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Background For emergency department (ED) patients with suspected infection, a vital sign-based clinical rule is often calculated shortly after the patient arrives. The clinical rule score (normal or abnormal) provides information about diagnosis and/or prognosis. Since vital signs vary over time, the clinical rule scores can change as well. In this prospective multicentre study, we investigate how often the scores of four frequently used clinical rules change during the ED stay of patients with suspected infection. Methods Adult (≥ 18 years) patients with suspected infection were prospectively included in three Dutch EDs between March 2016 and December 2019. Vital signs were measured in 30-min intervals and the quick Sequential Organ Failure Assessment (qSOFA) score, the Systemic Inflammatory Response Syndrome (SIRS) criteria, the Modified Early Warning Score and the National Early Warning Score (NEWS) score were calculated. Using the established cut-off points, we analysed how often alterations in clinical rule scores occurred (i.e. switched from normal to abnormal or vice versa). In addition, we investigated which vital signs caused most alterations. Results We included 1433 patients, of whom a clinical rule score changed once or more in 637 (44.5%) patients. In 6.7–17.5% (depending on the clinical rule) of patients with an initial negative clinical rule score, a positive score occurred later during ED stay. In over half (54.3–65.0%) of patients with an initial positive clinical rule score, the score became negative later on. The respiratory rate caused most (51.2%) alterations. Conclusion After ED arrival, alterations in qSOFA, SIRS, MEWS and/or NEWS score are present in almost half of patients with suspected infection. The most contributing vital sign to these alterations was the respiratory rate. One in 6–15 patients displayed an abnormal clinical rule score after a normal initial score. Clinicians should be aware of the frequency of these alterations in clinical rule scores, as clinical rules are widely used for diagnosis and/or prognosis and the optimal moment of assessing them is unknown.

Background To improve medication surveillance and provide pharmacotherapeutic support in University Hospitals Leuven, a back-office clinical service, called “Check of Medication Appropriateness” (CMA), was developed, consisting of clinical rule based screening for medication inappropriateness. The aim of this study is twofold: 1) describing the development of CMA and 2) evaluating the preliminary results, more specifically the number of clinical rule alerts, number of actions on the alerts and acceptance rate by physicians. Methods CMA focuses on patients at risk for potentially inappropriate medication and involves the daily checking by a pharmacist of high-risk prescriptions generated by advanced clinical rules integrating patient specific characteristics with details on medication. Pharmacists’ actions are performed by adding an electronic note in the patients’ medical record or by contacting the physician by phone. A retrospective observational study was performed to evaluate the primary outcomes during an 18-month study period. Results 39,481 clinical rule alerts were checked by pharmacists for which 2568 (7%) electronic notes were sent and 637 (1.6%) phone calls were performed. 37,782 (96%) alerts were checked within four pharmacotherapeutic categories: drug use in renal insufficiency (25%), QTc interval prolonging drugs (11%), drugs with a restricted indication or dosing (14%) and overruled very severe drug-drug interactions (50%). The emergency department was a frequently involved ward and anticoagulants are the drug class for which actions are most frequently carried out. From the 458 actions performed for the four abovementioned categories, 69% were accepted by physicians. Conclusions These results demonstrate the added value of CMA to support medication surveillance in synergy with already integrated basic clinical decision support and bedside clinical pharmacy. Otherwise, the study also highlighted a number of limitations, allowing improvement of the service. Electronic supplementary material The online version of this article (10.1186/s12911-019-0748-5) contains supplementary material, which is available to authorized users.

Background: In intensive care environments, technology is omnipresent whereby ensuring constant monitoring and the administration of critical drugs to unstable patients. A clinical decision support system (CDSS), with its widespread possibilities, can be a valuable tool in supporting adequate patient care. However, it is still unclear how decision support alerts should be presented to physicians and other medical staff to ensure that they are used most effectively. Objective: To determine the effect of four different alert presentation methods on alert compliance after the implementation of an advanced CDSS on the intensive care unit (ICU) in our hospital. Methods: A randomized clinical trial was executed from August 2010 till December 2011, which included all patients admitted to the ICU of our hospital. The CDSS applied contained a set of thirteen locally developed clinical rules. The percentage of alert compliance was compared for four alert presentation methods: pharmacy intervention, physician alert list, electronic health record (EHR) section and pop-up alerts. Additionally, surveys were held to determine the method most preferred by users of the CDSS. Results: In the study period, the CDSS generated 902 unique alerts, primarily due to drug dosing during decreased renal function and potassium disturbances. Alert compliance was highest for recommendations offered in pop-up alerts (41%, n = 68/166), followed by pharmacy intervention (33%, n = 80/244), the physician alert list (20%, n = 40/199) and the EHR section (19%, n = 55/293). The method most preferred by clinicians was pharmacy intervention, and pop-up alerts were found suitable as well if applied correctly. The physician alert list and EHR section were not considered suitable for CDSSs in the process of this study. Conclusion: The alert presentation method used for CDSSs is crucial for the compliance with alerts for the clinical rules and, consequently, for the efficacy of these systems. Active alerts such as pop-ups and pharmacy intervention were more effective than passive alerts, which do not automatically appear within the clinical workflow. In this pilot study, ICU clinicians also preferred pharmacy intervention and pop-up alerts. More research is required to expand these results to other departments and other hospitals, as well as to other types of CDSSs and different alert presentation methods. (C) 2013 Elsevier B.V. All rights reserved.

Journal Article; Research Support, Non-U.S. Gov't; BACKGROUND Patients with testicular germ cell cancer (GCC) have a high cure rate; however, cancer-related fatigue is the most common complication among patients with GCC undergoing treatment with chemotherapy. Although exercise is widely recommended, information about the physio-pathological effects of cancer therapy on skeletal muscle is very limited. Our aim is to evaluate the effects of an individualized program of muscular strength and endurance with aerobic training on cancer-related fatigue. METHODS/DESIGN The present study is a randomized controlled trial comparing an individualized program of muscular strength and endurance with aerobic training compared to a control group. We will conduct this trial in patients undergoing chemotherapy, recruited by the Department of Oncology of Virgen de la Victoria Hospital (Málaga). Patients will be included and evaluated before the first cycle of chemotherapy and assigned randomly to the experimental or control group. Cancer-related fatigue, physical condition and biological samples will be measured at the beginning and at the end of an 8-week intervention by the same evaluator, who will be unaware of the allocation of participants to each group. Furthermore, there will be monitoring for 6 months (24 weeks) after training for all outcome variables. DISCUSSION This study hopes to offer patients with GCC an individualized exercise program with aerobic training for cancer-related fatigue. Such a scheme, if beneficial, could be implemented successfully within public health. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02433197 . Date of registration: 13 April 2015. Yes

Delirium is an acute confusional state commonly affecting hospitalized older patients. As a part of the Improving Care of Vulnerable Elders (ICOVE) project, interventions were designed to improve delirium screening and reduce use of strong anticholinergic medications while avoiding contributing to alert fatigue. Methods: Baseline compliance was assessed for each step in the workflow. The intervention was designed in cooperation with the clinicians who are responsible for those steps and built using the integrated decision support facilities of the electronic patient record system. Compliance after the intervention is assessed using the same computerized measures used to determine the baseline and using statistical process control charts. Results: Baseline compliance for delirium screening was 62.3%. Baseline compliance for avoiding strong anticholinergics was 84.3%, but varied from 17.2% to 97.3% for different therapeutic classes. Clinicians asked for a column added to a patient summary table to indicate whether delirium screening had been performed, and a non-interruptive onscreen alert for strong anticholinergic medications. However, the prescribing alert could only be implemented as a modal dialog alert or a passive alert accessed through clicking a tab in the patient record. We implemented the modal dialog alert for orders and the passive alert for active medications. Conclusions: We were able to perform computerized assessment of delirium screening and avoidance of strong anticholinergic medications, although both rules contained ambiguous terms which needed to be defined for the intervention. Assessment of multiple outcomes proved useful both for assessing the quality of care and for identifying where additional support was needed. Assessing the specificity of inferences about data not recorded in structured fields also revealed areas for improvement that would otherwise be missed. Additional functionality for flexibility in decision support in electronic patient record systems may be needed to combat alert fatigue, although this must be weighed against the need to maintain a consistent user experience.

Introduction: Our advanced clinical decision support (CDS) system, entitled 'adverse drug event alerting system' (ADEAS), is in daily use in our hospital pharmacy. It is used by hospital pharmacists to select patients at risk of possible adverse drug events (ADEs). The system retrieves data from several information systems, and uses clinical rules to select the patients at risk of ADEs. The clinical rules are all medication related and are formulated using seven risk categories. Objective: This studies objectives are to 1) evaluate the use of the CDS system ADEAS in daily hospital pharmacy practice, and 2) assess the rule effectiveness and positive predictive value (PPV) of the clinical rules incorporated in the system. Setting: Leiden University Medical Center, The Netherlands. All patients admitted on six different internal medicine and cardiology wards were included. Measures: Outcome measures were total number of alerts, number of patients with alerts and the outcome of these alerts: whether the hospital pharmacist gave advice to prevent a possible ADE or not. Both overall rule effectiveness and PPV and rule effectiveness and PPV per clinical rule risk category were scored. Study design: During a 5 month study period safety alerts were generated daily by means of ADEAS. All alerts were evaluated by a hospital pharmacist and if necessary, healthcare professionals were subsequently contacted and advice was given in order to prevent possible ADEs. Results: During the study period ADEAS generated 2650 safety alerts in 931 patients. In 270 alerts (10%) the hospital pharmacist contacted the physician or nurse and in 204 (76%) cases this led to an advice to prevent a possible ADE. The remaining 2380 alerts (90%) were scored as non-relevant. Most alerts were generated with clinical rules linking pharmacy and laboratory data (1685 alerts). The overall rule effectiveness was 0.10 and the overall PPV was 0.08. Combination of rule effectiveness and PPV was highest for clinical rules based upon the risk category ''basic computerized physician order entry (CPOE) medication safety alerts fine-tuned to high risk patients'' (rule efficiency=0.17; PPV=0.14). Conclusion: ADEAS can effectively be used in daily hospital pharmacy practice to select patients at risk of potential ADEs, but to increase the benefits for routine patient care and to increase efficiency, both rule effectiveness and PPV for the clinical rules should be improved. Furthermore, clinical rules would have to be refined and restricted to those categories that are potentially most promising for clinical relevance, i.e. ''clinical rules with a combination of pharmacy and laboratory data'' and ''clinical rules based upon the basic CPOE medication safety alerts fine-tuned to high risk patients''.