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The Columbia-Presbyterian Medical Center decision-support system as model for implementing the Arden Syntax
Abstract
Columbia-Presbyterian Medical Center is implementing a decision-support system based on the Arden Syntax for Medical Logic Modules (MLM's). The system uses a compiler-interpreter pair. MLM's are first compiled into pseudo-codes, which are instructions for a virtual machine. The MLM's are then executed using an interpreter that emulates the virtual machine. This design has resulted in increased portability, easier debugging and verification, and more compact compiled MLM's. The time spent interpreting the MLM pseudo-codes has been found to be insignificant compared to database accesses. The compiler, which is written using the tools "lex" and "yacc," optimizes MLM's by minimizing the number of database accesses. The interpreter emulates a stack-oriented machine. A phased implementation of the syntax was used to speed the development of the system.
... Online allows for the computation of prognostic estimates of outcomes like survival rates or relapse risks for adjuvant systemic therapies. These computations are based on the comparison of a current patient case, which is described in terms of some crucial data, with a large patient case population, [Hess (2008)]. Somehow analogous, PREDICT uses an advanced data model and profound statistical methods in order to compute a prognosis of outcome for patients, who have undergone breast surgery, see [Wishart et al (2010), Wishart et al (2012)]. ...
... However, the establishing of such a system requires suitable encoding of guidelines in some rule syntax and a corresponding module for their automated interpretation, see for example [Hripcsak et al (1991), van der Lei and Talman (1997)]. The encoding of guidelines in an intuitive representation especially for medical fields with long-term treatment like breast cancer is known as a major challenge, [Musen et al (2006)]. ...
Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning.
... At CPMC, Arden Syntax is used to represent knowledge in the Hospital information system (HIS) with decision-support that now run in production with real patient data [2]. The system converts source MLM's to pseudocodes for a virtual machine. ...
... Some kind of dynamic linking is preferred, so that the system can still run when adding or changing MLM-modules. The size of each compiled module will take approximately 500 bytes, which is about the same size as the with the pseudocode method [2]. if varl="A" and decrease of var2 < 10 then conclude true; elseif varl="B" and max var2 >= 10 then conclude true; else conclude false; endif; action: ...
A method is presented where medical knowledge modules, written in the Arden Syntax, are used in a decision-support system (DSS). Knowledge modules are, after syntax-checking, translated into the object oriented programming language C++, compiled and linked to the DSS. The object oriented approach together with developed tools, such as knowledge editor and translator, makes it possible to implement the Arden Syntax and to get an efficient, easy-maintained DSS. Work on a prototype shows that this approach has several advantages when building a DSS where medical knowledge is represented in the Arden Syntax.
... We took a more open-ended approach. Health care providers at Columbia-Presbyterian Medical Center (CPMC) have access to computer-generated alerts and interpretations on their patients [10]. We set out to obtain feedback (in the form of electronic comments) from providers about the alerts and interpretations, in whatever form and on whatever aspect the provider desired. ...
... CPMC provides automated decision-support through its clinical event monitor [10], which is based upon the Arden Syntax for Medical Logic Modules [13]. Clinical Figure 1. ...
Columbia-Presbyterian Medical Center's health care providers have access to alerts and interpretations generated by an Arden Syntax-based clinical event monitor. They have the opportunity to send comments to the clinical information services staff. Over a period of 26 months, they sent 126 comments. The comments were analyzed using the critical incident technique, resulting in a hierarchy of categories that summarizes user concerns. The majority of comments (65) indicated that the messages were actually (8) or at least potentially useful (57). A minority (28) indicated that they were unhelpful (27) or actually harmful (1). Another group (27) made suggestions or asked questions. The comments have been very helpful for the maintenance of Medical Logic Modules (MLMs) and the clinical event monitor itself.
... To convert MLMs into an executable format, Arden Syntax compilers described in the literature usually either transform code into intermediate all-purpose programming languages such as Java [8][9][10] or C++ [11], or into specific virtual machine code [12]. The construction of such a compiler by means of a parser generator presupposes a computable language description in the form of a grammar, usually provided in Backus-Naur form. ...
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.
... CIGs follow standard formats, such as XML, RDF, and any other standard format. Examples of such knowledge acquisition include use of an Arden Syntax editor to explicitly transform the clinical knowledge into an executable module, an approach mentioned in [10]. ...
Objective:
The objective of this study is to help a team of physicians and knowledge engineers acquire clinical knowledge from existing practices datasets for treatment of head and neck cancer, to validate the knowledge against published guidelines, to create refined rules, and to incorporate these rules into clinical workflow for clinical decision support.
Methods and materials:
A team of physicians (clinical domain experts) and knowledge engineers adapt an approach for modeling existing treatment practices into final executable clinical models. For initial work, the oral cavity is selected as the candidate target area for the creation of rules covering a treatment plan for cancer. The final executable model is presented in HL7 Arden Syntax, which helps the clinical knowledge be shared among organizations. We use a data-driven knowledge acquisition approach based on analysis of real patient datasets to generate a predictive model (PM). The PM is converted into a refined-clinical knowledge model (R-CKM), which follows a rigorous validation process. The validation process uses a clinical knowledge model (CKM), which provides the basis for defining underlying validation criteria. The R-CKM is converted into a set of medical logic modules (MLMs) and is evaluated using real patient data from a hospital information system.
Results:
We selected the oral cavity as the intended site for derivation of all related clinical rules for possible associated treatment plans. A team of physicians analyzed the National Comprehensive Cancer Network (NCCN) guidelines for the oral cavity and created a common CKM. Among the decision tree algorithms, chi-squared automatic interaction detection (CHAID) was applied to a refined dataset of 1229 patients to generate the PM. The PM was tested on a disjoint dataset of 739 patients, which gives 59.0% accuracy. Using a rigorous validation process, the R-CKM was created from the PM as the final model, after conforming to the CKM. The R-CKM was converted into four candidate MLMs, and was used to evaluate real data from 739 patients, yielding efficient performance with 53.0% accuracy.
Conclusion:
Data-driven knowledge acquisition and validation against published guidelines were used to help a team of physicians and knowledge engineers create executable clinical knowledge. The advantages of the R-CKM are twofold: it reflects real practices and conforms to standard guidelines, while providing optimal accuracy comparable to that of a PM. The proposed approach yields better insight into the steps of knowledge acquisition and enhances collaboration efforts of the team of physicians and knowledge engineers.
... Later versions (2.5 and higher) are capable of processing complex data such as tree structured microbiology data or possibly even random sets of entire patient records. Even the traditional limitation to a single patient focus retained by most Arden Syntax engines, such as the model implementation at the Columbia Presbyterian Medical Center (CPMC) [19], may have to be overcome e.g., for infection outbreak monitoring. ...
Objective:
Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden Syntax Medical Logic Modules must be able to retrieve patient data from the electronic medical record in order to enable automated decision making. For patient data with a simple structure, for instance a list of laboratory results, or, in a broader view, any patient data with a list or table structure, this mapping process is straightforward. Nevertheless, if patient data are of a complex nested structure the mapping process may become tedious. Two clinical requirements - to process complex microbiology data and to decrease the time between a critical laboratory event and its alerting by monitoring Health Level 7 (HL7) communication - have triggered the investigation of approaches for providing complex patient data from electronic medical records inside Arden Syntax Medical Logic Modules.
Methods and materials:
The data mapping capabilities of current versions of the Arden Syntax standard as well as interfaces and data mapping capabilities of three different Arden Syntax environments have been analyzed. We found and implemented three different approaches to map a test sample of complex microbiology data for 22 patients and measured their execution times and memory usage. Based on one of these approaches, we mapped entire HL7 messages onto congruent Arden Syntax objects.
Results:
While current versions of Arden Syntax support the mapping of list and table structures, complex data structures are so far unsupported. We identified three different approaches to map complex data from electronic patient records onto Arden Syntax variables; each of these approaches successfully mapped a test sample of complex microbiology data. The first approach was implemented in Arden Syntax itself, the second one inside the interface component of one of the investigated Arden Syntax environments. The third one was based on deserialization of Extended Markup Language (XML) data. Mean execution times of the approaches to map the test sample were 497ms, 382ms, and 84ms. Peak memory usage amounted to 3MB, 3MB, and 6MB.
Conclusion:
The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with an appropriate XML data format.
... In a cooperation project with the system vendor, the PDMS (Integrated Care Manager, ICM ® , Dräger Medical, Lübeck, Germany) has been enhanced with modular decision support functions based on the Arden Syntax for Medical Logic Systems. This language has been designed to represent medical knowledge in a standardized and shareable form [16], and has found its traditional role for datadriven clinical event monitoring [17][18][19]. Arden Syntax "may be considered as a hybrid between classical production rules and procedural representation of clinical algorithms" [20]. In Arden, medical knowledge is contained in Medical Logic Modules (MLMs). ...
Objective:
Bacterial infections frequently cause prolonged intensive care unit (ICU) stays. Repeated measurements of the procalcitonin (PCT) biomarker are typically used for early detection and follow up of bacterial infections and sepsis, but those PCT measurements are costly. To avoid overutilization, we developed and evaluated a clinical decision support system (CDSS) in Arden Syntax which computes necessary and preventable PCT orders.
Methods:
The CDSS implements a rule set based on the latest PCT value, the time period since this measurement, and the PCT trend scenario. We assessed the CDSS effects on the daily rate of ordered PCT tests within a prospective study having two ON and two OFF phases in a surgical ICU. In addition, we performed interviews with the participating physicians to investigate their experience with the CDSS advice.
Results:
Prior to the deployment of the CDSS, 22% of the performed PCT tests were potentially preventable according to the rule set. During the first ON phase the daily rate of ordered PCT tests per patient decreased significantly from 0.807 to 0.662. In subsequent OFF, ON and OFF phases, however, PCT utilization reached again daily rates of 0.733, 0.803, and 0.792, respectively. The interviews demonstrated that the physicians were aware of the problem of PCT overutilization, which they primarily attributed to acute time constraints. The responders assumed that the majority of preventable measurements are indiscriminately ordered for patients during longer ICU stays.
Conclusion:
We observed an 18% reduction of PCT tests within the first four weeks of CDSS support in the investigated ICU. This reduction may have been influenced by raised awareness of the overutilization problem; the extent of this influence cannot be determined in our study design. No reduction of PCT tests could be observed during the second ON phase. The physician interviews indicated that time critical ICU situations can prevent extensive reflection about the necessity of individual tests. In order to achieve an enduring effect on PCT utilization, we will have to proceed to electronic order entry.
... Contrary to other implementations of Arden Syntax [2,3], we programmed an engine to read and execute the serialized MLMs. The engine is used to coordinate communications with the surround- ing environment. ...
The Arden Syntax for Medical Logic Systems is a standard for clinical knowledge representation, maintained by the Health Level Seven (HL7) organization and approved by the American National Standards Institute (ANSI). It offers a wide range of syntactical constructs (various forms of numer-ical, logical, temporal operators, conditions, …), each of which crisply defines a specific unit of clinical knowledge (yes-no evaluations). As medical conditions and conclusions cannot always be formulated in a strict manner, methods of fuzzy set theory and logic are used to represent uncer-tainty, which is usually a part of practical clinical knowledge. Based on the extension of Arden Syntax to Fuzzy Arden Syntax by Vetterlein et al. (on the basis of Tiffe's earlier extension), we im-plemented a Fuzzy Arden Syntax compiler which is able to process a fully fuzzified version of Ar-den Syntax. We describe the compiler, its components (lexer, parser, and synthesis), and discuss its implementation.
... MEDAILLE has a syntax checker and an integrated terminology. Translation of MLMs into an executable form can be done by a number of compilers [12,13]. ...
The Guideline Interchange Format (GLIF) and the Arden Syntax are methodologies that were created for the purpose of sharing certain kinds of medical knowledge. While the Arden Syntax is already a standard of the American Society for Testing and Materials (ASTM) and has been used to implement medical decision rules, GLIF is an evolving methodology for representing the logic and flow of clinical guidelines. In this paper we seek to define the relationship between GLIF and the Arden Syntax, highlighting the complementary role that they play in sharing medical knowledge. While the Arden Syntax was designed to represent single decision rules in self-contained units called Medical Logic Modules (MLMs), GLIF specifies entire guidelines that are generally intended to unfold over time. An MLM has a single specification that is computable, while guideline development in GLIF can be done at three different levels of abstraction: an conceptual flowchart of medical decisions and actions, a computable specification that includes well-defined delineation of decision criteria and patient data, and an implementable specification, that includes local adaptations and mapping of guideline variables to institutional databases. The current version of GLIF uses a superset of the Arden Syntax logic grammar to specify logical and temporal decision criteria, but includes additional constructs that support other elements required by complex clinical guidelines. GLIF also includes an MLMmacro class that enables mapping of guideline recommendations into MLMs, in cases where the implementing institution wishes to use MLMs. 1.
... The terminologic knowledge they contain adds to the burden of keeping the content accurate , but also provides some support for the task in the form of knowledge-based terminology maintenance. The original plan for the clinical information system being constructed at Columbia University and the New York Presbyterian Hospital (NYPH, formerly Presbyterian Hospital) in 1988 required that a single coding system be used to encode data acquired from multiple sources, for storage in a single, coherent data repository [7]. The data sources did not use the same (or often, any) standard terminology, but no single standard terminology existed to which the source terms could be mapped. ...
The Medical Entities Dictionary (MED) has served as a unified terminology at New York Presbyterian Hospital and Columbia University for more than 20 years. It was initially created to allow the clinical data from the disparate information systems (e.g., radiology, pharmacy, and multiple laboratories, etc.) to be uniquely codified for storage in a single data repository, and functions as a real time terminology server for clinical applications and decision support tools. Being conceived as a knowledge base, the MED incorporates relationships among local terms, between local terms and external standards, and additional knowledge about terms in a semantic network structure. Over the past two decades, we have sought to develop methods to maintain, audit and improve the content of the MED, such that it remains true to its original design goals. This has resulted in a complex, multi-faceted process, with both manual and automated components. In this paper, we describe this process, with examples of its effectiveness. We believe that our process provides lessons for others who seek to maintain complex, concept-oriented controlled terminologies.
... Medical Logic Modules (MLMs) 23 are software modules, written in the Arden Syntax, 24 -26 that, when implemented in a clinical information system, 27 run on databases of patient data and typically provide alerts or reminders for clinicians. 28, 29 The purpose of an MLM is to store knowledge required for triggering an action based on data in a patient database. ...
Objective: To allow exchange of clinical practice guidelines among institutions and computer-based applications.
Design: The GuideLine Interchange Format (GLIF) specification consists of the GLIF model and the GLIF syntax. The GLIF model is an object-oriented representation that consists of a set of classes for guideline entities, attributes for those classes, and data types for the attribute values. The GLIF syntax specifies the format of the test file that contains the encoding.
Methods: Researchers from the InterMed Collaboratory at Columbia University, Harvard University (Brigham and Women's Hospital and Massachusetts General Hospital), and Stanford University analyzed four existing guideline systems to derive a set of requirements for guideline representation. The GLIF specification is a consensus representation developed through a brainstorming process. Four clinical guidelines were encoded in GLIF to assess its expressivity and to study the variability that occurs when two people from different sites encode the same guideline.
Results: The encoders reported that GLIF was adequately expressive. A comparison of the encodings revealed substantial variability.
Conclusion: GLIF was sufficient to model the guidelines for the four conditions that were examined. GLIF needs improvement in standard representation of medical concepts, criterion logic, temporal information, and uncertainty.
... Clinical Trial Alerts are provided by the National Library of Medicine. The Medical Logic Modules Library provides a sample set of the Arden Syntax project of the Medical Informatics Department [5]. The Physician's Desk Reference includes a fully indexed and searchable version of the full text of the PDR, the PDR for Nonprescription Drugs and the PDR for Ophthalmology. ...
In conjunction with other researchers at Columbia-Presbyterian Medical Center (CPMC) we have developed a number of hypertext and free text retrieval computer applications aimed at an extremely diverse audience which includes students and faculty in a university setting as well as health care providers and patients in hospital and clinic settings. Hypertext and free text systems offer features which make them ideal for presenting information in a wide variety of contexts; however, they also have several major weaknesses which must be addressed before these applications can be useful tools. We have learned to maximize the strengths and minimize the weaknesses to present material in a manner that is individualized to the needs of each user from the research scientist in the lab to the patient at the bedside.
... Many clinical information systems (CIS) include applications which require the use of controlled vocabularies . For example, alerting systems, such as the HELP system [1] and the CPMC system [2], use medical logic to query patient data which is represented as controlled terms. Diagnostic systems, such as QMR [3] and DXplain [4], use controlled terminology to obtain clinical information for making diagnoses. ...
A considerable amount of research has been concerned with the development of natural language systems to automate the encoding of clinical information that occurs in textual form. The task is very complex, and not many language processors are used routinely within clinical information systems. Those systems that are operational, have been implemented in narrow domains for particular applications. For a system to be truly useful, it should be designed so that it could be widely used within the clinical environment. This paper examines architectural requirements we have identified as being necessary for portability and describes the architecture of the system we developed. Our system was designed so that it could be used in different domains to serve a variety of applications. It has been integrated with the clinical information system at Columbia-Presbyterian Medical Center where it routinely encodes clinical information from radiological reports of patients.
... The implementation at CPMC uses a virtual machine. 16 This implies that the Arden compiler produces specific code for this virtual machine; the produced compiled code can be reused, provided that the virtual machine is rewritten for the target information system. Another practical result is that MLMs can be added without recompiling or linking. ...
The Arden Syntax was introduced more than 10 years ago, but it is still not in widespread use. One reason might be that for each particular architecture and information system, a different Arden Syntax compiler must be written as well as a program for the runtime execution of the medical logic modules (MLMs). The authors have designed and implemented an architecture that increases the portability of Arden Syntax rules, using the Java platform. The portability to a target information system is achieved by the addition of appropriate adapter components, which they call mappers. These mappers are dynamically selected using explicit and implicit elements of MLMs. Furthermore, they can help translate data from the clinical information system representation into the representation needed by an MLM. This was validated by an experiment in two clinical units. Also, the authors propose a convention to name signals that trigger other MLMs (called intermediate states) so that they remain unique to each institution. The authors implemented this architecture in their clinical system and in an XML-based medical record application that has been used experimentally in their urology and nephrology departments. The Tetrasys company that provided the medical record was able to incorporate their runtime without modifications, and typical MLM execution time was less than 1 sec.
Standards gewinnen in der medizinischen Informatik zunehmend an Bedeutung. Die Arbeit beschreibt die für die medizinische Informatik wichtigen Standardisierungsorganisationen sowie existierende Standards und laufende Arbeiten.
BACKGROUND : The Arden Syntax is a standard medical knowledge encoding language which is the most widely studied and used. However, performance degradation in monitoring clinical events is the significant barrier to the standard CDSS dissemination. PURPOSE : We propose a design of real-time clinical event monitor(CEM) for the Arden Syntax based CDSS. METHOD : The main idea is to minimize workloads towards existing Hospital Information System (HIS) with least building cost. For the minimum building cost we decided to use trigger. Hripcsak G, P. et al.[4] say that developing CEM using internal function is the easiest and fastest (both in building time and performance) method. However, triggers may cause significant performance degradation of the HIS. Therefore to minimize the workloads we split MLM evoking event into three levels, real-event, macro-event, and micro-event. And we divided monitoring work to be performed both inside the HIS and outside the HIS. The realevent is the event specified in evoke slot. The macro-event is non-constrained real-event which only specifies the sort of data to be monitored and not the constraints. One macro-event can have one or more micro-events. The micro-event is an atomic event of its macro-event. Our CEM is designed to create the least number of triggers when registering events. It monitors only distinct micro-events by triggers. When the system encounters a new micro-event to register, it adds monitoring condition into the existing trigger as many as possible, instead of creating a new one. And macro-events are inferenced from the detected micro-events information. The macro-events and related MLM list is sent to CEM compoenent working outside the HIS and the real-events are validated in that component. RESULT : We successfully implemented and evaluated our design. The experimental results show that adopting our clinical event monitor to real-time hospital information system is promising.
Introduction and Historical PerspectiveStructure of Primary Care Asthma ServicesContent of Asthma ServicesGuideline ImplementationSummaryReferences
The topics discussed in this chapter relate to formal methods for knowledge representation and reasoning that are gaining momentum through international efforts in many spheres, including health care. Although these methods have not yet had much impact on clinical decision support as currently implemented and deployed, it is expected that they will have growing importance in coming years, driven by the need to bring together the many disparate efforts and perspectives that require more adaptable, flexible, and robust methodologies.
Objective:
Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data management system (PDMS) at our local intensive care units does not natively support patient overviews from customizable CDS routines, but local physicians indicated a demand for multi-patient tabular overviews of important clinical parameters such as key laboratory measurements. As our PDMS installation provides Arden Syntax support, we set out to explore the capability of Arden Syntax for multi-patient CDS by implementing a prototypical dashboard for visualizing laboratory findings from patient sets.
Methods and material:
Our implementation leveraged the object data type, supported by later versions of Arden, which turned out to be serviceable for representing complex input data from several patients. For our prototype, we designed a modularized architecture that separates the definition of technical operations, in particular the control of the patient context, from the actual clinical knowledge. Individual Medical Logic Modules (MLMs) for processing single patient attributes could then be developed according to well-tried Arden Syntax conventions.
Results:
We successfully implemented a working dashboard prototype entirely in Arden Syntax. The architecture consists of a controller MLM to handle the patient context, a presenter MLM to generate a dashboard view, and a set of traditional MLMs containing the clinical decision logic. Our prototype could be integrated into the graphical user interface of the local PDMS. We observed that with realistic input data the average execution time of about 200ms for generating dashboard views attained applicable performance.
Conclusion:
Our study demonstrated the general feasibility of creating multi-patient CDS routines in Arden Syntax. We believe that our prototypical dashboard also suggests that such implementations can be relatively easy, and may simultaneously hold promise for sharing dashboards between institutions and reusing elementary components for additional dashboards.
Attempts to modify physician behaviour and reduce practice variation with guidelines have had limited success, largely because of inadequate attention and resources devoted to implementing the guidelines in clinical production environments.
While much of what determines the ultimate impact of a guideline has little to do with technology, information technology offers new and powerful methods for guideline implementation. These methods include concurrent and delayed patient-specific decision support, workflow modification, and delayed feedback of aggregate patient data. Ideally, technology should be used to reduce physician cognitive burden and workload while simultaneously achieving guideline objectives.
The most effective use of information technology occurs when patient-specific decision support is delivered concurrently with no effort required on the part of the physician. Physician order entry systems provide the most straightforward means of accomplishing this. However, until the clinical information system infrastructure is in place to support patient-specific feedback during an encounter,implementation strategies such as nurse-initiated orders and disease state management remain viable and important alternatives.
Healthcare is considered a service profession and most of what clinicians do is manage information. Thus, information is not a necessary adjunct to care. It is care and effective patient management that require effective management of patients' clinical data. This perspective is supported by the World Health Organisation in its use of the quotation from Gonzalo Vecina Neto, head of the Brazilian National Health Regulatory Agency, ‘There is no health without management, and there is no management without information’.
This opinion paper discusses how traditional clinical decision-making led ‘by the doctor’ is unsustainable in the modern era and how e-technologies will facilitate distributed effective decision-making and new divisions of labour across the health workforce.
Electronic medical record systems (EMRs) can be made more attractive to the clinicians if Clinical Decision Support Systems (CDSS) are integrated with them. However, CDSS have to be developed with integration in mind, such that they may be integrated not just with the local EMR but EMRs developed by others as well. Web Services Technology ameliorates the challenge of integration if the CDSS is well-designed but several other issues still need to be considered. The integration has to allow two-way data exchange between the CDSS and the EMR, which requires the EMR also to expose a set of interfaces. Further, the CDSS itself needs integration with services on which it depends for its functionality. In the semantic data capture initiative (SDCI) project, we integrated, Proteus (http://proteme.org), an open source, process-oriented clinical decision support system with Henry Ford Health System's EMR, Care Plus. The effort involved addressing some of these challenges and some that are unique to a system like Proteus.
Patient empowerment might be one key to reduce the pressure on health care systems challenged by the expected demographic changes. Knowledge based systems can, in combination with automated sensor measurements, improve the patients' ability to review their state of health and make informed decisions. The Arden Syntax as a standardized language to represent medical knowledge can be used to express the corresponding decision rules. In this paper we introduce ARDEN2BYTECODE, a newly developed open source compiler for the Arden Syntax. ARDEN2BYTECODE runs on Java Virtual Machines (JVM) and translates Arden Syntax directly to Java Bytecode (JBC) executable on JVMs. ARDEN2BYTECODE easily integrates into service oriented architectures, like the Open Services Gateway Initiative (OSGi) platform. Apart from an evaluation of compilation performance and execution times, ARDEN2BYTECODE was integrated into an existing knowledge supported exercise training system and recorded training sessions have been used to check the implementation.
The Arden Syntax is an HL7 standard language for representing medical knowledge as logic statements. Despite nearly 2 decades of availability, Arden Syntax has not been widely used. This has been attributed to the lack of a generally available compiler to implement the logic, to Arden's complex syntax, to the challenges of mapping local data to data references in the Medical Logic Modules (MLMs), or, more globally, to the general absence of decision support in healthcare computing. An XML representation (ArdenML) may partially address the technical challenges. MLMs created in ArdenML can be converted into executable files using standard transforms written in the Extensible Stylesheet Language Transformation (XSLT) language. As an example, we have demonstrated an approach to executing MLMs written in ArdenML using the Drools business rule management system. Extensions to ArdenML make it possible to generate a user interface through which an MLM developer can test for logical errors.
In this study, knowledge discovery tools were implemented to identify and extract practice patterns from structured clinical data. The implementation process consisted of the selection of a care domain, data collection, identification of patient attributes and outcomes, identification of care setting, modeling clinical and operational processes, and enabling data navigation. This process allowed identification of variation in practice among patient subgroups, and among care facilities. The developed techniques were demonstrated within the Labor and Delivery (L&D) setting supported by electronic nursing documentation. Retrospective data from 2,611 L&D patients admitted during the 2-month period of January and February 2006 were selected for analysis. A tool was developed to support navigation among patient profiles that enabled the user to view patterns of nursing practice and outcomes associated with specified patient characteristics. Nursing processes were represented using five scoring models to measure the hourly quantity of nursing care, referred to as Nursing Effort, received by each patient in the study. Scoring models considered nurse-to-patient ratios, the number of concurrent patients being treated by a given nurse, patient acuities, and the number of activities documented for each patient as represented by computerized nurse-entered documentation. Nursing Effort scores, along with patient attributes, were used in an analysis of patient outcomes including the duration of labor stages, the occurrence of various labor events, and cost of care. Significant differences were detected in the amount of Nursing Effort received according to patient acuity and the facility where care was provided. Using survival analysis techniques, significant relationships were identified between Nursing Effort scores and the durations of various labor stages. Regression models facilitated the identification of significant relationships between particular patient attributes and outcomes. The development of knowledge discovery tools in this study demonstrates the feasibility of a computerized care process model that provides real-time case profiling and outcome forecasting through the identification of variations in nursing care and patient characteristics. Additionally, generalized benefits of the practice pattern extraction capability, which extend to other clinical domains, are presented with supporting examples from the L&D setting. Doctor of Philosophy; National Library of Medicine (Grant #T15LM07124)
Implementing Computer-Interpretable Guidelines (CIGs) in active computer-based decision support systems promises to improve the acceptance and application of guidelines in daily practice. The model and underlying language are the core characteristics of every CIG approach. However, currently no standard model or language has been accepted by the CIG community. This aim of this chapter is to provide an overview of well-known approaches and to formulate a set of (minimal) requirements that can be used in the process of developing new CIG approaches or improving existing ones. It presents five CIG approaches (the Arden Syntax, GLIF, PROforma, Asbru and EON), followed by a general discussion of the strong points of each approach as well as their implications for future research.
The concept of "one-stop information shopping" is becoming a reality at Columbia-Presbyterian Medical Center. Our goal is to provide access from a single workstation to clinical, research, and library resources; university and hospital administrative systems; and utility functions such as word processing and mail. We have created new organizational units and installed a network of workstations that can access a variety of resources and systems on any of seventy-two different host computers/servers. In November 1991, 2,600 different individuals used the clinical information system, 700 different individuals used the library resources, and 900 different individuals used hospital administrative systems via the network. Over the past four years, our efforts have cost the equivalent of $23 million or approximately 0.5% of the total medical center budget. Even small improvements in productivity and in the quality of work of individuals who use the system could justify these expenditures. The challenges we still face include the provision of additional easy-to-use applications and development of equitable methods for financial support.
We have developed a system to provide case-specific explanations for SQL query results. The explanation facility, called SQLX, is intended to improve user acceptance of clinical rules that are encoded in the SQL query language and are triggered by updates to a relational database. Our design goal is to combine the efficiency and familiarity of the SQL query model with a more intuitive and case-specific display of query results. SQLX defines an augmented SQL syntax that allows the incorporation of explanation text directly into query specifications. A query analyzer determines which retrieved data logically contribute to rule firing, and combines the data with explanation text to generate a case-specific explanation. Although features of the SQL query model limit the use of this method as a general-purpose rule-explanation facility, the current design accommodates a wide range of SQL query formulations and can provide efficient processing and intuitive explanations of many clinical rules.
The concept of "one stop information shopping" is becoming a reality at Columbia Presbyterian Medical Center (CPMC). The goal of our effort is to provide access to university and hospital administrative systems as well as clinical and library applications from a single workstation, which also provides utility functions such as word processing and mail. Since June 1987, CPMC has invested the equivalent of 2.8 million on an annual basis. This cost is 0.3% of the medical center's annual budget. These expenditures could be justified by very small improvements in time savings for personnel and/or decreased length of hospital stay and/or more efficient use of resources. In addition to the direct benefits which we detail, a major benefit is the ease with which additional computer-based applications can be added incrementally at an extremely modest cost.
The Arden Syntax for medical logic modules (Arden) was used to test the feasibility of encoding large, complex care plans. The critical portions of an existing paper-based care plan for the management of patients following coronary artery bypass graft (CABG) surgery were encoded in Arden and an X-windows user-interface was developed. The Arden Syntax proved adequate for encoding all of the necessary functions of the care plan. The limitations of the current Arden Syntax and possible additions to Arden are discussed.
The paper reports experiences from the implementation and use of data-driven decision support based on the Arden Syntax in three different environments: in a health-care centre, in a clinical laboratory, and in a research department. Methods and tools used for realization of decision support systems (DSSs) are shortly presented, and integration aspects of the DSS with running clinical applications and existing patient databases are discussed. The application areas are also described, together with validation procedures for the developed knowledge modules.
In implementing a clinical event monitor (CEM), a decision-support system, we worked with an existing repository of clinical data (Keystone), fed from ancillary systems using HL7. The rules are written in the Arden Syntax, an ASTM standard for expressing medical knowledge as medical logic modules (MLMs). The Arden Syntax leaves unspecified the clinical data model and deductive database access language; we briefly describe our query language and the related medical concepts dictionary (MCD). This paper gives an overview of our implementation of the Arden Syntax, the MCD and the deductive database access language, with reasons for the major design decisions. Overall, less than a quarter of the development effort has gone into the Arden compiler and interpreter; the rest has focused on accessing the data and integrating with other systems. We feel that the Arden Syntax has proved its worth in writing rules; effort should now be focused on medical vocabularies and data models.
This article reviews the efforts of HBO & Company in the production of a first phase clinical alerting system based on the Arden Syntax. The alerting system was integrated with a clinical data repository and clinical workstation to process returning laboratory results. Investigations with expert systems resulted in a C language alerting system. GUI prototyping of an authoring environment led to a Smalltalk language authoring system. Future development is expected to broaden the system scope and address the evolution of the Arden Syntax.
When developing a clinical decision support system that uses knowledge expressed in Arden Syntax, the availability of a robust means of translating Arden Syntax into an executable module becomes critical. This paper describes an approach where Arden Syntax is translated into an intermediate pseudo-Arden language that is in turn compiled and linked to create the executable module. The pseudo-Arden language is defined in C++ using specialized class libraries and preprocessor macros. This approach provides an alternative means of developing the code generator for an Arden Syntax compiler.
The Arden Syntax is a standard description syntax for modular medical knowledge. The purpose of the Arden Syntax is to allow the construction of medical knowledge bases out of elementary medical logic modules (MLMs) that may be contributed and shared by different institutions. The format of the input data is not defined in the Arden Syntax, but left to the user. Every input and output must be rewritten for the local data access definition before an MLM can be used. It is suggested that by using the Health Level Seven (HL7) interface definition to define the communication and data transfer between the MLMs and the medical data base the shareability of MLMs can be enhanced.
Develop a representational schema for clinical concepts and apply it to the task of encoding radiology reports of the chest.
The schema was developed following a manual analysis of sample reports from the domain. The schema has two main components: the Medical Entities Dictionary (MED), which specifies the formal representation of the concepts in the domain and of their structures, and the natural-language processor, which specifies the linguistic expressions of the concepts. The schema was evaluated by applying it to a test set of 7,500 reports. Two-hundred reports from the test set were manually analyzed by a medical expert to determine the accuracy and success rate of the system.
82% of the 7,500 reports that contained relevant clinical information were successfully structured automatically. For the smaller set of 200 reports, 80% were structured successfully with an accuracy rate of 97%.
The schema is a formal representation for clinical concepts in radiology reports, and provides domain coverage that is particularly well-suited for natural-language processing of radiology for use in a decision support system.
To design and develop a computer-based health-care record system to address the needs of the patients and providers of a homeless population.
A computer-based health-care record system being developed for Boston's Healthcare for the Homeless Program (BHCHP) uses client-server technology and distributed database strategies to provide a common medical record for this transient population. The differing information requirements of physicians, nurses, and social workers are specifically addressed in the graphic application interface to facilitate an integrated approach to health care. This computer-based record system is designed for remote and portable use to integrate smoothly into the daily practice of providers of care to the homeless. The system uses remote networking technology and regular phone lines to support multiple concurrent users at remote sites of care.
A stand-alone, pilot system is in operation at the BHCHP medical respite unit. Information on 129 patient encounters from 37 unique sites has been entered. A full client-server system has been designed. Benchmarks show that while the relative performance of a communication link based upon a phone line is 0.07 to 0.15 that of a local area network, optimization permits adequate response.
Medical records access in a transient population poses special problems. Use of client-server and distributed database strategies can provide a technical foundation that provides a secure, reliable, and accessible computer-based medical record in this environment.
Develop a knowledge-based representation for a controlled terminology of clinical information to facilitate creation, maintenance, and use of the terminology.
The Medical Entities Dictionary (MED) is a semantic network, based on the Unified Medical Language System (UMLS), with a directed acyclic graph to represent multiple hierarchies. Terms from four hospital systems (laboratory, electrocardiography, medical records coding, and pharmacy) were added as nodes in the network. Additional knowledge about terms, added as semantic links, was used to assist in integration, harmonization, and automated classification of disparate terminologies.
The MED contains 32,767 terms and is in active clinical use. Automated classification was successfully applied to terms for laboratory specimens, laboratory tests, and medications. One benefit of the approach has been the automated inclusion of medications into multiple pharmacologic and allergenic classes that were not present in the pharmacy system. Another benefit has been the reduction of maintenance efforts by 90%.
The MED is a hybrid of terminology and knowledge. It provides domain coverage, synonymy, consistency of views, explicit relationships, and multiple classification while preventing redundancy, ambiguity (homonymy) and misclassification.
The Columbia Clinical Repository is the foundation of the Clinical Information System at the Columbia Presbyterian Medical Center (CPMC). The Repository is implemented as a relational database on an IBM mainframe, using a generic design that employs a small number of tables. Client applications on remote platforms send and receive data through Database Access Modules (DAMs), which support the HL7 protocol, while applications on the mainframe manipulate data through DAMs supporting a locally defined "query template". Implementation using static (compiled) SQL is compared to dynamic (ad hoc) SQL in terms of efficiency and flexibility.
The development of large-scale, clinically accepted decision support systems (DSS) calls for powerful and commonly available methods and tools for knowledge acquisition, system realisation, and knowledge base maintenance. The paper addresses problems associated with the integration of knowledge-based systems within the clinical setting with special reference to (i) data driven decision support, (ii) the Arden Syntax as a knowledge representation format and, (iii) the HELIOS software engineering environment. Architecture of a DSS based on Arden Syntax and its integration in the HELIOS environment are presented. Realisation of the DSS is discussed in relation to client-server architecture and object-oriented databases, which are essential concepts of the HELIOS environment. Sharability and reusability of the knowledge, together with commonality of used software tools are also discussed.
Development of medical knowledge bases is a time-consuming process, and no single medical institution can develop medical knowledge bases covering all areas of medicine. The use of medical knowledge representation standards such as the Arden Syntax is an attempt to enhance the writability and readability of computer-stored knowledge and facilitate transfer and sharing among institutions. A method for the realisation of decision support systems based on knowledge formulated according to the Arden Syntax is presented. An essential tool in this process is a medical logic module (MLM) pre-compiler, translating MLMs into an object-oriented programming language, C++. Advantages of the C++ approach compared with other alternatives are discussed.
To maximize the value of computerized medical records systems, an organizing structure is needed. That structure can be provided by a controlled medical terminology (CMT). At Columbia-Presbyterian Medical Center, we have been employing a controlled medical terminology, our Medical Entities Dictionary (MED), to mediate the storage and retrieval of patient data and enable decision support applications. This paper describes how the MED is actually used for data management in our distributed clinical information systems environment. Our system tools which access the MED for production purposes facilitate the mapping of terms from many sources to a uniform representation of concepts and also return information about the relationships between concepts. Applications which access a CMT for production purposes should be optimized for performance in high volume settings, fault tolerant, synchronizable, extensible, portable, and maintainable. We briefly describe our system architecture and then demonstrate how we utilize the MED for translation and semantic information as data is moved into and out of our patient database. We discuss our current tools and present a preview of the next generation of applications which will manage access to the MED for our production systems.
We began implementation of a medical decision support system (MDSS) at the Columbia-Presbyterian Medical Center (CPMC) using the Arden Syntax in 1992. The Clinical Event Monitor which executes the Medical Logic Modules (MLMs) runs on a mainframe computer. Data are stored in a relational database and accessed via PL/I programs known as Data Access Modules (DAMs). Currently we have 18 clinical, 12 research and 10 administrative MLMs. On average, the clinical MLMs generate 50357 simple interpretations of laboratory data and 1080 alerts each month. The number of alerts actually read varies by subject of the MLM from 32.4% to 73.5%. Most simple interpretations are not read at all. A significant problem of MLMs is maintenance, and changes in laboratory testing and message output can impair MLM execution significantly. We are now using relational database technology and coded MLM output to study the process outcome of our MDSS.
The issues and implementation of a clinical event monitor are described. An event monitor generates messages for providers, patients, and organizations based on clinical events and patient data. For example, an order for a medication might trigger the generation of a warning about a drug interaction. A model based on the active database literature has as its main components an event (which triggers a rule to fire), a condition (which tests whether an action ought to be performed), and an action (often the generation of a message). The details of implementing such a monitor are described, using as an example the Columbia-Presbyterian Medical Center clinical event monitor, which is based on the Arden Syntax for Medical Logic Modules.
Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described.
We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance.
The Arden Syntax for Medical Logic Modules standard language for knowledge-based computer systems is described.
Knowledge systems can use computerized patient data in decision-making. Although they have the potential to reduce adverse drug events and infection rates, improve drug dosing, and decrease the cost of care, knowledge systems have not yet reached the average patient. Arden Syntax for Medical Logic Modules is the standard language for defining clinical decision rules that drive alerts, reminders, clinical guidelines, and data interpretations. Each medical logic module (MLM) in an Arden Syntax knowledge base is designed to make one type of decision. MLMs usually represent either rules that can be encoded, such as generating a warning that the potassium concentration is decreasing in a patient taking digoxin, or complex decision trees for individual patient care plans and clinical protocols. An MLM contains maintenance slots (title, file name, version, originating institution, author, date, specialist, validation information), library slots (stating the MLM's purpose and providing keywords for searching), and knowledge slots (containing the "essence" of the MLM). Arden Syntax is receiving growing support from the medical and information systems communities as the standard language for medical knowledge systems, but legal, ethical, regulatory, and ownership issues remain.
If pharmacy is to grow and prosper as a knowledge profession, it should adopt an accepted standard language for representing active, applied knowledge in computer systems.
We argue that the optimal use of communication channels in clinical event monitors is an important design consideration for these systems. We review the state-of-the-art in selection of communication channels, including our current approach--allowing users to choose the communication channel by which the event monitor sends each notification. We describe a new approach that we are in the process of developing. In this new approach, we view event monitoring as the decision of whether and how to send new patient data to a clinician and apply the principle of maximum expected utility to this decision problem. Our initial experience with this approach suggests that notifying clinicians of normal patient data may be of high utility. We also found that methods for explanation in uncertain reasoning may be necessary in this approach.
Computer decision support systems are computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care. They can simplify access to data needed to make decisions, provide reminders and prompts at the time of a patient encounter, assist in establishing a diagnosis and in entering appropriate orders, and alert clinicians when new patterns in patient data are recognized. Decision support systems that present patient-specific recommendations in a form that can save clinicians time have been shown to be highly effective, sustainable tools for changing clinician behavior. Designing and implementing such systems is challenging because of the computing infrastructure required, the need for patient data in a machine-processible form, and the changes to existing workflow that may result. Despite these difficulties, there is substantial evidence from trials in a wide range of clinical settings that computer decision support systems help clinicians do a better job caring for patients. As computer-based records and order-entry systems become more common, automated decision support systems will be used more broadly.
The Arden Syntax for sharing medical knowledge bases is described. Its current focus is on knowledge that is represented as a set of independent modules that can provide therapeutic suggestions, alerts, diagnosis scores, etc. The syntax is based largely upon HELP and the Regenstrief Medical Record System. Each module, called a Medical Logic Module or MLM, is made of slots grouped into maintenance, library, and knowledge categories. The syntax has provisions for querying a clinical database and representing time. Several clinical information systems were analyzed and appear to be compatible with the syntax. The syntax has been tested for syntactic ambiguities using the tools lex and yacc. Seventeen institutions are currently in the process of adopting the Arden Syntax for their decision-support systems. A subcommittee of ASTM has been formed to develop standards for sharing medical knowledge bases. The Arden Syntax has been published by ASTM as a initial standard for sharing medical knowledge.
The National Library of Medicine is developing a Unified Medical Language System (UMLS) which addresses the need for integration of several large, nationally accepted vocabularies. This is important to the clinical information system under development at the Columbia-Presbyterian Medical Center (CPMC). We are using UMLS components as the core of our effort to integrate existing local CPMC vocabularies which are not among the source vocabularies of the UMLS. We are also using the UMLS to build a knowledge base of vocabulary structure and content such that logical rules can be developed to assist in the management of our integrated vocabularies. At present, the UMLS Semantic Network is used to organize terms which describe laboratory procedures. We have developed a set of rules for identifying undesirable conditions in our vocabulary. We have applied these rules to 526 laboratory test terms and have found ten cases (2%) of definite redundancy and sixty-eight cases (13%) of potential redundancy. The rules have also been used to organize the terminology in new ways that facilitate its management. Using the UMLS model as a vocabulary knowledge base allows us to apply an expert system approach to vocabulary integration and management.
Patient data is central to a Clinical Information System (CIS). The organization of the data in a patient database is essential to the functioning of the system. If the CIS contains a medical decision support component, further requirements are imposed on the database. It must be capable of accurately representing a broad range of clinical information in coded form, and be organized for efficient retrievals by patient, time, and type of clinical term.This paper presents a generalized schema for a clinical patient database within the relational database model. The general design makes it possible to represent diverse clinical data in a standard structure and to organize the data so that it is densely clustered by patient and time.
The clinical information system under development at Columbia Presbyterian Medical Center includes a relational patient database and a decision support system. The design incorporates a database of system information, or “Metadatabase”, which serves to integrate three forms of medical knowledge with clinical applications: medical entities, events, and decision logic. The Metadatabase is implemented in standard relational technology, and is intended to supply information to all phases of application development.
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