Background: Many people take medicines to control high blood pressure (BP), or hypertension. Randomized clinical trials (RCT) are usually used for the evaluation of effects of medicines. However, RCT have some serious...Background: Many people take medicines to control high blood pressure (BP), or hypertension. Randomized clinical trials (RCT) are usually used for the evaluation of effects of medicines. However, RCT have some serious problems. Data and Methods: We evaluated the effects of BP medicines in Japan using a dataset containing 113,979 cases. We employed four statistical methods in the analysis. First, we simply compared the systolic blood pressure (SBP) of individuals with and without BP medicines. We then used a regression model with a dummy variable, representing taking medicines or not. We replaced the dummy variable by its expected value, and estimated the regression model again. Finally, we selected individuals who had both taken and not taken medicines at different times. The effect of sample selection was also considered in the estimation. Results: For the simple comparison, SBP with BP medicines was 11 mmHg higher than without medicines. In the next regression analysis, SBP with BP medicines was still 5 mmHg higher. When the dummy variable was replaced by its expected value, SBP with medicines decreased by 7 mmHg. For individuals taking medicines at some times and not at others, SBP decreased by 9 and 8 mmHg in models with and without a sample bias correction, respectively. Conclusion: The methods eliminated some problems of RCT and might be attractive. However, we obtained contradictory conclusions depending on the statistical methods employed, despite using the identical dataset. Statistical methods must be selected carefully to obtain a reliable evaluation. Limitations: The dataset was observatory, and the sample period was only 3 years.展开更多
Background: The cost and economic burden of diabetes are a serious worldwide issue. In this study, we evaluated medical payments for persons diagnosed with diabetes and the factors that led to a person having diabetes...Background: The cost and economic burden of diabetes are a serious worldwide issue. In this study, we evaluated medical payments for persons diagnosed with diabetes and the factors that led to a person having diabetes to reduce its prevalence. Methods: A dataset containing 113,979 medical checkups and 3,671,783 monthly medical, dental, care-giving and pharmacy payment records of one health insurance society was used. The dataset contains information of normal and healthy persons. The sample period ran from April, 2013 to March, 2016. The medical payments for persons diagnosed with diabetes were calculated. The regression analysis was used to remove the effects of age and gender. The probit analysis was used to analyze the factors that led to a person having diabetes. Results: In 2.9% of cases, the person undergoing the checkup was diagnosed with diabetes, and the medical payments for these patients were 2.7 times as much as the average medical payment per person. This result did not change significantly even if age and gender were considered. The results of the probit analysis suggested that body mass index, high systolic blood pressure, low diastolic blood pressure, eating habits, physical activities, smoking, drinking alcohol and sleeping were important factors for diabetes. Conclusion: The diabetes might be a costlier disease than previously thought in Japan. By the estimation, 8% of all medical payments were made for these persons with diabetes, which is much higher than the result shown by national survey data. However, overall prevalence could be recused by efforts such as prevention of overweight and obesity.展开更多
In this paper, we evaluate the difference between the first and second measurements of blood pressure (BP) when BP is measured twice using the results of 17,775 medical checkups. The two measurements for both systolic...In this paper, we evaluate the difference between the first and second measurements of blood pressure (BP) when BP is measured twice using the results of 17,775 medical checkups. The two measurements for both systolic BP (SBP) and the diastolic BP (DBP) fluctuated a large amount even though they were measured at a short interval. The first measurements were 6.7 and 2.4 mmHg higher than the second ones for SBP and DBP, suggesting a white coat effect. Then, the factors that might affect the differences between the two measurements were analyzed by the regression models. For both SBP and DBP, the difference increased as the first measurement increased. Age, gender, BMI and alcohol consumption were other important factors affecting the difference. In the case of a typical male individual, the typical criteria for hypertension of 140/90, 160/100 and 180/110 mmHg criteria in the first measurement would correspond to 135/86, 150/94 and 165/102 mmHg in the second measurement. The necessity of developing accurate and cost-efficient BP measurement methods is strongly suggested.展开更多
Background: High blood pressure (BP) or hypertension is considered one of the top global disease burden risk factors. In November 2017, the ACC/AHA and other organizations announced a new hypertension guideline of 130...Background: High blood pressure (BP) or hypertension is considered one of the top global disease burden risk factors. In November 2017, the ACC/AHA and other organizations announced a new hypertension guideline of 130/80 mmHg. Data and Methods: We evaluate the effects of BP on increases in medical expenditures using transformation tobit models and a dataset containing 175,123 medical checkups and 6,312,125 receipts from 88,211 individuals in three health insurance societies. The sample period was April 2013 to March 2016. We first created a database of combined checkup results and medical expenditures. The power transformation tobit model was then used to remove the effects of other variables, and we investigated the relation between medical expenditures and BP, especially systolic BP (SBP). Results: We observed negative effects of SBP on medical expenditures. The results raise uncertainty about the reliability of the new guideline, at least for SBP. Although the simple correlation coefficient of medical expenditures and SBP was positive, the sign of the SBP estimate became negative when a variable representing obesity was included. In terms of other medical checkup items, while LDL is considered the “bad” cholesterol, it reduced medical expenditures. Conclusion: Our results did not support the new 2017 ACC/AHA guideline for SBP. A wide and careful range of reviews not only for heart diseases but also for other disease types will be absolutely necessary. New studies to verify the guideline should also be conducted. Limitations: The dataset was observatory, the sample period only 3 years, and we could not complete a time-series analysis of individuals.展开更多
文摘Background: Many people take medicines to control high blood pressure (BP), or hypertension. Randomized clinical trials (RCT) are usually used for the evaluation of effects of medicines. However, RCT have some serious problems. Data and Methods: We evaluated the effects of BP medicines in Japan using a dataset containing 113,979 cases. We employed four statistical methods in the analysis. First, we simply compared the systolic blood pressure (SBP) of individuals with and without BP medicines. We then used a regression model with a dummy variable, representing taking medicines or not. We replaced the dummy variable by its expected value, and estimated the regression model again. Finally, we selected individuals who had both taken and not taken medicines at different times. The effect of sample selection was also considered in the estimation. Results: For the simple comparison, SBP with BP medicines was 11 mmHg higher than without medicines. In the next regression analysis, SBP with BP medicines was still 5 mmHg higher. When the dummy variable was replaced by its expected value, SBP with medicines decreased by 7 mmHg. For individuals taking medicines at some times and not at others, SBP decreased by 9 and 8 mmHg in models with and without a sample bias correction, respectively. Conclusion: The methods eliminated some problems of RCT and might be attractive. However, we obtained contradictory conclusions depending on the statistical methods employed, despite using the identical dataset. Statistical methods must be selected carefully to obtain a reliable evaluation. Limitations: The dataset was observatory, and the sample period was only 3 years.
文摘Background: The cost and economic burden of diabetes are a serious worldwide issue. In this study, we evaluated medical payments for persons diagnosed with diabetes and the factors that led to a person having diabetes to reduce its prevalence. Methods: A dataset containing 113,979 medical checkups and 3,671,783 monthly medical, dental, care-giving and pharmacy payment records of one health insurance society was used. The dataset contains information of normal and healthy persons. The sample period ran from April, 2013 to March, 2016. The medical payments for persons diagnosed with diabetes were calculated. The regression analysis was used to remove the effects of age and gender. The probit analysis was used to analyze the factors that led to a person having diabetes. Results: In 2.9% of cases, the person undergoing the checkup was diagnosed with diabetes, and the medical payments for these patients were 2.7 times as much as the average medical payment per person. This result did not change significantly even if age and gender were considered. The results of the probit analysis suggested that body mass index, high systolic blood pressure, low diastolic blood pressure, eating habits, physical activities, smoking, drinking alcohol and sleeping were important factors for diabetes. Conclusion: The diabetes might be a costlier disease than previously thought in Japan. By the estimation, 8% of all medical payments were made for these persons with diabetes, which is much higher than the result shown by national survey data. However, overall prevalence could be recused by efforts such as prevention of overweight and obesity.
文摘In this paper, we evaluate the difference between the first and second measurements of blood pressure (BP) when BP is measured twice using the results of 17,775 medical checkups. The two measurements for both systolic BP (SBP) and the diastolic BP (DBP) fluctuated a large amount even though they were measured at a short interval. The first measurements were 6.7 and 2.4 mmHg higher than the second ones for SBP and DBP, suggesting a white coat effect. Then, the factors that might affect the differences between the two measurements were analyzed by the regression models. For both SBP and DBP, the difference increased as the first measurement increased. Age, gender, BMI and alcohol consumption were other important factors affecting the difference. In the case of a typical male individual, the typical criteria for hypertension of 140/90, 160/100 and 180/110 mmHg criteria in the first measurement would correspond to 135/86, 150/94 and 165/102 mmHg in the second measurement. The necessity of developing accurate and cost-efficient BP measurement methods is strongly suggested.
文摘Background: High blood pressure (BP) or hypertension is considered one of the top global disease burden risk factors. In November 2017, the ACC/AHA and other organizations announced a new hypertension guideline of 130/80 mmHg. Data and Methods: We evaluate the effects of BP on increases in medical expenditures using transformation tobit models and a dataset containing 175,123 medical checkups and 6,312,125 receipts from 88,211 individuals in three health insurance societies. The sample period was April 2013 to March 2016. We first created a database of combined checkup results and medical expenditures. The power transformation tobit model was then used to remove the effects of other variables, and we investigated the relation between medical expenditures and BP, especially systolic BP (SBP). Results: We observed negative effects of SBP on medical expenditures. The results raise uncertainty about the reliability of the new guideline, at least for SBP. Although the simple correlation coefficient of medical expenditures and SBP was positive, the sign of the SBP estimate became negative when a variable representing obesity was included. In terms of other medical checkup items, while LDL is considered the “bad” cholesterol, it reduced medical expenditures. Conclusion: Our results did not support the new 2017 ACC/AHA guideline for SBP. A wide and careful range of reviews not only for heart diseases but also for other disease types will be absolutely necessary. New studies to verify the guideline should also be conducted. Limitations: The dataset was observatory, the sample period only 3 years, and we could not complete a time-series analysis of individuals.
