Development of a web-based decision support system for insulin self-titration.

Insulin is the most potent agent for the treatment of diabetes mellitus. However insulin treatment requires frequent evaluation of blood glucose levels and adjustment of the insulin dose. This process is called titration. To guide patients with type 2 diabetes using once-daily long-acting insulin, we have developed a web-based decision support system for insulin self-titration. The purpose of this paper is to provide an overview of the phases of development and the final design of the system. We reviewed the literature, consulted an expert panel, and conducted interviews with patients to elicit system requirements. This revealed four important aspects: the insulin titration algorithm, the handling of hypoglycemic events, telemedicine functionalities, and visiting frequency monitoring. We used these requirements to develop a fully functional system.

Development of a computerised alert system, ADEAS, to identify patients at risk for an adverse drug event.

INTRODUCTION: Adverse drug events (ADEs) are frequent and pose an important risk for patients treated with drugs. Fortunately, a substantial part of ADEs is preventable, and computerised physician order entry with a sophisticated clinical decision support system may be used to reach this goal. OBJECTIVE: To develop a new automated system that could improve the quality of medication surveillance. The system should focus on detecting patients at risk for an ADE by combining data from the hospital information system and computerised physician order entry (drug prescription data, drug-drug interaction alerts, clinical chemical laboratory parameters, demographic features), using clinical rules. METHODS: The clinical rules were formulated in a multidisciplinary team, based on seven risk categories. The new system was composed in a guideline-based decision support framework consisting of both a guideline development module and a decision support module. A total of 121 clinical rules were built into the system. Validation of the system and a proof of principle test were performed. RESULTS: The adverse drug event alerting system (ADEAS) was developed and validated successfully. The proof of principle test showed that ADEAS has potential clinical usefulness. ADEAS generated alerts and detected additional potential risk situations, which were not generated by the conventional medication surveillance. CONCLUSION: We developed a pharmacy decision support system ADEAS that focuses on the detection of situations prone to lead to an ADE and might help clinicians to take timely corrective interventions and thereby can prevent patient harm.

The effect of computer reminders on GPs' prescribing behaviour: a cluster-randomised trial.

OBJECTIVE: It is difficult to control drug-prescribing behaviour in general practice, despite the development and distribution of guidelines. The purpose of this study was to assess the effect on drug-prescribing behaviour of implementing prescribing guidelines by means of a reactive computer reminder system (CRS). DESIGN: Cluster-randomised controlled trial with an incomplete block design in the south of the Netherlands: 25 GPs (7 GP practices) received reminders about antibiotics and asthma/COPD prescriptions, 28 GPs (7 GP practices) received reminders about cholesterol prescriptions. Prescription guidelines were integrated into the computerised GP information system. MEASUREMENTS: Both performance indicators and prescription volumes were calculated as the main outcome measures. Next to individual volume measure, sum scores were constructed on the volume measures per drug group (antibiotics, asthma/COPD and cholesterol). RESULTS: Variation between GPs turned out to be larger and more skewed than expected. No differences between groups were found for indicators and volumes related to recommendations advocating certain drugs. Although there was a tendency towards clinically relevant results for prescription volumes that were supposed to drop, the difference in sum score between the groups was not significant. For antibiotic prescriptions that were supposed to drop, the sum score for the intervention group was 28.2 (95% CI: 20.8-44.5) prescriptions per 1000 patients per GP, while this was 39.7 (95% CI: 29.7-64.1) for the control group (p 0.2). For prescriptions asthma/COPD that were supposed to drop, the sum score for the intervention group was 1.1 (95% CI: 0.6-2.6) prescriptions per 1000 patients per GP, while this was 2.2 (95% CI: 1.4-4.3) for the control group (p 0.1). On three specific recommendations (on quinolones for cystitis, corticosteroids for CPOD, and antibiotics for acute sore throat) significant differences were found. CONCLUSIONS: This study turned out to be underpowered due to high inter doctor variation in prescribing behaviour. Nevertheless, computerised reminders sometimes have a favourable effect on restricting certain drugs that are not or no longer indicated in general practice.

Three-Layer Model for the design of a Protocol Support System.

OBJECTIVE: The aim of the PropeR project is to investigate the impact of Active Computerized Protocol Support (ACPS) on daily care processes in different settings (home care and hospital care). ACPS consists of an active Protocol Support System (PSS) that is linked to an Electronic Patient Record system. The aim of this paper is to describe how we have taken the organizational and social aspects into account in the hospital setting and the consequences of this approach for the design of the PSS. METHODS: Socio-technical approaches have been applied. Observations and interviews with various health care providers were performed at the hematology and oncology department of the University Hospital Maastricht. Ten extensive sessions with a specialist physician and research nurse took place to further elaborate a study protocol and to discuss how it is integrated in daily practice. The knowledge editor component of Gaston was used to build a computer interpretable version of the selected protocol. RESULTS AND CONCLUSIONS: To support the representation of a study protocol integrated in routine clinical care, a Three-Layer Model was developed. This model distinguishes the protocol description, local adaptations to the protocol and communication as three separate layers. These layers have been incorporated into the knowledge acquisition tool Gaston. The Three-Layer Model makes easy updating possible, and also supports transferability of computerized (study) protocols to other organizations.

The PropeR way to support medical doctors in daily practice. Developing the protocol based DSS.

This paper describes the first phase of the development of a Protocol based Decision Support System (PDSS) that will be linked to an Electronic Patient Record system (EPR system). The protocol system will be pro-active: the physician will be automatically prompted from the EPR of a particular patient if the protocol that applies for that patient defines it necessary. The PropeR project studies the impact of a PDSS that is linked to an EPR on daily care processes. There are two areas of research: hospital and home care. This paper describes the application in the hospital. The protocol that is being computerized is a treatment protocol for Acute Myelogenous Leukaemia (AML) that also studies treatment alternatives (conventional versus experimental treatment). This paper based AML protocol has been translated into a formal representation. The KA-tool Gaston is used to make this representation. Twenty-eight subprotocols have been organized in a hierarchical structure with three levels. One of the aims of the project is to make a representation of the AML protocol that can be used in other organizations as well. The main problem we encountered is that the representation not only contains the content of the protocol, but also aspects of application of that protocol in daily care of the hospital and aspects of support. The solution to this problem is the creation of two layers of representation: the first layer is an exact copy of the protocol and thus sharable and the second layer focuses on the support of the protocol in the daily working processes and is mainly domain specific: for the University Hospital Maastricht. At the moment, this division into two layers is being discussed.

Design and implementation of a framework to support the development of clinical guidelines.

This paper describes and discusses a framework that facilitates the development of clinical guideline application tasks. The framework, named GASTON covers all stages in the guideline development process, ranging from the definition of models that represent guidelines to the implementation of run-time systems that provide decision support, based on the guidelines that were developed during the earlier stages. The GASTON framework consists of (1) a newly developed guideline representation formalism that uses the concepts of primitives, problem-solving methods (PSMs) and ontologies to represent the guidelines of various complexity and granularity and different application domains, (2) a guideline authoring environment that enables guideline authors to define the guidelines, based on the newly developed guideline representation formalism and (3) a guideline execution environment that translates defined guidelines into a more efficient symbol level representation, which can be read in and processed by an execution time engine. The paper describes a number of design criteria that were formulated regarding the aspects of guideline representation, guideline authoring and guideline execution and explains the framework by example in terms of the four stages that were identified in the guideline development process and the tools that were developed to support each stage. It also shows examples of systems that were developed by means of the GASTON framework.

Design of a consumer health record for supporting the patient-centered management of chronic diseases.

This paper describes and discusses the design and usage of a shareable consumer health record system to investigate whether these systems can assist in the management of chronic diseases. This web-based system that can be used both by care providers and patients contains medical and patient information, provides access to websites that contain quality information, provides guideline-based advice, allows discussion between patients and allows us to interrogate both patients and care providers on a regular basis in order to get a good impression of the utility of such a consumer record for both chronic patients and the physicians and nurses. A health record system that was developed for the area of Diabetes is presented as an example.

The application of ontologies and problem-solving methods for the development of shareable guidelines.

Recently, studies have shown the benefits of using clinical guidelines in the practice of medicine. Computer-based clinical guidelines are increasingly applied in diverse areas such as policy development, utilization management, education, conduct of clinical trials, and workflow facilitation. This paper discusses some of the representations suggested in literature, discusses their weak and strong points, and demonstrates and discusses a new approach that extends earlier developed formalisms by combining primitives, ontologies and the use of problem-solving methods (PSMs). The approach is supported by a framework that facilitates the entire guideline authoring process. The paper demonstrates this framework and presents examples of guidelines, PSMs and systems that were developed by means of this approach. The overall goal of this approach is to improve the acceptance of shareable guidelines and decision support systems in daily care by facilitating the guideline acquisition and execution phases.

An ontological approach for the development of shareable guidelines.

Computer-based clinical guidelines and protocols are being increasingly applied in diverse areas. Although there is still little standardization to facilitate sharing, various parties are engaged in the development of shareable guideline representation formalisms and corresponding decision support systems. This paper mentions some of these developed representations, discusses their pros en cons, and demonstrates and discusses a new approach, which combines common elements from earlier-developed formalisms with new ones to improve the reusability and shareability of developed guidelines. An ontological representation is presented that formalizes guidelines in terms of domain-specific knowledge and employed generic strategies that use this domain-specific knowledge in order to solve particular guideline tasks. Furthermore, a framework is described that supports this representation and three examples are shown of guidelines of various granularity and complexity that were developed by means of this approach.

A test ordering system with automated reminders for primary care based on practice guidelines.

In this article we describe a real-time automated reminder system that has been developed to change Family Physicians' (FP) test ordering behavior. The system focuses on the appropriateness of test requests. We aim at using the system as a substitute for written feedback by human experts. The reminder system consists of a knowledge base, an order entry system and modules to provide passive and active support in the form of reminders to FPs. The system generates critical comments about the rationality of the test requests at the moment the FP orders a test that is not in line with national or regional guidelines. For the first validation of the knowledge base we compared the comments of a human expert to the comments of the reminder system on three random samples of test requests. The overall agreement in the subsequent validation rounds was 46, 60 and 69%. The corrections made in the knowledge base after each validation round resulted in a reminder system with 149 reminders concerning various medical problems. Due to the corrections in the knowledge base the reminder system reacts better over the subsequent validation rounds.

GASTON: an architecture for the acquisition and execution of clinical guideline-application tasks.

Recently, studies have shown the benefits of using clinical guidelines in the practice of medicine. There have been numerous efforts to develop clinical decision support systems that support guideline-based care in an automated fashion, covering a wide range of clinical settings and tasks. Despite these efforts, only a few systems progressed beyond the prototype stage and the research laboratory. For guideline-based clinical decision support systems to be successful, a balance must be made between intuitive but imprecise representations usually encountered by most of today's systems and representations that support a strong underlying clinical performance model. The project described in this paper tries to achieve such a balance. It presents the GASTON architecture that contains a set of reusable software components for the application of guidelines, including design-time components to facilitate the guideline authoring process based on guideline representation models along with execution-time components for building decision support systems that incorporate these guidelines. This architecture was used to develop several guideline representation models such as a rule-based representation to model rule-based guidelines and guideline representation models that address more complex tasks. Also, decision support systems that incorporate these models were developed with the architecture. For the representation and application of various classes of guidelines, rules were also viewed as instances of more complex tasks. By identifying similar characteristics of sets of rules, we developed several tasks such as a drug intera ction and drug contraindication task. Based on these models, we have developed and validated guidelines and decision support systems for use in several application domains such as intensive care, family physicians and psychiatry. In order to be able to represent more complex time-oriented plans, new guideline representation models are being developed.

A strategy for developing practice guidelines for the ICU using automated knowledge acquisition techniques.

OBJECTIVES: To implement practice guideline entry tools in a reminder system in order to provide decision support to health care workers in clinical care and emergency care environments. To design a knowledge acquisition environment that enables physicians to formulate, update, and verify guidelines without the assistance of a knowledge engineer. METHODS: We developed a knowledge acquisition environment for the Intensive Care Unit (ICU) consisting of 1) a graphical knowledge acquisition tool, 2) tools that perform logical and semantic tests on proposed guidelines, 3) a Patient Data Management System (PDMS) containing clinical patient data, and 4) an expert system that reminds ICU health care workers of inconsistencies between a treatment plan and implemented guidelines. Physicians enter the guidelines using the knowledge acquisition tool, after which consistency and correctness tests are performed on the guidelines. The guidelines are then transferred to the knowledge base of the reminder system and validated by applying the new guidelines to a large stored data set of previous patients. If the new guidelines are approved, they are exported to the reminder system that is used in daily practice. RESULTS: ICU physicians used the knowledge acquisition tool to enter 58 guidelines into the reminder system's knowledge base. These guidelines were tested on a data set consisting of 803 previously admitted patients. As a result, 27 guidelines fired at least once, generating 406 reminders in total. Of the 406 generated reminders, 356 (88%) were issued correctly and 50 (12%) were false alarms. The reminders that were issued correctly involved 3 situations: 1) the database contained inconsistent or incomplete information, 2) the actions or decisions of the health care workers were not the most appropriate ones, and 3) there was a potential risk involved. All false alarms were caused by the fact that the corresponding guidelines were not specific enough to handle certain exceptions. As a result of this analysis, the guidelines could be improved in such a way as to eliminate all false alarms. CONCLUSIONS: These first results demonstrate that this bottom-up knowledge acquisition strategy, implemented by the automated knowledge acquisition tools, enables medical specialists to improve the quality of computer support in an ICU without assistance of a knowledge engineer.