Antibiotic resistance information exchanges : interim guidance

Antibiotic resistance (AR) is a major clinical and public health threat with potential to unravel more than half a century of human health advances offered by modern medical care. Unfortunately, modern healthcare delivery is notably contributory to the spread of antibiotic-resistant organisms, as patients who have become colonized with resistant organisms often receive care across multiple healthcare settings (e.g., ambulatory care, acute care hospitals (ACHs), and various long-term care (LTC) settings, including long-term acute care hospitals (LTACHs) and skilled nursing facilities (SNFs)).Although the threat of antibiotic-resistant organism transmission from a colonized patient to physically proximate patients remains for the duration of colonization, the lack of information sharing between healthcare facilities often results in the colonized status of a patient being unknown to a receiving or admitting facility. When this occurs, the appropriate infection control precautions are less likely to be used from the start of patient care, which increases the likelihood that resistant organisms will spread to other patients.The need for improved AR situational awareness is a major challenge to the U.S. Centers for Disease Control and Prevention\u2019s (CDC\u2019s) strategy to contain the most threatening forms of resistance and the genes responsible for such phenotypes. To fulfill their central role in implementing the CDC\u2019s containment strategy, some state health departments have developed systems (Multidrug-Resistant Organism (MDRO) Registries or MDRO Alert Systems, referred to herein as AR Information Exchanges (ARIEs)) that track patients previously colonized or infected with specific MDROs and then alert healthcare providers when these patients are admitted to a facility. The term AR Information Exchange emphasizes the importance of multidirectional information flow amongst healthcare facilities and public health authorities, as opposed to unidirectional data collection and storage.This interim guidance is intended for operational use by individuals and organizations responsible for developing or enhancing an ARIE; however, it does not constitute legal advice. Public health agencies should follow applicable laws, statues, and/or regulations when developing ARIEs with questions about directed to the entity\u2019s legal counsel.CS 324851-AARIE-Interim-Guidance-508.pdf20211158

Comparative study of healthcare messaging standards for interoperability in ehealth systems

Advances in the information and communication technology have created the field of "health informatics," which amalgamates healthcare, information technology and business. The use of information systems in healthcare organisations dates back to 1960s, however the use of technology for healthcare records, referred to as Electronic Medical Records (EMR), management has surged since 1990’s (Net-Health, 2017) due to advancements the internet and web technologies. Electronic Medical Records (EMR) and sometimes referred to as Personal Health Record (PHR) contains the patient’s medical history, allergy information, immunisation status, medication, radiology images and other medically related billing information that is relevant. There are a number of benefits for healthcare industry when sharing these data recorded in EMR and PHR systems between medical institutions (AbuKhousa et al., 2012). These benefits include convenience for patients and clinicians, cost-effective healthcare solutions, high quality of care, resolving the resource shortage and collecting a large volume of data for research and educational needs. My Health Record (MyHR) is a major project funded by the Australian government, which aims to have all data relating to health of the Australian population stored in digital format, allowing clinicians to have access to patient data at the point of care. Prior to 2015, MyHR was known as Personally Controlled Electronic Health Record (PCEHR). Though the Australian government took consistent initiatives there is a significant delay (Pearce and Haikerwal, 2010) in implementing eHealth projects and related services. While this delay is caused by many factors, interoperability is identified as the main problem (Benson and Grieve, 2016c) which is resisting this project delivery. To discover the current interoperability challenges in the Australian healthcare industry, this comparative study is conducted on Health Level 7 (HL7) messaging models such as HL7 V2, V3 and FHIR (Fast Healthcare Interoperability Resources). In this study, interoperability, security and privacy are main elements compared. In addition, a case study conducted in the NSW Hospitals to understand the popularity in usage of health messaging standards was utilised to understand the extent of use of messaging standards in healthcare sector. Predominantly, the project used the comparative study method on different HL7 (Health Level Seven) messages and derived the right messaging standard which is suitable to cover the interoperability, security and privacy requirements of electronic health record. The issues related to practical implementations, change over and training requirements for healthcare professionals are also discussed

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

Encounter management

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Мікросервіс парсингу і аналізу текстів, що отримуються з електронної медичної картки

Загальний обсяг роботи: 73 сторінки, 12 ілюстрацій, 19 таблиць, перелік посилань із 20 найменувань. Актуальність теми. Галузь аналізу великих даних, зокрема медичних, стрімко розвивається, і є великий попит на інструменти що дозволяють вилучати точкову інформацію з різного роду форматів даних. Медична інформація характеризується великим об’ємом різнорідних даних та, як і будь яка система обміну даними, певною мірою доповнюється мета інформацію, через збитковості даних часто виникають ситуації коли аналіз уповільнюється в рази, а інколи взагалі стає неможливим. Ці інструменти мають бути швидкими та гнучкими для забезпечення аналізу великих об’ємів даних. На разі, існує доволі мало рішень для парсингу повідомлень HL7 на платформі JVM, найпоширенішій платформі для розробки, а іcнуючі мають дуже низку швидкість парсингу точкової інформації. Мета та задачі дослідження. Метою даної роботи є удосконалення існуючих рішень для парсинга повідомлень медичного стандарту HL7. Задачею дослідження є реалізація парсера повідомлень стандарту HL7, що є більш ефективною для обробки великих масивів даних. Вирішення поставлених завдань та досягнуті результати. Було запропоновано розробку парсера на базі Scala та бібліотеки для побудови синтаксичного аналізатора Parboiled2, що мають достатньо можливостей для покращення роботи уже існуючого інструмента HAPI HL7 Terser для JVM платформи та Akka http для забезпення REST API та можливості впровадження як міні сервісу. Створений парсер було порівняно з HAPI HL7 Terser на наборі даних, що моделює отримання різної інформації з повідомлення. Об’єкт дослідження. Парсери повідомлень медичного стандарту HL7 Предмет дослідження. Граматика та структура медичного стандарту HL7 Методи дослідження. Досліджується структура повідомлення медичного стандарту HL7, його формат, особливості. Аналізуються інструменти, необхідні для створення парсера для таких повідомлень, а саме інструментарій створення синтаксичного аналізатора на основі граматик, інструменти для побудови DSL для запитів інформації. Наукова новизна Рішення що використовує Scala та Parboiled2 для покращення виконання задач парсингу інформаціїз медичного формату HL7. На разі, існує єдиний аналог для JVM, що дозволяє отримати будь-яку інформацію з повідомлення, це – HAPI HL7 Terser. За допомогою рішень, описаних в цій роботі, швидкість парсингу повідомлень збільшилась в середньому у 8 разів. Практичне значення одержаних результатів Розроблене рішення дозволяє отримати різнородну інформацію з повідомлення медичного стандрата HL7 на порядок швидше за існуючі аналоги на платформі JVM.The thesis contains 73 pages, 12 figures, 19 tables, 20 references. Relevance. The branch of analysis of large data, in particular medical, is rapidly developing, and there is a great demand for tools that allow to extract point information from various types of data formats. Medical information is characterized by a large amount of heterogeneous data and, like any data exchange system, the information is supplemented to a certain extent with information, due to the loss of data, situations often arise where the analysis slows down at times, and sometimes even becomes impossible. These tools should be fast and flexible to provide analysis of large amounts of data. At the moment, there are quite a few solutions for parsing HL7 messages on the JVM platform, a common development platform, and there are a lot of speed of parsing of point information. Purpose. The purpose of this work is to improve existing solutions for parsing messages of medical standard HL7. The task of the study is the implementation of the message parser standard HL7, which is more efficient for processing large data sets. Results. It was suggested to develop a parser based on Scala and a library for building Parboiled2 parser that have enough opportunities to improve the work of the existing HAPI HL7 Terser tool for the JVM platform and Akka http for the sake of the REST API and the possibility of implementing a mini service. The created parser was comparable to the HAPI HL7 Terser on a data set, simulating the receipt of various information from the message. Object of research. Message parsers of medical standard HL7. Subject of research. Grammar and structure of medical standard HL7. Research methods. The structure of the report of the medical standard HL7, its format, features is investigated. The tools needed to create a parser for such messages are analyzed, namely the tools for creating a grammar-based parser, tools for building DSL for information requests. Scientific novelty The solution uses Scala and Parboiled2 to improve the performance of information parsing tasks from medical format HL7. At the moment, there is only one analog for the JVM, which allows you to get any information from the message, it's HAPI HL7 Terser. With the help of the solutions described in this work, the message parsing speed has increased by an average of 8 times. Practical value. The developed solution allows you to obtain heterogeneous information from the medical standard HL7 message an order of magnitude faster than existing analogues.Общий объем работы: 73 страницы, 12 иллюстраций, 19 таблиц, перечень ссылок из 20 наименований. Актуальность темы. Отрасль анализа больших данных, в частности медицинских, стремительно развивается, и есть большой спрос на инструменты позволяющие изымать точечную информацию из различного рода форматов данных. Медицинская информация характеризуется большим объемом разнородных данных и, как и любая система обмена данными, в определенной степени дополняется цель информацию, из-за убыточности данных часто возникают ситуации, когда анализ замедляется в разы, а иногда вообще становится невозможным. Эти инструменты должны быть быстрыми и гибкими для обеспечения анализа больших объемов данных. На данный момент, существует довольно мало решений для парсинга сообщений HL7 на платформе JVM, распространенной платформе для разработки, а иcнуючи имеют очень ряд скорость парсинга точечной информации. Цель и задачи исследования. Целью данной работы является совершенствование существующих решений для парсинга сообщений медицинского стандарта HL7. Задачей исследования является реализация парсера сообщений стандарта HL7, что является более эффективной для обработки больших массивов данных. Решение поставленных задач и достигнутые результаты Было предложено разработку парсера на базе Scala и библиотеки для построения синтаксического анализатора Parboiled2, что имеют достаточно возможностей для улучшения работы уже существующего инструмента HAPI HL7 Terser для JVM платформы и Akka http для забезпення REST API и возможности внедрения мини сервиса. Созданный парсер было сравнимо с HAPI HL7 Terser на наборе данных, моделирующий получения различной информации из сообщения. Объект исследования Парсеры сообщений медицинского стандарта HL7. Предмет исследования Грамматика и структура медицинского стандарта HL7. Методы исследования Исследуется структура сообщение медицинского стандарта HL7, его формат, особенности. Анализируются инструменты, необходимые для создания парсера для таких сообщений, а именно инструментарий создания синтаксического анализатора на основе грамматик, инструменты для построения DSL для запросов информации. Научная новизна Решение использующий Scala и Parboiled2 для улучшения выполнения задач парсинга информации из медицинского формата HL7. На данный момент, существует единственный аналог для JVM, что позволяет получить любую информацию из сообщения, это - HAPI HL7 Terser. С помощью решений, описанных в этой работе, скорость парсинга сообщений увеличилась в среднем в 8 раз. Практическое значение полученных результатов. Разработанное решение позволяет получить разнородных информацию из сообщения медицинского стандрат HL7 на порядок быстрее существующих аналогов

A Two-Level Identity Model To Support Interoperability of Identity Information in Electronic Health Record Systems.

The sharing and retrieval of health information for an electronic health record (EHR) across distributed systems involves a range of identified entities that are possible subjects of documentation (e.g., specimen, clinical analyser). Contemporary EHR specifications limit the types of entities that can be the subject of a record to health professionals and patients, thus limiting the use of two level models in healthcare information systems that contribute information to the EHR. The literature describes several information modelling approaches for EHRs, including so called “two level models”. These models differ in the amount of structure imposed on the information to be recorded, but they generally require the health documentation process for the EHR to focus exclusively on the patient as the subject of care and this definition is often a fixed one. In this thesis, the author introduces a new identity modelling approach to create a generalised reference model for sharing archetype-constrained identity information between diverse identity domains, models and services, while permitting reuse of published standard-based archetypes. The author evaluates its use for expressing the major types of existing demographic reference models in an extensible way, and show its application for standards-compliant two-level modelling alongside heterogeneous demographics models. This thesis demonstrates how the two-level modelling approach that is used for EHRs could be adapted and reapplied to provide a highly-flexible and expressive means for representing subjects of information in allied health settings that support the healthcare process, such as the laboratory domain. By relying on the two level modelling approach for representing identity, the proposed design facilitates cross-referencing and disambiguation of certain demographics standards and information models. The work also demonstrates how it can also be used to represent additional clinical identified entities such as specimen and order as subjects of clinical documentation

A Review of Interoperability Standards in E-health and Imperatives for their Adoption in Africa

The ability of healthcare information systems to share and exchange information (interoperate) is essential to facilitate the quality and effectiveness of healthcare services. Although standardization is considered key to addressing the fragmentation currently challenging the healthcare environment, e-health standardization can be difficult for many reasons, one of which is making sense of the e-health interoperability standards landscape. Specifically aimed at the African health informatics community, this paper aims to provide an overview of e-health interoperability and the significance of standardization in its achievement. We conducted a literature study of e-health standards, their development, and the degree of participation by African countries in the process. We also provide a review of a selection of prominent e-health interoperability standards that have been widely adopted especially by developed countries, look at some of the factors that affect their adoption in Africa, and provide an overview of ongoing global initiatives to address the identified barriers. Although the paper is specifically aimed at the African community, its findings would be equally applicable to many other developing countries