Infection Control Through Clinical Pipelines Built with Arden Syntax MLM Building Blocks.

Healthcare-associated infections (HAIs) may have grave consequences for patients. In the case of sepsis, the 30-day mortality rate is about 25%. HAIs cost EU member states an estimated 7 billion Euros annually. Clinical decision support tools may be useful for infection monitoring, early warning, and alerts. MONI, a tool for monitoring nosocomial infections, is used at University Hospital Vienna, but needs to be clinically and technically revised and updated. A new, completely configurable pipeline-based system for defining and processing HAI definitions was developed and validated. A network of data access points, clinical rules, and explanatory output is arranged as an inference network, a clinical pipeline as it is called, and processed in a stepwise manner. Arden-Syntax-based medical logic modules were used to implement the respective rules. The system was validated by creating a pipeline for the ECDC PN5 pneumonia rule. It was tested on a set of patient data from intensive care medicine. The results were compared with previously obtained MONI output as a suitable reference, yielding a sensitivity of 93.8% and a specificity of 99.8%. Clinical pipelines show promise as an open and configurable approach to graphically-based, human-readable, machine-executable HAI definitions.

Health Digital Twins with Clinical Decision Support.

This paper studies the feasibility of incorporating clinical decision support (CDS) into health digital twins (HDTs). A HDT is visualized in a web application, health data are stored in a FHIR-based electronic health record, and an Arden-Syntax-based CDS interpretation and alert service is connected. The prototype focuses on interoperability of these components. The study confirms the feasibility of CDS integration into HDTs and provides insight into possibilities for further expansion.

Microbiological and Virological Knowledge-Based Alert Service.

Hospital wards need immediate information about multi-resistant pathogens and contagious viruses in their hospitalized patients. An alert service configurable with Arden-Syntax-based alert definitions passing through an ontology service to complement results from microbiology and virology with high-level terms was implemented as proof of concept. Integration into the University Hospital Vienna's IT landscape is ongoing.

Arden Syntax on FHIR.

Arden Syntax, a medical knowledge representation and processing language for clinical decision support tasks supervised by Health Level Seven International (HL7), was extended with HL7's Fast Healthcare Interoperability Resources (FHIR) constructs to allow standardized data access. The new version, Arden Syntax version 3.0, was successfully balloted as part of the audited, consensus-based, iterative HL7 standards development process.

A Comparative Study of the Arden Syntax and GDL Clinical Knowledge Representation Languages.

The expressiveness of a medical knowledge representation language has significant impact on the effectiveness of a knowledge-based clinical decision support system. We assess the expressiveness of two such languages, Arden Syntax and the Guideline Definition Language. Using data extracted from both languages' specifications, we quantify expressiveness by means of language syntax and the number of supported operators. Preliminary results show that Arden Syntax is a more dynamic standard, having better readability and a higher number and more diverse operators than GDL. In contrast, GDL is a more rigid language that utilizes an underlying data model specification in the openEHR framework.

A Digital Clinical Guideline Based on HL7 Arden Syntax for the Treatment of Children with Traumatic Brain Injury.

BACKGROUND: Intracranial hypertension is a serious complication accompanying the intensive care of children with traumatic brain injury. Intensive care of these patients is based on internationally accepted guidelines and their local editions. OBJECTIVE: The goal was to develop a software system for digital implementation of the clinical protocol for the treatment of intracranial hypertension in children, based on HL7 Arden Syntax clinical decision support. METHODS: Arden Syntax, an HL7 medical knowledge representation and processing standard, was used to develop a digital version of the local guideline. RESULTS: Comparison of 37 patients given conventional treatment with a second group of 84 patients treated with the digital clinical guideline yielded statistically significant differences. CONCLUSION: The digital clinical guideline system undoubtedly improves the doctor's awareness of the patient's existing condition and potential complications of intracranial hypertension.

Cerebral Autoregulation Monitoring and Online Arden Syntax Clinical Decision Support for the Treatment of Intracranial Hypertension in Children with Traumatic Brain Injury.

BACKGROUND: Intracranial hypertension is a serious complication in the intensive care of children with severe traumatic brain injury (STBI). OBJECTIVE: The goal was to create a computer system for simultaneous neuromonitoring of cerebral parameters and Arden-Syntax-based clinical decision support (CDS) in children with STBI undergoing intensive care treatment. METHODS: Intensive care of these patients is based on internationally accepted guidelines. Arden Syntax, which is an HL7 medical knowledge representation and processing standard for CDS systems, was used to develop digital algorithms for these guidelines. RESULTS: Comparison of a group of 37 conventionally treated patients with a second group (84 patients) monitored and treated with the combined CDS system yielded statistically significant differences. CONCLUSION: A combination of cerebral autoregulation monitoring with Arden-Syntax-based CDS in accordance with guidelines for the treatment of intracranial hypertension in children with STBI provides markedly better treatment outcomes. It opens up new options for the use of standards to formalize and process medical knowledge in neuromonitoring.

Exploring Methods of Implementing Arden Syntax for CDS Hooks.

BACKGROUND: Specifications for Arden Syntax lack provisions for the standardized access of clinical decision support (CDS) services. The CDS Hooks standard provides such access. OBJECTIVES: To extend an ArdenSuite reference implementation of the Arden Syntax by providing a CDS-Hooks-compatible interface. METHODS: With the use case Hepaxpert, an Arden-Syntax-based expert system for the interpretation of hepatitis serology test results, a needs analysis was performed to identify changes required in the ArdenSuite reference implementation to support the CDS Hooks API. Arden Syntax language support for CDS Hooks was also assessed. RESULTS: The needs assessment was performed in three phases: hook assessment, hook context definition, and Card definition. For the use case, the ArdenSuite was modified to include a new hook and hook context, which defines the type of CDS service as well its input parameters. Card definitions were created in the ArdenSuite. Examples of Arden Syntax support for the use case are presented for all three phases. CONCLUSION: Minor changes in the ArdenSuite made it compatible with the CDS Hooks specification.

Augmenting Analytics Software for Clinical Microbiology by Man-Machine Interaction.

In the present study, we intended to solve identification problems in analyzing the results of microbiology by proactive man-machine interaction. We modified the analytics software MOMO so that it flags laboratory results containing textual elements unknown to the thesaurus, and a human expert assigns the elements to the respective existing thesaurus elements or creates new ones. In 773,309 laboratory results, roughly 2.6% contained unassigned elements and would have been ignored in thesaurus-based analyses for purposes other than simply reporting microbiological findings to physicians. In current use, the thesaurus is kept up to date with synonyms, syntactic deviations, misspellings, and entries not contained earlier, with man-machine interaction of 2-3 hours per week. This approach helps to accommodate both up-to-date clinical reporting for immediate patient care as well as up-to-date queries for infection surveillance and epidemiology, outbreak management, quality control and benchmarking, and antimicrobial stewardship.

Integral Homeostasis Index in a Decision Support System for the Assessment and Prediction of the Clinical Condition of Children with Severe Mechanical Trauma.

OBJECTIVE: Daily assessment of the acid-base balance (ABB) in blood is one of the important elements of multi-parameter patient monitoring at intensive care units (ICUs). The present work aims to determine the effectiveness and validity of the integral homeostasis index IHx calculated from ABB blood test data for the assessment and prognosis of children with critical traumatic conditions. METHODS: 345 patients were studied. IHx was calculated and the data were subjected to statistical evaluation. An Arden-Syntax-based clinical decision support (CDS) platform was used. One purpose of the study was to incorporate the platform into the ICU IT landscape of the hospital, and the second purpose was to develop a CDS module for the calculation of IHx and present the results in real time to the attending physician. RESULTS: Integral homeostasis index IHx calculations as well as their prompt assessment permit better and more rapid treatment of children with severe traumatic injury.

Implementing CDS Hooks Communication in an Arden-Syntax-Based Clinical Decision Support Platform.

INTRODUCTION: Arden Syntax is a Health Level Seven International standard for the development of clinical decision support (CDS) solutions. CDS Hooks is a specification for an interface to call CDS services from an electronic health record. Implementing the CDS Hooks interface into ArdenSuite, an Arden-Syntax-based CDS platform, will further enhance its interoperability with external systems. METHODS: The development of this interface consisted of three parts: (1) The RESTful interface defined by CDS Hooks had to be implemented; this included the support of specifically formatted data for the input and output of the CDS functions. (2) The existing FHIR connector had to be adjusted. In CDS Hooks, a FHIR server can be defined for each CDS service call individually. In the current version of the connector, a FHIR server has to be configured in advance to call the CDS service. (3) Additional data points that did not exist previously, such as a description or hook for each CDS service, had to be collected and saved. RESULTS: Basic support of the CDS Hooks API was established in the ArdenSuite and tested. The FHIR connector was adapted. DISCUSSION: The missing parts for full CDS Hooks support were implemented. As a use case, we employed Hepaxpert, an interpretive system for hepatitis serology tests. CDS Hooks defines FHIR as the only data source. ArdenSuite, in contrast, offers the option of various data sources with connectors and extensions.

Separating Business Logic from Medical Knowledge in Digital Clinical Workflows Using Business Process Model and Notation and Arden Syntax.

BACKGROUND: Evidence-based clinical guidelines have a major positive effect on the physician's decision-making process. Computer-executable clinical guidelines allow for automated guideline marshalling during a clinical diagnostic process, thus improving the decision-making process. OBJECTIVES: Implementation of a digital clinical guideline for the prevention of mother-to-child transmission of hepatitis B as a computerized workflow, thereby separating business logic from medical knowledge and decision-making. METHODS: We used the Business Process Model and Notation language system Activiti for business logic and workflow modeling. Medical decision-making was performed by an Arden-Syntax-based medical rule engine, which is part of the ARDENSUITE software. RESULTS: We succeeded in creating an electronic clinical workflow for the prevention of mother-to-child transmission of hepatitis B, where institution-specific medical decision-making processes could be adapted without modifying the workflow business logic. CONCLUSION: Separation of business logic and medical decision-making results in more easily reusable electronic clinical workflows.

Achieving Interoperability Between Arden-Syntax-Based Clinical Decision Support and openEHR-Based Data Systems.

BACKGROUND: Arden Syntax is an international standard for medical knowledge representation and processing. The openEHR Foundation publishes specifications for the creation of electronic health records based on interoperable data models. OBJECTIVES: To perform a feasibility study showing how Arden Syntax medical logic modules (MLMs) can access openEHR data. METHODS: Medexter's ArdenSuite was applied as an implementation of an Arden-Syntax-based clinical decision support framework, and Marand's EhrScape as an implementation of an openEHR system, for the purpose of data exchange. To assess their interoperability, we developed a use case in which ArdenSuite was connected to EhrScape; the purpose was to determine whether a patient suffers from orthostatic hypotension based on data supplied by EhrScape and decision support provided by Arden Syntax MLMs. RESULTS: An archetype query language request was sent from an MLM to EhrScape, and the results were sent back. CONCLUSION: This preliminary study clearly shows that the ArdenSuite's MLMs can communicate with openEHR-based data sources.

A detailed analysis of the Arden Syntax expression grammar.

OBJECTIVE: The Arden Syntax for Medical Logic Systems is a standard for encoding and sharing medical knowledge in the form of Medical Logic Modules. To improve accessibility for clinicians, the originators of the standard deliberately designed Arden Syntax expressions to resemble natural language, and parentheses around operands are not generally required. For certain patterns of nested expressions, however, the use of parentheses is mandatory, otherwise they are not accepted by an Arden Syntax environment. In this study, we refer to such patterns as anomalies. The purpose of this paper is to investigate the extent and the circumstances of such anomalies, and to outline a solution based on an alternative grammar encoding approach. METHODS: To analyze the distribution of anomalies in nested expressions, we developed two custom-made complementary utilities. The first utility, termed parser, checks a single expression pattern against the specification-compliant grammar for syntactic correctness. The second utility, termed composer, automatically creates an extensive amount of expression patterns by permuting and nesting operators without the use of parentheses, and stores these together with the expected syntactic correctness. By means of these utilities we conducted a comprehensive analysis of anomalies by comparing the expected correctness with the actual correctness. Any detected anomalies are stored into a set of files, grouped by the respective top-level operator, for a subsequent analysis. RESULTS: The composer utility nested 165 unary, binary, or ternary operators of Arden Syntax version 2.8 to a depth of two, resulting in a set of 76,533 expression patterns, of which 18,978 (24.8%) have been identified as anomalies. An automated assessment of their practical relevance for medical knowledge encoding is infeasible. Manual screening of selected samples indicated that only a small proportion of the detected anomalies would be relevant. The cause of the anomalies lies in the encoding of the grammar. A change of the basic encoding approach with some additional customizations eliminates the anomalies. A working expression parser is included in the supplementary material. CONCLUSION: Arden Syntax expressions are affected by anomalies. Since only a small proportion of them have practical relevance and they cannot cause false calculations or clinical decisions, their practical impact is likely limited. However, they may be potential points of confusion for knowledge engineers. An alternative expression grammar, based on a different encoding approach, would not only eliminate the anomalies, but could considerably facilitate both maintenance and further development of the standard.

Evolution of the Arden Syntax: Key Technical Issues from the Standards Development Organization Perspective.

BACKGROUND: The initial version of the Arden Syntax for Medical Logic Systems was created to facilitate explicit representation of medical logic in a form that could be easily composed and interpreted by clinical experts in order to facilitate clinical decision support (CDS). Because of demand from knowledge engineers and programmers to improve functionality related to complex use cases, the Arden Syntax evolved to include features typical of general programming languages but that were specialized to meet the needs of the clinical decision support environment, including integration into a clinical information system architecture. METHOD: Review of the design history and evolution of the Arden Syntax by workers who participated in this evolution from the perspective of the standards development organization (SDO). RESULTS: In order to meet user needs, a variety of features were successively incorporated in Arden Syntax. These can be grouped in several classes of change, including control flow, data structures, operators and external links. These changes included expansion of operators to manipulate lists and strings; a formalism for structured output; iteration constructs; user-defined objects and operators to manipulate them; features to support international use and output in different natural languages; additional control features; fuzzy logic formalisms; and mapping of the entire syntax to XML. The history and rationale of this evolution are summarized. CONCLUSION: In response to user demand and to reflect its growing role in clinical decision support, the Arden Syntax has evolved to include a number of powerful features. These depart somewhat from the original vision of the syntax as simple and easily understandable but from the SDO perspective increase the utility of this standard for implementation of CDS. Backwards compatibility has been maintained, allowing continued support of the earlier, simpler decision support models.

Executable medical guidelines with Arden Syntax-Applications in dermatology and obstetrics.

INTRODUCTION: Clinical decision support systems (CDSSs) are being developed to assist physicians in processing extensive data and new knowledge based on recent scientific advances. Structured medical knowledge in the form of clinical alerts or reminder rules, decision trees or tables, clinical protocols or practice guidelines, score algorithms, and others, constitute the core of CDSSs. Several medical knowledge representation and guideline languages have been developed for the formal computerized definition of such knowledge. One of these languages is Arden Syntax for Medical Logic Systems, an International Health Level Seven (HL7) standard whose development started in 1989. Its latest version is 2.10, which was presented in 2014. In the present report we discuss Arden Syntax as a modern medical knowledge representation and processing language, and show that this language is not only well suited to define clinical alerts, reminders, and recommendations, but can also be used to implement and process computerized medical practice guidelines. METHODS: This section describes how contemporary software such as Java, server software, web-services, XML, is used to implement CDSSs based on Arden Syntax. Special emphasis is given to clinical decision support (CDS) that employs practice guidelines as its clinical knowledge base. RESULTS: Two guideline-based applications using Arden Syntax for medical knowledge representation and processing were developed. The first is a software platform for implementing practice guidelines from dermatology. This application employs fuzzy set theory and logic to represent linguistic and propositional uncertainty in medical data, knowledge, and conclusions. The second application implements a reminder system based on clinically published standard operating procedures in obstetrics to prevent deviations from state-of-the-art care. A to-do list with necessary actions specifically tailored to the gestational week/labor/delivery is generated. DISCUSSION: Today, with the latest versions of Arden Syntax and the application of contemporary software development methods, Arden Syntax has become a powerful and versatile medical knowledge representation and processing language, well suited to implement a large range of CDSSs, including clinical-practice-guideline-based CDSSs. Moreover, such CDS is provided and can be shared as a service by different medical institutions, redefining the sharing of medical knowledge. Arden Syntax is also highly flexible and provides developers the freedom to use up-to-date software design and programming patterns for external patient data access.

Arden Syntax MLM Building Blocks for Microbiological Concepts and Their Application in Infection Surveillance.

BACKGROUND: The diagnosis - and hence definitions - of healthcare-associated infections (HAIs) rely on microbiological laboratory test results in specific constellations. OBJECTIVES: To construct a library that provides interoperable building blocks for the analysis of microbiological laboratory test results. METHODS: We used Java for preprocessing raw microbiological laboratory test results and Arden Syntax for knowledge-based querying of data based on microbiology information elements used in European surveillance criteria for HAIs. To test the library and quantify how often these information elements occur in the data, we performed a retrospective cohort study on adult patients admitted for at least 24 hours to an intensive care unit at the Vienna General Hospital in 2013. RESULTS: We identified eleven information elements for which information was electronically available. These elements were identified positively 1,239 times in 1,184 positive microbiology tests from 563 patients. DISCUSSION: The availability of a library for the analysis of microbiology laboratory test results in HAI terms facilitates electronic HAI surveillance.

Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

Arden Syntax Clinical Foundation Framework for Event Monitoring in Intensive Care Units: Report on a Pilot Study.

The creation of clinical decision support systems has received a strong impulse over the last years, but their integration into a clinical routine has lagged behind, partly due to a lack of interoperability and trust by physicians. We report on the implementation of a clinical foundation framework in Arden Syntax, comprising knowledge units for (a) preprocessing raw clinical data, (b) the determination of single clinical concepts, and (c) more complex medical knowledge, which can be modeled through the composition and configuration of knowledge units in this framework. Thus, it can be tailored to clinical institutions or patients' caregivers. In the present version, we integrated knowledge units for several infection-related clinical concepts into the framework and developed a clinical event monitoring system over the framework that employs three different scenarios for monitoring clinical signs of bloodstream infection. The clinical event monitoring system was tested using data from intensive care units at Vienna General Hospital, Austria.