System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support (original) (raw)
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A highly scalable, interoperable clinical decision support service
Journal of the American Medical Informatics Association, 2014
To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2012
A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable serviceoriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service.
Development of a Clinical Decision Support System
2020
Development of a Clinical Decision Support System Introduction CDSSs aim for improving clinical decision-making and patient safety [88]. They can improve patient care by "providing the right information to the right person at the right point in workflow in the right intervention format through the right channel" [126]. CDSSs may support decisions passively, e.g., by error recognitions using computerized physician order entry (CPOE) and monitoring a patient situation, or actively, e.g., by providing alerts in unusual or dangerous situations, recommending medications, and supporting physicians to find optimal decisions. Active decision support systems that require a rethinking and reorganizing of decisions and health care plans from clinicians (e.g., support for diagnostic and treatment decisions) are more likely to fail their acceptance [154]. In such cases, clinicians ignore or overwrite the decisions of a system and, finally, stop using it. Once a CDSS is built, its clinical acceptance depends on an appropriate integration, by means of both its technical adaption to existing clinical systems, specifically to the local electronic health record (EHR), as well as user-friendly interfaces. Well developed and clinically integrated, CDSSs can minimize errors, promote patient safety, save time and, finally, decrease the costs of care [88]. A successful CDSS development and clinical integration requires to reach one of these expected benefits without impairing the remaining, or at least to increase the cost-benefit ratio [88] The work of Berner et al. [12] reviews CDSSs to investigate their impact and effectiveness on clinical decision-making and points out various challenges. Challenges concern technical issues, such as data integration, system development, issues around the vocabulary, system output and maintenance, as well as organizational and personal issues, such as vendors, developers and users, and, finally, legal and ethical issues. To address all these
Clinical Decision Support System A few instances of CDSS application
A CDSS is a system which assists in the clinical decision making process by providing updated and current information. Clinical Decision Support Systems (CDSS) have been evolving for the last thirty years and they really are not a new concept. The focus of these systems has however undergone a substantial change and they are now being designed to actually support the clinical decision making process. The earliest models were more of a source of information and were similar to databases. Then the 'critic' model was developed which was based on accepted evidenced based protocols and wherein a clinician could check with the system as to the completeness of his clinical plan. It would then suggest improvements to the proposed plan. They can assist in varying tasks such as administrative, clinical, pharmacy (prescribing), laboratory result reporting, etc. They have become so specialized that in 2003 an attempt had been made to classify them (Sim and Berlin, 2003). The main advantage of using a CDSS (Clinical Decision Support Systems) is that it can be very handy in working under stress and in busy settings. They can keep treatments according to protocols and hence reduce the rate of clinical errors. The theme of using EBM (Evidenced Based Medicine) to achieve optimum benefit for the patient is one of the fundamental principles in clinical governance (Boissel et al., 2003). Managed care and the medically literate public are expecting health practitioners to adhere to accepted guidelines and hence practice in a more or less uniform pattern. DSS are now in development which is based on accepted protocols, developed by experts in their respective fields (van Oosterhout et al., 2003). Prescribing errors can be reduced as medicines can be checked for suitability, drug interactions when a pharmacy DSS is used. The concept of CPOE (computerized physician order entry) has become familiar today amongst informaticians. Here the physician's orders are directly entered electronically into a computer, which being networked to a information system and running a CDSS in the background checks for validity of the order according to established guidelines, drug dosage is verified according to the patient's age or body weight and drug interactions and allergies are intimated immediately at entry. Studies done in ICU (Intensive Care Units) have been encouraging of this method of prescribing (Lillis, 2003). Managed care and clinical governance, in order to control unnecessary tests, have made it necessary for doctors, especially GPs to follow guidelines in requesting procedures such as CT and MRI scans (Bindels et al., 2003). These guidelines when inbuilt into the CDSS the GPs use, work in the background to monitor the requests for such costly procedures and suitably intimate the physician when it may not be acceptable.
The Open Medical Informatics Journal, 2010
Despite their potential to significantly improve health care, advanced clinical decision support (CDS) capabilities are not widely available in the clinical setting. An important reason for this limited availability of CDS capabilities is the application-specific and institution-specific nature of most current CDS implementations. Thus, a critical need for enabling CDS capabilities on a much larger scale is the development and adoption of standards that enable current and emerging CDS resources to be more effectively leveraged across multiple applications and care settings. Standards required for such effective scaling of CDS include (i) standard terminologies and information models to represent and communicate about health care data; (ii) standard approaches to representing clinical knowledge in both human-readable and machine-executable formats; and (iii) standard approaches for leveraging these knowledge resources to provide CDS capabilities across various applications and care settings. A number of standards do exist or are under development to meet these needs. However, many gaps and challenges remain, including the excessive complexity of many standards; the limited availability of easily accessible knowledge resources implemented using standard approaches; and the lack of tooling and other practical resources to enable the efficient adoption of existing standards. Thus, the future development and widespread adoption of current CDS standards will depend critically on the availability of tooling, knowledge bases, and other resources that make the adoption of CDS standards not only the right approach to take, but the cost-effective path to follow given the alternative of using a traditional, ad hoc approach to implementing CDS.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2012
The Clinical Decision Support Consortium has completed two demonstration trials involving a web service for the execution of clinical decision support (CDS) rules in one or more electronic health record (EHR) systems. The initial trial ran in a local EHR at Partners HealthCare. A second EHR site, associated with Wishard Memorial Hospital, Indianapolis, IN, was added in the second trial. Data were gathered during each 6 month period and analyzed to assess performance, reliability, and response time in the form of means and standard deviations for all technical components of the service, including assembling and preparation of input data. The mean service call time for each period was just over 2 seconds. In this paper we report on the findings and analysis to date while describing the areas for further analysis and optimization as we continue to expand our use of a Services Oriented Architecture approach for CDS across multiple institutions.
Integrating Clinical Decision Support into Workflow
2011
This project was funded as an Accelerating Change and Transformation in Organizations and Networks (ACTION) task order contract. ACTION is a 5-year implementation model of fieldbased research that fosters public-private collaboration in rapid-cycle, applied studies. ACTION promotes innovation in health care delivery by accelerating the development, implementation, diffusion, and uptake of demand-driven and evidence-based products, tools, strategies, and findings. ACTION also develops and diffuses scientific evidence about what does and does not work to improve health care delivery systems. It provides an impressive cadre of deliveryaffiliated researchers and sites with a means of testing the application and uptake of research knowledge. With a goal of turning research into practice, ACTION links many of the Nation's largest health care systems with its top health services researchers. For more information about this initiative, go to http://www.ahrq.gov/research/action.htm.