Vision-based estimation of manipulation forces by deep learning of laparoscopic surgical images obtained in a porcine excised kidney experiment.

In robot-assisted surgery, in which haptics should be absent, surgeons experience haptics-like sensations as "pseudo-haptic feedback". As surgeons who routinely perform robot-assisted laparoscopic surgery, we wondered if we could make these "pseudo-haptics" explicit to surgeons. Therefore, we created a simulation model that estimates manipulation forces using only visual images in surgery. This study aimed to achieve vision-based estimations of the magnitude of forces during forceps manipulation of organs. We also attempted to detect over-force, exceeding the threshold of safe manipulation. We created a sensor forceps that can detect precise pressure at the tips with three vectors. Using an endoscopic system that is used in actual surgery, images of the manipulation of excised pig kidneys were recorded with synchronized force data. A force estimation model was then created using deep learning. Effective detection of over-force was achieved if the region of the visual images was restricted by the region of interest around the tips of the forceps. In this paper, we emphasize the importance of limiting the region of interest in vision-based force estimation tasks.

Designing a muon scattering scanner for nuclear debris measurement.

Removal of fuel debris is planned to start at Unit 2 of the Fukushima Daiichi Nuclear Power Plant. During the removal, it is desirable to distinguish fuel debris from radioactive wastes and to sort the fuel debris accordingly to the amounts of nuclear material contained. Muon scattering tomography invented at Los Alamos in the early 2000s is highly sensitivity to high-atomic-number materials such as uranium. A muon scanner to sort the debris is designed and currently in production. One of the challenges is to operate the muon scanner in the presence of high γ-ray radiations from the debris: muon-event-identification electronics and a muon-tracking algorithm in the presence of high γ-ray radiations were developed.

Alpha emitter detection systems using a UV light detector.

To visualize alpha contamination, an alpha-particle detection system has been developed that is capable of detecting alpha-induced UV lights from a few meters distance in dark environments. It detects UV lights from ionized nitrogen with a photomultiplier tube. To identify the contaminated spot quickly, large diameter lenses were designed and tested.

Developing and Sustaining an Open Source Electronic Health Record: Evidence from a Field Study in Japan.

Electronic Health Records (EHRs) are at the heart of reforms aimed at improving the efficiency and quality of healthcare services provided to citizens. Although there is still some skepticism, open source (OS) EHR is a growing phenomenon in health informatics. Given the widespread adoption of OS software (OSS) in several domains, including operating systems, and enterprise systems, the repeated shortfalls faced by healthcare organizations with dominant proprietary EHRs create an opportunity for other alternatives, such as OSS to demonstrate their abilities in addressing these well-documented problems, including inflexibility, high costs, and low interoperability. However, scholars have expressed extensive concerns about the sustainability of OS EHR. Recognizing that OSS project sustainability relies on their governance arrangements, this case study reports on the evolution of the governance and sustainability of a Japanese OS EHR project and provides rich insights to other open source EHR initiative stakeholders, including physicians, developers, researchers, and policy-makers.

The Development of Medical Markup Language Version 4 as a Clinical Document Exchange Format for Nationwide EHR Systems.

Medical Markup Language (MML) is a standard format for exchange of healthcare data among healthcare providers. Following the last major update (version 3), we developed new modules and discussed the requirements for the next major updates. Subsequently, in 2016 we released MML version 4 and used it to obtain clinical data from healthcare providers for a nationwide electronic health records (EHR) system. In this article we provide an overview of this major update of MML version 4 and discuss its interoperability for clinical data.

Governance and Sustainability of an Open Source Electronic Health Record: An Interpretive Case Study of OpenDolphin in Japan.

Electronic Health Records (EHRs) are at the heart of reforms aiming for improving the efficiency and quality of citizens healthcare services. Although there is still some skepticism, open source (OS) EHR is a growing phenomenon in health informatics. Given the widespread adoption of OS software (OSS) in several domains, including operating systems, and enterprise systems, the repeated shortfalls faced by healthcare organizations with dominant proprietary EHRs create an opportunity for other alternatives, such as OSS to demonstrate their abilities in addressing these well-documented problems, including inflexibility, high costs, and low interoperability. However, scholars have expressed extensive concerns about the sustainability of OS EHR. Recognizing that OSS project sustainability relies on their governance arrangements, this case study reports on the evolution of the governance and sustainability of a Japanese OS EHR project and provides rich insights to other open source EHR initiative stakeholders, including physicians, developers, researchers, and policymakers.

Original Laboratory Test Code Mapping System Using Test Result Data on Electronic Health Record.

Laboratory tests results have potential secondary usage. Each healthcare facility has a laboratory test code. Hence, test code mapping is required to support laboratory technicians. An automatic code mapping can reduce the burden of manual mapping during data preparation. The authors developed a semi-automatic mapping support system that uses the newest test results generated in the electronic health record.

Designing Archetype Models for Each Step of Workflow in Medication.

Medication processes are consisted with multiple steps by professionals and consumers. Physicians prescribe drugs to patient with conformance, but sometimes they were changed to other drugs. We designed concept models to capture medication workflow process records by openEHR archetype models, and four templates were determined with each step of the medication process. We will show the detail of clinical modeling about medication workflow in this article.

The prevalence and disease burden of severe eosinophilic asthma in Japan.

Background: There are limited data on the prevalence and burden of severe eosinophilic asthma (SEA) both in Japan and globally. This study aimed to assess the prevalence and burden of SEA in Japan. Methods: This study was a retrospective, observational cohort analysis using health records or health insurance claims from patients with severe asthma treated at Kyoto University Hospital. The primary outcome was the prevalence of SEA, defined as a baseline blood eosinophil count ≥300 cells/µL. Secondary outcomes included frequency and risk factors of asthma exacerbations, and asthma-related healthcare resource utilization and costs. Results: Overall, 217 patients with severe asthma were included; 160 (74%) had eosinophil assessments. Of these, 97cases (61%), 54cases (34%), and 33cases (21%) had a blood eosinophil count ≥150, ≥300, and ≥500 cells/µL, respectively. Proportion of SEA was 34%. Blood eosinophil count was not associated with a significantly increased frequency of exacerbations. In the eosinophilic group, lower % forced expiratory volume in 1 second and higher fractional exhaled nitric oxide were predictive risk factors, while the existence of exacerbation history was a predictive risk factor for asthma exacerbations in the non-eosinophilic group. Severe asthma management cost was estimated as ¥357,958/patient-year, and asthma exacerbations as ¥26,124/patient-year. Conclusions: Approximately, one-third of patients with severe asthma in Japan have SEA. While risk factors for exacerbations differed between SEA and severe non-eosinophilic asthma, both subgroups were associated with substantial disease and economic burden. From subgroup analysis, blood eosinophil counts could be an important consideration in severe asthma management.

AGING AND HEALTH TECHNOLOGY ASSESSMENT: AN IDEA WHOSE TIME HAS COME.

OBJECTIVES: With the increase in technologies to support an aging population, health technology assessment (HTA) of aging-related technologies warrants special consideration. At Health Technology Assessment international (HTAi) 2016 and HTAi 2017, an international panel explored interests in HTA focused on aging. METHODS: Panelists from five countries shared the state of aging and HTA in their countries. Opportunities were provided for participants to discuss and rate the themes identified by the panelists. RESULTS: In 2016, the highest ranked themes were: (i) identifying unmet needs of older adults that could be met by technology-how can HTA help?; (ii) differences in assessment of aging-related technologies-what is the scope?; and (iii) involvement of older adults and caregivers. These themes became the starting point for discussion in 2017, for which the highest ranked themes were: (i) identification of challenges in HTA and aging; and (ii) approaches to advancing effectiveness of HTA for aging. CONCLUSION: These discussions allowed for examination of future directions for HTA and aging: engagement of older adults to inform the agenda of HTA and the broader public policy enterprise; a systems approach to thinking about needs of older persons should support the type and level of care desired by the individual rather than the health institutions, and HTA should reflect these desires when evaluating technological aides; and there is potential for health information systems and "big data" to support HTA activities that assess usability of technologies for older adults. We hope to build on the momentum of this community to continue exploring opportunities for aging and HTA.

Generation of openEHR Test Datasets for Benchmarking.

openEHR is a widely used EHR specification. Given its technology-independent nature, different approaches for implementing openEHR data repositories exist. Public openEHR datasets are needed to conduct benchmark analyses over different implementations. To address their current unavailability, we propose a method for generating openEHR test datasets that can be publicly shared and used.

Privacy Policy Implementation on the Nation-Wide EHR in Japan for Hospitals and Patients.

Shared clinical information is an important contribution to regional medicine. Clinical information sharing with patients is also recommended to motivate patients and promote health. On the other hand, the threat of information leaks, caused by internet connected records, is critical to hospitals. The traditional approach is complete isolation of hospital networks, instead of information sharing. The authors propose methods here to maximize information sharing by following hospital preferences for electronic health records.

Authenticating Unknown Doctors for Access to EHRs Based on Societal Trust.

Many isolated EHRs in Japan hinders the availability of patients' clinical data who need treatment in a region outside the scope of their local EHR. We propose a timelier approach that increases availability of patient clinical data to unknown doctors and has the patient and their representative involved; they can grant access to doctors who are anonymous to the patients' local EHR domain.

Mapping HL7 CDA R2 Formatted Mass Screening Data to OpenEHR Archetypes.

Mass screening of adults was performed to manage employee healthcare. The screening service defined the data collection format as HL7 Clinical Document Architecture (CDA) R2. To capture mass screening data for nationwide electronic health records (her), we programmed a model within the CDA format and mapped the data items to the ISO13606/openEHR archetype for semantic interoperabiilty.

Development of Unified Lab Test Result Master for Multiple Facilities.

A clinical study requires massive amounts of of lab test data, especially for rare diseases. Before creating a protocol, the hypothesis if the protocol will work with enough amount of patients' dataset has to be proved. However, a single facility, such as a university hospital, often faces a lack of number of patients for specific target diseases. Even if collecting datasets from several facilities, there is no active master table that can merge lab test results between the facility datasets. Therefore, the authors develop a unified lab test result master. Because test master standards such as JLAC10 and LOINC are provided from a viewpoint of academic classification of laboratory medicine, the classification does not fit clinical classification, which doctors understand with a mind-set of establishing a clinical study protocol. The authors establish a method to unify masters using an active lab test result master from two university hospitals.

Restructuring an EHR system and the Medical Markup Language (MML) standard to improve interoperability by archetype technology.

In 2001, we developed an EHR system for regional healthcare information inter-exchange and to provide individual patient data to patients. This system was adopted in three regions in Japan. We also developed a Medical Markup Language (MML) standard for inter- and intra-hospital communications. The system was built on a legacy platform, however, and had not been appropriately maintained or updated to meet clinical requirements. To improve future maintenance costs, we reconstructed the EHR system using archetype technology on the Ruby on Rails platform, and generated MML equivalent forms from archetypes. The system was deployed as a cloud-based system for preliminary use as a regional EHR. The system now has the capability to catch up with new requirements, maintaining semantic interoperability with archetype technology. It is also more flexible than the legacy EHR system.

Development of a methodology for the detection of hospital financial outliers using information systems.

Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers.

Applying secret sharing for HIS backup exchange.

To secure business continuity is indispensable for hospitals to fulfill its social responsibility under disasters. Although to back up the data of the hospital information system (HIS) at multiple remote sites is a key strategy of business continuity plan (BCP), the requirements to treat privacy sensitive data jack up the cost for the backup. The secret sharing is a method to split an original secret message up so that each individual piece is meaningless, but putting sufficient number of pieces together to reveal the original message. The secret sharing method eases us to exchange HIS backups between multiple hospitals. This paper evaluated the feasibility of the commercial secret sharing solution for HIS backup through several simulations. The result shows that the commercial solution is feasible to realize reasonable HIS backup exchange platform when template of contract between participating hospitals is ready.

Tele-auscultation support system with mixed reality navigation.

The aim of this research is to develop an information support system for tele-auscultation. In auscultation, a doctor requires to understand condition of applying a stethoscope, in addition to auscultatory sounds. The proposed system includes intuitive navigation system of stethoscope operation, in addition to conventional audio streaming system of auscultatory sounds and conventional video conferencing system for telecommunication. Mixed reality technology is applied for intuitive navigation of the stethoscope. Information, such as position, contact condition and breath, is overlaid on a view of the patient's chest. The contact condition of the stethoscope is measured by e-textile contact sensors. The breath is measured by a band type breath sensor. In a simulated tele-auscultation experiment, the stethoscope with the contact sensors and the breath sensor were evaluated. The results show that the presentation of the contact condition was not understandable enough for navigating the stethoscope handling. The time series of the breath phases was usable for the remote doctor to understand the breath condition of the patient.

Qualitative evaluation of the supporting system for diagnosis procedure combination code selection.

In Japan, medical staff must select a diagnosis procedure combination (DPC) code for each inpatient upon admission. We report on the development and evaluation of a supporting system for DPC code selection. This system, based on a machine learning method developed by Okamoto et al., makes DPC code suggestions that are derived from medical practice information pertaining to inpatients. The use of the suggestions helps medical staff select an appropriate DPC code for each inpatient. We asked health information management professionals to evaluate the system and to compare the suggested DPC codes with those selected by doctors. They reported that the system was generally useful and that using this system they could find some cases of hospitalized patients whose DPC codes needed correction. However, they also determined the precision of the system needs improvement.