Decision-making under pressure: medical errors in uncertain and dynamic environments

A dimensional analysis of experienced intensive care unit nurses' clinical decision-making for bleeding after cardiac surgery

BACKGROUND

Bleeding following cardiac surgery is common and serious, yet a gap persists in understanding how experienced intensive care nurses identify and respond to such complications.

AIM

To describe the clinical decision-making of experienced intensive care unit nurses in addressing bleeding after cardiac surgery.

STUDY DESIGN

This qualitative study adopted the Recognition-Primed Decision Model as its theoretical framework. Thirty-nine experienced nurses from four adult intensive care units participated in semi-structured interviews based on the critical decision method. The interviews explored their clinical judgements and decisions in bleeding situations, and data were analysed through dimensional analysis, an alternative to grounded theory.

RESULTS

Participants maintained consistent vigilance towards post-cardiac surgery bleeding, recognizing it through a haemorrhagic dimension associated with blood loss and chest drainage and a hypovolemic dimension focusing on the repercussions of reduced blood volume. These dimensions organized their understanding of bleeding types (i.e., normal, medical, surgical, tamponade) and necessary actions. Their decision-making encompassed monitoring bleeding, identifying the cause, stopping the bleeding, stabilizing haemodynamic and supporting the patient and family. Participants also adapted their actions to specific circumstances, including local practices, professional autonomy, interprofessional dynamics and resource availability.

CONCLUSIONS

Nurses' decision-making was shaped by their personal attributes, the patient's condition and contextual circumstances, underscoring their expertise and pivotal role in anticipating actions and adapting to diverse conditions. The concept of actionability emerged as the central dimension explaining their decision-making, defined as the capability to implement actions towards specific goals within the possibilities and constraints of a situation.

RELEVANCE TO CLINICAL PRACTICE

This study underscores the need for continual updates to care protocols to align with current evidence and for quality improvement initiatives to close existing practice gaps. Exploring the concept of actionability further, developing adaptability-focused educational programmes, and understanding decision-making intricacies are crucial for informing nursing education and decision-support systems.

Exploring the competencies of Chinese critical care nurses in mobile medical teams based on the onion model: A qualitative study

BACKGROUND

With frequent conflicts, natural disasters, and public health emergencies globally, mobile medical teams (MMTs) are becoming increasingly critical. Importantly, the competency of critical care nurses in MMTs can substantially affect the effectiveness and quality of its rescue efforts. Yet, these nurses' competencies are not well understood.

AIM

This study examined the competencies of critical care nurses in MMTs using the Onion Model.

STUDY DESIGN

A qualitative descriptive method was used to describe the competencies of Chinese MMT critical care nurses. From April to May 2022, a convenience sample of 18 participants (14 critical care nurses and 4 surgeons) from 10 MMTs was recruited for semi-structured interviews. Deductive and inductive coding methods were combined for content analysis.

RESULTS

In total, 29 competencies were identified, which were grouped into four major domains using the Onion Model. From the outer to inner layers, these domains were knowledge and skills, professional abilities, professional quality, and personal traits. Several novel competencies emerged, including field medical equipment operation skills, on-site hazard identification and safety prevention skills, triage knowledge, and field survival skills.

CONCLUSIONS

Using the Onion Model, this study furthers the understanding of the competency of critical care nurses in MMTs, especially by revealing the novel competencies. Further, the results can be used to recruit, evaluate, and train critical care nurses for MMTs.

RELEVANCE TO CLINICAL PRACTICE

Understanding MMT critical care nurses' competencies can help managers plan and provide relevant training and education before deployment, which can improve nurses' performance, and especially reduce the mortalities and disabilities from trauma.

Death by accidental intravenous administration of gasoline

Herein, we present the case of accidental intravenous injection of gasoline in a 62-year-old male who was admitted to a dialysis center for his regular hemodialysis. Due to previous contact with another SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) positive patient, the hemodialysis was conducted in an isolated room. At the end of the procedure, the nurse, wearing all necessary personal protective equipment (PPE), in the intent to clean the dialysis catheter, applied medical gasoline, instead of 0.9% sodium chloride, intravenously to the patient. Soon afterwards, the patient's clinical condition deteriorated, and cardiopulmonary resuscitation was started. Despite the immediate reaction of the medical staff, after two successful cardiopulmonary reanimation and necessary intensive care measures, the patient suffered respiratory, metabolic, and lactic acidosis, hypotension, and tachyarrhythmia and ultimately died 7 h after the incident. The autopsy was conducted under the order of the district attorney. Main autopsy findings were marked congestion; right pleural and pericardial effusion; brain and lung edema; enlarged heart with left ventricle thickening and mild perivascular fibrosis; nephrosclerosis; tubular thyroidization; and interstitial fibrosis with inflammation. Gasoline presence was indisputably proven by conducted toxicology analysis in lung, bile, and brain samples. Traces of gasoline could be noted in the patient's blood sample in comparison to the blood that did not contain gasoline, but it was not possible to confidently claim that gasoline was present in the blood. Based on relevant findings, we concluded that the death of the patient was violent and that the cause of death was acute intoxication by gasoline.

The role of information systems in emergency department decision-making-a literature review

OBJECTIVES

Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED.

MATERIALS AND METHODS

We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes.

RESULTS

Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes.

DISCUSSION

Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation.

CONCLUSION

We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

Enhancing neurosurgical navigation operation flow management through personal digital assistant technology: a prospective cohort study

Purpose

This prospective cohort study aims to evaluate the impact of digital health technology especially Personal Digital Assistants (PDA) in neurosurgical procedure management, focusing on surgical safety check accuracy, efficiency, and patient satisfaction.

Methods

The study included 211 neurosurgical cases from January to December 2022. The control group of 106 patients followed traditional verification methods, while the experimental group of 105 patients used PDA. The PDA system facilitated real-time data collection, verification, and transmission. The study compared both groups in terms of check times, accuracy rates, and patient satisfaction, and used multivariate regression to assess the impact of baseline parameters on these outcomes.

Results

The study found that the experimental group using the PDA system reduced the average verification time by approximately 8 min, achieving 100.0% accuracy in preoperative and postoperative checks, significantly better than the control group (91.5% pre- and post-operation). Multivariate regression confirmed a 48.1% reduction in postoperative verification time due to the PDA system (p < 0.001), with the model showing high explanatory power (R2 = 0.911). Other examined factors, including patient age and nurse experience, had no significant effects. Similarly, the PDA's introduction markedly improved verification accuracy, with no significant impact from other variables (p = 0.010).

Conclusion

The application of the PDA system in neurosurgical operations significantly enhanced the accuracy and efficiency of surgical safety checks, reduced nursing errors, optimized nursing workflows, and improved patient satisfaction. These results provide valuable insights for the application of PDA technology in high-risk medical fields, demonstrating potential of digital health tools in enhancing surgical safety and efficiency.

Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process

BACKGROUND

Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process.

METHODS

The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM's different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset.

RESULTS

The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard.

CONCLUSIONS

In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.

Concussion-Related Decision-Making by Certified Athletic Trainers: Implications for Concussion Prevention and Care

Concussions are a common sport-related injury that require appropriate initial care. Athletic trainers, often a primary source of healthcare for student-athletes, are key individuals involved in initial concussion diagnostic and management decisions. Challenges exist within the athletic environment that may hinder the consistency, efficacy, and/or effectiveness of concussion-related decision-making by athletic trainers, thereby impacting secondary concussion prevention and patient health. The purpose of this study was to identify factors that impact the intentions of athletic trainers to make appropriate concussion-related decisions under various circumstances. Overall, 1029 participants completed a survey examining educational precursors (quantity and quality of healthcare communication educational focus), demographic precursors (age, gender, educational degree, and employment setting), theory-based mediators (attitudes, perceived norms, and personal agency), and external mediators (knowledge, salience, and communication/collaboration practices) on appropriate concussion-related decision-making intentions. Data were analyzed using a two-step structural equation modeling approach. Quality of healthcare communication educational focus indirectly impacted appropriate concussion-related decision-making intentions via perceived behavioral control and communication/collaboration practices. Additionally, several factors impacted intentions to make appropriate concussion-related decisions directly including employment setting, self-efficacy, and general attitudes towards decision-making and concussions. Concussion prevention is aided by the initial and appropriate action taken by a healthcare professional to reduce immediate consequences; however, this action may be influenced by stakeholder relationships. These influential factors of decision-making may place athletes at further injury risk and negatively impact overall athlete health. As such, a sound theoretical framework incorporating the complexity of factors that may influence decision-making is needed.

Trigger tool-based description of adverse events in helicopter emergency medical services in Qatar

INTRODUCTION

Adverse events (AEs) in helicopter emergency medical services (HEMS) remain poorly reported, despite the potential for harm to occur. The trigger tool (TT) represents a novel approach to AE detection in healthcare. The aim of this study was to retrospectively describe the frequency of AEs and their proximal causes (PCs) in Qatar HEMS.

METHODS

Using the Pittsburgh Adverse Event Tool to identify AEs in HEMS, we retrospectively analysed 804 records within an existing AE TT database (21-month period). We calculated outcome measures for triggers, AEs and harm per 100 patient encounters, plotted measures on statistical process control charts, and conducted a multivariate analysis to report harm associations.

RESULTS

We identified 883 triggers in 536 patients, with a rate of 1.1 triggers per patient encounter, where 81.2% had documentation errors (n=436). An AE and harm rate of 27.7% and 3.5%, respectively, was realised. The leading PC was actions by HEMS Crew (81.6%; n=182). The majority of harm (57.1%) stemmed from the intervention and medication triggers (n=16), where deviation from standard of care was common (37.9%; n=11). Age and diagnosis-adjusted odds were significant in the patient condition (6.50; 95% CI 1.71 to 24.67; p=0.01) and interventional (11.85; 95% CI 1.36 to 102.92; p=0.03) trigger groupings, while age and diagnosis had no effect on harm.

CONCLUSION

The TT methodology is a robust, reliable and valid means of AE detection in the HEMS domain. While an AE rate of 27.7% is high, more research is required to understand prehospital clinical decision-making and reasons for guideline deviance. Furthermore, focused quality improvement initiatives to reduce AEs and documentation errors should also be addressed in future research.

Cognitive biases and moral characteristics of healthcare workers and their treatment approach for persons with advanced dementia in acute care settings

Introduction

Palliative care (PC) delivery for persons with advanced dementia (AD) remains low, particularly in acute-care settings. Studies have shown that cognitive biases and moral characteristics can influence patient care through their effect on the thinking patterns of healthcare workers (HCWs). This study aimed to determine whether cognitive biases, including representativeness, availability, and anchoring, are associated with treatment approaches, ranging from palliative to aggressive care in acute medical situations, for persons with AD.

Methods

Three hundred fifteen HCWs participated in this study: 159 physicians and 156 nurses from medical and surgical wards in two hospitals. The following questionnaires were administered: a socio-demographic questionnaire; the Moral Sensitivity Questionnaire; the Professional Moral Courage Scale; a case scenario of a person with AD presenting with pneumonia, with six possible interventions ranging from PC to aggressive care (referring to life-prolonging interventions), each given a score from (-1) (palliative) to 3 (aggressive), the sum of which is the "Treatment Approach Score;" and 12 items assessing perceptions regarding PC for dementia. Those items, the moral scores, and professional orientation (medical/surgical) were classified into the three cognitive biases.

Results

The following aspects of cognitive biases were associated with the Treatment Approach Score: representativeness-agreement with the definition of dementia as a terminal disease and appropriateness of PC for dementia; availability-perceived organizational support for PC decisions, apprehension regarding response to PC decisions by seniors or family, and apprehension regarding a lawsuit following PC; and anchoring-perceived PC appropriateness by colleagues, comfort with end-of-life conversations, guilt feelings following the death of a patient, stress, and avoidance accompanying care. No association was found between moral characteristics and the treatment approach. In a multivariate analysis, the predictors of the care approach were: guilt feelings about the death of a patient, apprehension regarding senior-level response, and PC appropriateness for dementia.

Conclusion

Cognitive biases were associated with the care decisions for persons with AD in acute medical conditions. These findings provide insight into the potential effects of cognitive biases on clinical decisions, which may explain the disparity between treatment guidelines and the deficiency in the implementation of palliation for this population.

Making machine learning matter to clinicians: model actionability in medical decision-making

Machine learning (ML) has the potential to transform patient care and outcomes. However, there are important differences between measuring the performance of ML models in silico and usefulness at the point of care. One lens to use to evaluate models during early development is actionability, which is currently undervalued. We propose a metric for actionability intended to be used before the evaluation of calibration and ultimately decision curve analysis and calculation of net benefit. Our metric should be viewed as part of an overarching effort to increase the number of pragmatic tools that identify a model's possible clinical impacts.

Non-traumatic acute myelopathies: Clinical and imaging features in a real world emergency setting

OBJECTIVE

The aetiologic diagnosis of non-traumatic acute myelopathies (AMs), and their differentiation from other mimicking conditions (i.e. 'mimics'), are clinically challenging, especially in the emergency setting. Here, we sought to identify: (i) red flags suggesting diagnoses alternative to AMs and (ii) clinical signs and magnetic resonance imaging (MRI) features differentiating non-compressive from compressive AMs.

MATERIALS AND METHODS

We retrospectively retrieved MRI scans of spinal cord dictated at emergency room from January 2016 to December 2020 in the suspicion of AMs. Patients with traumatic myelopathies and those with subacute/chronic myelopathies (i.e. MRI scans acquired >48 h from symptom onset) were excluded from analysis.

RESULTS

Our search retrieved 105 patients; after excluding 16 cases of traumatic myelopathies and 14 cases of subacute/chronic myelopathies, we identified 30 cases with non-compressive AMs, 30 cases with compressive AMs and 15 mimics. The presence of pyramidal signs (p = 0.012) and/or pain (p = 0.048) correctly identified 88% of cases with AMs. We failed to identify clinical indicators for distinguishing non-compressive and compressive AMs, although cases with inflammatory AMs were younger than cases with all the remaining conditions (p < 0.05). Different MRI patterns could be described according to the final diagnosis: among non-compressive AMs, inflammatory lesions were more often posterior or central; vascular malformation had a fairly widespread distribution; spine ischaemia was more often central. Anterior or lateral compression were more often associated with neoplasms and disc herniation , whereas hemorrhages and infections produced spine compression on all sides.

CONCLUSION

We propose a simple clinical indicator (i.e. pyramidal signs and/or pain) to distinguish AMs from their mimics in an emergency setting. Urgent spinal cord MRI remains essential to discriminate compressive and non-compressive aetiologies.

The impact of COVID-19 workflow changes on radiation oncology incident reporting

Background

The Ottawa Hospital's Radiation Oncology program maintains the Incident Learning System (ILS)—a quality assurance program that consists of report submissions of errors and near misses arising from all major domains of radiation. In March 2020, the department adopted workflow changes to optimize patient and provider safety during the COVID‐19 pandemic.

Purpose

In this study, we analyzed the number and type of ILS submissions pre‐ and postpandemic precautions to assess the impact of COVID‐19‐related workflow changes.

Methods

ILS data was collected over six one‐year time periods between March 2016 and March 2021. For all time periods, the number of ILS submissions were counted. Each ILS submission was analyzed for the specific treatment domain from which it arose and its root cause, explaining the impetus for the error or near miss.

Results

Since the onset of COVID‐19‐related workflow changes, the total number of ILS submissions have reduced by approximately 25%. Similarly, there were 30% fewer ILS submissions per number of treatment courses compared to prepandemic data. There was also an increase in the proportion of “treatment planning” ILS submissions and a 50% reduction in the proportion of “decision to treat” ILS submissions compared to previous years. Root cause analysis revealed there were more incidents attributable to “poor, incomplete, or unclear documentation” during the pandemic year.

Conclusions

COVID‐19 workflow changes were associated with fewer ILS submissions, but a relative increase in submissions stemming from poor documentation and communication. It is imperative to analyze ILS submission data, particularly in a changing work environment, as it highlights the potential and realized mistakes that impact patient and staff safety.

A Patient Outcomes-Driven Feedback Platform for Emergency Medicine Clinicians: Human-Centered Design and Usability Evaluation of Linking Outcomes Of Patients (LOOP)

Background

The availability of patient outcomes–based feedback is limited in episodic care environments such as the emergency department. Emergency medicine (EM) clinicians set care trajectories for a majority of hospitalized patients and provide definitive care to an even larger number of those discharged into the community. EM clinicians are often unaware of the short- and long-term health outcomes of patients and how their actions may have contributed. Despite large volumes of patients and data, outcomes-driven learning that targets individual clinician experiences is meager. Integrated electronic health record (EHR) systems provide opportunity, but they do not have readily available functionality intended for outcomes-based learning.

Objective

This study sought to unlock insights from routinely collected EHR data through the development of an individualizable patient outcomes feedback platform for EM clinicians. Here, we describe the iterative development of this platform, Linking Outcomes Of Patients (LOOP), under a human-centered design framework, including structured feedback obtained from its use.

Methods

This multimodal study consisting of human-centered design studios, surveys (24 physicians), interviews (11 physicians), and a LOOP application usability evaluation (12 EM physicians for ≥30 minutes each) was performed between August 2019 and February 2021. The study spanned 3 phases: (1) conceptual development under a human-centered design framework, (2) LOOP technical platform development, and (3) usability evaluation comparing pre- and post-LOOP feedback gathering practices in the EHR.

Results

An initial human-centered design studio and EM clinician surveys revealed common themes of disconnect between EM clinicians and their patients after the encounter. Fundamental postencounter outcomes of death (15/24, 63% respondents identified as useful), escalation of care (20/24, 83%), and return to ED (16/24, 67%) were determined high yield for demonstrating proof-of-concept in our LOOP application. The studio aided the design and development of LOOP, which integrated physicians throughout the design and content iteration. A final LOOP prototype enabled usability evaluation and iterative refinement prior to launch. Usability evaluation compared to status quo (ie, pre-LOOP) feedback gathering practices demonstrated a shift across all outcomes from “not easy” to “very easy” to obtain and from “not confident” to “very confident” in estimating outcomes after using LOOP. On a scale from 0 (unlikely) to 10 (most likely), the users were very likely (9.5) to recommend LOOP to a colleague.

Conclusions

This study demonstrates the potential for human-centered design of a patient outcomes–driven feedback platform for individual EM providers. We have outlined a framework for working alongside clinicians with a multidisciplined team to develop and test a tool that augments their clinical experience and enables closed-loop learning.

Safety culture in emergency medicine: An exploratory qualitative study

BACKGROUND

Safety culture in Emergency Departments (EDs) requires special attention due to unique operational feature of the ED environment. Which may influence a culture of patients' safety in the ED.

OBJECTIVE

To identify the factors that influence patient safety culture in EDs.

METHODS

A qualitative study using semi-structured interviews with 12 ED staff was carried out in two Australian EDs. The data was thematically analysed to identify and describe the factors perceived by staff as influencing patient safety culture.

RESULTS

The findings revealed four super-ordinate themes and 19 categories. The themes were the following: (1) Environmental and Organisational; (2) Healthcare Professional (3) Managerial factors; and (4) Patients factors.

CONCLUSIONS

Safety culture in the ED is influenced by complex set of factors. The results of this study may help ED workers with improving patient safety culture and healthcare quality in the ED.

Patients’ Perceptions of Quality of Care: A Teamwork Intervention Study in a Surgical Ward

Introduction

Improving teamwork competencies among health care professionals is important for patient safety. Few previous studies have investigated whether a teamwork intervention has an impact on patients’ perceptions of quality of care.

Objective

To investigate patients’ perceptions of quality of care before and after the implementation of a team training program in a surgical ward.

Methods

A quasi-experimental pre- and posttest design was used. The TeamSTEPPS® team training program was implemented in a surgical ward. Three groups of consecutively sampled patients responded to the Quality from the Patient's Perspective (QPP) questionnaire including four dimensions with 25 items. In addition to the QPP, six items were developed for this study. In total, 223 patients responded to the questionnaire. The mean age was 59.6 years, and there were 128 males and 94 females.

Results

The physical-technical condition dimension and four items showed significantly higher scores after six months of intervention. The majority of the patients scored quality of care in the four dimensions as very high at all three time points. Younger patients reported the lowest care quality.

Conclusion

The results in this study indicate that the teamwork intervention had a minimal impact on the patients’ perceptions of quality of care, with only significant differences between baseline and six months of intervention in one dimension and three items. At each data collection time point, the numbers of patients who perceived quality of care as modest decreased slightly. Younger patients were more likely to perceive care quality as modest.

Improving Emergency Department Patient-Physician Conversation Through an Artificial Intelligence Symptom-Taking Tool: Mixed Methods Pilot Observational Study

BACKGROUND

Establishing rapport and empathy between patients and their health care provider is important but challenging in the context of a busy and crowded emergency department (ED).

OBJECTIVE

We explore the hypotheses that rapport building, documentation, and time efficiency might be improved in the ED by providing patients a digital tool that uses Bayesian reasoning-based techniques to gather relevant symptoms and history for handover to clinicians.

METHODS

A 2-phase pilot evaluation was carried out in the ED of a German tertiary referral and major trauma hospital that treats an average of 120 patients daily. Phase 1 observations guided iterative improvement of the digital tool, which was then further evaluated in phase 2. All patients who were willing and able to provide consent were invited to participate, excluding those with severe injury or illness requiring immediate treatment, with traumatic injury, incapable of completing a health assessment, and aged <18 years. Over an 18-day period with 1699 patients presenting to the ED, 815 (47.96%) were eligible based on triage level. With available recruitment staff, 135 were approached, of whom 81 (60%) were included in the study. In a mixed methods evaluation, patients entered information into the tool, accessed by clinicians through a dashboard. All users completed evaluation Likert-scale questionnaires rating the tool's performance. The feasibility of a larger trial was evaluated through rates of recruitment and questionnaire completion.

RESULTS

Respondents strongly endorsed the tool for facilitating conversation (61/81, 75% of patients, 57/78, 73% of physician ratings, and 10/10, 100% of nurse ratings). Most nurses judged the tool as potentially time saving, whereas most physicians only agreed for a subset of medical specialties (eg, surgery). Patients reported high usability and understood the tool's questions. The tool was recommended by most patients (63/81, 78%), in 53% (41/77) of physician ratings, and in 76% (61/80) of nurse ratings. Questionnaire completion rates were 100% (81/81) by patients and 96% (78/81 enrolled patients) by physicians.

CONCLUSIONS

This pilot confirmed that a larger study in the setting would be feasible. The tool has clear potential to improve patient-health care provider interaction and could also contribute to ED efficiency savings. Future research and development will extend the range of patients for whom the history-taking tool has clinical utility.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00024115; https://drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00024115.

Physicians under Pressure: Evidence from Antibiotics Prescribing in England

BACKGROUND

Many physicians are experiencing increasing demands from both their patients and society. Evidence is scarce on the consequences of the pressure on physicians' decision making. We present a theoretical framework and predict that increasing pressure may make physicians disregard societal welfare when treating patients.

SETTING

We test our prediction on general practitioners' antibiotic-prescribing choices. Because prescribing broad-spectrum antibiotics does not require microbiological testing, it can be performed more quickly than prescribing for narrow-spectrum antibiotics and is therefore often preferred by the patient. In contrast, from a societal perspective, inappropriate prescribing of broad-spectrum antibiotics should be minimized as it may contribute to antimicrobial resistance in the general population.

METHODS

We combine longitudinal survey data and administrative data from 2010 to 2017 to create a balanced panel of up to 1072 English general practitioners (GPs). Using a series of linear models with GP fixed effects, we estimate the importance of different sources of pressure for GPs' prescribing.

RESULTS

We find that the percentage of broad-spectrum antibiotics prescribed increases by 6.4% as pressure increases on English GPs. The link between pressure and prescribing holds for different sources of pressure.

CONCLUSIONS

Our findings suggest that there may be societal costs of physicians working under pressure. Policy makers need to take these costs into account when evaluating existing policies as well as when introducing new policies affecting physicians' work pressure. An important avenue for further research is also to determine the underlying mechanisms related to the different sources of pressure.JEL-code: I11, J28, J45.

HIGHLIGHTS

Many physicians are working under increasing pressure.We test the importance of pressure on physicians' prescribing of antibiotics.The prescribed rate of broad-spectrum antibiotics increases with pressure.Policy makers should be aware of the societal costs of pressured physicians.[Formula: see text].

Teams managing civilian and military complex trauma: What are the competencies required in austere environments and the potential of simulation technology to address them?

Surgical training in civilian hospitals may not be sufficient for managing complex trauma in a setting where such care is not commonly practiced. Understanding the challenges that civilian teams face when moving to austere environments can inform the competencies that need to be trained. The aim of this study was to explore the competencies required in austere environments for teams managing complex trauma, and how they can be trained with simulation technologies. Ethnographic field observations were conducted, and field notes were synthesized. The field notes were structured with the elements of Activity Theory to generate the teams' competencies that need to be trained. A literature review was conducted to verify the results and identify examples of relevant simulation modalities. The analysis resulted in a structured list of competencies for civilian teams to manage complex trauma in an austere environment and recommendations which simulation technologies could be used in training of those competencies based on published studies. Our study contributes to understanding the challenges that civilian teams face when operating in an austere environment. A systematized list of competencies with suggested simulation technologies directs future research to improve quality of complex trauma training in civilian and military collaboration.

Establishing Research Priorities for the Emergency Severity Index Using a Modified Delphi Approach

INTRODUCTION

The accuracy of an initial ED triage decision has been reported to drive the clinical trajectory for ED patients, and, therefore, this assessment is critical to patient safety. The Emergency Severity Index-a 5-point score assigned by a triage nurse and based on disease acuity, patient potential for decompensation, and anticipated resource use-is used both in the United States and internationally. In the US, the Emergency Severity Index is used by up to 94% of the academic medical center emergency departments. In 2020, the Emergency Nurses Association acquired the intellectual property rights to the Emergency Severity Index and is responsible for its maintenance and improvement.

OBJECTIVE

The purpose of this study was to establish a research agenda for the improvement of individual and institutional understanding and use of the Emergency Severity Index.

METHODS

Modified Delphi process was used with 3 rounds of data collection.

RESULTS

Round 1 yielded 112 issues, which were collapsed into 18 potential research questions in 4 general categories: education and training (6 questions), workplace environment (3 questions), emergency care services (7 questions), and special populations (2 questions). These questions were used in round 2 to establish importance. Round 3 yielded a rank ordering of both categories and research questions.

DISCUSSION

The research priorities as set through the use of this modified Delphi process align well with current gaps in the literature. Research in these areas should be encouraged to improve the understanding of educational, environmental, and process challenges to emergency nurses' triage decisions and accuracy of Emergency Severity Index assignments.

Monitoring Diagnostic Safety Risks in Emergency Departments: Protocol for a Machine Learning Study

BACKGROUND

Diagnostic decision making, especially in emergency departments, is a highly complex cognitive process that involves uncertainty and susceptibility to errors. A combination of factors, including patient factors (eg, history, behaviors, complexity, and comorbidity), provider-care team factors (eg, cognitive load and information gathering and synthesis), and system factors (eg, health information technology, crowding, shift-based work, and interruptions) may contribute to diagnostic errors. Using electronic triggers to identify records of patients with certain patterns of care, such as escalation of care, has been useful to screen for diagnostic errors. Once errors are identified, sophisticated data analytics and machine learning techniques can be applied to existing electronic health record (EHR) data sets to shed light on potential risk factors influencing diagnostic decision making.

OBJECTIVE

This study aims to identify variables associated with diagnostic errors in emergency departments using large-scale EHR data and machine learning techniques.

METHODS

This study plans to use trigger algorithms within EHR data repositories to generate a large data set of records that are labeled trigger-positive or trigger-negative, depending on whether they meet certain criteria. Samples from both data sets will be validated using medical record reviews, upon which we expect to find a higher number of diagnostic safety events in the trigger-positive subset. Machine learning will be used to evaluate relationships between certain patient factors, provider-care team factors, and system-level risk factors and diagnostic safety signals in the statistically matched groups of trigger-positive and trigger-negative charts.

RESULTS

This federally funded study was approved by the institutional review board of 2 academic medical centers with affiliated community hospitals. Trigger queries are being developed at both organizations, and sample cohorts will be labeled using the triggers. Machine learning techniques such as association rule mining, chi-square automated interaction detection, and classification and regression trees will be used to discover important variables that could be incorporated within future clinical decision support systems to help identify and reduce risks that contribute to diagnostic errors.

CONCLUSIONS

The use of large EHR data sets and machine learning to investigate risk factors (related to the patient, provider-care team, and system-level) in the diagnostic process may help create future mechanisms for monitoring diagnostic safety.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/24642.

The proportion of computed tomography kidneys, ureters and bladder (CTKUB) scans that comply with scan extent protocol in an emergency department: a clinical audit and dose ramification study

INTRODUCTION

To assess computed tomography kidneys, ureters and bladder (CTKUB) scan extent protocol compliance and associated doses in the Emergency Department (ED) of an Australian tertiary hospital.

METHODS

A retrospective clinical audit of 150 consecutive ED CTKUB cases was completed. For each patient, scan extent compliance at the superior (kidneys) and inferior (pubic symphysis) borders, in reference to the protocol was recorded. Compliance and non-compliance (over-/under-scanning) was identified, described (superior/inferior), quantified (via IMPAX measurements) and recorded via a purpose-built audit tool. In addition, a PBU40 phantom was scanned to assess the percentage of dose (DLP) increase per centimetre of over-scanning to contextualise results.

RESULTS

A notable non-compliance with department protocol was noted. Eight cases (5.3%) demonstrated overall CT scan extent compliance. The remaining 142 cases (94.7%) demonstrated some form of non-compliance; superiorly, inferiorly or both. Analysing the 150 superior and 150 inferior data points independently, the most common non-compliance was over-scanning at the kidneys by 4 cm to5 cm (19 cases, ~10% extra DLP) beyond tolerance and over-scanning inferiorly at the pubic symphysis by 1 cm to 2 cm (29 cases, ~6.4% extra DLP). Estimated dose increases of up to 35% to 45% were found when clinical audit results were simulated using a PBU40.

CONCLUSIONS

Over-scanning is a predominant occurrence in CTKUB scans in this department. Reasons for over-scanning weren't investigated. It's anticipated this audit will lead to greater awareness of scan extent compliance and dose ramifications of non-compliance. The usage of more easily identified anatomical landmarks and a follow-up audit is suggested.

A human factors intervention in a hospital - evaluating the outcome of a TeamSTEPPS program in a surgical ward

BACKGROUND

Patient safety in hospitals is being jeopardized, since too many patients experience adverse events. Most of these adverse events arise from human factors, such as inefficient teamwork and communication failures, and the incidence of adverse events is greatest in the surgical area. Previous research has shown the effect of team training on patient safety culture and on different areas of teamwork. Limited research has investigated teamwork in surgical wards. The aim of this study was to evaluate the professional and organizational outcomes of a team training intervention among healthcare professionals in a surgical ward after 6 and 12 months. Systems Engineering Initiative for Patient Safety 2.0 was used as a conceptual framework for the study.

METHODS

This study had a pre-post design with measurements at baseline and after 6 and 12 months of intervention. The intervention was conducted in a urology and gastrointestinal surgery ward in Norway, and the study site was selected based on convenience and the leaders' willingness to participate in the project. Survey data from healthcare professionals were used to evaluate the intervention. The organizational outcomes were measured by the unit-based sections of the Hospital Survey of Patient Safety Culture Questionnaire, and professional outcomes were measured by the TeamSTEPPS Teamwork Perceptions Questionnaire and the Collaboration and Satisfaction about Care Decisions in Teams Questionnaire. A paired t-test, a Wilcoxon signed-rank test, a generalized linear mixed model and linear regression analysis were used to analyze the data.

RESULTS

After 6 months, improvements were found in organizational outcomes in two patient safety dimensions. After 12 months, improvements were found in both organizational and professional outcomes, and these improvements occurred in three patient safety culture dimensions and in three teamwork dimensions. Furthermore, the results showed that one of the significant improved teamwork dimensions "Mutual Support" was associated with the Patient Safety Grade, after 12 months of intervention.

CONCLUSION

These results demonstrate that the team training program had effect after 12 months of intervention. Future studies with larger sample sizes and stronger study designs are necessary to examine the causal effect of a team training intervention in this context.

TRIAL REGISTRATION NUMBER

ISRCTN13997367 (retrospectively registered).

Building a Taxonomy to Understand Health Care Worker's Response to Workplace 'Pressure' in Complex, Volatile and Emergency Situations

This research aims to better understand performance under pressure as experienced by health and emergency staff in the workplace. Three basic questions underpin the work: (1) how do health and emergency workers experience and make sense of the 'pressures' entailed in their jobs? (2) What impacts do these pressures have on their working lives and work performance, both positively and negatively? (3) Can we develop a useful explanatory model for 'working under pressure' in complex, volatile and emergency situations? The present article addresses the first question regarding the nature of pressure; a subsequent article will address the question of its impact on performance. Using detailed interviews with workers in a range of roles and from diverse settings across Ecuador, our analysis aims to better understand the genesis of pressure, how people respond to it and to gain insights into managing it more effectively, especially with a view to reducing workplace errors and staff burnout. Rather than imposing preformulated definitions of either 'pressure' or 'performance', we took an emic approach to gain a fresh understanding of how workers themselves experience, describe and make sense of workplace pressure. This article catalogues a wide range of pressures as experienced by our participants and maps relationships between them. We argue that while individuals are often held responsible for workplace errors, both 'pressure' and 'performance' are multifactorial, involving individuals, teams, case complexity, expertise and organizational systems and these must be considered in order to gain better understandings of performing under pressure.

Exploring nurses' perception of taking care of patients with coronavirus disease (COVID-19): A qualitative study

Aim

Healthcare staff, especially nurses, who are in the frontline of caring of patients with COVID-19 have valuable experiences about taking care of these patients. Therefore, the aim of this study was exploring nurses' perception of taking care of patients with COVID-19.

Design

This qualitative study was performed using the conventional content analysis method.

Methods

13 nurses who were taking care of patients with COVID-19 were selected using purposeful sampling in the Lorestan University of Medical Sciences. The data were collected through telephone interviews and analysed based on the Lundman and Graneheim's approach.

Results

Qualitative analysis of the data revealed 3 sub-categories, 8 categories and 3 main categories including care erosion, nursing professional growth and necessities.

Relevance to clinical practice

Improve the work situation of the nurses during care of COVID-19 patients, which can directly or indirectly improve the quality of care of these patients.

Enhancing Healthcare Decision-Making Process: Findings from Orthopaedic Field

In the healthcare field, the decision-making process is part of the broad spectrum of “clinical reasoning”, which is recognised as the whole process by which a physician decides about patients’ treatments and cares. Several clinicians’ intrinsic variables lead to this decisional path. Little is known about the inference of these variables in triggering biases in decisions about the post-discharge period in the surgical field. Accordingly, this research aims to understand if and how cognitive biases can affect orthopaedists in decision-making regarding the follow-up after knee and hip arthroplasty. To achieve this goal, an interview-based explorative case study was run. Three key-decisional orthopaedic surgeons were interviewed through a quality control tool aimed at monitoring the causes and effects of cognitive distortions. Coherently with the literature, eight biases come to light. All the interviewees agree on the presence of four common biases in orthopaedic surgery (Affect heuristic, Anchoring, Halo effect, Saliency). The other biases (Groupthink, Availability, Overconfidence, Confirmation), instead, depending on specific physicians’ intrinsic variables; namely: (i) working experience; (ii) working context. This finding contributes to the debate about the application of cognitive tools as leverage for improving the quality of clinical decision-making process and, indirectly, enhancing better healthcare outcomes.

Reducing medical error during a pandemic

On 30 January 2020, the WHO declared the coronavirus disease 2019 (COVID-19) a public health emergency of international concern. By 11 March 2020, it was designated a pandemic owing to its rapid worldwide spread. In this short article we provide some information that might be useful and help equip colleagues to reduce medical error during a pandemic.

We advocate a systems-based approach, rather than an individual’s sole responsibility, and, look at ways to provide safer healthcare.

Person- and job-specific factors of intuitive decision-making in clinical practice: results of a sample survey among Hungarian physicians and nurses

Objective: To assess the prevalence of intuitive decision-making (IDM) among health care practitioners (HCPs) and explore its person- and job-specific factors. Design and Outcome Measures: We used on-line survey data from a cross-sectional sample of Hungarian physicians and nurses (N = 460) to assess their reliance on IDM. In a second survey we asked physicians (N = 104) to rate medical specialties on dimensions of 'emergency' (necessity of making instantaneous decisions in unforeseeable situations) and 'complexity' (necessity of considering multiple perceptual and diagnostic aspects of patients' health condition along with diverse treatment options). Results: Altogether 40% of participants reported ever relying on IDM. Using logistic regression analysis, we found the estimated probability of IDM was 0.24 greater for physicians than for nurses, 0.10 greater for females than for males, and 0.11 greater for advanced level HCPs than for novices. Reaching expert level further increased (by 0.31) the probability of IDM for physicians, but not for nurses. Concerning physicians, practicing in a medical specialty of 'high likelihood of emergency' or 'high complexity' increased the probability of IDM by 0.25 and 0.23; the same effects for nurses were 0.20 and 0.07. We found some (inconclusive) evidence for education positively influencing HCPs' propensity for IDM. Additionally, we performed content analysis of participants' free-text answers to explore the psychological background of IDM instances. HCPs educated in the subject of IDM were found more disposed to perform or request further medical investigation, less prone to deviate from medical protocols, apter to reflect on their mental processes, and more inclined to rely on a large scope of information for their decisions. Conclusions: The associations between job- and person-specific factors and HCPs' propensity for IDM may have implications for their training and allocation in the health care system. Education has great potential for enhancing the quality of IDM in clinical practice.

Self-valuation: Attending to the Most Important Instrument in the Practice of Medicine

OBJECTIVE

To measure self-valuation, involving constructive prioritization of personal well-being and a growth mindset perspective that seeks to learn and improve as the primary response to errors, in physicians and evaluate its relationship with burnout and sleep-related impairment.

METHODS

We analyzed cross-sectional survey data collected between July 1, 2016, and October 31, 2017, from 5 academic medical centers in the United States. All faculty and medical-staff physicians at participating organizations were invited to participate. The self-valuation scale included 4 items measured on a 5-point (0-4) Likert scale (summative score range, 0-16). The self-valuation scale was developed and pilot tested in a sample of 250 physicians before inclusion in the multisite wellness survey, which also included validated measures of burnout and sleep-related impairment.

RESULTS

Of the 6189 physicians invited to participate, 3899 responded (response rate, 63.0%). Each 1-point score increase in self-valuation was associated with -1.10 point lower burnout score (95% CI, -1.16 to -1.05; standardized β=-0.53; P<.001) and 0.81 point lower sleep-related impairment score (95% CI, -0.85 to -0.76; standardized β=-0.47; P<.001), adjusting for sex and medical specialty. Women had lower self-valuation (Cohen d=0.30) and higher burnout (Cohen d=0.22) than men. Lower self-valuation scores in women accounted for most of the sex difference in burnout.

CONCLUSION

Low self-valuation among physicians is associated with burnout and sleep-related impairment. Further research is warranted to develop and test interventions that increase self-valuation as a mechanism to improve physician well-being.

CADDIE2-evaluation of a clinical decision-support system for early detection of systemic inflammatory response syndrome in paediatric intensive care: study protocol for a diagnostic study

INTRODUCTION

Systemic inflammatory response syndrome (SIRS) is one of the most critical indicators determining the clinical outcome of paediatric intensive care patients. Clinical decision support systems (CDSS) can be designed to support clinicians in detection and treatment. However, the use of such systems is highly discussed as they are often associated with accuracy problems and 'alert fatigue'. We designed a CDSS for detection of paediatric SIRS and hypothesise that a high diagnostic accuracy together with an adequate alerting will accelerate the use. Our study will (1) determine the diagnostic accuracy of the CDSS compared with gold standard decisions created by two blinded, experienced paediatricians, and (2) compare the system's diagnostic accuracy with that of routine clinical care decisions compared with the same gold standard.

METHODS AND ANALYSIS

CADDIE2 is a prospective diagnostic accuracy study taking place at the Department of Pediatric Cardiology and Intensive Care Medicine at the Hannover Medical School; it represents the second step towards our vision of cross-institutional and data-driven decision-support for intensive care environments (CADDIE). The study comprises (1) recruitment of up to 300 patients (start date 1 August 2018), (2) creation of gold standard decisions (start date 1 May 2019), (3) routine SIRS assessments by physicians (starts with recruitment), (4) SIRS assessments by a CDSS (start date 1 May 2019), and (5) statistical analysis with a modified approach for determining sensitivity and specificity and comparing the accuracy results of the different diagnostic approaches (planned start date 1 July 2019).

ETHICS AND DISSEMINATION

Ethics approval was obtained at the study centre (Ethics Committee of Hannover Medical School). Results of the main study will be communicated via publication in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT03661450; Pre-results.

Fast and slow thinking; and the problem of conflating clinical reasoning and ethical deliberation in acute decision-making

Expertise in a medical specialty requires countless hours of learning and practice and a combination of neural plasticity and contextual case experience resulting in advanced gestalt clinical reasoning. This holistic thinking assimilates complex segmented information and is advantageous for timely clinical decision-making in the emergency department and paediatric or neonatal intensive care units. However, the same agile reasoning that is essential acutely may be at odds with the slow deliberative thought required for ethical reasoning and weighing the probability of patient morbidity. Recent studies suggest that inadequate ethical decision-making results in increased morbidity for patients and that clinical ethics consultation may reduce the inappropriate use of life-sustaining treatment. Behavioural psychology research suggests there are two systems of thinking - fast and slow - that control our thoughts and therefore our actions. The problem for experienced clinicians is that fast thinking, which is instinctual and reflexive, is particularly vulnerable to experiential biases or assumptions. While it has significant utility for clinical reasoning when timely life and death decisions are crucial, I contend it may simultaneously undermine the deliberative slow thought required for ethical reasoning to determine appropriate therapeutic interventions that reduce future patient morbidity. Whilst health-care providers generally make excellent therapeutic choices leading to good outcomes, a type of substitutive thinking that conflates clinical reasoning and ethical deliberation in acute decision-making may impinge on therapeutic relationships, have adverse effects on patient outcomes and inflict lifelong burdens on some children and their families.

Collaboration and Satisfaction About Care Decisions in Team questionnaire-Psychometric testing of the Norwegian version, and hospital healthcare personnel perceptions across hospital units

AIM

To translate "The Collaboration and Satisfaction About Care Decisions in Team" questionnaire (CSACD-T) into Norwegian and test it for psychometric properties. The further aim was to describe and compare healthcare personnel's collaboration and satisfaction about team decision-making (TDM) across hospital units.

DESIGN

A cross-sectional study.

METHODS

The questionnaire was translated into Norwegian. A total of 247 healthcare personnel at two hospitals responded to the questionnaire. An explorative factor analysis was performed to test the factor structure of the questionnaire, while a Cronbach's alpha analysis was used to test for internal consistency. A one-way ANOVA analysis and a Kruskal-Wallis test were applied to test for differences between hospital units.

RESULTS

The results demonstrate that the Norwegian version of the CSACD-T has promising psychometric properties regarding construct validity and internal consistency. The mean score of the CSACD-T was significantly higher in the maternity ward group than in the emergency room group.

An interoperable clinical decision-support system for early detection of SIRS in pediatric intensive care using openEHR

BACKGROUND

Clinical decision-support systems (CDSS) are designed to solve knowledge-intensive tasks for supporting decision-making processes. Although many approaches for designing CDSS have been proposed, due to high implementation costs, as well as the lack of interoperability features, current solutions are not well-established across different institutions. Recently, the use of standardized formalisms for knowledge representation as terminologies as well as the integration of semantically enriched clinical information models, as openEHR Archetypes, and their reuse within CDSS are theoretically considered as key factors for reusable CDSS.

OBJECTIVE

We aim at developing and evaluating an openEHR based approach to achieve interoperability in CDSS by designing and implementing an exemplary system for automated systemic inflammatory response syndrome (SIRS) detection in pediatric intensive care.

METHODS

We designed an interoperable concept, which enables an easy integration of the CDSS across different institutions, by using openEHR Archetypes, terminology bindings and the Archetype Query Language (AQL). The practicability of the approach was tested by (1) implementing a prototype, which is based on an openEHR based data repository of the Hannover Medical School (HaMSTR), and (2) conducting a first pilot study.

RESULTS

We successfully designed and implemented a CDSS with interoperable knowledge bases and interfaces by reusing internationally agreed-upon Archetypes, incorporating LOINC terminology and creating AQL queries, which allowed retrieving dynamic facts in a standardized and unambiguous form. The technical capabilities of the system were evaluated by testing the prototype on 16 randomly selected patients with 129 days of stay, and comparing the results with the assessment of clinical experts (leading to a sensitivity of 1.00, a specificity of 0.94 and a Cohen's kappa of 0.92).

CONCLUSIONS

We found the use of openEHR Archetypes and AQL a feasible approach to bridge the interoperability gap between local infrastructures and CDSS. The designed concept was successfully transferred into a clinically evaluated openEHR based CDSS. To the authors' knowledge, this is the first openEHR based CDSS, which is technically reliable and capable in a real context, and facilitates clinical decision-support for a complex task. Further activities will comprise enrichments of the knowledge base, the reasoning processes and cross-institutional evaluations.