Problem formulation by medical students: an observation study

<p>Abstract</p> <p>Background</p> <p>Medical problems are often complex and ill-structured. In formulating the problem, one has to discriminate pertinent elements from irrelevant information in order to effectively find a solution. In this observation study, we describe how medical students formulate the problem of a complex case.</p> <p>Methods</p> <p>32 third year medical students were presented with a complex case of endocarditis. They were asked to synthesize the case and give the best formulation of the problem. They were then asked to provide a diagnosis. A subsequent group of 25 students were presented with the problem already formulated and were also asked for the diagnosis. We analyzed the student's problem formulations using the presence or absence of essential elements of the case, the use of higher-order concepts and the use of relations between concepts.</p> <p>Results</p> <p>12/32 students presented with the case made the correct diagnosis. Diagnostic accuracy was significantly associated with the use of higher-order concepts and relations between concepts. Establishing explicit relations was particularly important. Almost all students who missed the diagnosis could not elicit any relations between concepts but only reported factual observations. When presented with an already formulated problem, 19/25 students made the correct diagnosis. (p < 0.05)</p> <p>Conclusion</p> <p>When faced with a complex new case, students may not have the structured knowledge to recognize the nature of the problem. They have to build new schema or problem representation. Our observations suggest that this process involves using higher-order concepts and establishing new relations between concepts. The fact that students could recognize the disease when presented with a formulated problem but had more difficulty when presented with the original complex case indicates that knowledge of the clinical features may be necessary but not sufficient for problem formulation. Our hypothesis is that problem formulation represents a distinct ability.</p

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe

Transverse momentum spectra of charged particles in proton-proton collisions at s=900\sqrt{s} = 900 GeV with ALICE at the LHC

The inclusive charged particle transverse momentum distribution is measured in proton-proton collisions at $\sqrt{s} = 900$ GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region $(|\eta|<0.8)$ over the transverse momentum range $0.15<p_{\rm T}<10$ GeV/$c$. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for $|\eta|<0.8$ is $\left<p_{\rm T}\right>_{\rm INEL}=0.483\pm0.001$ (stat.) $\pm0.007$ (syst.) GeV/$c$ and \left_{\rm NSD}=0.489\pm0.001 (stat.) $\pm0.007$ (syst.) GeV/$c$, respectively. The data exhibit a slightly larger $\left<p_{\rm T}\right>$ than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.Comment: 20 pages, 8 figures, 2 tables, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/390

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Patient Safety in Internal Medicine

AbstractHospital Internal Medicine (IM) is the branch of medicine that deals with the diagnosis and non-surgical treatment of diseases, providing the comprehensive care in the office and in the hospital, managing both common and complex illnesses of adolescents, adults, and the elderly. IM is a key ward for Health National Services. In Italy, for example, about 17.3% of acute patients are discharged from the IM departments. After the epidemiological transition to chronic/degenerative diseases, patients admitted to hospital are often poly-pathological and so requiring a global approach as in IM. As such transition was not associated—with rare exceptions—to hospital re-organization of beds and workforce, IM wards are often overcrowded, burdened by off-wards patients and subjected to high turnover and discharge pressure. All these factors contribute to amplify some traditional clinical risks for patients and health operators. The aim of our review is to describe several potential errors and their prevention strategies, which should be implemented by physicians, nurses, and other healthcare professionals working in IM wards

Preventing stroke recurrence in patients with patent foramen ovale, antithrombotic therrapy, foramen closure, or therapeutic abstention? A decision analytic perspective.

Emphasis on the role of patent foramen ovale as a potential risk factor for ischemic paradoxical stroke has recently increased. Current therapeutic options for secondary stroke prevention include long-term antithrombotic therapies and invasive closure of the defect, but selective indications have not been evaluated. Therefore we developed a Markov-based decision analysis model for a hypothetical cohort of patients 55 years of age with presumed paradoxical embolism, measuring for each therapy the risks of stroke recurrence, treatment-related complications, and death after 5 years and the quality-adjusted life-years. Over a wide range of stroke risk recurrence (0.8% per year to 7% per year), the gain provided by closure of the defect exceeded the one obtained by other therapeutic options. When the risk exceeded 0.8% per year and 1.4% per year, respectively, this was also verified for anticoagulation and antiplatelet therapies compared with therapeutic abstention. Therapeutic abstention was the preferred strategy under 0.8% per year. Sensitivity analyses identified key parameters influencing the choice of therapy. These included estimates of stroke recurrence, bleeding rates, surgery-related case fatality rates, and age. Considering the risks of treatment and the devastating consequences of a recurrent stroke, our model suggests that if the estimated risk of paradoxical stroke recurrence is > 0.8% per year, therapeutic abstention becomes the worst option. Above this threshold secondary stroke prevention with anticoagulation therapy or surgical closure of the defect is the preferred strategy, and assessment of both the risk of stroke recurrence and the risk related to therapeutic options should guide individual therapeutic decision making

BRIEF REPORT: Beyond Clinical Experience: Features of Data Collection and Interpretation That Contribute to Diagnostic Accuracy

BACKGROUND: Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN: Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS: Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS: Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION: Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success

Interprofessional collaborative reasoning by residents and nurses in internal medicine: Evidence from a simulation study

Clinical reasoning has been studied in residents or nurses, using interviews or patient-provider encounters. Despite a growing interest in interprofessional collaboration, the notion of collaborative reasoning has not been well studied in clinical settings. Our study aims at exploring resident-nurse collaborative reasoning in a simulation setting. We enrolled 14 resident-nurse teams from a general internal medicine division in a mixed methods study. Teams each managed one of four acute case scenarios, followed by a stimulated-recall session. A qualitative, inductive analysis of the transcripts identified five dimensions of collaborative reasoning: diagnostic reasoning, patient management, patient monitoring, communication with the patient, and team communication. Three investigators (two senior physicians, one nurse) assessed individual and team performances using a five-point Likert scale, and further extracted elements supporting the collaborative reasoning process. Global assessment of the resident-nurse team was not simply an average of individual performances. Qualitative results underlined the need to improve situational awareness, particularly for task overload. Team communication helped team members stay abreast of each other's thoughts and improve their efficiency. Residents and nurses differed in their reasoning processes, and awareness of this difference may contribute to improving interprofessional collaboration. Understanding collaborative reasoning can provide an additional dimension to interprofessional education