A plan for evaluation of the quality of medical care is needed in order to provide medical services of good quality for patients. In general, in medical quality assurance and medical quality improvement, clinical indicators on processes (i.e., provision of medical services) and outcomes (i.e., effectiveness of provision of medical services) for evaluation are utilized. This paper discussed the feasibility of utilization of DPC data referring to the actual conditions of the U.S. in which many clinical indicators on medical care for hospitalization are utilized.
In the U.S, a government agency, non-profit organizations and private insurance companies conduct evaluation of the quality of medical care utilizing clinical indicators, and feed back the results to hospitals and clinicians. Some of them also do public reporting. Moreover, the systems of pay for performance have been introduced. However, while the evaluation of quality of medical care contributes to quality assurance and improvement, it is pointed out that the systems of public reporting and pay for performance cause adverse selection and inadequate medical care.
In Japan, we can grasp the information of medical care based on a standardized form. However, there is a limitation that we cannot obtain sufficient information for appropriate evaluation. Therefore, trigger indicators for showing signs for improvement on problems and tasks should be extracted from DPC data, and in combination with other data sourses, it is important to establish a system for conducting standardization and quality improvement of medical care considering those results.

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This paper estimates the technical efficiency of hospitals using the DPC (Diagnosis Procedure Combination) data. This DPC data is a balanced panel of 127 hospitals in a three-year period between FY2005 and FY2007.
By using the DPC data, this study has the following three new points. First, in the efficiency estimation, the main output is measured by a number of inpatients weighted by case mix index from the DPC. This adjustment would improve the accuracy of the output measurement.
Second, we adopt “Hospital Standardized Mortality Ratio” as a quality control variable. Previous studies suffer from the lack of a quality variable and cannot control the quality of a medical service provided by hospitals.
Third, we adopted the “true fixed effect model” in Greene (2005) which distinguishes between inefficiency and heterogeneity of hospitals. This heterogeneity will be captured by a value of the fixed effect variable in the model.
As a result of efficiency estimation, the mean level of the efficiency is around 59%- 61%. This level is relatively low compared to previous studies. This would be caused by controlling the quality of medical service.
In addition, the value of the fixed effect variable has a 0.9 mean level and single peaked distribution. The results point out that fixed effect values would be a kind of indicator on the production or cost structure of hospitals.
The policy implication from these results is that the value of the fixed effect variable would be available to improve fairness among hospitals in the reimbursement system. This idea can apply to all kinds of Case Mix Groups and would require further examination.

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[Background] The diagnosis procedure combination (DPC) is a method for classifying patients into combined types of medical care associated with disease codes of ICD-10. The standardized clinical information by the DPC is quite valuable for evaluating medical costs and the quality of care and sharing the information among medical professions, policy makers, owners of medical facilities, and researchers. Lately, numbers of studies have been conducted using the DPC data. However, there are still few studies to examine the validity of the DPC system.
[Objective] The main objective of this study is to evaluate the validity of the DPC data base for hospital management. For this purpose, we will test an empirical hypothesis such that length of DPC experience influence the efficiency improvement of resource allocation for in-hospital care.
[Methods] This study focuses on patients who are diagnosed with “gastric cancer”, “appendicitis”, “gallbladder disease (including gallstones)” ,and “hernia”. For each diagnosis group, we estimate the effects of length of DPC experience on the length of hospital stay and medical costs, which would imply the resource allocation within a medical facility. In order to control for the effect of laparoscopic surgery on outcomes we will adjust the possible bias caused by the endogeneity of choosing high-tech treatment, using an instrumental variable method.
[Results] For all diseases, both the average length of hospital stay and costs are the lowest in hospitals which have longer DPC experience. Then, the mean length of hospital stay and medical costs tend to be longer and higher in medical facilities which have shorter DPC experience.
[Conclusion] Our results show that the longer DPC experience would improve the efficiency of resource allocation. A possible policy implication is that hospital management will be improved not simply because medical facilities utilize the DPC data, but because they have been activated as DPC hospitals for several years and they have a certain length of DPC experience.

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To elucidate the current status of the health care delivery system of Japan, the spatial distribution of health care resources and the amount to be allocated were quantitatively estimated by integrated analyses of micro data of the Patient Survey and DPC case-mix registry. Visualization of secondary medical service areas of patient residence and admitted hospital indicated the association of patient traveling distance and health care services provided. Comprehensive analysis of the Tokyo metropolitan area showed more traveling for cancer and heart surgery and less traveling for brain surgery and long term care. Multivariate logistic analysis of national data for the admission to distant hospitals revealed a high ratio for heart, orthopedic and cancer surgery and low for injury, general gastrointestinal and elderly patient surgery. The number of estimated acute care beds in Japan was 460 thousand, about half of the current general beds, with the average length of hospital stay being 12 days. The estimation of needed health care resources indicated a deficiency of physicians in the Hokkaido and Tohoku areas and of nurses in the Kanto and Tokai areas, a general deficiency of ICU beds, and up to 110 thousand rehabilitation beds to be prepared.

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To demonstrate the feasibility of medical-care process analysis, a series of data analysis was carried out for the surgery case of colon cancer (DPC 060035xx0100xx) from the DPC data. In addition to epidemiologic analyses of age, gender, etc., analyses of the surgery procedure and pathological region, preoperative and postoperative hospital days and the stage of a cancer, and surgery technique were possible from the format 1 file (FF 1 file). From E file and F file, analyses of the usage of an antimicrobial agent in the peri-operative term for surgery, the anesthetization time, and the amount of transfusions were possible. Although the DPC data had neither laboratory data nor radiological finding and no information about a long-term prognosis, either, it was suggested that detailed analyses of a medical-care process are possible, and this can be used as a base for a large-scale clinical study.

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The Diagnosis Procedure Combination (DPC) database contains discharge data and administrative claim data, including diagnoses, comorbidities and complications coded with ICD-10 (International Classification of Diseases and Related Health Problems, Tenth Revision) codes ; procedures; duration of anesthesia; volume of blood transfusion; drugs and devices used; length of stay; discharge status; and costs. Data are collected over 6 months (from July 1 to December 31) each year. In 2008, data on approximately 2.9 million in-patients were collected from 855 hospitals, which represent approximately 40% of all acute care in-patient hospitalization in Japan. Researchers can utilize the DPC database to identify, track, and analyze national trends in healthcare utilization, access, outcomes and costs. The database can be utilized for clinical epidemiological studies. The aims of this report are to (i) explain the details of the DPC database, (ii) compare the DPC database with the US administrative database (including the Medicare Claim Database and the Nationwide Inpatient Sample database), (iii) clarify the advantages and disadvantages of the DPC database, (iv) present several clinical research cases using the DPC database and (v) discuss the important role of the DPC database for the development of clinical studies and health service research in Japan.

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It is said that proper antimicrobial use is dealt with from the viewpoint of infectious patients' safe and certain recovery and prevention of the appearance and spread of antibiotic-resistant bacteria as well as making efficient use of medical expenses, and particularly, proper management of antimicrobial use is an important problem from the aspect of economy as well. Therefore, I investigated how measures (a use application system of antiMRSA medicine / carbapenem-based medicine, a monitor system, a warning notice system) for the direction for management of antimicrobial use and the DPC system introduction may have influenced medicine costs. As a result, the quantity of carbapenem-based medicine consumed and the total amount of money used for the antimicrobial were reduced by half, though the total quantity of the antimicrobial agent consumed was almost constant for the investigation period. Furthermore, the average number of hospitalization days decreased, too.
It is thought that, from these factors, due to efforts for proper antimicrobial use, a change from broad-spectrum antimicrobials to narrow-spectrum as well as replacing expensive antimicrobials with cheaper products, etc. has resulted in progress in the selection of appropriate antimicrobials. I understood that the direction for management of antimicrobial use based on proper use results in a big cost cut effect on medicine costs.

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