Dataset Information

Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

ABSTRACT: BACKGROUND AND PURPOSE:The Severity-Based Stroke Triage Algorithm for Emergency Medical Services endorses routing patients with suspected large vessel occlusion acute ischemic strokes directly to endovascular stroke centers (ESCs). We sought to evaluate different specifications of this algorithm within a region. METHODS:We developed a discrete event simulation environment to model patients with suspected stroke transported according to algorithm specifications, which varied by stroke severity screen and permissible additional transport time for routing patients to ESCs. We simulated King County, Washington, and Mecklenburg County, North Carolina, distributing patients geographically into census tracts. Transport time to the nearest hospital and ESC was estimated using traffic-based travel times. We assessed undertriage, overtriage, transport time, and the number-needed-to-route, defined as the number of patients enduring additional transport to route one large vessel occlusion patient to an ESC. RESULTS:Undertriage was higher and overtriage was lower in King County compared with Mecklenburg County for each specification. Overtriage variation was primarily driven by screen (eg, 13%-55% in Mecklenburg County and 10%-40% in King County). Transportation time specifications beyond 20 minutes increased overtriage and decreased undertriage in King County but not Mecklenburg County. A low- versus high-specificity screen routed 3.7× more patients to ESCs. Emergency medical services spent nearly twice the time routing patients to ESCs in King County compared with Mecklenburg County. CONCLUSIONS:Our results demonstrate how discrete event simulation can facilitate informed decision making to optimize emergency medical services stroke severity-based triage algorithms. This is the first step toward developing a mature simulation to predict patient outcomes.

SUBMITTER: Bogle BM

PROVIDER: S-EPMC5639945 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

Bogle Brittany M BM Asimos Andrew W AW Rosamond Wayne D WD

Stroke 20170915 10

<h4>Background and purpose</h4>The Severity-Based Stroke Triage Algorithm for Emergency Medical Services endorses routing patients with suspected large vessel occlusion acute ischemic strokes directly to endovascular stroke centers (ESCs). We sought to evaluate different specifications of this algorithm within a region.<h4>Methods</h4>We developed a discrete event simulation environment to model patients with suspected stroke transported according to algorithm specifications, which varied by str ...[more]

PMID: 28916666

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Project description:OBJECTIVES:It is desirable that public preferences are established and incorporated in emergency healthcare reforms. The aim of this study was to investigate preferences for local versus centralised provision of all emergency medical services (EMS) and explore what individuals think are important considerations for EMS delivery. DESIGN:A discrete choice experiment was conducted. The attributes used in the choice scenarios were: travel time to the hospital, waiting time to be seen, length of stay in the hospital, risks of dying, readmission and opportunity for outpatient care after emergency treatment at a local hospital. SETTING:North East England. PARTICIPANTS:Participants were a randomly sampled general population, aged 16 years or above recruited from Healthwatch Northumberland network database of lay members and from clinical contact with Northumbria Healthcare National Health Service Foundation Trust via Patient Experience Team. PRIMARY AND SECONDARY OUTCOME MEASURES:Analysis used logistic regression modelling techniques to determine the preference of each attribute. Marginal rates of substitution between attributes were estimated to understand the trade-offs individuals were willing to make. RESULTS:Responses were obtained from 148 people (62 completed a web and 86 a postal version). Respondents preferred shorter travel time to hospital, shorter waiting time, fewer number of days in hospital, low risk of death, low risk of readmission and outpatient follow-up care in their local hospital. However, individuals were willing to trade off increased travel time and waiting time for high-quality centralised care. Individuals were willing to travel 9 min more for a 1-day reduction in length of stay in the hospital, 38 min for a 1% reduction in risk of death and 112 min for having outpatient follow-up care at their local hospital. CONCLUSIONS:People value centralised EMS if it provides higher quality care and are willing to travel further and wait longer.

Project description:The emergency medical services (EMS) cover initiatives and services established to provide essential medical assistance in situations of acute illness. Triage-methods for systematic prioritizing of patients according to how urgent patients need care, including triage of requests of acute medical treatment, are adopted in hospitals as well as in the pre-hospital settings. This systematic review searched to identify available research on the effects of validated triage systems for use in the pre-hospital EMS on health outcomes, patient safety, patient satisfaction, user-friendliness, resource use, goal achievement, and the quality on the information exchange between the different settings of the EMS (for example the quality of documentation). The specific research questions were: 1) are pre-hospital triage systems effective, 2) is one triage system more effective than others, and 3) is it effective to use the same triage system in two or more settings of the EMS-chain? We conducted a systematic literature search in nine databases up to June 2012. We searched for systematic reviews (SRs), randomized controlled trials (RCTs), non-randomized controlled trials (non-RCTs), controlled before and after studies (CBAs) and interrupted time series analyses (ITSs). Two persons independently reviewed titles and abstracts, and the same persons read all possibly relevant full text articles and rated the methodological quality where relevant. The literature search identified 11011 unique references. A total of 120 publications were read in full text. None of the identified articles fulfilled our inclusion criteria, thus our question on the effects of pre-hospital triage systems, if one system is better than other systems, and the question on effects of using the same triage system in two or more settings of the EMS, remain unanswered. We conclude that there is an evidence gap regarding the effects of pre-hospital triage systems and the effects of using the same triage system in two or more settings of the EMS. The finding does not mean that pre-hospital triage systems are ineffective, but that we lack knowledge about potential effects. When introducing a new assessment tool in the EMS, it is timely to conduct well-planned studies aimed to assess the effect.

Project description:ObjectivesThis feasibility study aimed to model in silico the current healthcare system for patients triaged to a primary care disposition following a call to National Health Service (NHS) 111 and determine the effect of reconfiguring the healthcare system to ensure a timely primary care service contact.DesignDiscrete event simulation.SettingSingle English NHS 111 call centre in Yorkshire.ParticipantsCallers registered with a Bradford general practitioner who contacted the NHS 111 service in 2021 and were triaged to a primary care disposition.Primary and secondary outcome measuresFace validity of conceptual model. Comparison between real and simulated data for quarterly counts (and 95% CIs) for patient contact with emergency ambulance (999), 111, and primary and secondary care services. Mean difference and 95% CIs in healthcare system usage between simulations and difference in mean proportion of avoidable admissions for callers who presented to an emergency department (ED).ResultsThe simulation of the current system estimated that there would be 39 283 (95% CI 39 237 to 39 328) primary care contacts, 2042 (95% CI 2032 to 2051) 999 calls and 1120 (95% CI 1114 to 1127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean percentage increase of 196.1% (95% CI 192.2% to 199.9%) in primary care contacts, and a mean percentage decrease of 78.0% (95% CI 69.8% to 86.2%) in 999 calls and 88.1% (95% CI 81.7% to 94.5%) in ED attendances. Avoidable ED attendances reduced by a mean of -26 (95% CI -35 to -17).ConclusionIn this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost-effective and acceptable to both patients and primary care clinicians.

Project description:Background. Increasing demand for provision of care to stroke survivors creates challenges for health care planners. A key concern is the optimal alignment of health care resources between provision of acute care, rehabilitation, and among different segments of rehabilitation, including inpatient rehabilitation, early supported discharge (ESD), and outpatient rehabilitation (OPR). We propose a novel application of discrete event simulation (DES) combined with a genetic algorithm (GA) to identify the optimal configuration of rehabilitation that maximizes patient benefits subject to finite health care resources. Design. Our stroke rehabilitation optimal model (sROM) combines DES and GA to identify an optimal solution that minimizes wait time for each segment of rehabilitation by changing care capacity across different segments. sROM is initiated by generating parameters for DES. GA is used to evaluate wait time from DES. If wait time meets specified stopping criteria, the search process stops at a point at which optimal capacity is reached. If not, capacity estimates are updated, and an additional iteration of the DES is run. To parameterize the model, we standardized real-world data from medical records by fitting them into probability distributions. A meta-analysis was conducted to determine the likelihood of stroke survivors flowing across rehabilitation segments. Results. We predict that rehabilitation planners in Alberta, Canada, have the potential to improve services by increasing capacity from 75 to 113 patients per day for ESD and from 101 to 143 patients per day for OPR. Compared with the status quo, optimal capacity would provide ESD to 138 (s = 29.5) more survivors and OPR to 262 (s = 45.5) more annually while having an estimated net annual cost savings of $25.45 (s = 15.02) million. Conclusions. The combination of DES and GA can be used to estimate optimal service capacity.HighlightsWe created a hybrid model combining a genetic algorithm and discrete event simulation to search for the optimal configuration of health care service capacity that maximizes patient outcomes subject to finite health system resources.We applied a probability distribution fitting process to standardize real-world data to probability distributions. The process consists of choosing the distribution type and estimating the parameters of that distribution that best reflects the data. Standardizing real-word data to a best-fitted distribution can increase model generalizability.In an illustrative study of stroke rehabilitation care, resource allocation to stroke rehabilitation services under an optimal configuration allows provision of care to more stroke survivors who need services while reducing wait time.Resources needed to expand rehabilitation services could be reallocated from the savings due to reduced wait time in acute care units. In general, the predicted optimal configuration of stroke rehabilitation services is associated with a net cost savings to the health care system.

Project description:BackgroundThe American College of Surgeons Committee on Trauma sets national targets for the accuracy of field trauma triage at ≥95% sensitivity and ≥65% specificity, yet the cost-effectiveness of realizing these goals is unknown. We evaluated the cost-effectiveness of current field trauma triage practices compared with triage strategies consistent with the national targets.Study designThis was a cost-effectiveness analysis using data from 79,937 injured adults transported by 48 emergency medical services agencies to 105 trauma and nontrauma hospitals in 6 regions of the western United States from 2006 through 2008. Incremental differences in survival, quality-adjusted life years (QALYs), costs, and the incremental cost-effectiveness ratio (costs per QALY gained) were estimated for each triage strategy during a 1-year and lifetime horizon using a decision analytic Markov model. We considered an incremental cost-effectiveness ratio threshold of <$100,000 to be cost-effective.ResultsFor these 6 regions, a high-sensitivity triage strategy consistent with national trauma policy (sensitivity 98.6%, specificity 17.1%) would cost $1,317,333 per QALY gained, and current triage practices (sensitivity 87.2%, specificity 64.0%) cost $88,000 per QALY gained, compared with a moderate sensitivity strategy (sensitivity 71.2%, specificity 66.5%). Refining emergency medical services transport patterns by triage status improved cost-effectiveness. At the trauma-system level, a high-sensitivity triage strategy would save 3.7 additional lives per year at a 1-year cost of $8.78 million, and a moderate sensitivity approach would cost 5.2 additional lives and save $781,616 each year.ConclusionsA high-sensitivity approach to field triage consistent with national trauma policy is not cost-effective. The most cost-effective approach to field triage appears closely tied to triage specificity and adherence to triage-based emergency medical services transport practices.

Project description:OBJECTIVES:This study shows how a networked approach relying on 'real-world' emergency medical services (EMS) records might contribute to tracing frequent users of care services on a regional scale. Their tracing is considered of importance for policy-makers and clinicians, since they represent a considerable workload and use of scarce resources. While existing approaches for data collection on frequent users tend to limit scope to individual or associated care providers, the proposed approach exploits the role of EMS as the network's 'ferryman' overseeing and recording patient calls made to an entire network of care providers. DESIGN:A retrospective study was performed analysing 2012-2017 EMS calls in the province of Drenthe, the Netherlands. Using EMS data, benefits of the networked approach versus existing approaches are assessed by quantifying the number of frequent users and their associated calls for various categories of care providers. Main categories considered are hospitals, nursing homes and EMS. SETTING:EMS in the province of Drenthe, the Netherlands, serving a population of 491?867. PARTICIPANTS:Analyses are based on secondary patient data from EMS records, entailing 212?967 transports and 126?758 patients, over 6 years (2012-2017). RESULTS:Use of the networked approach for analysing calls made to hospitals in Drenthe resulted in a 20% average increase of frequent users traced. Extending the analysis by including hospitals outside Drenthe increased ascertainment by 28%. Extending to all categories of care providers, inside Drenthe, and subsequently, irrespective of their location, resulted in an average increase of 132% and 152% of frequent users identified, respectively. CONCLUSIONS:Many frequent users of care services are network users relying on multiple regional care providers, possibly representing inefficient use of scarce resources. Network users are effectively and efficiently traced by using EMS records offering high coverage of calls made to regional care providers.

Project description:BackgroundIn Sweden, the rapid emergency triage and treatment system (RETTS-A) is used in the pre-hospital setting. With RETTS-A, patients triaged to the lowest level could safely be referred to a lower level of care. The national early warning score (NEWS) has also shown promising results internationally. However, a knowledge gap in optimal triage in the pre-hospital setting persists. This study aimed to evaluate RETTS-A performance, compare RETTS-A with NEWS and NEWS 2, and evaluate the emergency medical service (EMS) nurse's field assessment with the physician's final hospital diagnosis.MethodsA prospective, observational study including patients (≥16 years old) transported to hospital by the Gothenburg EMS in 2016. Three comparisons were made: 1) Combined RETTS-A levels orange and red (high acuity) compared to a predefined reference emergency, 2) RETTS-A high acuity compared to NEWS and NEWS 2 score ≥ 5, and 3) Classification of pre-hospital nurse's field assessment compared to hospital physician's diagnosis. Outcomes of the time-sensitive conditions, mortality and hospitalisation were examined. The statistical tests included Mann-Whitney U test and Fisher's exact test, and several binary classification tests were determined.ResultsOverall, 4465 patients were included (median age 69 years; 52% women). High acuity RETTS-A triage showed a sensitivity of 81% in prediction of the reference patient with a specificity of 64%. Sensitivity in detecting a time-sensitive condition was highest with RETTS-A (73%), compared with NEWS (37%) and NEWS 2 (35%), and specificity was highest with NEWS 2 (83%) when compared with RETTS-A (54%). The negative predictive value was higher in RETTS-A (94%) compared to NEWS (91%) and NEWS 2 (92%). Eleven per cent of the final diagnoses were classified as time-sensitive while the nurse's field assessment was appropriate in 84% of these cases.ConclusionsIn the pre-hospital triage of EMS patients, RETTS-A showed sensitivity that was twice as high as that of both NEWS and NEWS 2 in detecting time-sensitive conditions, at the expense of lower specificity. However, the proportion of correctly classified low risk triaged patients (green/yellow) was higher in RETTS-A. The nurse's field assessment of time-sensitive conditions was appropriate in the majority of cases.

Dataset Information

Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

Publications

Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

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