A service oriented architecture to implement clinical guidelines for evidence-based medical practice

Health information technology (HIT) has been identified as the fundamental driver to streamline the healthcare delivery processes to improve care quality and reduce operational costs. Of the many facets of HIT is Clinical Decision Support (CDS) which provides the physician with patient-specific inferences, intelligently filtered and organized, at appropriate times. This research has been conducted to develop an agile solution to Clinical Decision Support at the point of care in a healthcare setting as a potential solution to the challenges of interoperability and the complexity of possible solutions. The capabilities of Business Process Management (BPM) and Workflow Management systems are leveraged to support a Service Oriented Architecture development approach for ensuring evidence based medical practice. The aim of this study is to present an architecture solution that is based on SOA principles and embeds clinical guidelines within a healthcare setting. Since the solution is designed to implement real life healthcare scenarios, it essentially supports evidence-based clinical guidelines that are liable to change over a period of time. The thesis is divided into four parts. The first part consists of an Introduction to the study and a background to existing approaches for development and integration of Clinical Decision Support Systems. The second part focuses on the development of a Clinical Decision Support Framework based on Service Oriented Architecture. The CDS Framework is composed of standards based open source technologies including JBoss SwitchYard (enterprise service bus), rule-based CDS enabled by JBoss Drools, process modelling using Business Process Modelling and Notation. To ensure interoperability among various components, healthcare standards by HL7 and OMG are implemented. The third part provides implementation of this CDS Framework in healthcare scenarios. Two scenarios are concerned with the medical practice for diagnosis and early intervention (Chronic Obstructive Pulmonary Disease and Lung Cancer), one case study for Genetic data enablement of CDS systems (New born screening for Cystic Fibrosis) and the last case study is about using BPM techniques for managing healthcare organizational perspectives including human interaction with automated clinical workflows. The last part concludes the research with contributions in design and architecture of CDS systems. This thesis has primarily adopted the Design Science Research Methodology for Information Systems. Additionally, Business Process Management Life Cycle, Agile Business Rules Development methodology and Pattern-Based Cycle for E-Workflow Design for individual case studies are used. Using evidence-based clinical guidelines published by UK’s National Institute of Health and Care Excellence, the integration of latest research in clinical practice has been employed in the automated workflows. The case studies implemented using the CDS Framework are evaluated against implementation requirements, conformance to SOA principles and response time using load testing strategy. For a healthcare organization to achieve its strategic goals in administrative and clinical practice, this research has provided a standards based integration solution in the field of clinical decision support. A SOA based CDS can serve as a potential solution to complexities in IT interventions as the core data and business logic functions are loosely coupled from the presentation. Additionally, the results of this this research can serve as an exemplar for other industrial domains requiring rapid response to evolving business processes

Multiscale Quantitative Imaging of Human Femoral Heads Using X-ray Microtomography

PhDClinical diagnostic tools provide limited information on the underlying structural and mechanical properties of bone-tissue affected by degenerative and bone metabolic diseases. In-vivo bone failure studies provide limited information due to constraints such as X-ray dosage, cost and various other practicalities. In-vitro studies are thus required to enhance understanding of this phenomenon. The aims of this study were to use quantitative high-definition X-ray Micro-Tomography (XMT) to assess factors contributing to pathological and non-pathological bone failure and repair in relation to the mechanics of whole human femoral heads. XMT images of one normal and six pathological femoral heads were collected at 26 – 8.8 μm voxel resolution and evaluated to determine structural features; bone mineral concentration (BMC); and using image analysis, identify microcallus formations. In addition, in-vitro compression tests were carried out on specimens taken from regions with different anatomical loading. Bone quality was then related to the anatomical loading and BMC. Results from non-pathological tissue where used to establish a baseline for measurements of structural features. Microcallus formations where identified and used as markers to map the occurrence of bone damage. In osteoarthritic (OA) heads, the damage was found to be concentrated in localised clusters. Conversely, in the osteoporotic head damage was distributed homogeneously throughout the entire specimen. No significant difference in the BMC was observed, however there was a iii significant difference in the bone quality values between the non-pathological and pathological heads, and also between the pathologies. In-vitro mechanical testing revealed a difference in the mechanical properties of OA trabecular bone in relation to bone quality measurements but the samples exhibited no significant correlation to anatomical loading. X-ray Ultra Microscopy (XuM) at 200nm and 775nm voxel resolution was used to investigate the nano-morphology of individual trabeculae. The XuM images showed differences in bone structure and fewer osteocyte lacunae present close to fracture site. XuM also identified micro-cracks within trabeculae that were encased by microcallus formations. The application of novel quantitative high definition X-ray imaging to clinically relevant tissue at multiple length scales has provided new metrological data on the distribution of damage within pathological tissue. Insight into the vulnerability of diseased tissue to damage could ultimately lead to improved diagnosis from clinical radiographs

Comparative TMJ imaging accuracy using iCAT cone beam computerized tomography.

A blinded observational cross-sectional in vitro study was conducted to compare the diagnostic accuracy of observers viewing images made using cone beam computerized tomography (CBCT), panoramic radiography and linear tomography. The sample consisted of 37 TMJ articulations from 30 human skulls demonstrating either normal condylar morphology (n=19) or erosion of the lateral pole (n=18). The articulations were imaged using corrected angle linear tomography, normal and TMJ specific panoramic radiography and CBCT. Images and 10 re-reads were presented to 10 observers. Multiple CBCT multi-planar images were presented both statically and interactively. Intra-observer reliability was determined by weighted kappa (Kw) and diagnostic accuracy by the fitted area under the ROC curve (Az). Means were compared using ANOVA (piÜ.05). Our results show CBCT images provide superior reliability and greater accuracy than corrected angle linear tomography and TMJ panoramic projections in the detection of condylar cortical erosion

DEVELOPING VALUE-ADDED PEPTIDE ANTIOXIDANTS FROM RENDERING PRODUCTS

Synthetic antioxidants, such as butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), Vitamin E and ethoxyquin, have been commonly added to formulated animal feeds in order to delay discoloration and deterioration due to oxidation. However, these synthetic antioxidants have been limited in their applications as food additives because of potential health hazards. Specifically, synthetic antioxidants have been considered to be linked to various forms of cancer, most commonly kidney, liver and bladder cancer. In this work, value-added peptide antioxidants from rendering products were developed for use in potential aquaculture and pet food markets as natural antioxidant substitutes for synthetic antioxidants. The antioxidant peptides developed from the rendering protein were studied based on obtaining the hydrolysates fractions, together with evaluation antioxidant properties, ultrafiltration and analysis sequence of identified peptide. In the initial studies, three typical rendering proteins (poultry meal, fish meal and premium pet meal) characteristic compositions of three rendering proteins were investigated, including moisture content, ash content, fat content, and protein content. Then, the antioxidant capacity of three alkaline rendering proteins hydrolysates, including poultry meal hydrolysates, fish meal hydrolysates and premium pet meal hydrolysates, were examined. The antioxidant activities of alkaline hydrolysates were evaluated using five methods including two based on the free radical scavenging capacity (DPPH, ABTS radical scavenging assay and one oxygen radical absorbance capacity (ORAC) assay). Hydrophobic antioxidant capacities of alkaline hydrolysates were determined by ‰-Carotene Linoleic Acid System. Oxidation Stability Index (OSI) was used to evaluated the anti-lipid oxidation ability. The antioxidant peptides developed from proteolytic hydrolysis of premium pet meal were the analyzed using Response surface optimization, Ultra-Filtration and LC-MS. The optimum hydrolysis condition on temperature, enzyme to substrate ratio, and the hydrolysis time were obtained by Response Surface Methodology (RSM). Abilities of scavenging ABT*+ free radicals and degree of the hydrolysis were employed as indicators of Response surface methodology. Under the optimum hydrolysis conditions, the proteolytic hydrolysates fractions were separated by the ultrafiltration to obtain different molecular weight proteolytic hydrolysates fractions. During this process, the antioxidant capacity was also evaluated by the ABTS*+ scavenging free radical assay. For the last step, peptides less than 1000Da peptide that were derived from premium pet meal were identified using LC-MS, indicating of the possible amino acid sequences of Leu-Thr-Cys or Iso-Thr-Cys and His-Cys

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

A multi-scale imaging approach to understand osteoarthritis development

X-ray phase-contrast imaging is an innovative and advanced imaging method. Contrary to conventional radiology, where the image contrast is primarily determined by X-ray attenuation, phase-contrast images contain additional information generated by the phase shifts or refraction of the X-rays passing through matter. The refractive effect on tissue samples is orders of magnitude higher than the absorption effect in the X-ray energy range used in biomedical imaging. This technique makes it possible to produce excellent and enhanced image contrast, particularly when examining soft biological tissues or features with similar X-ray attenuation properties. In combination with high spatial resolution detector technology and computer tomography, X-ray phase-contrast imaging has been proved to be a powerful method to examine tissue morphology and the evolution of pathologies three-dimensionally, with great detail and without the need of contrast agents. This Thesis work has focused on developing an accurate, multi-scale X-ray-based methodology for imaging and characterizing the early stages of osteoarthritis. X-ray phase-contrast images acquired at different spatial resolutions provide unprecedented insights into cartilage and the development of its degeneration, i.e., osteoarthritis. Other types of X-ray phase-contrast imaging techniques and setups using spatial resolutions ranging from micrometer down to nanometer were applied. Lower spatial resolutions allow large sample coverage and comprehensive representations, while the nanoscale analysis provides a precise depiction of anatomical details and pathological signs. X-ray phase-contrast results are correlated to data obtained, on the same specimens, by standard laboratory methods, such as histology and transmission electron microscopy. Furthermore, X-ray phase-contrast images of cartilage were acquired using different X-ray sources and results were compared in terms of image quality. It was shown that with the use of synchrotron radiation, more detailed images and much faster data acquisitions could be achieved. A second focus in this Thesis work has been the investigation of the reaction of healthy and degenerated cartilage under different physical pressures, simulating the different levels of stress to which the tissue is subject during daily movements. A specifically designed setup was used to dynamically study cartilage response to varying pressures with X-ray phase-contrast micro-computed tomography, and a fully volumetric and quantitative methodology to accurately describe the tissue morphological variations. This study revealed changes in the behavior of the cartilage cell structure, which differ between normal and osteoarthritic cartilage tissues. The third focus of this Thesis is the realization of an automated evaluation procedure for the discrimination of healthy and cartilage images with osteoarthritis. In recent years, developments in neural networks have shown that they are excellently suited for image classification tasks. The transfer learning method was applied, in which a pre-trained neural network with cartilage images is further trained and then used for classification. This enables a fast, robust and automated grouping of images with pathological findings. A neural network constructed in this way could be used as a supporting instrument in pathology. X-ray phase-contrast imaging computed tomography can provide a powerful tool for a fully 3D, highly accurate and quantitative depiction and characterization of healthy and early stage-osteoarthritic cartilage, supporting the understanding of the development of osteoarthritis.Röntgen-Phasenkontrast-Bildgebung ist eine innovative und weiterführende Bildgebungsmethode. Im Gegensatz zu herkömlichen Absorptions-Röntgenaufnahmen, wie sie in der Radiologie verwendet werden, wird der Kontrast bei dieser Methode aus dem Effekt der Phasenverschiebung oder auch Brechung der Röngtenstrahlen gebildet. Der Brechungseffekt bei Gewebeproben ist um ein Vielfaches höher als der Absorptionseffekt des elektromagnetischen Spektrums der Röntgenstrahlen. Diese Methode ermöglicht die Darstellung von großen Kontraste im Gewebe. Unter Verwendung eines hochauflösenden Detektors und in Kombination mit der Computer-Tomographie, ist Phasenkontrast-Bildgebung eine sehr gute Methode um Knorpelgewebe und Arthrose im Knorpel zu untersuchen. Diese Arbeit beschreibt primär ein Verfahren zur Darstellung arthrotischen Knorpels im Anfangsstadium. Die mit verschiedenen Auflösungen und 3D-Phasen-Kontrast-Methoden produzierten Aufnahmen ermöglichen einen noch nie dagewesenen Einblick in den Knorpel und die Entwicklung von Arthrose im Anfangsstadium. Hierbei kam die propagationsbasierte Phasenkontrastmethode mit einer Auflösung im mikrometer Bereich und die (Nano)-Holotomographie-Methode mit einer Auflösung im Submicrometer Bereich zum Einsatz. Durch Auflösung im mikrometer Bereich kann ein großes Volumen im Knorpel gescannt werden, während die Nano-Holotomographie Methode eine sehr große Detailauflösung aufweißt. Die Phasenkontrast-Aufnahmen werden mit zwei anderen wissenschaftlichen Methoden verglichen: mikroskopische Abbildungen histologisch aufgearbeiteter Knorpelproben und Aufnahmen eines Transmissionselektroskop zeigen sehr große Übereinstimmungen zur Röntgen-Phasenkontrast-Bildgebung. Desweiteren wurden Phasenkontrast-Aufnahmen von Knorpel aus unterschiedlichen Röntgenquellen verglichen. Hierbei zeigte sich, dass mit Hilfe des Teilchenbeschleunigers (Synchrotron) detailreichere und schnellere Aufnahmen erzielt werden können. Bilder aus Flüssig-Metall-Quellen zeigen sich durchaus von guter Qualität, erfordern jedoch sehr lange Aufnahmezeiten. In dieser Arbeit wird zudem das Verhalten von Knorpelgewebe, welches ein Anfangsstadium von Arthrose aufweist, unter physikalischem Druck untersucht. Hierfür wurden 3D-Computertomographie-Aufnahmen von komprimiertem Knorpelgewebe angefertig und mit Aufnahmen ohne Komprimierung verglichen. Ein quantitativer Vergleich machte Veränderungen des Verhaltens der Knorpelzellstruktur (Chondronen) sichtbar. Es konnte gezeigt werden, dass Chondrone bei arthrotischem Knorpel ein verändertes Kompressionsverhalten haben. Der dritte Fokus dieser Arbeit liegt auf der automatisierten Auswertung von Aufnahmen gesunden und arthrotischen Knorpelgewebes. Die Entwicklungen im Bereich der Neuronale Netze zeigten in den letzten Jahren, dass diese sich hervoragend für Bildklassifizierungsaufgaben eignen. Es wurde die Methode des transferierenden Lernens angewandt, bei der ein vortrainiertes Neuronales Netz mit Knorpelbildern weitertrainiert und anschließend zur Klassifizierung eingesetzt wird. Dadurch ist eine schnelle, robuste und automatisierte Gruppierung von Bildern mit pathologischen Befunden möglich. Ein derart konstruiertes Neuronales Netz könnte als unterstützendes Instrument in der Pathologie angewandt werden. Röntgen-Phasenkontrast-CT kann ein leistungsstarkes Werkzeug für eine umfassende, hochpräzise und quantitative 3D-Darstellung und Charakterisierung von gesundem Knorpel und athrotischem Knorpel im Frühstadium bieten, um das Verständnis der Entwicklung von Osteoarthritis zu erweitern

Implementation of workflow engine technology to deliver basic clinical decision support functionality

BACKGROUND: Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. RESULTS: We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. CONCLUSIONS: We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform

Generation of Skin Disease into the Synthetic Fingerprints

Diplomová práce se zabývá návrhem a implementací nástroje, s jehož pomocí je možné simulovat stopy konkrétních onemocnění kůže v umělém otisku prstu. Vybraná onemocnění pro tuto práci jsou bradavice a atopický ekzém. Generování známek onemocnění probíhá do umělého otisku vytvořeného aplikací SFinGe. Existující otisky prstů s onemocněním z databáze STRaDe jsou analyzovány, následně jsou navrženy postupy pro simulaci konkrétních onemocnění do umělého otisku prstu, ty jsou implementovány a výsledek je vyhodnocen.The thesis deals with design and implementation of a tool for simulating marks of chosen skin diseases into a synthetic fingerprint. The diseases selected to work with are warts and atopic eczema. The marks of diseases are generated into a synthetic fingerprint image created by the SFinGe application. Existing disesase-affected fingerprints from the STRaDe database are analysed in detail. Then, methods for simulating the diseases into a synthetic fingerprint are proposed, implemented, and the results are evaluated.

On-site customer analytics and reporting (OSCAR):a portable clinical data warehouse for the in-house linking of hospital and telehealth data

This document conveys the results of the On-Site Customer Analytics and Reporting (OSCAR) project. This nine-month project started on January 2014 and was conducted at Philips Research in the Chronic Disease Management group as part of the H2H Analytics Project. Philips has access to telehealth data from their Philips Motiva tele-monitoring and other services. Previous projects within Philips Re-search provided a data warehouse for Motiva data and a proof-of-concept (DACTyL) solution that demonstrated the linking of hospital and Motiva data and subsequent reporting. Severe limitations with the DACTyL solution resulted in the initiation of OSCAR. A very important one was the unwillingness of hospitals to share personal patient data outside their premises due to stringent privacy policies, while at the same time patient personal data is required in order to link the hospital data with the Motiva data. Equally important is the fact that DACTyL considered the use of only Motiva as a telehealth source and only a single input interface for the hospitals. OSCAR was initiated to propose a suitable architecture and develop a prototype solution, in contrast to the proof-of-concept DACTyL, with the twofold aim to overcome the limitations of DACTyL in order to be deployed in a real-life hospital environment and to expand the scope to an extensible solution that can be used in the future for multiple telehealth services and multiple hospital environments. In the course of the project, a software solution was designed and consequently deployed in the form of a virtual machine. The solution implements a data warehouse that links and hosts the collected hospital and telehealth data. Hospital data are collected with the use of a modular service oriented data collection component by exposing web services described in WSDL that accept configurable XML data messages. ETL processes propagate the data, link, and load it on the OS-CAR data warehouse. Automated reporting is achieved using dash-boards that provide insight into the data stored in the data warehouse. Furthermore, the linked data is available for export to Philips Re-search in de-identified format