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Background: The Centers for Medicare & Medicaid Services' Stage 2 final rule requires that eligible hospitals provide a visit summary electronically at transitions of care in order to qualify for "meaningful use" incentive payments. However, Massachusetts state law and Federal law prohibit the transmission of documents containing "sensitive" data unless there is a new patient consent for each transmission., Objectives: To describe the implementation and evaluation of a rule-based decision support system used to screen transition of care documents for sensitive data., Methods: We implemented a rule-based document screening system to identify transition of care documents that might contain sensitive data. The transmission of detected documents is withheld until a new patient consent is obtained. The documents that were flagged as containing sensitive data were reviewed in two different time periods to verify that the decision support system was not missing documents or withholding more documents than necessary., Results: The rule-based screening system has been in regular production use for the past 18 months. During the first evaluation period, 3% of 5,841 documents were identified as containing sensitive data (true-positive rate of 44%). After additional enhancements to the rules, the system was evaluated a second time and 4.5% of 6,935 documents were identified as containing sensitive data (true-positive rate of 98.4%)., Conclusion: The analysis of the system demonstrates that production rules can be used to automatically screen the content of transition of care documents for sensitive data. The utilization of the rule-based decision support system enabled our hospitals to achieve meaningful use and, at the same time, remain compliant with state and federal laws.

Carrot (Daucus carota L.) is a vegetable crop that is grown throughout the year across various regions of Brazil in rotation or in succession to other cultures. Herbicide residual effect has emerged as a concern, because of the possibility of carryover. Thus, the objective of this study was to evaluate the effect of tembotrione and atrazine residues - in mixture and isolated - on carrot planted in succession to corn. The experiment was designed in randomized blocks with five replications. Treatments consisted of tembotrione (50.4 g ha(-1)), tembotrione (100.8 g ha(-1)), tembotrione + atrazine (50.4 g ha(-1)+ 2 L ha(-1)), tembotrione + atrazine (100.8 g ha(-1)+ 2 L ha(-1)), and atrazine (2.00 L ha(-1)) applied eight months before carrot seeding, plus a control treatment with no herbicide application. Investigated variables were shoot dry mass, productivity, and classification of carrot roots. The presence of atrazine and tembotrione decreased dry mass in the area, and only tembotrione reduced total root productivity. Thus, there is a carryover effect to tembotrione application that reduces the dry matter accumulation of shoot and total productivity, and an atrazine + tembotrione (100.8 g ha(-1)) mixture reduces the total productivity after application of these herbicides to soil.

Introduction: For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial., Methods: Thirteen EDs participated in this trial. The 10 sites receiving the CDS intervention used the Epic(®) EHR. All sites implementing EHR-based CDS built the rules by using the vendor's CDS engine. Based on a sociotechnical analysis, we designed the CDS so that recommendations could be displayed immediately after any provider entered prediction rule data. One central site developed and tested the intervention package to be exported to other sites. The intervention package included a clinical trial alert, an electronic data collection form, the CDS rules and the format for recommendations., Results: The original PECARN head trauma prediction rules were derived from physician documentation while this pragmatic trial led each site to customize their workflows and allow multiple different providers to complete the head trauma assessments. These differences in workflows led to varying completion rates across sites as well as differences in the types of providers completing the electronic data form. Site variation in internal change management processes made it challenging to maintain the same rigor across all sites. This led to downstream effects when data reports were developed., Conclusions: The process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial.

Objective: To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma., Materials and Methods: We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians., Results: The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service., Discussion: The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock., Conclusion: With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Objective: Clinical data warehouses have accelerated clinical research, but even with available open source tools, there is a high barrier to entry due to the complexity of normalizing and importing data. The Office of the National Coordinator for Health Information Technology's Meaningful Use Incentive Program now requires that electronic health record systems produce standardized consolidated clinical document architecture (C-CDA) documents. Here, we leverage this data source to create a low volume standards based import pipeline for the Informatics for Integrating Biology and the Bedside (i2b2) clinical research platform. We validate this approach by creating a small repository at Partners Healthcare automatically from C-CDA documents., Materials and Methods: We designed an i2b2 extension to import C-CDAs into i2b2. It is extensible to other sites with variances in C-CDA format without requiring custom code. We also designed new ontology structures for querying the imported data., Results: We implemented our methodology at Partners Healthcare, where we developed an adapter to retrieve C-CDAs from Enterprise Services. Our current implementation supports demographics, encounters, problems, and medications. We imported approximately 17 000 clinical observations on 145 patients into i2b2 in about 24 min. We were able to perform i2b2 cohort finding queries and view patient information through SMART apps on the imported data., Discussion: This low volume import approach can serve small practices with local access to C-CDAs and will allow patient registries to import patient supplied C-CDAs. These components will soon be available open source on the i2b2 wiki., Conclusions: Our approach will lower barriers to entry in implementing i2b2 where informatics expertise or data access are limited., (© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objective: To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions., Materials and Methods: 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., Results: 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., Discussion: We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS., Conclusions: 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.

The mushroom Agaricus brasiliensis (sun mushroom), native from the southeast of Brazil, is well known by its medicinal properties that include effects on diabetes, cholesterol levels, and osteoporosis. The antimutagenic effects of A. brasiliensis has been investigated recently and revealed some controversial results depending on the temperature by which the A. brasiliensis tea is obtained. In the present study, we evaluated the effect of the A. brasiliensis extract prepared in two different temperatures, 4°C and 25°C, on the doxorubicin-induced DNA strand breaks and chromosomal aberrations (CAs) in human lymphocytes. The results demonstrated that A. brasiliensis was able to reduce the DXR-induced DNA damage in both temperatures; however, the CA test was more sensitive to demonstrate a better reduction when the cells were treated with an extract obtained at 25°C. A. brasiliensis extract obtained in different temperatures exhibited antigenotoxic and anticlastogenic effects in human lymphocytes.

Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

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.

Background: There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows., Methods: We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines., Conclusion: The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.

An important barrier to the widespread dissemination of clinical decision support (CDS) is the heterogeneity of information models and terminologies used across healthcare institutions, health information systems, and CDS resources such as knowledge bases. To address this problem, the Health Level 7 (HL7) Virtual Medical Record project (an open, international standards development effort) is developing community consensus on the clinical information exchanged between CDS engines and clinical information systems. As a part of this effort, the HL7 CDS Work Group embarked on a multinational, collaborative effort to identify a representative set of clinical data elements required for CDS. Based on an analysis of CDS systems from 20 institutions representing 4 nations, 131 data elements were identified as being currently utilized for CDS. These findings will inform the development of the emerging HL7 Virtual Medical Record standard and will facilitate the achievement of scalable, standards-based CDS.

Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points. We report in this paper on challenges we faced while pursuing this research: knowledge representation and modeling, data interchange and standards adoption, the process of getting agreement on content, logistics of integrating into a system that already has multiple CDS interventions, legal issues around privacy and access, inter-team communication and organization.

Introduction: We evaluated the feasibility of using an electronic protocol developed for research use (Research-eProtocol-insulin) for blood glucose management in usual intensive care unit clinical practice., Methods: We implemented the rules of Research-eProtocol-insulin in the electronic medical record of the Intermountain Healthcare hospital system (Clinical-eProtocol-insulin) for use in usual clinical practice. We evaluated the performance of Clinical-eProtocol-insulin rules in the intensive care units of seven Intermountain Healthcare hospitals and compared this performance with the performance of Research-eProtocol-insulin at the LDS Hospital Shock/Trauma/Respiratory Intensive Care Unit., Results: Clinician (nurse or physician) compliance with computerized protocol recommendations was 95% (of 21,325 recommendations) with Research-eProtocol-insulin and 92% (of 109,458 recommendations) with Clinical-eProtocol-insulin. The blood glucose distribution in clinical practice (Clinical-eProtocol-insulin) was similar to the research use distribution (Research-eProtocol-insulin); however, the mean values (119 mg/dl vs 113 mg/dl) were statistically different (P = 0.0001). Hypoglycemia rates in the research and practice settings did not differ: the percentage of measurements < or =40 mg/dl (0.11% vs 0.1%, P = 0.65) and the percentage of patients with at least one blood glucose < or =40 mg/dl (4.2% vs 3%, P = 0.23) were not statistically significantly different., Conclusion: Our electronic blood glucose protocol enabled translation of a research decision-support tool (Research-eProtocol-insulin) to usual clinical practice (Clinical-eProtocol-insulin).

Authors evaluated the impact of computerized alerts on the quality of outpatient laboratory monitoring for transplant patients. For 356 outpatient liver transplant patients managed at LDS Hospital, Salt Lake City, this observational study compared traditional laboratory result reporting, using faxes and printouts, to computerized alerts implemented in 2004. Study alerts within the electronic health record notified clinicians of new results and overdue new orders for creatinine tests and immunosuppression drug levels. After implementing alerts, completeness of reporting increased from 66 to >99 %, as did positive predictive value that a report included new information (from 46 to >99 %). Timeliness of reporting and clinicians' responses improved after implementing alerts (p <0.001): median times for clinicians to receive and complete actions decreased to 9 hours from 33 hours using the prior traditional reporting system. Computerized alerts led to more efficient, complete, and timely management of laboratory information.

Chronically anticoagulated patients taking the drug Warfarin require time intensive management and followup processes to avoid complications. The "Chronic Anticoagulation Clinic" (CAC) protocol is a set of production rules that help manage, treat, and follow-up such patients. The CAC protocol has been in regular use at Intermountain Healthcare (Salt Lake City, UT, USA) for over three years. The results demonstrate an improvement on the number of patients with anticoagulation levels within the desired target range. The protocol alerts have a high acceptance rate (83.4%) and were able to help patients remember to collect their next coagulation test. The CAC protocol results show that production rules can improve the management of chronically anticoagulated patients. Additional studies are required to verify if this experience can be transferred to other institutions.

Growing and maintaining a simple and flexible EMR (Electronic Medical Record) becomes a complicated task in light of diverse and distributed legacy data representation, advancing technologies, changes in medical practice and procedure, and changes in data regulation. Utilizing several abstraction mechanisms can simplify application development and maintenance, and provide flexibility for data evolution and migration. Newer applications built on these abstractions can be the beneficiary of slower obsolescence and lower maintenance costs.

Purpose: This report describes an ongoing transition from the HELP Hospital Information System to HELP II, a replacement Health Information System built to manage clinical information captured in a variety of medical settings. The focus of the article is on the medical decision support provided by this system and studied by researchers at the University of Utah and Intermountain Health Care (IHC), a large health care organization in Utah, for many years., Methods: Select success features of the original HELP system's decision support environment are identified and lessons learned are related. Plans for transferring these features to HELP II are discussed., Results: The article focuses on four features: (1) the importance of easy access to patient data essential for decision support, (2) the commitment to continued measurement and revision of both the logic and the interventional strategy in a decision support application, (3) experience with data mining as a tool for developing decision support tools, and (4) the role of clinical reports in supporting the decision making process.

Objectives: To discuss the advantages and disadvantages of an interfaced approach to clinical information systems architecture., Methods: After many years of internally building almost all components of a hospital clinical information system (HELP) at Intermountain Health Care, we changed our architectural approach as we chose to encompass ambulatory as well as acute care. We now seek to interface applications from a variety of sources (including some that we build ourselves) to a clinical data repository that contains a longitudinal electronic patient record., Results: We have a total of 820 instances of interfaces to 51 different applications. We process nearly 2 million transactions per day via our interface engine and feel that the reliability of the approach is acceptable. Interface costs constitute about four percent of our total information systems budget. The clinical database currently contains records for 1.45 m patients and the response time for a query is 0.19 sec., Discussion: Based upon our experience with both integrated (monolithic) and interfaced approaches, we conclude that for those with the expertise and resources to do so, the interfaced approach offers an attractive alternative to systems provided by a single vendor. We expect the advantages of this approach to increase as the costs of interfaces are reduced in the future as standards for vocabulary and messaging become increasingly mature and functional.

Objective: To analyze whether computer-generated reminders about infections could influence clinicians' practice patterns and consequently improve the detection and management of nosocomial infections., Design: The conclusions produced by an expert system developed to detect and manage infections were presented to the attending clinicians in a pediatric hospital to determine whether this information could improve detection and management. Clinician interventions were compared before and after the implementation of the system., Measurements: The responses of the clinicians (staff physicians, physician assistants, and nurse practitioners) to the reminders were determined by review of paper medical charts. Main outcome measures were the number of suggestions to treat and manage infections that were followed before and after the implementation of COMPISS (Computerized Pediatric Infection Surveillance System). The clinicians' opinions about the system were assessed by means of a paper questionnaire distributed following the experiment., Results: The results failed to show a statistical difference between the clinicians' treatment strategies before and after implementation of the system (P: > 0.33 for clinicians working in the emergency room and P: > 0.45 for clinicians working in the pediatric intensive care unit). The questionnaire results showed that the respondents appreciated the information presented by the system., Conclusion: The computer-generated reminders about infections were unable to influence the practice patterns of clinicians. The methodologic problems that may have contributed to this negative result are discussed.

Adverse drug events are known to be a major health problem worldwide. It is estimated that the annual costs related to these events in the United States are greater than the total costs with cardiovascular disease care. Decision support systems that assist drug ordering have demonstrated to be a powerful tool to prevent prescription errors and adverse drug events. On the other hand, some issues related to the development, implementation, configuration, and evaluation of these decision support systems still need further research. This paper presents the development and evaluation of a decision support system prototype that helps with the prevention of adverse drug events by detecting drug-drug interactions in drug orders. The structure of the system tries to solve some of the problems described by the literature, such as integration with hospital information systems, adaptability to local needs, and knowledge base maintenance. The proposed model has shown to be an effective method for representing drug-drug interactions. The prototype was evaluated by a retrospective study using a dataset with 37.237 prescriptions. The system was able to detect 10.044 (27.0%) orders containing one or more drug-drug interactions. Among these interactions, 6.4% had high severity. In a future study, it is intended to apply the developed system in a real-time on-line environment, evaluating the benefits achieved in terms of improvement in medical practice and patient outcomes.

This paper describes a drug ordering decision support system that helps with the prevention of adverse drug events by detecting drug-drug interactions in drug orders. The architecture of the system was devised in order to facilitate its use attached to physician order entry systems. The described model focuses in issues related to knowledge base maintenance and integration with external systems. Finally, a retrospective study was performed. Two knowledge bases, developed by different academic centers, were used to detect drug-drug interactions in a dataset with 37,237 drug prescriptions. The study concludes that the proposed knowledge base architecture enables content from other knowledge sources to be easily transferred and adapted to its structure. The study also suggests a method that can be used on the evaluation and refinement of the content of drug knowledge bases.

Hospital-acquired infections are responsible for an increase in patient mortality and costs. Their detection is essential to permit better infection control. We developed an expert system specifically to detect infections in pediatric patients. The expert system is implemented at LDS Hospital that has a level three newborn intensive care unit and well baby units. We describe how the knowledge base of the expert system was developed, implemented, and validated in a retrospective study. The results of the system were compared to manual reviewer results. The expert system had a sensitivity of 84.5% and specificity of 92.8% in detecting hospital-acquired infections when compared to a physician reviewer. The Cohen's kappa between the expert system and the physician reviewer was 0.62 (p < .001).

The integration of clinical systems almost always requires a translation phase, where vocabularies are compared and the similar concepts are matched. The lack of standards in the area of medical concept representation makes this task very difficult. The authors describe the development of a frame-based application that automatically translates terms found in one vocabulary to another. The application implements an innovative scoring algorithm that ranks the best matches using an exponential scale. Preliminary results and the comparison against a manual process in the same domain are also discussed.