Reducing uncertainty in triaging mental health presentations: examining triage decision-making

Medical maximization: The effect of personality on triage decision-making

Mass Casualty Incidents (MCIs) rapidly overwhelm the ability of local medical resources to deliver comprehensive and definitive medical care and they have been occurring more frequently in recent decades and affect countries of all socioeconomic backgrounds (Hart et al., 2018). As such, it is important to understand how individuals make such decisions in these events and what factors can hinder or help the process. In this study we focused on the critical role of maximization within MCI triage. Triaging an MCI requires juggling the demand and supply of resources, time, and focus, likely leading to various decisions involving compromise/sacrifice. In a vignette study, hosted on Amazon Mturk (n = 235, Mean age = 38.05, 51.49% self-identified as male), which involved triaging over 100 patients we found that trait differences maximization impacted the willingness to use a "black tag". Furthermore, maximization also impacted how much information an individual needed about the patient before being willing to use a black tag. Overall, this research demonstrates the importance of understanding factors that create individual differences in how people make decisions during MCI events, especially those decisions that involve the use of potentially lifesaving treatments.

Triage Decision-Making in Interdisciplinary Pediatric Chronic Pain Programs

BACKGROUND

Interdisciplinary pediatric chronic pain programs are ideal treatment settings for youth with chronic pain who are complex from a biopsychosocial perspective. There is currently no evidence-based clinical decision support to guide nurses triaging patients to such programs, which increases the risk for haphazard triage decisions.

AIMS

To explore and describe the decision-making practices of and contextual influences on nurses triaging patients to interdisciplinary pediatric chronic pain programs.

DESIGN

A qualitative exploratory descriptive design.

SETTINGS

Interdisciplinary Pediatric Chronic Pain Programs.

PARTICIPANTS/SUBJECTS

In all, 12 nurses across 11 different interdisciplinary pediatric chronic pain programs participated in this study.

METHODS

Individual, semi-structured interviews were conducted, transcribed verbatim, and analyzed using concurrent content analysis, guided by the Cognitive Continuum Theory and the Theoretical Domains Framework.

RESULTS

Findings focused on the complexity of the pediatric chronic pain population and the leading role nurses play in triage without evidence-based guidance. Analysis generated three prominent themes: (1) nurse-led triage determinants; (2) process of triage decision-making; and (3) external influences on triage decision-making.

CONCLUSIONS

Triage decision making in the setting of interdisciplinary pediatric chronic pain programs is complex and often led by nurses. There is a desire amongst nurses to adopt an evidence-based clinical decision support triage tool (CDS), which may streamline the referral and triage process and foster a system whereby patients in highest need for interdisciplinary care are best prioritized.

Competencies Emergency and Mental Health Nurses Need in Triage in Acute Mental Health Care: A Narrative Review

INTRODUCTION

Emergency and mental health nurses are, in many countries, the designated professionals to conduct acute mental health triage. This review aimed to identify competencies these nurses need in major acute health care services such as emergency and accident departments and mental health crisis services for triage for psychiatric patients in crisis.

METHODS

For familiarization and construction of an initial thematic framework, we have searched the databases MEDLINE, CINAHL, Academic Search Premier, and PsycINFO since 1975. For indexing and sorting, the web-based application Rayyan was used to identify relevant studies. ATLAS.ti 22 was used for data extraction, reviewing, summary, and display using labels relevant for our research questions: knowledge, skills, and attitude. For appraisal of the included studies, the Mixed Methods Appraisal Tool and the Scale of the Assessment for Narrative Reviews were used.

RESULTS

Thirty one studies were included and were overall rated as adequate, mostly published since 2000. Competencies needed by nurses in AMHT contain a high level of specialist knowledge (risk assessment, de-escalation, triage tools, psychopathology, law/regulations, care pathways), skills (clinical skills, communication, collaboration, coordinating care), and attitude (nonjudgmental, confidence).

DISCUSSION

Emergency and mental health nurses require a significant amount of competencies beyond basic nursing education in acute mental health triage. Most described competencies pertain both to knowledge and skills. Less is known about attitude. To integrate the several competencies knowledge, skills, and attitude, clinical reasoning is needed to organize chaos in unpredictable and complex patient situations.

Evaluation of the effectiveness of the Australian Mental Health Triage Scale in the emergency department: The case of Turkey

PURPOSE

To examine the effectiveness of the Australian Mental Health Triage Scale(AMHTS) in Turkey.

DESIGN AND METHODS

The study is a methodological and semiexperimental study. It was carried out with 30 emergency service nurses and 378 psychiatric patients at a university hospital. The validity and reliability of the AMHTS were examined.

FINDINGS

The reliability of the AMHTS is good level (Cohen's κ = 0.631, p < 0.05). It is valid for making the patients' waiting time in triage more efficient(p < 0.05), and increases the nurses' ability to determine the treatment acuity.

PRACTICE IMPLICATIONS

It is an important tool that affects the quality of emergency psychiatric care for nurses working in the emergency departments of general hospitals.

Effects of environmental distractors on nurse emergency triage accuracy: a pilot study protocol

Background

The clinical decisions of emergency department triage nurses need to be of the highest accuracy. However, studies have found repeatedly that these nurses over- or underestimate the severity of patient health conditions. This has major consequences for patient safety and patient flow management. Workplace distractors such as noise and task interruptions have been pointed to as factors that might explain this inaccuracy. The use of a serious game reproducing the work environment during triage affords the opportunity to explore the impact of these distractors on nurse emergency triage accuracy, in a safe setting.

Methods/design

A pilot study with a factorial design will be carried out to test the acceptability and feasibility of a serious game developed specifically to simulate the triage process in emergency departments and to explore the primary effects of distractors on nurse emergency triage accuracy. Eighty emergency nurses will be randomized into four groups: three groups exposed to different distractors (A, noise; B, task interruptions; C, noise and task interruptions) and one control group. All nurses will have to complete 20 clinical vignettes within 2 h. For each vignette, a gold standard assessment will be determined by experts. Pre-tests will be conducted with clinicians and certified emergency nurses to evaluate the appeal of the serious game.

Discussion

Study results will inform the design of large-scale investigations and will help identify teaching, training, and research areas that require further development.

The impact of adult trauma triage training on decision-making skills and accuracy of triage decision at emergency departments in Malaysia: A randomized control trial

INTRODUCTION

Patients who visit emergency departments need to undergo a precise assessment to determine their priority and accurate triage category to ensure they receive the right treatment.

AIM

To identify the effect of triage training on the skills and accuracy of triage decisions for adult trauma patients.

METHOD

A randomized controlled trial design was conducted in ten emergency department of public hospitals. A total of 143 registered nurses and medical officer assistants who performed triage roles were recruited for the control group (n = 74) and the intervention group (n = 69). The skill and accuracy of triage decisions were measured two weeks and four weeks after the intervention group were exposed to the intervention.

RESULTS

There was a significant effect on the skill of triage decision-making between the control and the intervention group p < 0.001, η²_partial = 0.31. Concerning the accuracy of triage decisions, the effect was significantly different between the control group and the intervention group p < 0.001, η²_partial = 0.66 across time.

CONCLUSION

The triage training improved the skills of the participants and the accuracy of triage decision-making across time.

Embracement of the person with mental illness at an emergency hospital service: a qualitative research

OBJECTIVES

to understand actions of nurses who care for people person with mental illness at a Referenced Emergency Unit in a university hospital.

METHODS

a qualitative research based on Alfred Schütz's social phenomenology. Data collection was performed between December 2015 and January 2016 through phenomenological interviews with 13 nurses from an Emergency Unit.

RESULTS

nurses embrace according to their previous experiences. They easily identify biological complaints and, when they recognize psychiatric signs and symptoms, refer them to the psychiatrist. They raise doubts about what to do, so they expect to be qualified for such action, believing that a protocol could help as well as they need more time.

FINAL CONSIDERATIONS

the understanding of the lived type of nurse who embraces people with mental distress made possible in this study need recognition for research and interventions that focus on biological, psychic and social dimension articulation at embracement.

Novel technique for reorganisation of opinion order to interval levels for solving several instances representing prioritisation in patients with multiple chronic diseases

CONTEXT

Telemedicine has been increasingly used in healthcare to provide services to patients remotely. However, prioritising patients with multiple chronic diseases (MCDs) in telemedicine environment is challenging because it includes decision-making (DM) with regard to the emergency degree of each chronic disease for every patient.

OBJECTIVE

This paper proposes a novel technique for reorganisation of opinion order to interval levels (TROOIL) to prioritise the patients with MCDs in real-time remote health-monitoring system.

METHODS

The proposed TROOIL technique comprises six steps for prioritisation of patients with MCDs: (1) conversion of actual data into intervals; (2) rule generation; (3) rule ordering; (4) expert rule validation; (5) data reorganisation; and (6) criteria weighting and ranking alternatives within each rule. The secondary dataset of 500 patients from the most relevant study in a remote prioritisation area was adopted. The dataset contains three diseases, namely, chronic heart disease, high blood pressure (BP) and low BP.

RESULTS

The proposed TROOIL is an effective technique for prioritising patients with MCDs. In the objective validation, remarkable differences were recognised among the groups' scores, indicating identical ranking results. In the evaluation of issues within all scenarios, the proposed framework has an advantage of 22.95% over the benchmark framework.

DISCUSSION

Patients with the most severe MCD were treated first on the basis of their highest priority levels. The treatment for patients with less severe cases was delayed more than that for other patients.

CONCLUSIONS

The proposed TROOIL technique can deal with multiple DM problems in prioritisation of patients with MCDs.

Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure

Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. Through major advancements in technology, particularly in wireless networking, cloud computing and data storage, RHMS is becoming a feasible aspect of modern medicine. RHMS for the prioritisation of patients with multiple chronic diseases (MCDs) plays an important role in sustainably providing high-quality healthcare services. Further investigations are required to highlight the limitations of the prioritisation of patients with MCDs over a telemedicine environment. This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decision-making theory to address the current problems in the prioritisation of patients with MCDs.

Factors influencing clinical decision making used by mental health nurses to provide provisional diagnosis: A scoping review

Medical diagnosis has traditionally been the role of medical officers. However, mental health nurses working in crisis/emergency settings within Australia are expected to provide a provisional diagnosis postassessment of a consumer. There is limited literature and understanding how mental health nurses develop a provisional diagnosis. In this scoping review, we aimed to first identify and describe the clinical decision-making processes used by mental health nurses across a variety of clinical settings. Second, we sought to explore the factors influencing mental health nurse's diagnostic practice in a variety of settings. Literature was searched using CINAHL (EBSCOhost), PubMed, and ProQuest. Peer-reviewed literature published between 2007 and 2017 was used for this scoping review. Two major themes were identified: clinical decision making (CDM) in mental health nursing and diagnostic practice in nursing. A combination of clinician, environmental, and patient factors were found to have influenced CDM. Furthermore, mental health nurses rely heavily on tacit knowledge when making clinical decisions. Little is known about the use of diagnostic practice in mental health nursing in Australia; however, the limited literature revealed an overlap between the factors which influence CDM and diagnostic practice, respectively. Further research is needed into the use of diagnostic practice in mental health nursing to develop frameworks to assist with CDM pertaining to application of provisional diagnosis by mental health nurses working in assessment environments.

Care provider allocation on admissions to acute mental health wards: The development and validation of the Admission Team Score List

Currently, support tools are lacking to prioritize steps in the care coordination process to enable safe practice and effective clinical pathways in the first phase of acute psychiatric admissions. This study describes the development, validity, and reliability of an acute care coordination support tool, the Admission Team Score List (ATSL). The ATSL assists in care provider allocation during admissions. Face validity and feasibility of the ATSL were tested in 77 acute admissions. Endscores of filled out ATSL's were translated to recommended team compositions. These ATSL team (ATSL-T) compositions were compared to the actually present team (AP-T) and the most preferred team (MP-T) composition in hindsight. Consistency between the ATSL-T and the MP-T was substantial; K_w  = 0.70, P < 0.001, 95% CI [0.55-0.84]. The consistency between the ATSL-T and AP-T was moderate; K_w  = 0.43, P < 0.001, 95% CI [0.23-0.62]. The ATSL has an adequate (inter-rater) reliability; ICC = 0.90, P < 0.001, 95% CI [0.65-0.91]. The ATSL study is an important step to promote safety and efficient care based on care provider allocation, for service users experiencing an acute admission. The ATSL may stimulate structured clinical decision-making during the hectic process around acute psychiatric admissions.

Factors influencing health practitioners' cognitive processing and decision-making style

Successful interventions, healthcare planning, and patient-centered care require explanation, justification, and collaboration through interprofessional clinical decision-making (CDM). Understanding health practitioners' decision-making styles and influencing factors can enhance CDM capabilities. Health professionals and students (N = 229) completed an online survey on their decision-making styles, interprofessional education, interprofessional practice, discipline education, clinical experience, processing styles, personality, interpersonal motivational factors, and age. To assess the influence of task structure, participants answered CDM questions on a high- and a low-structured case study. Age demonstrated an effect on the level of clinical experience, while clinical experience also mediated the effect of age on rational processing styles. While personality results were mixed, consistent with previous findings, conscientiousness predicted rational processing style. Effects of interpersonal motivation on personality were also mixed, insofar as results indicated an association between conscientiousness and both experiential and rational processing styles. Interpersonal motivation also predicted rational processing styles. The complexity of CDM and factors influencing healthcare practitioners' processing and decision-making styles was highlighted. To optimize CDM processes by addressing errors and biases, CDM, and practice complexity, healthcare practitioner education should include theory-driven CDM orientation frameworks.

Embracing the wild profusion: A Foucauldian analysis of the impact of healthcare standardization on nursing knowledge and practice

Standardization has emerged as the dominant principle guiding the organization and provision of healthcare, with standards resultantly shaping how nurses conceptualize and deliver patient care. Standardization has been critiqued as homogenizing diverse patient experiences and diminishing nurses' skills and critical thinking; however, there has been limited examination of the philosophical implications of standardization for nursing knowledge and practice. In this manuscript, I draw on Foucault's philosophy of order and categorization to inform an analysis of the consequences of healthcare standardization for the profession of nursing. I utilize three exemplars to illustrate the impact of the primacy of standardized thinking and practices on nurses, patients and families: pain assessments using the 0-10 pain scale; patient triage emergency departments through the Canadian Triage and Acuity Scale; and determination of cause of death within the context of the current opioid crisis. Through each exemplar, I demonstrate that standardization reductively constrains nursing knowledge and the health and healthcare experiences of patients and populations. I argue that the centrality of standardization must be re-envisioned to embrace the complexity of health and more effectively and meaningfully frame nursing knowledge and practice within healthcare systems.

Sociodemographic Influences of Emergency Department Care for Anxiety Disorders

This study examines variations in content of care for anxiety-related emergency department (ED) visits in the USA across various sociodemographic strata. The 2009-2012 National Hospital Ambulatory Medical Care Survey was used to identify all visits to general hospital EDs in which an anxiety diagnosis was recorded (n = 1930). Content and equitability of care was assessed utilizing logistic regression models. There were an estimated 1,856,000 ED visits with anxiety-related discharge diagnoses in the USA annually. Content of care and disposition varied by age, race/ethnicity, and insurance status. Visits by Medicaid patients were more likely than visits by privately insured patients to include a toxicology screen (OR = 1.67, p < .05) and visits by patients with either Medicaid or Medicare were less likely to include an EKG (OR = 0.53, p < .05 and OR = 0.52, p < .05, respectively). Understanding variations in ED care for anxiety can identify opportunities for intervention, both in the ED and upstream in appropriate healthcare settings.

Based Real Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related "Big Data" Using Body Sensors information and Communication Technology

The growing worldwide population has increased the need for technologies, computerised software algorithms and smart devices that can monitor and assist patients anytime and anywhere and thus enable them to lead independent lives. The real-time remote monitoring of patients is an important issue in telemedicine. In the provision of healthcare services, patient prioritisation poses a significant challenge because of the complex decision-making process it involves when patients are considered 'big data'. To our knowledge, no study has highlighted the link between 'big data' characteristics and real-time remote healthcare monitoring in the patient prioritisation process, as well as the inherent challenges involved. Thus, we present comprehensive insights into the elements of big data characteristics according to the six 'Vs': volume, velocity, variety, veracity, value and variability. Each of these elements is presented and connected to a related part in the study of the connection between patient prioritisation and real-time remote healthcare monitoring systems. Then, we determine the weak points and recommend solutions as potential future work. This study makes the following contributions. (1) The link between big data characteristics and real-time remote healthcare monitoring in the patient prioritisation process is described. (2) The open issues and challenges for big data used in the patient prioritisation process are emphasised. (3) As a recommended solution, decision making using multiple criteria, such as vital signs and chief complaints, is utilised to prioritise the big data of patients with chronic diseases on the basis of the most urgent cases.

Cognitive continuum theory in interprofessional healthcare: A critical analysis

Effective clinical decision making is among the most important skills required by healthcare practitioners. Making sound decisions while working collaboratively in interprofessional healthcare teams is essential for modern healthcare planning, successful interventions, and patient care. The cognitive continuum theory (CCT) is a model of human judgement and decision making aimed at orienting decision-making processes. CCT has the potential to improve both individual health practitioner, and interprofessional team understanding about, and communication of, clinical decision-making processes. Examination of the current application of CCT indicates that this theory could strengthen interprofessional team clinical decision making (CDM). However, further research is needed before extending the use of this theoretical framework to a wider range of interprofessional healthcare team processes. Implications for research, education, practice, and policy are addressed.