Shunsuke Doi

Japanese EMRs and IT in Medicine: Expansion, Integration, and Reuse of Data.

Objectives The prevalence of electronic medical record in Japan varies according to the size of the hospital which is 62.5% in major hospitals, 21.7% in medium, 9.1% in small size hospitals, and 16.5% in clinics. The complete paperless system is very limited, though some major hospitals are aiming at this system. Several regional network systems which connect different platforms of EMRs, have been developing in many districts, while the final picture of a regional network has not been clearly proposed. To develop a whole electronic health record or personal health records system from the regional network data, we have several obstacles to overcome such as standardization, a privacy act, unique national health number. Methods Some experimental trials have just been started. The reuse of the accumulated data has also just been initiated. We exploited text mining systems (term frequency-inverse document frequency method) to find similar cases and auto-audit Japanese diagnosis related group (DRG) coding by using discharge summaries. Results The same or even a more extreme phenomenon of huge data accumulation is occurring in genetic research and confluence of multi-disciplines of informatics is the next step, which has an enormous accumulation of data and discoveries of the relations beyond the dimension of each informatics. Conclusions We need another approach to science apart from the conventional method, and data-driven approach with data mining techniques must be brought in for each field. Informaticians have new important roles as coordinators to link up numerous phenomena over dimensions.

Development of Doctors Search Engine based on ICD-10

Chiba University Hospital website has a lot of information and helps visitors to find all kinds of information about the hospital, while too much information makes it difficult to find a suitable doctor as a specialist for them. Visitors have to search every department website one by one. This task is very troublesome, especially large hospital. To solve this problem, we developed a specialist search engine. By entering a disease name, the engine will find the specialists for the disease. The engine can control synonyms by using International Statistical Classification of Diseases and Related Health Problems (ICD), Japanese Standard Disease-Code Master and arrange the specialists in order of the experience.

Document Tagging Method for Low-resolution Medical Documents in Hospital Information Systems

Recently, a lot of paper-based documents used in hospitals have been computerized because of diffusion of Hospital Information Systems (HIS). However, some of previously scanned documents do not have enough resolution for document image processing, e.g. OCR Engine, due to storage limitation of the system. Currently, such documents are still archived in HIS, but not used effectively now. These should be converted to electrical data for resemble case search. This paper discusses document image processing methods to search low-resolution medical documents. As the first step of this study, we propose a tagging method for low-resolution document images archived in HIS. This paper shows the detail of the proposed method and experimental results to discusses the effectiveness of the proposed method. We also show problems and future works of this study in the end of paper.

Estimation and Evaluation of Future Demand and Supply of Healthcare Services Based on a Patient Access Area Model

Accessibility to healthcare service providers, the quantity, and the quality of them are important for national health. In this study, we focused on geographic accessibility to estimate and evaluate future demand and supply of healthcare services. We constructed a simulation model called the patient access area model (PAAM), which simulates patients’ access time to healthcare service institutions using a geographic information system (GIS). Using this model, to evaluate the balance of future healthcare services demand and supply in small areas, we estimated the number of inpatients every five years in each area and compared it with the number of hospital beds within a one-hour drive from each area. In an experiment with the Tokyo metropolitan area as a target area, when we assumed hospital bed availability to be 80%, it was predicted that over 78,000 inpatients would not receive inpatient care in 2030. However, this number would decrease if we lowered the rate of inpatient care by 10% and the average length of the hospital stay. Using this model, recommendations can be made regarding what action should be undertaken and by when to prevent a dramatic increase in healthcare demand. This method can help plan the geographical resource allocation in healthcare services for healthcare policy.

What we expect for wearable health, from clinical settings

Today so many devices of wearable health are produced and they are very useful in physical training and leisure. Increasing aged population arises the problem of life style related disease, ie, diabetes mellitus, atherosclerosis, hyper lipidemia. Medical practitioners expect so much on wearable health devices in controlling these diseases. But most of them have no chance to mention what they want. We provided a small chance what they want if they can contribute the development of wearable health devices. 10 minutes of brain storming produced so much idea and after that we put them into affinity diagram. We classified them between passive health and active health. Active health is what physicians want. We hope this study will open the gate among physicians, education specialists and IT developers.

A study on keyword detection using weighted similarity and character sequence for low-resolution medical documents

By the diffusion of Hospital Information Systems, many medical documents have been computerized. In addition, most of paper documents before computerization have been also scanned and archived as document images. These were usually converted to text data by using document analysis techniques and Optical Character Reader (OCR) and archived for medical document retrieval. However, the resolutions of some documents are not sufficient for character recognition because of storage spaces, scanning regulations and so on. Therefore, we cannot search desired keywords in the documents, as a result, these documents are not still used effectively in medical document retrieval systems. In this study, we discuss a keyword detection and extraction methods for these document images. As the first step of this study, this paper proposes a method to detect and extract desired words from these documents by using weighted dissimilarity and character sequence. Evaluation experiments using actual medical documents are conducted to discuss the effectiveness of the proposed method.

Using GIS to Simulate Inpatient's Behavior and Visualize Healthcare Demand

Abstract In this study, we developed the Patient Access Area Model by using a Geographic information system (GIS), and, in order to evaluate the balance of medical supply and demand in the future in small areas, simulated patients’ access to hospitals. We set the accessible area by patients’ transit time for each hospital. The patients living in each 500 meters mesh were allowed to enter hospitals only within the access area. The hospitals have its limit to admit patients based on their actual numbers of beds. We distributed inpatients from each mesh across hospitals. For the evaluation of demand, if patients could not be distributed to the hospitals within the accessible area, we defined the situation as “over-demand.” As a result, although it was expected that over 9000 inpatients will not receive inpatient care in a southwest area region in the studied prefecture, most of the over-demand is in the densely regions along large traffic lines in 2030. Using this model, we can know demand for local health resources more clearly. This method is very useful to plan geographical resource allocation in medical services.