Related Experiment Videos
Analysis of Medical Care Expenditure by Japanese Prefecture using Fuzzy Robust Regression Model
Yoshiyuki Yabuuchi1, Takayuki Kawaura2, Junzo Watada3
1Shimonoseki City University, Japan.
Studies in Health Technology and Informatics
|December 10, 2014
Summary
Lifestyle-related diseases significantly impact healthcare costs and reduce life expectancy. Prevention through exercise, diet, and avoiding smoking is key. This study analyzes the link between medical spending and lifestyle factors using a novel model.
Area of Science:
- Public Health
- Health Economics
- Biostatistics
Background:
- Lifestyle-related diseases account for a substantial portion of national healthcare expenditure, estimated at 179 billion yen (15.13% of total fiscal medical care costs in 2012).
- These diseases are a primary cause of reduced healthy life expectancy and place a significant burden on national medical finances.
- Preventive measures including moderate exercise, balanced diet, and smoking cessation are known to mitigate these health issues.
Purpose of the Study:
- To analyze the relationship between medical care expenditure and specific lifestyle factors.
- To develop and apply a controllable model for understanding health economics related to lifestyle choices.
Main Methods:
- Utilized a fuzzy robust regression model, designed as a controllable system descriptor.
- Applied the model to investigate correlations between healthcare costs and selected lifestyle determinants.
Main Results:
- The study quantifies the significant financial impact of lifestyle-related diseases on national healthcare spending.
- Identified key lifestyle factors influencing medical care expenditure.
Conclusions:
- Lifestyle-related diseases represent a major economic challenge in healthcare.
- The developed fuzzy robust regression model offers a viable approach for analyzing the complex interplay between lifestyle and healthcare costs.
- Emphasizes the importance of lifestyle modification for reducing disease burden and healthcare expenditure.
Related Concept Videos
01:25Statistical Methods for Analyzing Epidemiological Data
1.3K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.3K
01:17Clearance Models: Noncompartmental Models
352
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
352
01:11Regression Analysis
9.1K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
9.1K
01:11Residuals and Least-Squares Property
9.9K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
9.9K
00:59Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
416
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
416
01:17Classification of Illness
9.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
9.5K