Tonghui Ling

Grid-based implementation of XDS-I as part of image-enabled EHR for regional healthcare in Shanghai

PurposeDue to the rapid growth of Shanghai city to 20 million residents, the balance between healthcare supply and demand has become an important issue. The local government hopes to ameliorate this problem by developing an image-enabled electronic healthcare record (EHR) sharing mechanism between certain hospitals. This system is designed to enable healthcare collaboration and reduce healthcare costs by allowing review of prior examination data obtained at other hospitals. Here, we present a design method and implementation solution of image-enabled EHRs (i-EHRs) and describe the implementation of i-EHRs in four hospitals and one regional healthcare information center, as well as their preliminary operating results.MethodsWe designed the i-EHRs with service-oriented architecture (SOA) and combined the grid-based image management and distribution capability, which are compliant with IHE XDS-I integration profile. There are seven major components and common services included in the i-EHRs. In order to achieve quick response for image retrieving in low-bandwidth network environments, we use a JPEG2000 interactive protocol and progressive display technique to transmit images from a Grid Agent as Imaging Source Actor to the PACS workstation as Imaging Consumer Actor.ResultsThe first phase of pilot testing of our image-enabled EHR was implemented in the Zhabei district of Shanghai for imaging document sharing and collaborative diagnostic purposes. The pilot testing began in October 2009; there have been more than 50 examinations daily transferred between the City North Hospital and the three community hospitals for collaborative diagnosis. The feedback from users at all hospitals is very positive, with respondents stating the system to be easy to use and reporting no interference with their normal radiology diagnostic operation.ConclusionsThe i-EHR system can provide event-driven automatic image delivery for collaborative imaging diagnosis across multiple hospitals based on work flow requirements. This project demonstrated that the grid-based implementation of IHE XDS-I for image-enabled EHR could scale effectively to serve a regional healthcare solution with collaborative imaging services. The feedback from users of community hospitals and large hospital is very positive.

Combining text retrieval and content-based image retrieval for searching a large-scale medical image database in an integrated RIS/PACS environment

Medical imaging modalities generate huge amount of medical images daily, and there are urgent demands to search large-scale image databases in an RIS-integrated PACS environment to support medical research and diagnosis by using image visual content to find visually similar images. However, most of current content-based image retrieval (CBIR) systems require distance computations to perform query by image content. Distance computations can be time consuming when image database grows large, and thus limits the usability of such systems. Furthermore, there is still a semantic gap between the low-level visual features automatically extracted and the high-level concepts that users normally search for. To address these problems, we propose a novel framework that combines text retrieval and CBIR techniques in order to support searching large-scale medical image database while integrated RIS/PACS is in place. A prototype system for CBIR has been implemented, which can query similar medical images both by their visual content and relevant semantic descriptions (symptoms and/or possible diagnosis). It also can be used as a decision support tool for radiology diagnosis and a learning tool for education.

Implementation methods of medical image sharing for collaborative health care based on IHE XDS-I profile

Abstract. IHE XDS-I profile proposes an architecture model for cross-enterprise medical image sharing, but there are only a few clinical implementations reported. Here, we investigate three pilot studies based on the IHE XDS-I profile to see whether we can use this architecture as a foundation for image sharing solutions in a variety of health-care settings. The first pilot study was image sharing for cross-enterprise health care with federated integration, which was implemented in Huadong Hospital and Shanghai Sixth People’s Hospital within the Shanghai Shen-Kang Hospital Management Center; the second pilot study was XDS-I–based patient-controlled image sharing solution, which was implemented by the Radiological Society of North America (RSNA) team in the USA; and the third pilot study was collaborative imaging diagnosis with electronic health-care record integration in regional health care, which was implemented in two districts in Shanghai. In order to support these pilot studies, we designed and developed new image access methods, components, and data models such as RAD-69/WADO hybrid image retrieval, RSNA clearinghouse, and extension of metadata definitions in both the submission set and the cross-enterprise document sharing (XDS) registry. We identified several key issues that impact the implementation of XDS-I in practical applications, and conclude that the IHE XDS-I profile is a theoretically good architecture and a useful foundation for medical image sharing solutions across multiple regional health-care providers.

Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

Medical imaging document sharing solutions for various kinds of healthcare services based on IHE XDS/XDS-I profiles

One key problem for continuity of patient care is identification of a proper method to share and exchange patient medical records among multiple hospitals and healthcare providers. This paper focuses in the imaging document component of medical record. The XDS-I (Cross- Enterprise Document Sharing – Image) Profile based on the IHE IT-Infrastructure extends and specializes XDS to support imaging “document” sharing in an affinity domain. We present three studies about image sharing solutions based on IHE XDS-I Profile. The first one is to adopt the IHE XDS-I profile as a technical guide to design image and report sharing mechanisms between hospitals for regional healthcare service in Shanghai. The second study is for collaborating image diagnosis in regional healthcare services. The latter study is to investigate the XDS-I based clearinghouse for patient controlled image sharing in the RSNA Image Sharing Network Project. We conclude that the IHE XDS/XDS-I profiles can be used as the foundation to design medical image document sharing for Various Healthcare Services.

Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

Design of image sharing and exchanging for cross-enterprise and cross-domain collaborative healthcare in Shanghai

We designed the image-enabled EHR sharing solution (i-EHR) for cross-enterprise and cross-domain with SOA architecture and combined the grid-based image management and distribution capability, which are compliant with IHE XDS-I/XCA integration profiles. We selected one districts with four hospitals and two hospital groups as image sharing pilot testing bed. Our approach presented in this presentation uses peer-to-peer mode to share and exchange image data cross enterprise PACSs and domains, which provides single point of services to local systems so it is easy to integrate with different vendors PACS and easy to deploy to different hospitals to implement the i-EHR.

Three-Dimensional Visual Patient Based on Electronic Medical Diagnostic Records

Objective: an innovative concept and method is introduced to use a 3-D anatomical graphic pattern called visual patient (VP) visually to index, represent, and render the medical diagnostic records (MDRs) of a patient, so that a doctor can quickly learn the current and historical medical status of the patient by manipulating VP. The MDRs can be imaging diagnostic reports and DICOM images, laboratory reports and clinical summaries which can have clinical information relating to medical status of human organs or body parts. Methods: the concept and method included three steps. First, a VP data model called visual index object (VIO) and a VP graphic model called visual anatomic object (VAO) were introduced. Second, a series of processing methods of parsing and extracting key information from MDRs were used to fill the attributes of the VIO model of a patient. Third, a VP system (VPS) was designed to map VIO to VAO, to create a VP instance for each patient. Results: a prototype VPS has been implemented in a simulated hospital PACS/RIS integrated environment. Two evaluation results showed that more than 70% participating radiologists would like to use the VPS in their radiological imaging tasks, and the efficiency of using VPS to review the tested patients’ MDRs was 2.24 times higher than that of using PACS/RIS, while the average accuracy <Pac> by using PACS/RIS was better than that by using VPS; however, this difference was only about 4%. Conclusion: the developed VPS can show the medical status of patient organs/sub-organs with 3-D anatomical graphic pattern and will be welcomed by radiologists with better efficiency in reviewing the patients’ MDRs and with acceptable accuracy. Significance: the VP introduces a new way for medical professionals to access and interact with a huge amount of patient records with better efficiency in the big data era.

Principle and engineering implementation of 3D visual representation and indexing of medical diagnostic records (Conference Presentation)

Purpose: Due to the generation of a large number of electronic imaging diagnostic records (IDR) year after year in a digital hospital, The IDR has become the main component of medical big data which brings huge values to healthcare services, professionals and administration. But a large volume of IDR presented in a hospital also brings new challenges to healthcare professionals and services as there may be too many IDRs for each patient so that it is difficult for a doctor to review all IDR of each patient in a limited appointed time slot. In this presentation, we presented an innovation method which uses an anatomical 3D structure object visually to represent and index historical medical status of each patient, which is called Visual Patient (VP) in this presentation, based on long term archived electronic IDR in a hospital, so that a doctor can quickly learn the historical medical status of the patient, quickly point and retrieve the IDR he or she interested in a limited appointed time slot. Method: The engineering implementation of VP was to build 3D Visual Representation and Index system called VP system (VPS) including components of natural language processing (NLP) for Chinese, Visual Index Creator (VIC), and 3D Visual Rendering Engine.There were three steps in this implementation: (1) an XML-based electronic anatomic structure of human body for each patient was created and used visually to index the all of abstract information of each IDR for each patient; (2)a number of specific designed IDR parsing processors were developed and used to extract various kinds of abstract information of IDRs retrieved from hospital information systems; (3) a 3D anatomic rendering object was introduced visually to represent and display the content of VIO for each patient. Results: The VPS was implemented in a simulated clinical environment including PACS/RIS to show VP instance to doctors. We setup two evaluation scenario in a hospital radiology department to evaluate whether radiologists accept the VPS and how the VP impact the radiologists’ efficiency and accuracy in reviewing historic medical records of the patients. We got a statistical results showing that more than 70% participated radiologist would like to use the VPS in their radiological imaging services. In comparison testing of using VPS and RIS/PACS in reviewing historic medical records of the patients, we got a statistical result showing that the efficiency of using VPS was higher than that of using PACS/RIS. New Technologies and Results to be presented: This presentation presented an innovation method to use an anatomical 3D structure object, called VP, visually to represent and index historical medical records such as IDR of each patient and a doctor can quickly learn the historical medical status of the patient through VPS. The evaluation results showed that VPS has better performance than RIS-integrated PACS in efficiency of reviewing historic medical records of the patients. Conclusions: In this presentation, we presented an innovation method called VP to use an anatomical 3D structure object visually to represent and index historical IDR of each patient and briefed an engineering implementation to build a VPS to implement the major features and functions of VP. We setup two evaluation scenarios in a hospital radiology department to evaluate VPS and achieved evaluation results showed that VPS has better performance than RIS-integrated PACS in efficiency of reviewing historic medical records of the patients.

Clinical experiences of collaborative imaging diagnosis in Shanghai district healthcare services

To improve healthcare service quality with balancing healthcare resources between large and small hospitals, as well as reducing costs, each district health administration in Shanghai with more than 24 million citizens has built image-enabled electronic healthcare records (iEHR) system to share patient medical records and encourage patients to visit small hospitals for initial evaluations and preliminary diagnoses first, then go to large hospitals to have better specialists’ services. We implemented solution for iEHR systems, based on the IHE XDS-I integration profile and installed the systems in more than 100 hospitals cross three districts in Shanghai and one city in Jiangsu Province in last few years. Here, we give operational results of these systems in these four districts and evaluated the performance of the systems in servicing the regional collaborative imaging diagnosis.