PROforma: a general technology for clinical decision support systems

ROAD2H: Development and evaluation of an open-source explainable artificial intelligence approach for managing co-morbidity and clinical guidelines

Introduction

Clinical decision support (CDS) systems (CDSSs) that integrate clinical guidelines need to reflect real-world co-morbidity. In patient-specific clinical contexts, transparent recommendations that allow for contraindications and other conflicts arising from co-morbidity are a requirement. In this work, we develop and evaluate a non-proprietary, standards-based approach to the deployment of computable guidelines with explainable argumentation, integrated with a commercial electronic health record (EHR) system in Serbia, a middle-income country in West Balkans.

Methods

We used an ontological framework, the Transition-based Medical Recommendation (TMR) model, to represent, and reason about, guideline concepts, and chose the 2017 International global initiative for chronic obstructive lung disease (GOLD) guideline and a Serbian hospital as the deployment and evaluation site, respectively. To mitigate potential guideline conflicts, we used a TMR-based implementation of the Assumptions-Based Argumentation framework extended with preferences and Goals (ABA+G). Remote EHR integration of computable guidelines was via a microservice architecture based on HL7 FHIR and CDS Hooks. A prototype integration was developed to manage chronic obstructive pulmonary disease (COPD) with comorbid cardiovascular or chronic kidney diseases, and a mixed-methods evaluation was conducted with 20 simulated cases and five pulmonologists.

Results

Pulmonologists agreed 97% of the time with the GOLD-based COPD symptom severity assessment assigned to each patient by the CDSS, and 98% of the time with one of the proposed COPD care plans. Comments were favourable on the principles of explainable argumentation; inclusion of additional co-morbidities was suggested in the future along with customisation of the level of explanation with expertise.

Conclusion

An ontological model provided a flexible means of providing argumentation and explainable artificial intelligence for a long-term condition. Extension to other guidelines and multiple co-morbidities is needed to test the approach further.

Business Process Model and Notation and openEHR Task Planning for Clinical Pathway Standards in Infections: Critical Analysis

Background

Clinical pathways (CPs) are usually expressed by means of workflow formalisms, providing health care personnel with an easy-to-understand, high-level conceptual model of medical steps in specific patient conditions, thereby improving overall health care process quality in clinical practice. From a standardized perspective, the business process model and notation (BPMN), a widely spread general-purpose process formalism, has been used for conceptual modeling in clinical domains, mainly because of its easy-to-use graphical notation, facilitating the common understanding and communication of the parties involved in health care. However, BPMN is not particularly oriented toward the peculiarities of complex clinical processes such as infection diagnosis and treatment, in which time plays a critical role, which is why much of the BPMN clinical-oriented research has revolved around how to extend the standard to address these special needs. The shift from an agnostic, general-purpose BPMN notation to a natively clinical-oriented notation such as openEHR Task Planning (TP) could constitute a major step toward clinical process improvement, enhancing the representation of CPs for infection treatment and other complex scenarios.

Objective

Our work aimed to analyze the suitability of a clinical-oriented formalism (TP) to successfully represent typical process patterns in infection treatment, identifying domain-specific improvements to the standard that could help enhance its modeling capabilities, thereby promoting the widespread adoption of CPs to improve medical practice and overall health care quality.

Methods

Our methodology consisted of 4 major steps: identification of key features of infection CPs through literature review, clinical guideline analysis, and BPMN extensions; analysis of the presence of key features in TP; modeling of relevant process patterns of catheter-related bloodstream infection as a case study; and analysis and proposal of extensions in view of the results.

Results

We were able to easily represent the same logic applied in the extended BPMN-based process models in our case study using out-of-the-box standard TP primitives. However, we identified possible improvements to the current version of TP to allow for simpler conceptual models of infection CPs and possibly of other complex clinical scenarios.

Conclusions

Our study showed that the clinical-oriented TP specification is able to successfully represent the most complex catheter-related bloodstream infection process patterns depicted in our case study and identified possible extensions that can help increase its adequacy for modeling infection CPs and possibly other complex clinical conditions.

CDSS-RM: a clinical decision support system reference model

Clinical Decision Support Systems (CDSS) provide aid in clinical decision making and therefore need to take into consideration human, data interactions, and cognitive functions of clinical decision makers. The objective of this paper is to introduce a high level reference model that is intended to be used as a foundation to design successful and contextually relevant CDSS systems. The paper begins by introducing the information flow, use, and sharing characteristics in a hospital setting, and then it outlines the referential context for the model, which are clinical decisions in a hospital setting. Important characteristics of the Clinical decision making process include: (i) Temporally ordered steps, each leading to new data, which in turn becomes useful for a new decision, (ii) Feedback loops where acquisition of new data improves certainty and generates new questions to examine, (iii) Combining different kinds of clinical data for decision making, (iv) Reusing the same data in two or more different decisions, and (v) Clinical decisions requiring human cognitive skills and knowledge, to process the available information. These characteristics form the foundation to delineate important considerations of Clinical Decision Support Systems design. The model includes six interacting and interconnected elements, which formulate the high-level reference model (CDSS-RM). These elements are introduced in the form of questions, as considerations, and are examined with the use of illustrated scenario-based and data-driven examples. The six elements /considerations of the reference model are: (i) Do CDSS mimic the cognitive process of clinical decision makers? (ii) Do CDSS provide recommendations with longitudinal insight? (iii) Is the model performance contextually realistic? (iv) Is the ‘Historical Decision’ bias taken into consideration in CDSS design? (v) Do CDSS integrate established clinical standards and protocols? (vi) Do CDSS utilize unstructured data? The CDSS-RM reference model can contribute to optimized design of modeling methodologies, in order to improve response of health systems to clinical decision-making challenges.

Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation

OBJECTIVES

To develop a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer, and examine perceived usefulness, acceptability and areas for improvement of the DA.

DESIGN

Mixed methods.

SETTING

Single outpatient oncology department in central London.

PARTICIPANTS

Consecutive recruitment of 13 patients with stage II colorectal cancer, 12 of whom completed the study. Inclusion criteria were: age >18 years; complete resection for stage II adenocarcinoma of the colon or rectum; patients within 14-56 days after surgery; no contraindication to adjuvant chemotherapy; able to give written informed consent. Exclusion criterion: previous chemotherapy.

PRIMARY OUTCOMES

Patient perceived usefulness (assessed by the PrepDM questionnaire) and acceptability of the DA.

RESULTS

PrepDM scores, measuring the perceived usefulness of the DA in preparing the patient to communicate with their doctor and make a health decision, were above those reported in other patient groups. Patient acceptability scores were also high; however, interviews showed that there was evidence of a lack of understanding of key information among some patients, in particular their baseline risk of recurrence, the net benefit of combination chemotherapy and the rationale for having chemotherapy when cancer had apparently gone.

CONCLUSIONS

Patients found the DA acceptable and useful in supporting their decision about whether or not to have adjuvant chemotherapy. Suggested improvements for the DA include: sequential presentation of treatment options (eg, no treatment vs 1 drug, 1 drug vs 2 drugs) to enhance patient understanding of the difference between combination and single therapy, diagrams to help patients understand the rationale for chemotherapy to prevent a recurrence and inbuilt checks on patient understanding of baseline risk of recurrence and net benefit of chemotherapy.

Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision

OBJECTIVE

The objective of this review is to summarize the state of the art of clinical decision support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide a vision of what CDS might look like 25 years hence, or circa 2040.

METHOD

Informal review of the medical literature with iterative review and discussion among the authors to arrive at six axes (data, knowledge, inference, architecture and technology, implementation and integration, and users) to frame the review and discussion of selected barriers and facilitators to the effective use of CDS.

RESULT

In each of the six axes, significant progress has been made. Key advances in structuring and encoding standardized data with an increased availability of data, development of knowledge bases for CDS, and improvement of capabilities to share knowledge artifacts, explosion of methods analyzing and inferring from clinical data, evolution of information technologies and architectures to facilitate the broad application of CDS, improvement of methods to implement CDS and integrate CDS into the clinical workflow, and increasing sophistication of the end-user, all have played a role in improving the effective use of CDS in healthcare delivery.

CONCLUSION

CDS has evolved dramatically over the past 25 years and will likely evolve just as dramatically or more so over the next 25 years. Increasingly, the clinical encounter between a clinician and a patient will be supported by a wide variety of cognitive aides to support diagnosis, treatment, care-coordination, surveillance and prevention, and health maintenance or wellness.

Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks

OBJECTIVE

This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computer-interpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented.

MATERIALS AND METHODS

The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to (i) dynamically cope with temporal and resource constraints, and (ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile.

RESULTS

The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten different types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care.

CONCLUSION

The described methodology makes it possible to automatically generate patient-tailored care pathways, leveraging an incremental knowledge-driven engineering process that starts from the expert knowledge of medical professionals. The presented approach makes the most of the strengths inherent in both CIG languages and HTN planning and scheduling techniques: for the former, knowledge acquisition and representation of the original clinical protocol, and for the latter, knowledge reasoning capabilities and an ability to deal with complex temporal and resource constraints. Moreover, the proposed approach provides immediate access to technologies such as business process management (BPM) tools, which are increasingly being used to support healthcare processes.

Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems

OBJECTIVE

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways.

METHODS

A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation 'challenge' themes.

RESULTS

One hundred and eight relevant studies were selected for review. Twenty-five underlying 'challenge' themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed.

DISCUSSION AND CONCLUSION

We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings.

Patterns for collaborative work in health care teams

OBJECTIVE

The problem of designing and managing teams of workers that can collaborate working together towards common goals is a challenging one. Incomplete or ambiguous specification of responsibilities and accountabilities, lack of continuity in teams working in shifts, inefficient organization of teams due to lack of information about workers' competences and lack of clarity to determine if the work is delegated or assigned are examples of important problems related to collaborative work in healthcare teams. Here we address these problems by specifying goal-based patterns for abstracting the delegation and assignment of services. The proposed patterns should provide generic and reusable solutions and be flexible enough to be customizable at run time to the particular context of execution. Most importantly the patterns should support a mechanism for detecting abnormal events (exceptions) and for transferring responsibility and accountability for recovering from exceptions to the appropriate actor.

METHOD

To provide a generic solution to the problematic issues arising from collaborative work in teams of health workers we start from definitions of standard terms relevant for team work: competence, responsibility, and accountability. We make explicit the properties satisfied by service assignment and delegation in terms of competences, responsibilities, and accountability in normal scenarios and abnormal situations that require the enactment of recovery strategies. Based on these definitions we specify (1) a basic terminology, (2) design patterns for service assignment and delegation (with and without supervision), and (3) an exception manager for detecting and recovering from exceptions. We use a formal framework to specify design patterns and exceptions.

RESULTS

We have proved using Owicki-Gries Theory that the proposed patterns satisfy the properties that characterize service assignment and delegation in terms of competence, responsibility and accountability in normal and abnormal (exceptional) scenarios. We show that although abstract, the proposed patterns can be instantiated in an executable COGENT prototype, and can be mapped into the Tallis tool that enacts PROforma language specifications of medical guidelines.

CONCLUSIONS

The proposed patterns are generic and abstract enough to capture the normal and abnormal scenarios of assignment and delegation of tasks in collaborative work in health care teams.

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

Background

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic.

Results

We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture.

Conclusions

We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Formal representation of eligibility criteria: a literature review

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representation that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of these aspects (expression language, codification of eligibility concepts, and patient data modeling) to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward knowledge representation for sharable and computable eligibility criteria.

A goal-oriented framework for specifying clinical guidelines and handling medical errors

Computer-interpretable guidelines (CIGs) aim to improve patient care and reduce medical errors. Although CIGs implement evidence-based recommendations they cannot prevent exceptional behavior from happening. To address this problem we developed a framework that can monitor, detect, and handle exceptions that occur during normal CIG execution and can potentially prevent them from developing into medical errors. Our framework enables specifying the goals of a guideline and linking them with recommended tasks that could satisfy the goals. Exceptions are linked with goals that manage them, which can be realized by tasks or plans. To achieve a link between the tasks, plans, goals, monitored effects, and exceptions, our definition of goals and exceptions is state-based. We demonstrate our approach using a generic plan for management of a chronic disease and a particular instantiation for hypertension management.

The GRAIDS Trial: The development and evaluation of computer decision support for cancer genetic risk assessment in primary care

The development and evaluation of computer decision support for the assessment of cancer genetic risk in primary care is reported with two series of studies described: the RAGs (Risk Assessment in Genetics) studies and the GRAIDS (Genetic Risk Assessment in an Intranet and Decision Support) Trial. In the GRAIDS Trial, 45 general practices in Eastern England have been recruited and randomised. Comparison practices attend an educational session and receive clinical guidelines about familial breast and colorectal cancer. In the intervention practices a lead clinician is trained in cancer genetics and use of the GRAIDS software. The GRAIDS software is a simple pedigree-drawing program that implements clinical guidelines for familial breast and colorectal cancer and presents individualised information about breast cancer risk in a range of formats. Outcome measures of the trial include: frequency of software use, practitioners' attitudes towards the software, total number of referrals to secondary care about familial cancer and the proportion that meet regional referral criteria, and a patient-centred measure of informed decision making. The family history will become an increasingly important tool in primary care to assess genetic risk. This research evaluates an approach to support high-quality advice about cancer genetics in primary care which could be applied more broadly as our understanding of complex disease genetics increases.

A parallel guideline development and formalization strategy to improve the quality of clinical practice guidelines

PURPOSE

Clinical practice guidelines often contain ambiguities, inconsistencies, and logical errors that hamper implementation of these guidelines in practice. As guideline formalization is useful to verify the logical structure, consistency, and completeness of guidelines, several authors have argued that the formalization of guidelines concurrent with their development may improve their quality. However, experiences with such a parallel guideline development and formalization approach have not yet been reported. The goal of this study was to develop such a strategy and evaluate its application in practice.

METHODS

Existing methodologies for guideline development and guideline formalization were analyzed and used as a basis to develop a strategy in which guideline formalization is performed concurrently with guideline development. The developed strategy was applied in the development of a clinical practice guideline for cardiac rehabilitation.

RESULTS

A parallel guideline development and formalization strategy was developed that intertwines the processes of guideline development and guideline formalization. Central assets are early involvement of guideline formalization specialists and formalization tools, cooperation between guideline authors and guideline formalization specialists in the development of clinical algorithms, access to domain knowledge when formalization identifies inconsistencies or omissions, and formal verification of the guideline model prior to guideline dissemination. This strategy was applied in the development of a guideline for cardiac rehabilitation and helped to identify several vague and inconsistent recommendations and impracticabilities in the narrative guidelines that could be resolved before publication. In addition, the strategy ensured consistency between the narrative and formalized guideline.

CONCLUSIONS

Based on our experience, formalizing a guideline concurrent with its development is feasible in practice and we recommend applying such a strategy as it can be beneficial to the quality of and consistency between the guideline's narrative and formalized version.

Computerized clinical decision support: a technology to implement and validate evidence based guidelines

Faced with a documented crisis of patients not receiving appropriate care, there is a need to implement and refine evidence-based guidelines (EBGs) to ensure that patients receive the best care available. Although valuable in content, among their deficiencies, EBGs do not provide explicit methods to bring proven therapies to the bedside. Computerized information technology, now an integral part of the US healthcare system at all levels, presents clinicians with information from laboratory, imaging, physiologic monitoring systems, and many other sources. It is imperative that we clinicians use this information technology to improve medical care and efficacy of its delivery. If we do not do this, nonclinicians will use this technology to tell us how to practice medicine. Computerized clinical decision support (CCDS) offers a powerful method to use this information and implement a broad range of EBGs. CCDS is a technology that can be used to develop, implement, and refine computerized protocols for specific processes of care derived from EBGs, including complex care provided in intensive care units. We describe this technology as a desirable option for the trauma community to use information technology and maintain the trauma surgeon/intensivist's essential role in specifying and implementing best care for patients. We describe a process of logical protocol development based on standardized clinical decision making to enable EBGs. The resulting logical process is readily computerized, and, when properly implemented, provides a stable platform for systematic review and study of the process and interventions.

CONCLUSION

: CCDS to implement and refine EBG derived computerized protocols offers a method to decrease variability, test interventions, and validate improved quality of care.

Improving medical protocols by formal methods

OBJECTIVES

During the last decade, evidence-based medicine has given rise to an increasing number of medical practice guidelines and protocols. However, the work done on developing and distributing protocols outweighs the efforts on guaranteeing their quality. Indeed, anomalies like ambiguity and incompleteness are frequent in medical protocols. Recent efforts have tried to address the problem of protocol improvement, but they are not sufficient since they rely on informal processes and notations. Our objective is to improve the quality of medical protocols.

APPROACH

The solution we suggest to the problem of quality improvement of protocols consists in the utilisation of formal methods. It requires the definition of an adequate protocol representation language, the development of techniques for the formal analysis of protocols described in that language and, more importantly, the evaluation of the feasibility of the approach based on the formalisation and verification of real-life medical protocols. For the first two aspects we rely on earlier work from the fields of knowledge representation and formal methods. The third aspect, i.e. the evaluation of the use of formal methods in the quality improvement of protocols, constitutes our main objective. The steps with which we have carried out this evaluation are the following: (1) take two real-life reference protocols which cover a wide variety of protocol characteristics; (2) formalise these reference protocols; (3) check the formalisation for the verification of interesting protocol properties; and (4) determine how many errors can be uncovered in this way.

RESULTS

Our main results are: a consolidated formal language to model medical practice protocols; two protocols, each both modelled and formalised; a list of properties that medical protocols should satisfy; verification proofs for these protocols and properties; and perspectives of the potentials of this approach. Our results have been evaluated by a panel of medical experts, who judged that the problems we detected in the protocols with the help of formal methods were serious and should be avoided.

CONCLUSIONS

We have succeeded in demonstrating the feasibility of formal methods for improving medical protocols.

Electronic implementation of guidelines in the EsPeR system: a knowledge specification method

Despite initiatives to standardize methods for the development of clinical guidelines, several barriers hinder their integration in daily clinical practice: failure to fulfil quality criteria, poor effectiveness of their dissemination. Computerization of guidelines can favor their dissemination. The initial step of computerization is the knowledge specification from the text of the guideline. We describe the method of knowledge specification, which is used in EsPeR (Personalized Estimate of Risks), a web-based decision support system in preventive medicine, which allows, for a given person, to estimate risks and access recommendations, based on clinical profile. This method is based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify this algorithm, along with elementary messages of recommendation. Editing tools are used to facilitate the process of validation and the workflow between expert physicians and computer scientists. Applied to eleven different guidelines, the method allows a quick and valid computerization and integration in the EsPeR system. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

LISA: a web-based decision-support system for trial management of childhood acute lymphoblastic leukaemia

Continuation chemotherapy is a key component of the treatment of childhood acute lymphoblastic leukaemia. During this treatment phase, weekly dose adjustments are carried out based on current and historical full blood counts (FBCs). The dose decision pathway is complex and suboptimal therapy may result if information on FBC results is not readily available and/or the prescriber is inexperienced. A web-based decision-support system (Leukaemia Intervention Scheduling and Advice, 'LISA') was designed to facilitate access to FBC information across geographical locations and to assist with dosage adjustments. A balanced-block crossover analysis was performed to evaluate the system. Thirty-six clinicians with varying degrees of experience were each asked to decide on appropriate oral chemotherapy dosages for eight simulated cases: four using LISA and four without. LISA significantly reduced the number of erroneous prescriptions (zero of 144 with LISA vs. 54 of 144 without; P < 0.0001) without affecting the number of times subjects deliberately overrode the protocol (seven of 144 times using LISA and six of 144 without). Using LISA reduced the time taken by novices to reach a decision for each case but increased the time taken by experts. Thirty-five of 36 subjects said they would be likely to use the system if it were available. A system like LISA is likely to be acceptable to clinicians, and has the potential to increase protocol compliance and decrease prescribing errors while allowing clinicians to override the protocol in specific cases where sound reasons exist for doing so.

The syntax and semantics of the PROforma guideline modeling language

PROforma is an executable process modeling language that has been used successfully to build and deploy a range of decision support systems, guidelines, and other clinical applications. It is one of a number of recent proposals for representing clinical protocols and guidelines in a machine-executable format (see <www.openclinical.org>). In this report, the authors outline the task model for the language and provide an operational semantics for process enactment together with a semantics for expressions, which may be used to query the state of a task during enactment. The operational semantics includes a number of public operations that may be performed on an application by an external agent, including operations that change the values of data items, recommend or make decisions, manage tasks that have been performed, and perform any task state changes that are implied by the current state of the application. Disclosure: PROforma has been used as the basis of a commercial decision support and guideline technology Arezzo (Infermed, London, UK; details in text).

Automating complex guidelines for chronic disease: lessons learned

There is scant published experience with implementing complex, multistep computerized practice guidelines for the long-term management of chronic diseases. We have implemented a system for creating, maintaining, and navigating computer-based clinical algorithms integrated with our electronic medical record. This article describes our progress and reports on lessons learned that might guide future work in this field. We discuss issues and obstacles related to choosing and adapting a guideline for electronic implementation, representing and executing the guideline as a computerized algorithm, and integrating it into the clinical workflow of outpatient care. Although obstacles were encountered at each of these steps, the most difficult were related to workflow integration.

Representation primitives, process models and patient data in computer-interpretable clinical practice guidelines: a literature review of guideline representation models

Representation of clinical practice guidelines in a computer-interpretable format is a critical issue for guideline development, implementation, and evaluation. We studied 11 types of guideline representation models that can be used to encode guidelines in computer-interpretable formats. We have consistently found in all reviewed models that primitives for representation of actions and decisions are necessary components of a guideline representation model. Patient states and execution states are important concepts that closely relate to each other. Scheduling constraints on representation primitives can be modeled as sequences, concurrences, alternatives, and loops in a guideline's application process. Nesting of guidelines provides multiple views to a guideline with different granularities. Integration of guidelines with electronic medical records can be facilitated by the introduction of a formal model for patient data. Data collection, decision, patient state, and intervention constitute four basic types of primitives in a guideline's logic flow. Decisions clarify our understanding on a patient's clinical state, while interventions lead to the change from one patient state to another.

Toward a representation format for sharable clinical guidelines

Clinical guidelines are being developed for the purpose of reducing medical errors and unjustified variations in medical practice, and for basing medical practice on evidence. Encoding guidelines in a computer-interpretable format and integrating them with the electronic medical record can enable delivery of patient-specific recommendations when and where needed. Since great effort must be expended in developing high-quality guidelines, and in making them computer-interpretable, it is highly desirable to be able to share computer-interpretable guidelines (CIGs) among institutions. Adoption of a common format for representing CIGs is one approach to sharing. Factors that need to be considered in creating a format for sharable CIGs include (i) the scope of guidelines and their intended applications, (ii) the method of delivery of the recommendations, and (iii) the environment, consisting of the practice setting and the information system in which the guidelines will be applied. Several investigators have proposed solutions that improve the sharability of CIGs and, more generally, of medical knowledge. These approaches can be useful in the development of a format for sharable CIGs. Challenges in sharing CIGs also include the need to extend the traditional framework for disseminating guidelines to enable them to be integrated into practice. These extensions include processes for (i) local adaptation of recommendations encoded in shared generic guidelines and (ii) integration of guidelines into the institutional information systems.

A Pascal-based decision support system model for diagnosis and treatment processes in urology

This program is designed for a urologist as a Decision Support System to facilitate the pre-diagnosis and identify the definite diagnosis as quickly as possible with the help of symptoms and physical examination by taking into consideration all the possible diseases with cross-questioning. The aim is to enable the physician to display on the monitor all the possible diseases causing the arising symptoms by entering the symptoms and the physician's observations into the database with "yes" or "no" type answers.

Computer support for recording and interpreting family histories of breast and ovarian cancer in primary care (RAGs): qualitative evaluation with simulated patients

OBJECTIVES

To explore general practitioners' attitudes towards and use of a computer program for assessing genetic risk of cancer in primary care.

DESIGN

Qualitative analysis of semistructured interviews and video recordings of simulated consultations.

PARTICIPANTS

Purposive sample of 15 general practitioners covering a range of computer literacy, interest in genetics, age, and sex.

INTERVENTIONS

Each doctor used the program in two consultations in which an actor played a woman concerned about her family history of cancer. Consultations were videotaped and followed by interviews with the video as a prompt to questioning. MAIN OUTCOME MESURESs: Use of computer program in the Consultation.

RESULTS

The program was viewed as an appropriate application of information technology because of the complexity of cancer genetics and a sense of "guideline chaos" in primary care. Doctors found the program easy to use, but it often affected their control of the consultation. They needed to balance their desire to share the computer screen with the patient, driven by their concerns about the effect of the computer on doctor-patient communication, against the risk of premature disclosure of bad news.

CONCLUSIONS

This computer program could provide the necessary support to assist assessment of genetic risk of cancer in primary care. The potential impact of computer software on the consultation should not be underestimated. This study highlights the need for careful evaluation when developing medical information systems.

Building a flexible protocol information system with ready for use' web-technology

This paper describes how web technology, currently available, can be used to build a fast and easy flexible protocol information system. The interface design and functionalities of the system were based on experiences with a previous version of a protocol information system (ProtoVIEW). A wide range of diagnostic or therapeutic protocols could be retrieved and viewed with ProtoVIEW. The Web-based version contains all functionalities of the non web-based version plus several new functionalities. The web version contains an X-ray viewer and a great deal of interactivity such as validation of electronic patient data forms. The most important additional function is the context sensitive protocol support that may lead to improved protocol adherence. Finally, the web-based version can be accessed from any working place since patient data and protocols are stored centrally.

Decision support and disease management: a logic engineering approach

This paper describes the development and application of PROforma, a unified technology for clinical decision support and disease management. Work leading to the implementation of PROforma has been carried out in a series of projects funded by European agencies over the past 13 years. The work has been based on logic engineering, a distinct design and development methodology that combines concepts from knowledge engineering, logic programming, and software engineering. Several of the projects have used the approach to demonstrate a wide range of applications in primary and specialist care and clinical research. Concurrent academic research projects have provided a sound theoretical basis for the safety-critical elements of the methodology. The principal technical results of the work are the PROforma logic language for defining clinical processes and an associated suite of software tools for delivering applications, such as decision support and disease management procedures. The language supports four standard objects (decisions, plans, actions, and enquiries), each of which has an intuitive meaning with well-understood logical semantics. The development toolset includes a powerful visual programming environment for composing applications from these standard components, for verifying consistency and completeness of the resulting specification and for delivering stand-alone or embeddable applications. Tools and applications that have resulted from the work are described and illustrated, with examples from specialist cancer care and primary care. The results of a number of evaluation activities are included to illustrate the utility of the technology.

Disseminating medical knowledge: the PROforma approach

Medical knowledge is traditionally disseminated via the publication of documents and through participation in clinical practice. Information technology offers to extend both modes of dissemination, via electronic publishing and virtual reality training, for example. AI promises even more radical changes through the possibility of publishing clinical expertise in the form of expert systems, which assist patient care through active decision support and workflow management. PROforma is a knowledge representation language that is designed to support this new mode of dissemination. It is based on an intuitive model of the processes of care and well-understood logical semantics. This paper provides a description of the language and associated software tools, and discusses its potential roles in, and implications for, medical knowledge publishing.