Nyuuin (Japanese Edition)

Vocabulary list: Being sick in Japanese

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Results of estimation of the non-inclusive payment model. The non-inclusive payment became smaller for older patients, but we did not admit the effect of lower payments for patients age 70 or over in this study. Emergency hospitalization increased the non-inclusive payments, but a patient was an outpatient or returning home reduced the non-inclusive payments. The revision made the non-inclusive payment lower and revision made it higher.

The estimates of Trend and Trend 2 were not significant and we could not find time trends unlike the LOS case. The estimate of Over Period dummy was 24, and its t-value was Especially, the estimate of H27 was , yen and very high.

Translation

This was caused by the fact there were many patients who received surgeries of vitreous bodies with cataract surgeries. The value of H was 55, yen. H is after-cataract; that is a patient took a cataract surgery before and lens capsule becomes dirty again, and the surgery just makes the lens capsule clean. The payments for this surgery was lower than regular cataract surgeries. For the estimates of the Hospital dummies, the maximum was , Hp44 yen and the minimum was , yen Hp5 ; the difference was 22, yen or The difference was much smaller than that of the LOS.

We found that the differences of LOS among hospitals were very large but differences of the non-inclusive payments mainly payments related to surgeries were relatively small. Although the types of diseases were different, we got the similar results for diabetes [19] [21]. Another question is whether the LOS and the non-inclu- sive payments were related or not. The correlation coefficient of the estimates of hospital dummies between the LOS and non-inclusive payment models was 0. We could not say that the LOS and the non-inclusive pay were correlated.

This means that there was a strong political implication to reduce the LOS to control the medical payments. Among three revisions, only one revision significantly reduced the LOS. The results of this study shows that the LOS did not decrease much. However, the LOS could be reduced by the efforts of hospitals. For example, Kobato et al. More recently, the Ministry of Health, Labour and Welfare [25] released the Japanese medical payments reached 40 trillion yen in fiscal year Japanese fiscal year is from April to March , this figure is expected to increase as aging the population in the future.

The medical payment has become a big financial problem. As already pointed out by Nawata and Kawabuchi [21] , the best answers for this problem is to treat patients more efficiently and control payments without degradation of treatments. There were large differences in ALOS among hospitals even after eliminating effects of various factors. This suggested that it might be possible for many hospitals to reduce the LOS without degradation of treatments for cataract surgeries. In the revision of the medical payment system implemented April [26] , the cataract surgery is classified under the category of the Short Stay Operation Basic Payment 3.

If a hospital and a patient satisfy the required conditions, a hospital gets the same amount of payments. In cataract surgeries with lens insertion, a hospital get , yen if the LOS is 5 days or less. The numbers of diseases, hospitals and patients under this system are currently small, it will be expected to increase in the future.

In this paper, we conducted a long term survey of the cataract surgeries. We evaluated the effects of three revisions of the medical payment system that were done in , and About one million surgeries are performed in Japan annually. To evaluate these changes, we analyzed a dataset of 51, patients obtained from 60 hospitals Hp where surgeries more than one-eye cataract surgeries were performed during the period. The time trend reduced the LOS but degrees of reduction became smaller.

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For the analysis of the LOS, gender, age, numbers of comorbidities and complications, outpatient before hospitalization, and place to go back after hospitalization were significant variables. The time trend and squared of trend were significant and the LOS became shorter but effects became smaller as time went. H, H, H and H27 were positive and significant. The Specific Hospitalization Period also strongly affected the non-inclusive payments. Among three dummies which evaluated effects of the revisions, only the estimate of the dummy was significant and the revision reduced the LOS but not the other two.

There were large differences among estimates of the hospital dummies, indicating that there remained large differences among hospitals, even after eliminating the influences of various factors. For the analysis of the non-exclusive payments, gender, numbers of comorbidities and complications, being an outpatient before hospitalization, place to go back after hospitalization, emergency were significant variables. The effects of time trend was not admitted in this case. For the effects of the revisions, and dummies were significant but the signs were opposite.

The revision made the non-inclusive payment lower but revision made it higher. For the estimates of the Hospital dummies, the largest difference was 22, yen or In this study, we analyzed the LOS and medical payments for cataract surgeries. For financial sustainability of the Japanese medical system, it is necessary to evaluate other diseases. In this paper, characteristics of hospitals were not analyzed. These are subjects to be studied in the future.

We would like to thank an anonymous referee and the participants of the symposium for their helpful comments. We also thank various hospitals for their sincere cooperation. In Japanese [ 2 ] Nawata, K. In Japanese [ 6 ] Nawata, K. Evaluation of the Revision of the Medical Payment System. Open Journal of Applied Science, 5, Medical Management Services Group.

Day-Case or Overnight Stay? Clinical and Experimental Ophthalmology, 28, Saudi Medical Journal, 27, British Journal of Ophthalmology, 67, Journal of American Statistical Association, 76, Economics Bulletin, 33, Economics letters, , An Estimator Consistent under Heteroscedasticity. Economics Bulletin, 3, Toyo Keizai Shinpo Sha, Tokyo. In Japanese [ 24 ] Kobato, T.

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In Japanese [ 27 ] Barbieri, V. European Journal of Ophthalmology, 17, The paper is not in the journal. Kazumitsu Nawata 1,2 , Koichi Kawabuchi 3. We analyzed a dataset of 51, patients obtained from 60 hospitals Hp where more than one-eye cataract surgeries were performed during the period. For the LOS, we found that only the revision had significant impact on shortening the LOS but the other two did not. For non-inclusive payments and revisions had significant impacts and the differences among hospitals were much smaller than those of the LOS. Received 30 May ; accepted 22 June ; published 27 June 1.

Estimators and Tests of the BC Model 2. The likelihood function under the normality assumptions is given by , and , 2 where , is the probability density function of the standard normal assumption and is the variance of. N-Estimator Nawata [16] considered the roots of the equations, 4 and When the first- and third-moments of are zero, the estimator given by Equation 4 is consistent. The asymptotic distribution of the estimator hereafter, N-estimator becomes 5 where , , and 2. Under the null hypothesis, we get, 6 where element of.

Since under the null hypothesis, we can test using t as the test statistic [5]. Conflicts of Interest The authors declare no conflicts of interest. Cite this paper Nawata, K. Health , 8 , Please enable JavaScript to view the comments powered by Disqus. Health Most popular papers. National Eye Institute Facts about Cataract. In Japanese with English Abstract. A large part of the medical cost incurred by diabetic patients. However, LOS for diabetic patients has not been widely studied, and until recently, only a few studies [22] [23] had been conducted on this issue in Japan.

Nawata and Kawabuchi [5] [24] [25] analyzed the LOS of type 2 diabetes patients. It is necessary and important to analyze the behaviors of individual hospitals and give hospitals proper medical and managerial advice and assistance in using medical information more efficiently. We consider not only ALOS but also the variance at individual hospitals.

The Box-Cox transformation model [26] BC model under heteroscedasticity of error terms was used in the analysis. Sakia [27] and Hossain [28] have presented good summaries of the BC model, including empirical examples. The maximum likelihood estimator BC MLE , which maximizes the likelihood function under the normality assumption, is usually used for the estimation of the BC model. However, the BC MLE cannot be generally consistent, and has large biases, especially under heteroscedasticity of error terms [29].

Heteroscedasticity is a very important problem in the BC model, as was mentioned even in the original paper by Box and Cox [26]. The variances of LOS are often very different among hospitals.

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Therefore, we use an estimator that is robust with respect to heteroscedasticity for analysis of the LOS of type 2 diabetes patients. A dataset of 18, patients collected from 51 general hospitals was used.

Since we evaluated not only ALOS but also variance within hospitals, selected hospitals had at least 50 patients both before and after the revision. We assume that and for all i. Since we consider two periods, before and after the revision, is a random variable distribution with mean 0 and variance , where and denote periods before and after the revision, respectively.

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If , we get where are true parameter values, and the estimators of and obtained by Equation 2 are consistent from the same argument of Nawata [30]. However, if the model contains a constant term. Therefore, it usually becomes the third-moment restriction estimator of Nawata [31]. Let be the consistent root, and. The asymptotic distribution of this estimator is given by. The daily payments to hospitals before and after the revision DPC code: Although Japanese medical payments are measured in points hospitals are paid 10 yen per point , we use yen for convenience.

In the revision, payment for the eighth day was increased yen, but daily payments for the first to the seventh days were reduced by yen, and after the ninth day, the reduction was yen if LOS was longer than 29 days, payments were determined on a conventional fee-for-service basis. As a result, payment was reduced 12, yen or 3. In the case of diabetes, the dataset contains information on 27, patients, collected from July to March with the cooperation of various hospitals currently, the dataset is the latest one and was updated in For details, see Nawata and Kawabuchi [24].

We used the data of patients: Since we were evaluating the effects of the revision and analyzing variance of LOS in hospitals, we used the data. Daily payments before and after revision DPC code: There were 18, patients in these hospitals. Table 3 presents a summary of LOS by hospitals. Before the revision, the number of patients was and the ALOS at all the hospitals was Among hospitals, the shortest ALOS was 9.

As to the SD, the smallest was 3. After the revision, the number of patients was and the ALOS for these patients was The shortest ALOS among hospitals was 9. The smallest SD was 3. We chose the following as explanatory variables. The Female Dummy 0: The proportions of male and female patients were Since LOS tends to increase with patient age, we used Age as an explanatory variable. The average age of the patients was Therefore, we added an Age Dummy 1: Among diabetic patients, many were hospitalized to join an educational program for managing diabetes rather than to receive regular medical treatment.

For the purpose of hospitalization, we used the Education Dummy joining educational program: The proportion of patients joining an educational program was Other explanatory variables representing the characteristics of patients included Comorbidities number of Comorbidities , Complications numbers of complications , Acute Hospitalization Dummy acute hospitalization: Among our study subjects, A total of The proportion of the acute hospitalization patients, outpatients of the same hospital before hospitalization, patients introduced by other hospitals, patients returned to home, patients hospitalized in the winter, and patients hospitalized in the summer were Figure 1 shows the relation between LOS and number of patients.

Many patients were discharged from the hospital on the eighth day one week hospitalization. Therefore, we added a Day-8 dummy left on the eighth day: Furthermore, if the LOS exceeded the Specific Hospitalization Period 29 days , the medical payment switched to a conventional fee-for-service system. For principal disease classification, dummy variables based on the ICD code E In terms of classification, To evaluate the effects of the revisions on individual hospitals, 51 Hospital dummies and products of hospital dummies, and a Revision dummy after revision: The constant term was not used in the model.

As a result, of Equation 1 became. The estimates of coefficients are presented in Table 4. The Female and Age Dummies were not significant, however, although Sittig, Friedel and Wasem[31] reported that gender affected medical costs of type 2 diabetes outpatients. We could not admit the effects of these variables.

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As expected, comorbidities and complications made LOS longer. However, the estimates for Outpatient and Discharged Place Dummies were not significant, and we could not find any evidence that LOS depends on these variables. This implies that the LOS became shorter in the winter but not in summer. Since the Japanese society and hospital administration are usually operated a weekly base. Moreover, the daily payment increased on the eighth day, the incentive to discharge the patients on the eighth day became stronger by the revision. The daily payments become the conventional.

In other words, the incentives for hospitals to discharge patients become very weak once their LOS exceeds the Specific Hospitalization Period. With respect to the principal disease classifications, the estimate for the E There were surprisingly large differences among the estimates of Hospital Dummies. The largest was 6.

The estimates of , , are represented are Table 5. There were large differences in , and the feasibility of the proposed model was strongly suggested. Furthermore, all hospital dummies were orthogonal with each other. Therefore, become asymptotically independent, and we can use the standard F-test of variance for heteroscedasticity. We could not find any clear evidence that the variance decreased after the revision.

The daily payments, which are the marginal revenue of the hospital, decrease as the LOS becomes longer. Since it has become possible to compare hospitals throughout the nation, the criticism for unnecessarily long LOS will likely become more serious as time passes. Reputation is considered very important. Reputation is one reason why, because the public and patients tend to think DPC hospitals are better than non-DPC hospitals.

Third, DPC hospitals are required to computerize their medical information. This can help hospitals improve and standardize their medical treatments. Hospitals have strong incentives to reduce LOS for patients with long hospitalizations, but the incentives are weak or nonexistent for patients with shorter LOS. Therefore, the effects of the introduction and revisions to hospitals might not be the same. This means that the scattering of ALOS among hospitals becomes smaller.

Furthermore, hospitals try to reduce long LOS patients within hospitals and that makes variances of LOS within hospitals smaller.

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