevalence and healthcare expenditure. The future changes of socio-economic and policy environment will reduce the predicting effect of original model, so dynamic scenario analysis can be adopted in the further study.3) Its still in initial stage for diabetes’ economic burden prediction research with inadequate theoretical models to be developed in the further study. The prediction of diabetes’economic burden is prospective study, predictions of various methods are only scientific estimations, every model is simplify and abstraction of development process. So they only provide information from a certain angle, and they can’t fully reveal its development and changes. Thus, many predictive models can be constructed in the future, by evaluating to determine the optimal model. |
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