Public attitudes toward pandemic triage: Evidence from conjoint survey experiments in Switzerland.
ABSTRACT: The question of how to implement medical triages has become highly salient during the COVID-19 pandemic and continues to be actively discussed. It is important to know how members of the general public think about this issue. For one, knowledge about the public's standpoint can help resolve important questions where ethical considerations are by themselves not sufficient, for instance whether the patient's age should matter. It can also help identify if more communication with the public about medical ethics is needed. We study how members of the Swiss public would allocate intensive medical care among COVID-19 patients using data from two original conjoint survey experiments conducted in Switzerland in the context of the first and second pandemic waves in 2020 (N = 1457 & N = 1450). We find that our participants would not base triage decisions on the patient's age. However, they do give much importance to the patient's behavior prior and during illness, discriminate against non-nationals, and assign only a relatively small and inconsistent role to medical considerations. Our findings suggest that there is a need for more communication with the public about the ethics of medical triage.
Project description:BACKGROUND:Replacing traditional surveillance with syndromic surveillance is one of the major interests in public health. However, it is unclear whether the number of influenza patients is associated with the number of telephone triages in Japan. METHODS:This retrospective, observational study was conducted over the six-year period between January 2012 to December 2017. We used the dataset of a telephone triage service in Osaka, Japan and the data on influenza patients published from the Information Center of Infectious Disease in Osaka prefecture. Using a linear regression model, we calculated Spearman's rank-order coefficient and R2 of the regression model to assess the relationship between the number of telephone triages for fever and the number of influenza patients in Osaka. Furthermore, we calculated Spearman's rank-order coefficient and R2 between the predicted weekly number of influenza patients from the linear regression model and the actual weekly number of influenza patients for influenza outbreak season (December-April). RESULTS:There were 465,971 patients with influenza, and the number of telephone triages for fever was 420,928 among 1,065,628 total telephone triages during the study period. Our analysis showed that the Spearman rank-order coefficient was 0.932, and R2 and adjusted R2 were 0.869 and 0.842, respectively. The Spearman rank-order coefficient was 0.923 (P<0.001) and R2 was 0.832 in December-April (P<0.001). CONCLUSION:We revealed a positive relationship in this population between the number of influenza patients and the number of telephone triages for fever.
Project description:<h4>Background</h4>Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional approach-the Emergency Severity Index (ESI).<h4>Methods</h4>Using National Hospital and Ambulatory Medical Care Survey (NHAMCS) ED data, from 2007 through 2015, we identified all adult patients (aged ??18?years). In the randomly sampled training set (70%), using routinely available triage data as predictors (e.g., demographics, triage vital signs, chief complaints, comorbidities), we developed four machine learning models: Lasso regression, random forest, gradient boosted decision tree, and deep neural network. As the reference model, we constructed a logistic regression model using the five-level ESI data. The clinical outcomes were critical care (admission to intensive care unit or in-hospital death) and hospitalization (direct hospital admission or transfer). In the test set (the remaining 30%), we measured the predictive performance, including area under the receiver-operating-characteristics curve (AUC) and net benefit (decision curves) for each model.<h4>Results</h4>Of 135,470 eligible ED visits, 2.1% had critical care outcome and 16.2% had hospitalization outcome. In the critical care outcome prediction, all four machine learning models outperformed the reference model (e.g., AUC, 0.86 [95%CI 0.85-0.87] in the deep neural network vs 0.74 [95%CI 0.72-0.75] in the reference model), with less under-triaged patients in ESI triage levels 3 to 5 (urgent to non-urgent). Likewise, in the hospitalization outcome prediction, all machine learning models outperformed the reference model (e.g., AUC, 0.82 [95%CI 0.82-0.83] in the deep neural network vs 0.69 [95%CI 0.68-0.69] in the reference model) with less over-triages in ESI triage levels 1 to 3 (immediate to urgent). In the decision curve analysis, all machine learning models consistently achieved a greater net benefit-a larger number of appropriate triages considering a trade-off with over-triages-across the range of clinical thresholds.<h4>Conclusions</h4>Compared to the conventional approach, the machine learning models demonstrated a superior performance to predict critical care and hospitalization outcomes. The application of modern machine learning models may enhance clinicians' triage decision making, thereby achieving better clinical care and optimal resource utilization.
Project description:INTRODUCTION:In this observational study, we evaluated time-of-day variation in the incidence of fever that is seen at triage. The observed incidence of fever could change greatly over the day because body temperatures generally rise and fall in a daily cycle, yet fever is identified using a temperature threshold that is unchanging, such as ?38.0° Celsius (C) (?100.4° Fahrenheit [F]). METHODS:We analyzed 93,225 triage temperature measurements from a Boston emergency department (ED) (2009-2012) and 264,617 triage temperature measurements from the National Hospital Ambulatory Medical Care Survey (NHAMCS, 2002-2010), making this the largest study of body temperature since the mid-1800s. Boston data were investigated exploratorily, while NHAMCS was used to corroborate Boston findings and check whether they generalized. NHAMCS results are nationally representative of United States EDs. Analyses focused on adults. RESULTS:In the Boston ED, the proportion of patients with triage temperatures in the fever range (?38.0°C, ?100.4°F) increased 2.5-fold from morning to evening (7:00-8:59 PM vs 7:00-8:59 AM: risk ratio [RR] 2.5, 95% confidence interval [CI], 2.0-3.3). Similar time-of-day changes were observed when investigating alternative definitions of fever: temperatures ?39.0°C (?102.2°F) and ?40.0°C (?104.0°F) increased 2.4- and 3.6-fold from morning to evening (7:00-8:59 PM vs 7:00-8:59 AM: RRs [95% CIs] 2.4 [1.5-4.3] and 3.6 [1.5-17.7], respectively). Analyses of adult NHAMCS patients provided confirmation, showing mostly similar increases for the same fever definitions and times of day (RRs [95% CIs] 1.8 [1.6-2.1], 1.9 [1.4-2.5], and 2.8 [0.8-9.3], respectively), including after adjusting for 12 potential confounders using multivariable regression (adjusted RRs [95% CIs] 1.8 [1.5-2.1], 1.8 [1.3-2.4], and 2.7 [0.8-9.2], respectively), in age-group analyses (18-64 vs 65+ years), and in several sensitivity analyses. The patterns observed for fever mirror the circadian rhythm of body temperature, which reaches its highest and lowest points at similar times. CONCLUSION:Fever incidence is lower at morning triages than at evening triages. High fevers are especially rare at morning triage and may warrant special consideration for this reason. Studies should examine whether fever-causing diseases are missed or underappreciated during mornings, especially for sepsis cases and during screenings for infectious disease outbreaks. The daily cycling of fever incidence may result from the circadian rhythm.
Project description:OBJECTIVE:Mis-triage may have serious consequences for patients in mass casualty incidents (MCI) at sea. The purpose of this study was to assess outcome, reliability and validity of an analogue and a digital recording system for triage of a MCI at sea. METHODS:The study based on a triage exercise conducted with a cross-over-design. Forty-eight volunteers were presented a fictional MCI with 50 cases. The volunteers were randomly assigned to start with the analogue (Group A, starting with the analogue followed by the digital system) or digital system (Group B, starting with the digital followed by the analogue system). Triage score distribution and agreement between the triage methods and a predefined standard were reported. Reliability was analysed using Cronbach's Alpha and Cohen's Kappa. Validity was measured through sensitivity, specificity and predictive value. Treatment, period and carry-over-effects were analysed using a linear mixed-effects model. RESULTS:The number of patients triaged (total: n = 3545) with the analogue system (n = 1914; 79.75%) was significantly higher (p = 0.001) than with the digital system (n = 1631; 67.96%). A trend towards a higher percentage of correct triages with the digital system was observed (p = 0.282). Ratio of under-triage was significantly smaller with the digital system (p = 0.001). Validity measured with Cronbach's Alpha and Cohen's Kappa was higher with the digital system. So was sensitivity (category; green: 80.67%, yellow: 73.24%, red: 83.54%; analogue: green: 93.28%, yellow: 82.36%, red: 94.04%) and specificity of the digital system (green: 78.07%, yellow: 63.75%, red: 66.25%; analogue: green: 85.50%, yellow: 79.88%, red: 91.50%). Comparing the predictive values and accuracy, the digital system showed higher scores than the analogue system. No significant patterns of carry-over-effects were observed. CONCLUSIONS:Significant differences were found for the number of triages comparing the analogue and digital recording system. The digital system has a slightly higher reliability and validity than the analogue triage system.
Project description:The purpose of this study is to compare communication patterns in calls subjected to a malpractice claim with matched controls.In many countries, telephone advice nursing is patients' first contact with healthcare. Telenurses' assessment of callers' symptoms and needs are based on verbal communication only, and problems with over-triage and under-triage have been reported.A total sample of all reported medical errors (n=33) during the period 2003-2010 within Swedish Healthcare Direct was retrieved. Corresponding calls were thereafter identified and collected as sound files from the manager in charge at the respective call centres. For technical reasons, calls from four of the cases were not possible to retrieve. For the present study, matched control calls (n=26) based on the patient's age, gender and main symptom presented by the caller were collected.Male patients were in majority (n=16), and the most common reasons for calling were abdominal pain (n=10) and chest pain (n=5). There were statistically significant differences between the communication in the cases and controls: telenurses used fewer open-ended medical questions (p<0.001) in the cases compared to the control calls; callers provided telenurses with more medical information in the control calls compared to the cases (p=0.001); and telenurses used more facilitation and patient activation activities in the control calls (p=0.034), such as back-channel response (p=0.001), compared to the cases.The present study shows that telenurses in malpractice claimed calls used more closed-ended questioning compared to those in control calls, who used more open-ended questioning and back-channel response, which provided them with richer medical descriptions and more information from the caller. Hence, these communicative techniques are important in addition to solid medical and nursing competence and sound decision aid systems.
Project description:OBJECTIVES:To compare the quality of communication in out-of-hours (OOH) telephone triage conducted by general practitioners (GPs), nurses using a computerised decision support system and physicians with different medical specialities, and to explore the association between communication quality and efficiency, length of call and the accuracy of telephone triage. DESIGN:Natural quasi-experimental cross-sectional study. SETTING:Two Danish OOH services using different telephone triage models: a GP cooperative and the medical helpline 1813. PARTICIPANTS:1294 audio-recorded randomly selected OOH telephone triage calls from 2016 conducted by GPs (n=423), nurses using CDSS (n=430) and physicians with different medical specialities (n=441). MAIN OUTCOME MEASURES:Twenty-four physicians assessed the calls. The panel used a validated assessment tool (Assessment of Quality in Telephone Triage, AQTT) to measure nine aspects of communication, overall perceived communication quality, efficiency and length of call. RESULTS:The risk of poor quality was significantly higher in calls triaged by GPs compared with calls triaged by nurses regarding 'allowing the caller to describe the situation' (GP: 13.5% nurse: 9.8%), 'mastering questioning techniques' (GP: 27.4% nurse: 21.1%), 'summarising' (GP: 33.0% nurse: 21.0%) and 'paying attention to caller's experience' (GP: 25.7% nurse: 17.0%). The risk of poor quality was significantly higher in calls triaged by physicians compared with calls triaged by GPs in five out of nine items. GP calls were significantly shorter (2?min 57?s) than nurse calls (4?min 44?s) and physician calls (4?min 1?s). Undertriaged calls were rated lower than optimally triaged calls for overall quality of communication (p<0.001) and all specific items. CONCLUSIONS:Compared with telephone triage by GPs, the communication quality was higher in calls triaged by nurses and lower in calls triaged by physicians with different medical specialities. However, calls triaged by nurses and physicians were longer and perceived less efficient. Quality of communication was associated with accurate triage.
Project description:Limiting or withdrawing nonbeneficial medical care is considered ethically responsible throughout most of critical care and medical ethics literature. Practically, however, setting limits to treatment is often challenging. We review the literature to identify best practices for using the definition of futility as an anchoring concept to aid the ethical practice of ICU clinicians.<h4>Data sources</h4>Source data were obtained from a PubMed literature review.<h4>Study selection</h4>English language articles were chosen based on relevance to medical futility ethics, end-of-life care in the ICU, or communication and conflict mitigation strategies.<h4>Data extraction</h4>Independent evaluation of selected articles for recurrent content themes as relevant to our clinical case were compared among authors and based on consensus, quantitative and qualitative data from these sources were referenced directly.<h4>Data synthesis</h4>When life-sustaining treatment is unlikely to achieve a meaningful benefit such as symptom improvement, continued care may be discordant with the patient's goals. Institutional and cultural norms, unconscious biases, and difficulty with navigating conflicts all influence how un(comfortable) clinicians feel in setting limits to futile care. Defining futility in light of the patient's goals and values, focusing on outcomes rather than interventions, and being proactive in communication with families are the staples of medically meaningful critical care. Palliative measures should be framed affirmatively, and clinicians should be transparent about the limits of medicine.<h4>Conclusions</h4>Clinicians have an ethical obligation not to provide futile care. To practice accordingly, we must clearly understand the nature and forms of futility. Armed with this understanding, our discussions with family and surrogates in the ICU should fundamentally comprise 1) eliciting the patient's values and goals, 2) communicating which interventions serve those values and goals and which do not, and 3) offering only those interventions whose likely outcomes are in line with said values and goals.
Project description:<h4>Background</h4> Triage is a critical component of prehospital emergency care. Effective triage of patients allows them to receive appropriate care and to judiciously use personnel and hospital resources. In many low-resource settings prehospital triage serves an additional role of determining the level of destination facility. In South Africa, the Western Cape Government innovatively implemented the South African Triage Scale (SATS) in the public Emergency Medical Services (EMS) service in 2012. The prehospital provider perspectives and experiences of using SATS in the field have not been previously studied. <h4>Methods</h4> In this qualitative study, focus group discussions with cohorts of basic, intermediate and advanced life support prehospital providers were conducted and transcribed. A content analysis using an inductive approach was used to code transcripts and identify themes. <h4>Results</h4> 15 EMS providers participated in three focus group discussions. Data saturation was reached and four major themes emerged from the qualitative analysis: Implementation and use of SATS; Effectiveness of SATS; Limitations of the discriminator; and Special EMS considerations. Participants overall felt that SATS was easy to use and allowed improved communication with hospital providers during patient handover. Participants, however, described many clinical cases when their clinical gestalt triaged the patient to a different clinical acuity than generated by SATS. Additionally, they stated many clinical discriminators were too subjective to effectively apply or covered too broad a range of clinical severity (e.g., ingestions). Participants provided examples of how the prehospital environment presents additional challenges to using SATS such as changing patient clinical conditions, transport times and social needs of patients. <h4>Conclusions</h4> Overall, participants felt that SATS was an effective tool in prehospital emergency care. However, they described many clinical scenarios where SATS was in conflict with their own assessment, the clinical care needs of the patient or the available prehospital and hospital resources. Many of the identified challenges to using SATS in the prehospital environment could be improved with small changes to SATS and provider re-training. <h4>Supplementary Information</h4> The online version contains supplementary material available at 10.1186/s12873-021-00522-3.
Project description:<h4>Introduction</h4>Emergency department (ED) overcrowding is a major healthcare problem associated with worse patient outcomes and increased costs. Attempts to reduce ED overcrowding of patients with cardiac complaints have so far focused on in-hospital triage and rapid risk stratification of patients with chest pain at the ED. The Hollands-Midden Acute Regional Triage-Cardiology (HART-c) study aimed to assess the amount of patients left at home in usual ambulance care as compared with the new prehospital triage method. This method combines paramedic assessment and expert cardiologist consultation using live monitoring, hospital data and real-time admission capacity.<h4>Methods and analysis</h4>Patients visited by the emergency medical services (EMS) for cardiac complaints are included. EMS consultation consists of medical history, physical examination and vital signs, and ECG measurements. All data are transferred to a newly developed platform for the triage cardiologist. Prehospital data, in-hospital medical records and real-time admission capacity are evaluated. Then a shared decision is made whether admission is necessary and, if so, which hospital is most appropriate. To evaluate safety, all patients left at home and their general practitioners (GPs) are contacted for 30-day adverse events.<h4>Ethics and dissemination</h4>The study is approved by the LUMC's Medical Ethics Committee. Patients are asked for consent for contacting their GPs. The main results of this trial will be disseminated in one paper.<h4>Discussion</h4>The HART-c study evaluates the efficacy and feasibility of a prehospital triage method that combines prehospital patient assessment and direct consultation of a cardiologist who has access to live-monitored data, hospital data and real-time hospital admission capacity. We expect this triage method to substantially reduce unnecessary ED visits.
Project description:STUDY OBJECTIVES:Incorporating registered nurses (RN-level) into obstructive sleep apnea (OSA) management decisions has the potential to augment the workforce and improve patient access, but the appropriateness of such task-shifting in typical practice is unclear. METHODS:Our medical center piloted a nurse triage program for sleep medicine referrals. Using a sleep specialist-designed decision-making tool, nurses triaged patients referred for initial sleep studies to either home sleep apnea test (HSAT) or in-laboratory polysomnography (PSG). During the first 5 months of the program, specialists reviewed all nurse triages. We compared agreement between specialists and nurses. RESULTS:Of 280 consultations triaged by nurses, nurses deferred management decisions to sleep specialists in 6.1% (n = 17) of cases. Of the remaining 263 cases, there was 88% agreement between nurses and specialists (kappa 0.80, 95% confidence interval 0.74-0.87). In the 8.8% (n = 23) of cases where supervising specialists changed sleep study type, specialists changed from HSAT to PSG in 16 cases and from PSG to HSAT in 7. The most common indication for change in sleep study type was disagreement regarding OSA pretest probability (n = 14 of 23). Specialists changed test instructions in 3.0% (n = 8) of cases, with changes either related to the use of transcutaneous carbon dioxide monitoring (n = 4) or adaptive servo-ventilation (n = 4). CONCLUSIONS:More than 80% of sleep study triages by registered nurses in a supervised setting required no sleep specialist intervention. Future research should focus on how to integrate nurses into the sleep medicine workforce in a manner that maximizes efficiency while preserving or improving patient outcomes.