The concept of our running system is not only a management material but also integrated management resources, correction of mistake of medical treatment, application to EBM by the data mining of medical records. As for this system, it has become to grasp medical practice and medical material, which did not understand on current electronic receipt processing system accurately. In POAS (Point Of Act System), it is saved the management information, so-called, “man, money, material, and information.” Our system synchronizes with each department system including cost center department besides the image information can be exchanged. We could grasp Man (Business Process), Material (Medical Material and Medicine), Money (Expenditure for purchase and Receipt), Information (Medical Records) completely by this system.

 Diagnosis Procedure Combinations (DPCs), which are American DRG-like units used for a Japanese new medical payment system, were introduced on April 1, 2003 for 82 hospitals providing advanced medical care. This study analyzed the distribution patterns of length of stay (LOS) of several DPCs and their influencing factors on LOS to establish hospital-wide quality management systems. The LOS distributions of two groups, malignant tumors of the liver and intrahepatic bile duct, and cataract and lens-related diseases, showed a wide range and were negatively skewed. While a given DPC seems a more homogeneous patient group because it is classified by use of procedures, comorbidity, and post-treatment clinical conditions, the LOS distribution still showed a wide range. Each DPC has four types of payment fees depending on the LOS. Approximately half of the patients showed LOS below the national average, which is desirable from a hospital financial management point of view. Differences in LOS for the same DPC could not always be explained by the clinical variables preliminarily collected for the new payment system. Therefore, data warehouse needs to be established, which includes clinical variables for risk adjustment as well as variables related to inpatient management systems.

 High quality medical service offered at a low cost became more and more important. To realize an enhancement of the quality and efficiency of medical service, it is necessary for us to have a common scale to measure for medical economics and medical technology. We decided to introduce DPC into a special functioning hospital from April, 2003. We have developing the discharge summary system using ICD-10 database on our hospital information system, and strengthened a facility of DWH.

 And in order to support the process of optimizing cost allocations, we have developed a hospital cost accounting system. As a result, we expect to advance our system with the remarkable effect of these new functions.

 The authors developed the XML Schema in order both to the representation of tooth-tooth relation, tooth-restoration materials relation, material composition, definition and composition of virtual point/ line/angle/plane, and to the interchange of clinical information and knowledge in dental domain.

 We analyzed many findings in dental records with ontological approach, developed and discussed with UML modeling, and formulated the document model with W3C XML Schema. Although our model and schema is very small, which has only three super classes of “substance,” “relatedObject,” and “relation,” it has at least six advantages: (i) no limitation of granularity, (ii) no limitation of usecase, (iii) universal expressive power, (iv) easy subsumption/connotation under other XML Schema, (v) ability to express virtual substances, (vi) facility of composition/definition of substances or concepts, or technical terms.

 Therefore, our UML model and XML Schema is able to applied not only to healthcare service uses but also to research uses, in addition, not only to dental domain but also other domains.

 This research was granted by Research on Health Technology Assessment, Ministry of Health, Welfare and labour (12180103).

 Nursing information systems which can share data with each posts and patients are essential to built as for nursing staff of medical members. Kanto Medical Center NTT EC developed The Nursing Information System aiming at 1) sharing data, 2) supplying safe and efficient nursing care, 3) improving the quality of nursing by practical using of accumulated records. To build the system, we had studied following, 1) clarify the information owned jointly among nursing staffs and other specialty staffs, 2) define the range of standardization and make the master copy, 3) set the field of responsibility and make up partnership with nursing staffs and doctors; instruction, treatment, records and so on. Since it worked, it have been kept trying to improve by the re-organized core field members. As the system is hold in common, it is essential for the nursing members to cope with its evaluation. How efficiently it built in a limited time and condition depends on an ability of both a organization and staffs. It is important to build up a closer corporation with every profession to integrate the details with taking each share of response.

 This study had two main purposes. The first was to develop a standard set of items for electronic nursing data interchange between hospitals and home healthcare facilities. The second was to implement it on a system. In home health care, sharing patient information is important for continuity of nursing care and early stabilization of patients’ lives. Electronic data interchange of patient information needed for caring can potentially contribute to those goals. Thus we attempted to identify the item, which might comprise a patient summary written by nurses. Then, to make the granularity of each item equal, we subdivided them into 941 items. As a result, we developed the data set called Nursing Summary Data Item Set (NDIS). In order to use NDIS in actual systems, it is necessary to make Document Type Definition (DTD) of each use case. Then referring to existing nursing summaries used in three hospitals, we defined a DTD that applied NDIS and implemented it on an experimental system.

 The purpose of this study is to clarify the following three points on labels of nursing action required for electronic patient records for hospitals.

 ① clarify the structure of nursing actions through collection and analysis of labels of nursing action.

 ② clarify the complexity of nursing actions according to the information about the structure.

 ③ specify the required condition of labels of nursing action prepared for master file of nursing action.

 ‘MEDIS-DC’ collected 7,503 action labels that the nurses carry out (July, 2002) from 10 hospitals that had introduced the hospital information system and home nursing region. Of the nursing action labels, 3,776 were left as higher discretional ones from the viewpoint of assessment, plan, order and do. The analysis was carried out for them.

 We separated and assigned each action label into either “essential nursing action” and/or “the requested condition in the execution,” and reconstructed the whole structure. As a result, 153 action labels and 23 classes (classification according to the nursing target) were settled.

 “The requested condition in the execution” was classified into “person,” “time,” “equipment,” “place” and “notice.” There were “the basic set items” conditions, for “person” and “time,” which were applicable to all 153 actions. At the same time there were “specific items” conditions, applicable only for peculiar actions. Each proportion of the “specific items” applied was “person” 22%, “time” 24%, “equipment” 32%, “place” 23%, “notice (1)” 9%, “notice (2)” 12%, when 153 labels were the population parameter. As a result of cross tabulation of “23 classes” and “existence of the conditional factor,” Reduction of pain, Spirit psychological care, Rehabilitation, Cleanness of body and Excretion mainly had the action with the conditional factors. This may indicate that these forms of care had high complexity. Also we understood that the frame of 23 classes, meaning the nursing target, was deconstructed as a result of making cluster analysis from the viewpoint of the conditional factor of “person, time, equipment, place and notice.” The following are indicated: That the property of the complexity of 153 actions classified into 23 differs and that the new classification can be built from the viewpoint of the complexity.

 On the basis of the facts above, it is suggested that nursing actions are composed of 1st, 2nd and 3rd layers (nursing target), the 4th layer (which indicates the degree of complexity, etc), and the condition in the execution.

 Historically in Japan, the hospital information systems used to be designed as “Office Automation systems” from the viewpoint of hospital administrators’ convenience, which is practically responsible for the information accumulated for accounting management.

 We conducted the drastic change of hospital information system to be patient participatory health care provided in the New Hiroshima University Hospital (HUH). The bedside information systems were set up at all of 700 beds. Patients are able to access their past histories and future clinical care procedures with intelligible browse.

 The new information system in HUH (HU-MIND II) is designed as “Clinical Management System” (CMS). The core of CMS is Electronic Health Record (EHR), which aims to assure both of the patients’ right to know and the accountability of attendants. Without saying, the team practice including patients needs close communication. EHR are written not only by physicians, but also by all co-workers, which will enable them to make the team communication and ordering requirement reliable and to leave the evidence of conducted practices. In this point, CMS is dispensable tool of convenience and safety management of team practice. Besides, in the emergency care quick decision must be made despite its complicated procedures. Even after the treatment by nurses without physician’s order description, physicians are able to make reconfirmed record.

 Being based on the above demand, the new regulation of HUH is composed of 21 components of information collection, accumulation and use. Our focus there was how to make patients’ right compatible with attendants’ accountability. As the data owners, patients have initiative to access their own data at their bedsides. Then they will be able to know own health condition and treatment program and control data flow.