Clinical Decision Unit, an Extension of Emergency Department: An Experience and Advantage in a Tertiary Care Center (original) (raw)
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How do Iranian emergency doctors decide? Clinical decision making processes in practice
Emergency Medicine Journal, 2012
Introduction Emergency doctors must make decisions for many patients in a limited time. Various emergency cases are not compatible with routine conditions as described in textbooks, so doctors use clinical decision making (CDM) processes to act in the best possible way. In the present work, these processes and some of the related factors were assessed. Methods Decisions made by doctors were studied via patient medical records, doctors' notes and interviews with decision-making doctors from the Emergency Department of Rasul-Akram Hospital, Tehran, Iran. All doctors were unaware of this research, and they had previously studied CDM processes as part of their training curriculum. A total of 10 day and 10 night shifts (240 h) between 1 March 2010 and 30 May 2010 were considered for the study. Results Rule-based, event-driven, knowledge-based and skill-based decisions, respectively, were the most frequent processes used by doctors in 726 first visits. It was also found that 7% of decisions were not made on a known CDM basis, that all of them were for non-urgent and 'standard' patients, and that most patients who were non-urgent were referred to first-year postgraduates. Skill-based decisions were not applied in very urgent cases; 107 out of 726 decisions on first visits had shifted to knowledge-based process by the time of final treatment decisions. For final treatment decisions, rule-based and knowledge-based processes were more frequently used than other CDM processes. Conclusions The rule-based process is the most common CDM process used by emergency doctors, perhaps because of the minimisation of human error in this process. CDM choice may be influenced by triage level, treatment room and doctors' educational levels. Revealing and studying these factors may help shift decisions to the best possible decision making levels, defining a model in future research.
System outcomes associated with a pediatric emergency department clinical decision unit
CJEM, 2018
CLINICIAN'S CAPSULE What is known about the topic? Clinical decision units (CDUs) may reduce short-stay hospitalizations (<48 hours), which are associated with longer lengths of stay, increased staffing needs and higher costs. What did this study ask? What are the disposition outcomes and emergency department (ED) return rates following CDU care? Has CDU implementation changed short-stay hospitalization rates? What did this study find? Most CDU patients were discharged, and short-stay hospitalization rate significantly decreased by 0.39% with CDU implementation. Why does this study matter to clinicians? The CDU may reduce short-stay hospitalizations, and is a safe care option for pediatric patients requiring prolonged ED care.
Critical Care Research and Practice, 2018
Introduction. Appropriate decision-making is essential in emergency situations; however, little information is available on how emergency decision-makers decide on the emergency status of the patients shifted to the emergency department of the hospital. This study aimed at explaining the factors that influence the emergency specialists’ decision-making in case of emergency conditions in patients. Methods. This study was carried out with a qualitative content analysis approach. The participants were selected based on purposive sampling by the emergency specialists. The data were collected through semistructured interviews and were analyzed using the method proposed by Graneheim and Lundman. Results. The core theme of the study was “efforts to perceive the acute health threats of the patient.” This theme was derived from the main classes, including “the identification of the acute threats based on the patient’s condition” and “the identification of the acute threats based on periphera...
Clinical Decision Making Introduction
This paper examines the components of decision making and the process of making clinical decisions. An issue to consider is to what degree do we make decisions based on systematic reasoning, rational enquiry, and the best available evidence? What are the thinking processes, i.e. cognition, that we use when making accountable decisions, bearing mind a key part of accountability is our ability to articulate and justify the decisions we make. This also leads us to consider errors in decision making and thus ways to reduce them. What follows is by no means exhaustive, it is an introduction to the large study of decision making, reasoning and exercising clinical judgment. After a short exercise to define nursing clinical decision making, there are three sections: 1. Clinical Decision Making: Normative Theory, how it should be done. 2. Clinical Decision Making: Descriptive Theory, how it is done. 3. Clinical Decision Making: Prescriptive Theory, how it might be done better. You will be presented with: • An opportunity to review the concept of ‘decision making’. • An introduction to the components of clinical decision making. • A discussion on our abilities to use our ‘cognitive’ abilities and errors that may result from normal thinking. • An introduction to ideas of ‘human factors’ and ‘error wisdom’. • A brief consideration of the future for decision making based on information technologies.
This paper examines the components of decision making and the process of making clinical decisions. An issue to consider is to what degree do we make decisions based on systematic reasoning, rational enquiry, and the best available evidence? What are the thinking processes, i.e. cognition, that we use when making accountable decisions, bearing mind a key part of accountability is our ability to articulate and justify the decisions we make. This also leads us to consider errors in decision making and thus ways to reduce them. What follows is by no means exhaustive, it is an introduction to the large study of decision making, reasoning and exercising clinical judgment. After a short exercise to define nursing clinical decision making, there are three sections: 1. Clinical Decision Making: Normative Theory, how it should be done. 2. Clinical Decision Making: Descriptive Theory, how it is done. 3. Clinical Decision Making: Prescriptive Theory, how it might be done better.
International Journal of Interactive Multimedia and Artificial Intelligence
One of the biggest challenges for the management of the emergency department (ED) is to expedite the management of patients since their arrival for those with low priority pathologies selected by the classification systems, generating unnecessary saturation of the ED. Diagnostic decision support systems (DDSS) can be a powerful tool to guide diagnosis, facilitate correct classification and improve patient safety. Patients who attended the ED of a tertiary hospital with the preconditions of Manchester Triage system level of low priority (levels 3, 4 and 5), and with one of the five most frequent causes for consultation: dyspnea, chest pain, gastrointestinal bleeding, general discomfort and abdominal pain, were interviewed by an independent researcher with a DDSS, the Mediktor system. After the interview, we compare the Manchester triage and the final diagnoses made by the ED with the triage and diagnostic possibilities ordered by probability obtained by the Mediktor system, respectively. In a final sample of 214 patients, the urgency assignment made by both systems does not match exactly, which could indicate a different classification model, but there were no statistically significant differences between the assigned levels (S = 0.059, p = 0.442). The diagnostic accuracy between the final diagnosis and any of the first 10 Mediktor diagnoses was of 76.5%, for the first five diagnoses was 65.4%, for the first three diagnoses was 58%, and the exact match with the first diagnosis was 37.9%. The classification of Mediktor in this segment of patients shows that a higher level of severity corresponds to a greater number of hospital admissions, hospital readmissions and emergency screenings at 30 days, although without statistical significance. It is expected that this type of applications may be useful as a complement to the triage, to accelerate the diagnostic approach, to improve the request for appropriate complementary tests in a protocolized action model and to reduce waiting times in the ED.
Emergency department of a university hospital
European Journal of Emergency Medicine, 2013
Objectives Our main aim was to describe the path of patients seen in our emergency department (ED) and either admitted or transferred and to compare the characteristics of patients hospitalized in our hospital with those of transferred patients. Our secondary aim was to compare the receipts linked to patient hospital stays. Population and methods All patients seen in the ED of our hospital and ill enough to be either admitted or transferred were prospectively enrolled during 2 consecutive weeks. Information was obtained from the hospital discharge report and from local medical databases. The characteristics of the patients and receipts were compared according to their path. Results Among the 251 patients included in the study, 9% were transferred directly from the ED to another hospital. Among admitted patients, two-thirds were admitted to the short-stay unit (SSU). Schematically, patients transferred from the ED are more likely to be men around 50 years of age with few comorbidities, requiring surgery with relatively short hospital stays. Patients transferred from the SSU were more likely to be women around 67 years of age with severe comorbidities requiring medical care and longer stays. The mean receipt per day was two to three times greater for patients transferred from the ED as compared with patients hospitalized in our hospital. The mean receipt per day for patients transferred from the SSU also tended to be higher. Conclusion Our results show that patients requiring shorter care are transferred, whereas more severe patients are hospitalized on site. Hospitals will need solutions to optimize their receipts while fulfilling their public missions such as continuity of care.
Improving decision making in the emergency department with simple decision aids
PsycEXTRA Dataset, 2014
Objective. To investigate diagnostic accuracy in patient histories involving nonspecific complaints and the extent to which characteristics of physicians and structural properties of patient histories are associated with accuracy. Methods. Six histories of patients presenting to the emergency department (ED) with nonspecific complaints were provided to 112 physicians: 36 ED physicians, 50 internists, and 26 family practitioners. Physicians listed the 3 most likely diagnoses for each history and indicated which cue(s) they considered crucial. Four weeks later, a subset of 20 physicians diagnosed the same 6 histories again. For each history, experts had previously determined the correct diagnoses and the diagnostic cues. Results. Accuracy ranged from 14% to 64% correct diagnoses (correct diagnosis listed as the most likely) and from 29% to 87% correct differential diagnoses (correct diagnosis listed in the differential). Acute care physicians (ED physicians and internists) included the correct diagnosis in the differential in, on average, 3.4 histories, relative to 2.6 for the family practitioners (P = 0.001, d = .75). Diagnostic performance was fairly reliable (r = .61, P \ 0.001). Clinical experience was negatively correlated with diagnostic accuracy (r = -.25, P = 0.008). Two structural properties of patient histories-cue consensus and cue substitutability-were significantly associated with diagnostic accuracy, whereas case difficulty was not. Finally, prevalence of diagnosis also proved significantly correlated with accuracy. Conclusions. Average diagnostic accuracy in cases with nonspecific complaints far exceeds chance performance, and accuracy varies with medical specialty. Analyzing cue properties in patient histories can help shed light on determinants of diagnostic performance and thus suggest ways to enhance physicians' ability to accurately diagnose cases with nonspecific complaints. P atients presenting to the emergency department (ED) with nonspecific complaints, such as weakness, fatigue, or dizziness, pose a challenge to emergency physicians' diagnostic decision-making process. For instance, researchers involved in the Basel Non-Specific Complaints (BANC) Study 1 observed in unpublished data that in the ED, the misdiagnosis rate in cases involving nonspecific complaints is about 53%, relative to an overall rate of less than 10%. This high rate of errors matters because nonspecific complaints can be associated with life-threatening conditions that require prompt intervention to prevent further deterioration of the patient's health status. 1 Moreover, according to a large study, up to 20% of elderly patients presenting to the ED report nonspecific complaints. A key component in the process of diagnosing patients with nonspecific complaints is the patient history. 3 The information encapsulated therein guides the diagnostician's initial decision-making process. To investigate the properties of patient histories that affect diagnosticians' judgment, we presented original patient histories, as recorded by the admitting emergency physician, 4 to physicians with various medical specialties. We aimed to investigate 3 questions: First, is diagnosis of nonspecific complaints presenting at the ED better than chance? Second, does diagnostic accuracy relate to physicians'