Optimizing Triage and Hospitalization in Adult General Medical Emergency Patients. The Triage Project

Background: Patients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission. Methods/design: Prospective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures. We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons fordischarge delays, patient’s satisfaction with care, overall hospital costs and patients care needs after returning home. Discussion: Using a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient’s outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.

Revascularisation versus medical treatment in patients with stable coronary artery disease: network meta-analysis

OBJECTIVE To investigate whether revascularisation improves prognosis compared with medical treatment among patients with stable coronary artery disease. DESIGN Bayesian network meta-analyses to combine direct within trial comparisons between treatments with indirect evidence from other trials while maintaining randomisation. ELIGIBILITY CRITERIA FOR SELECTING STUDIES A strategy of initial medical treatment compared with revascularisation by coronary artery bypass grafting or Food and Drug Administration approved techniques for percutaneous revascularization: balloon angioplasty, bare metal stent, early generation paclitaxel eluting stent, sirolimus eluting stent, and zotarolimus eluting (Endeavor) stent, and new generation everolimus eluting stent, and zotarolimus eluting (Resolute) stent among patients with stable coronary artery disease. DATA SOURCES Medline and Embase from 1980 to 2013 for randomised trials comparing medical treatment with revascularisation. MAIN OUTCOME MEASURE All cause mortality. RESULTS 100 trials in 93 553 patients with 262 090 patient years of follow-up were included. Coronary artery bypass grafting was associated with a survival benefit (rate ratio 0.80, 95% credibility interval 0.70 to 0.91) compared with medical treatment. New generation drug eluting stents (everolimus: 0.75, 0.59 to 0.96; zotarolimus (Resolute): 0.65, 0.42 to 1.00) but not balloon angioplasty (0.85, 0.68 to 1.04), bare metal stents (0.92, 0.79 to 1.05), or early generation drug eluting stents (paclitaxel: 0.92, 0.75 to 1.12; sirolimus: 0.91, 0.75 to 1.10; zotarolimus (Endeavor): 0.88, 0.69 to 1.10) were associated with improved survival compared with medical treatment. Coronary artery bypass grafting reduced the risk of myocardial infarction compared with medical treatment (0.79, 0.63 to 0.99), and everolimus eluting stents showed a trend towards a reduced risk of myocardial infarction (0.75, 0.55 to 1.01). The risk of subsequent revascularisation was noticeably reduced by coronary artery bypass grafting (0.16, 0.13 to 0.20) followed by new generation drug eluting stents (zotarolimus (Resolute): 0.26, 0.17 to 0.40; everolimus: 0.27, 0.21 to 0.35), early generation drug eluting stents (zotarolimus (Endeavor): 0.37, 0.28 to 0.50; sirolimus: 0.29, 0.24 to 0.36; paclitaxel: 0.44, 0.35 to 0.54), and bare metal stents (0.69, 0.59 to 0.81) compared with medical treatment. CONCLUSION Among patients with stable coronary artery disease, coronary artery bypass grafting reduces the risk of death, myocardial infarction, and subsequent revascularisation compared with medical treatment. All stent based coronary revascularisation technologies reduce the need for revascularisation to a variable degree. Our results provide evidence for improved survival with new generation drug eluting stents but no other percutaneous revascularisation technology compared with medical treatment.

A new method to facilitate valid and consistent grading cardiac events in childhood cancer survivors using medical records

BACKGROUND Cardiac events (CEs) are among the most serious late effects following childhood cancer treatment. To establish accurate risk estimates for the occurrence of CEs it is essential that they are graded in a valid and consistent manner, especially for international studies. We therefore developed a data-extraction form and a set of flowcharts to grade CEs and tested the validity and consistency of this approach in a series of patients. METHODS The Common Terminology Criteria for Adverse Events version 3.0 and 4.0 were used to define the CEs. Forty patients were randomly selected from a cohort of 72 subjects with known CEs that had been graded by a physician for an earlier study. To establish whether the new method was valid for appropriate grading, a non-physician graded the CEs by using the new method. To evaluate consistency of the grading, the same charts were graded again by two other non-physicians, one with receiving brief introduction and one with receiving extensive training on the new method. We calculated weighted Kappa statistics to quantify inter-observer agreement. RESULTS The inter-observer agreement was 0.92 (95% CI 0.80-1.00) for validity, and 0.88 (0.79-0.98) and 0.99 (0.96-1.00) for consistency with the outcome assessors who had the brief introduction and the extensive training, respectively. CONCLUSIONS The newly developed standardized method to grade CEs using data from medical records has shown excellent validity and consistency. The study showed that the method can be correctly applied by researchers without a medical background, provided that they receive adequate training.

Intensive care without walls - introduction of a Medical Emergency Team system in a Swiss tertiary care centre.

QUESTIONS UNDER STUDY To improve the response of deteriorating patients during their hospital stay, the University Hospital Bern has introduced a Medical Emergency Team (MET). Aim of this retrospective cohort study is to review the preceding factors, patient characteristics, process parameters and their correlation to patient outcomes of MET calls since the introduction of the team. METHODS Data on patient characteristics, parameters related to MET activation and intervention and patient outcomes were evaluated. A Vital Sign Score (VSS), which is defined as the sum of the occurrence of each vital sign abnormalities, was calculated for all physiological parameters pre MET event, during event and correlation with hospital outcomes. RESULTS A total of 1,628 MET calls in 1,317 patients occurred; 262 (19.9%) of patients with MET calls during their hospital stay died. The VSS pre MET event (odds ratio [OR] 1.78, 95% confidence interval [CI] 1.50-2.13; AUROC 0.63; all p <0.0001) and during the MET call (OR 1.60, 95% CI 1.41-1.83; AUROC 0.62; all p <0.0001) were significantly correlated to patient outcomes. A significant increase in MET calls from 5.2 to 16.5 per 1000 hospital admissions (p <0.0001) and a decrease in cardiac arrest calls in the MET perimeter from 1.6 in 2008 to 0.8 per 1000 admissions was observed during the study period (p = 0.014). CONCLUSIONS The VSS is a significant predictor of mortality in patients assessed by the MET. Increasing MET utilisation coincided with a decrease in cardiac arrest calls in the MET perimeter.

Stroke Prevention - Medical and Lifestyle Measures.

Background: According to the World Health Organization, stroke is the 'incoming epidemic of the 21st century'. In light of recent data suggesting that 85% of all strokes may be preventable, strategies for prevention are moving to the forefront in stroke management. Summary: This review discusses the risk factors and provides evidence on the effective medical interventions and lifestyle modifications for optimal stroke prevention. Key Messages: Stroke risk can be substantially reduced using the medical measures that have been proven in many randomized trials, in combination with effective lifestyle modifications. The global modification of health and lifestyle is more beneficial than the treatment of individual risk factors. Clinical Implications: Hypertension is the most important modifiable risk factor for stroke. Efficacious reduction of blood pressure is essential for stroke prevention, even more so than the choice of antihypertensive drugs. Indications for the use of antihypertensive drugs depend on blood pressure values and vascular risk profile; thus, treatment should be initiated earlier in patients with diabetes mellitus or in those with a high vascular risk profile. Treatment of dyslipidemia with statins, anticoagulation therapy in atrial fibrillation, and carotid endarterectomy in symptomatic high-grade carotid stenosis are also effective for stroke prevention. Lifestyle factors that have been proven to reduce stroke risk include reducing salt, eliminating smoking, performing regular physical activity, and maintaining a normal body weight. © 2015 S. Karger AG, Basel.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices

SUMMARY There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

The application of medical informatics to the veterinary management programs at companion animal practices in Alberta, Canada: a case study.

Companion animals closely share their domestic environment with people and have the potential to, act as sources of zoonotic diseases. They also have the potential to be sentinels of infectious and noninfectious, diseases. With the exception of rabies, there has been minimal ongoing surveillance of, companion animals in Canada. We developed customized data extraction software, the University of, Calgary Data Extraction Program (UCDEP), to automatically extract and warehouse the electronic, medical records (EMR) from participating private veterinary practices to make them available for, disease surveillance and knowledge creation for evidence-based practice. It was not possible to build, generic data extraction software; the UCDEP required customization to meet the specific software, capabilities of the veterinary practices. The UCDEP, tailored to the participating veterinary practices', management software, was capable of extracting data from the EMR with greater than 99%, completeness and accuracy. The experiences of the people developing and using the UCDEP and the, quality of the extracted data were evaluated. The electronic medical record data stored in the data, warehouse may be a valuable resource for surveillance and evidence-based medical research.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Using Informatics and the Electronic Medical Record to Describe Antimicrobial Use in the Clinical Management of Diarrhea Cases at 12 Companion Animal Practices

Antimicrobial drugs may be used to treat diarrheal illness in companion animals. It is important to monitor antimicrobial use to better understand trends and patterns in antimicrobial resistance. There is no monitoring of antimicrobial use in companion animals in Canada. To explore how the use of electronic medical records could contribute to the ongoing, systematic collection of antimicrobial use data in companion animals, anonymized electronic medical records were extracted from 12 participating companion animal practices and warehoused at the University of Calgary. We used the pre-diagnostic, clinical features of diarrhea as the case definition in this study. Using text-mining technologies, cases of diarrhea were described by each of the following variables: diagnostic laboratory tests performed, the etiological diagnosis and antimicrobial therapies. The ability of the text miner to accurately describe the cases for each of the variables was evaluated. It could not reliably classify cases in terms of diagnostic tests or etiological diagnosis; a manual review of a random sample of 500 diarrhea cases determined that 88/500 (17.6%) of the target cases underwent diagnostic testing of which 36/88 (40.9%) had an etiological diagnosis. Text mining, compared to a human reviewer, could accurately identify cases that had been treated with antimicrobials with high sensitivity (92%, 95% confidence interval, 88.1%-95.4%) and specificity (85%, 95% confidence interval, 80.2%-89.1%). Overall, 7400/15,928 (46.5%) of pets presenting with diarrhea were treated with antimicrobials. Some temporal trends and patterns of the antimicrobial use are described. The results from this study suggest that informatics and the electronic medical records could be useful for monitoring trends in antimicrobial use.

An investigation into the factors that encourage learner participation in a large group medical classroom

BACKGROUND: Effective lectures often incorporate activities that encourage learner participation. A challenge for educators is how to facilitate this in the large group lecture setting. This study investigates the individual student characteristics involved in encouraging (or dissuading) learners to interact, ask questions, and make comments in class. METHODS: Students enrolled in a Doctor of Veterinary Medicine program at Ross University School of Veterinary Medicine, St Kitts, were invited to complete a questionnaire canvassing their participation in the large group classroom. Data from the questionnaire were analyzed using Excel (Microsoft, Redmond, WA, USA) and the R software environment (http://www.r-project.org/). RESULTS: One hundred and ninety-two students completed the questionnaire (response rate, 85.7%). The results showed statistically significant differences between male and female students when asked to self-report their level of participation (P=0.011) and their confidence to participate (P<0.001) in class. No statistically significant difference was identified between different age groups of students (P=0.594). Student responses reflected that an "aversion to public speaking" acted as the main deterrent to participating during a lecture. Female participants were 3.56 times more likely to report a fear of public speaking than male participants (odds ratio 3.56, 95% confidence interval 1.28-12.33, P=0.01). Students also reported "smaller sizes of class and small group activities" and "other students participating" as factors that made it easier for them to participate during a lecture. CONCLUSION: In this study, sex likely played a role in learner participation in the large group veterinary classroom. Male students were more likely to participate in class and reported feeling more confident to participate than female students. Female students in this study commonly identified aversion to public speaking as a factor which held them back from participating in the large group lecture setting. These are important findings for veterinary and medical educators aiming to improve learner participation in the classroom. Potential ways of addressing this challenge include addition of small group activities and audience response systems during lectures, and inclusion of training interventions in public speaking at an early stage of veterinary and medical curricula.

Prophylaxis of infectious complications with colony-stimulating factors in adult cancer patients undergoing chemotherapy-evidence-based guidelines from the Infectious Diseases Working Party AGIHO of the German Society for Haematology and Medical Oncology (DGHO).

BACKGROUND Current evidence on myelopoietic growth factors is difficult to overview for the practicing haematologist/oncologist. International guidelines are sometimes conflicting, exclude certain patient groups, or cannot directly be applied to the German health system. This guideline by the Infectious Diseases Working Party (AGIHO) of the German Society of Haematology and Medical Oncology (DGHO) gives evidence-based recommendations for the use of G-CSF, pegylated G-CSF, and biosimilars to prevent infectious complications in cancer patients undergoing chemotherapy, including those with haematological malignancies. METHODS We systematically searched and evaluated current evidence. An expert panel discussed the results and recommendations. We then compared our recommendations to current international guidelines. RESULTS We summarised the data from eligible studies in evidence tables, developed recommendations for different entities and risk groups. CONCLUSION Comprehensive literature search and expert panel consensus confirmed many key recommendations given by international guidelines. Evidence for growth factors during acute myeloid leukaemia induction chemotherapy and pegfilgrastim use in haematological malignancies was rated lower compared with other guidelines.

Risk factors for patient-reported medical errors in eleven countries

OBJECTIVES The aim of this study was to identify common risk factors for patient-reported medical errors across countries. In country-level analyses, differences in risks associated with error between health care systems were investigated. The joint effects of risks on error-reporting probability were modelled for hypothetical patients with different health care utilization patterns. DESIGN Data from the Commonwealth Fund's 2010 lnternational Survey of the General Public's Views of their Health Care System's Performance in 11 Countries. SETTING Representative population samples of 11 countries were surveyed (total sample = 19,738 adults). Utilization of health care, coordination of care problems and reported errors were assessed. Regression analyses were conducted to identify risk factors for patients' reports of medical, medication and laboratory errors across countries and in country-specific models. RESULTS Error was reported by 11.2% of patients but with marked differences between countries (range: 5.4-17.0%). Poor coordination of care was reported by 27.3%. The risk of patient-reported error was determined mainly by health care utilization: Emergency care (OR = 1.7, P < 0.001), hospitalization (OR = 1.6, P < 0.001) and the number of providers involved (OR three doctors = 2.0, P < 0.001) are important predictors. Poor care coordination is the single most important risk factor for reporting error (OR = 3.9, P < 0.001). Country-specific models yielded common and country-specific predictors for self-reported error. For high utilizers of care, the probability that errors are reported rises up to P = 0.68. CONCLUSIONS Safety remains a global challenge affecting many patients throughout the world. Large variability exists in the frequency of patient-reported error across countries. To learn from others' errors is not only essential within countries but may also prove a promising strategy internationally.

Loss of appetite in acutely ill medical inpatients: physiological response or therapeutic target?

Loss of appetite and ensuing weight loss is a key feature of severe illnesses. Protein-energy malnutrition (PEM) contributes significantly to the adverse outcome of these conditions. Pharmacological interventions to target appetite stimulation have little efficacy but considerable side effects. Therefore nutritional therapy appears to be the logical step to combat inadequate nutrition. However, clinical trial data demonstrating benefits are sparse and there is no current established standard algorithm for use of nutritional support in malnourished, acutely ill medical inpatients. Recent high-quality evidence from critical care demonstrating harmful effects when parenteral nutritional support is used indiscriminately has led to speculation that loss of appetite in the acute phase of illness is indeed an adaptive, protective response that improves cell recycling (autophagy) and detoxification. Outside critical care, there is an important gap in high quality clinical trial data shedding further light on these important issues. The selection, timing, and doses of nutrition should be evaluated as carefully as with any other therapeutic intervention, with the aim of maximising efficacy and minimising adverse effects and costs. In light of the current controversy, a reappraisal of how nutritional support should be used in acutely ill medical inpatients outside critical care is urgently required. The aim of this review is to discuss current pathophysiological concepts of PEM and to review the current evidence for the efficacy of nutritional support regarding patient outcomes when used in an acutely ill medical patient population outside critical care.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.