Optimizing Triage and Hospitalization in Emergency Patients
Optimizing Triage and Hospitalization in Emergency Patients
Hospital emergency departments (ED) are increasingly overwhelmed by patients with both, urgent and non-urgent problems. This leads to crowded waiting rooms with long waiting times. As a consequence, patients needing care urgently may not be treated in time, whereas patients with non-urgent problems may unnecessarily receive expensive emergency care. Time to effective treatment is one of the most important predictors for outcomes across different medical conditions ("time is cure"), including patients with septicemia, pneumonia, stroke ("time is brain"), myocardial infarction ("time is heart"). For these reasons, a well validated and accurate triage system in the ED is pivotal for an optimal initial triage of medical patients. Moreover, accurate ED triage should not only focus on treatment priority, but also on site-of-care decisions (i.e. outpatient versus inpatient management) and early identification and organization of post-acute care needs.
Different initial triage systems have been proposed including the Manchester triage system (MTS), the Australasian Triage Scale (ATS), the Canadian Triage and Acuity Scale (CTAS) and the Emergency Severity Index (ESI). Among these scores, the MTS is the most widely used score in European and North-American health care settings. The MTS assigns patients to one of 52 flowchart diagrams based on the principal initial presenting complaint. For each of these diagrams red flags are defined based on the clinical presentation and/or vital signs. A triage nurse categorizes patients into different algorithms, and determines treatment priority following a fixed algorithm. Patients are categorized into one of five priority groups (blue, green, yellow, orange, red) with different recommended times for physician assessment (reviewed in Christ et al.).
Only few rigorous clinical studies have investigated the performance of the MTS (and other triage scores) for initial triage decisions. A recent literature review found only four observational studies that have been published today in adult patients with low numbers of included patients (ranging from 50 to 167 patients); although the MTS showed good reliability within these studies, the accuracy of the MTS instrument was suboptimal with only 67% of high risk patients being correctly identified as high priority patients. Thus, there is urgent need for validation in a large, unselected and independent population of medical ED patients and for further refining of the MTS to increase its accuracy. Within the proposed TRIAGE study, we aim to validate the MTS and investigate whether inclusion of vital signs and blood parameters increases its accuracy for both, early identification of high risk patients needing immediate assistance, and patients where delays in initial treatment may not have detrimental consequences.
Initial triage is not only important to assign treatment priorities, but should also assist in estimating the medical risk of patients which influences site-of-care decisions, and post-acute care needs to optimize early planning of post-acute care/nursing support upon hospital admission. This could assist physicians and nurses to make more rational decisions about need for hospital stays and early involvement of social workers to organize the post discharge process ("admission is key to discharge"). For specific diagnoses, such as pneumonia, specific medical risk scores have been developed and are propagated by international guidelines to improve initial site-of-care decisions. Yet, there is need for an overall multi-disciplinary risk assessment system to better predict the risk of unselected medical patients and thus need for in hospital management, as well as post-acute care needs at an early stage of ED admission. Obviously, such a comprehensive triage tool can only be developed in close collaboration within the multi-professional team (physician, nurse, social worker).
A promising tool for the Swiss setting was developed in Geneva to predict post-acute institutional care needs and thus assess biopsychosocial risk of patients. As a scoring system at admission and day 3, the post-acute care discharge (PACD) score facilitates discharge planning. A PACD score of ≥8 points on day 3 of hospitalization was accurate to predict discharge to a post-acute care facility (area under the curve [AUC]: 0.82). Data from our institution showed a significant relation between biopsychosocial risk and discharge to a post-acute care facility. The "Selbstpflegeindex" (SPI) is a simple and commonly used nursing and geriatric tool to assess functional dependence in activities of daily life. A SPI score of <32 points indicates a risk for post-acute care deficit. Nurse led care and nurse led units (NLC and NLU) are defined as institutional settings, typically within acute care hospitals, which provide independent specialized nursing service for post-acute care patients, who need predominantly nursing care. They constitute a possible model of care for patients with low medical yet high nursing risk and are characterized and operationalized by five factors: 1) inpatient environment offering active treatment; 2) case mix based on care needs; 3) nursing leadership of the (multidisciplinary) clinical team; 4) nursing conceptualized as the predominant active therapy; 5) nurses' authority to admit and discharge patients. There are indications that post-acute care patients discharged from NLUs have a better functional status and greater psychological well-being, are more often discharged home than to another institution and less often readmitted to the hospital than patients receiving usual care. There are also indications that these patients are more satisfied with care. Within the proposed TRIAGE study we aim to validate and further improve these nursing/care scores to enable more wide-spread adoption for optimized patient management.
Discharge planning has to begin on admission. We and others have previously investigated the utility of different blood biomarkers for an optimized prognostic assessment in patients presenting to the ED with respiratory infections, sepsis, acute heart failure and myocardial infarction and other important medical conditions. Among different markers, pro-adrenomedullin (proADM) has generated interest as an accurate prognostic marker for adverse outcome with high validity across different medical situations. We also investigated biopsychosocial factors, which influence admission and discharge decision and are thus prerequisites for clinically meaningful site-of-care decision making. Reducing the number of in-hospital days is important not only for cost issues. Hospital-acquired disability is an emerging issue in health care and older, frail medical patients at high risk for allegedly premature referral to a nursing home with consecutive depression and further deterioration of mental and physical independence. To improve hospital management of patients with lower respiratory tract infections, we have developed a biomarker-enhanced clinical risk score (combining the CURB65 score and proADM). The efficacy and safety of this score was recently tested in a randomized controlled trial at the Kantonsspital Aarau. Based on these studies focusing on respiratory infections, we hypothesize that adding clinical parameters and prognostic biomarkers to an established triage risk score, such as the MTS, at the very proximal time point of ED admission, has a substantial and clinically relevant potential to improve its performance and translate into better triage of patients on admission and during hospitalization. This will help to identify both, high risk patients in need of urgent care and inhospital management and low risk patients where longer waiting times have no detrimental consequences and who can potentially be treated in outpatient, NLC, post-acute or nursing home settings.
Importantly, previous efforts to validate and improve current triage scores in unselected patients across different medical diagnoses presenting to the ED were limited by the isolated focus on the ED, a small sample size and/or small spectrum of medical conditions, and observational "hypothesis-generating" designs only. In addition, no study has investigated whether initial measurement of blood biomarkers and/or clinical parameters has the potential to improve patient triage. Thus, a large-scale comprehensive study is warranted to validate previous findings, investigate whether prognostic markers and clinical parameters could improve patient triage from admission to discharge and translate these findings into a new, improved initial triage system for use in routine clinical care throughout the hospital stay. Importantly, we aim to not only focus on medical risk, but also include biopsychological risk scores for post-acute care/nursing needs to enable a more comprehensive assessment of a patient's situation.
Such an enhanced initial patient assessment that supports a clinician's ability to accurately triage and risk stratify patients has the potential to facilitate early and appropriate therapeutic interventions and prevent unnecessary waiting times, improve important initial triage decisions in regard to site-of-care decisions, help recognize and plan post-acute care needs early for immediate social worker involvement, reduce duration of hospital stays and, overall, optimize allocation of health-care resources, and at the same time decrease mortality and morbidity by focusing the medical attention to high risk subjects. As part of an ongoing prospective and large-scale research effort, we plan to later evaluate the efficacy and safety of this new triage algorithm in a second cluster-randomized controlled trial (comparing the new algorithm with an usual care control group).
Background
Hospital emergency departments (ED) are increasingly overwhelmed by patients with both, urgent and non-urgent problems. This leads to crowded waiting rooms with long waiting times. As a consequence, patients needing care urgently may not be treated in time, whereas patients with non-urgent problems may unnecessarily receive expensive emergency care. Time to effective treatment is one of the most important predictors for outcomes across different medical conditions ("time is cure"), including patients with septicemia, pneumonia, stroke ("time is brain"), myocardial infarction ("time is heart"). For these reasons, a well validated and accurate triage system in the ED is pivotal for an optimal initial triage of medical patients. Moreover, accurate ED triage should not only focus on treatment priority, but also on site-of-care decisions (i.e. outpatient versus inpatient management) and early identification and organization of post-acute care needs.
Different initial triage systems have been proposed including the Manchester triage system (MTS), the Australasian Triage Scale (ATS), the Canadian Triage and Acuity Scale (CTAS) and the Emergency Severity Index (ESI). Among these scores, the MTS is the most widely used score in European and North-American health care settings. The MTS assigns patients to one of 52 flowchart diagrams based on the principal initial presenting complaint. For each of these diagrams red flags are defined based on the clinical presentation and/or vital signs. A triage nurse categorizes patients into different algorithms, and determines treatment priority following a fixed algorithm. Patients are categorized into one of five priority groups (blue, green, yellow, orange, red) with different recommended times for physician assessment (reviewed in Christ et al.).
Only few rigorous clinical studies have investigated the performance of the MTS (and other triage scores) for initial triage decisions. A recent literature review found only four observational studies that have been published today in adult patients with low numbers of included patients (ranging from 50 to 167 patients); although the MTS showed good reliability within these studies, the accuracy of the MTS instrument was suboptimal with only 67% of high risk patients being correctly identified as high priority patients. Thus, there is urgent need for validation in a large, unselected and independent population of medical ED patients and for further refining of the MTS to increase its accuracy. Within the proposed TRIAGE study, we aim to validate the MTS and investigate whether inclusion of vital signs and blood parameters increases its accuracy for both, early identification of high risk patients needing immediate assistance, and patients where delays in initial treatment may not have detrimental consequences.
Initial triage is not only important to assign treatment priorities, but should also assist in estimating the medical risk of patients which influences site-of-care decisions, and post-acute care needs to optimize early planning of post-acute care/nursing support upon hospital admission. This could assist physicians and nurses to make more rational decisions about need for hospital stays and early involvement of social workers to organize the post discharge process ("admission is key to discharge"). For specific diagnoses, such as pneumonia, specific medical risk scores have been developed and are propagated by international guidelines to improve initial site-of-care decisions. Yet, there is need for an overall multi-disciplinary risk assessment system to better predict the risk of unselected medical patients and thus need for in hospital management, as well as post-acute care needs at an early stage of ED admission. Obviously, such a comprehensive triage tool can only be developed in close collaboration within the multi-professional team (physician, nurse, social worker).
A promising tool for the Swiss setting was developed in Geneva to predict post-acute institutional care needs and thus assess biopsychosocial risk of patients. As a scoring system at admission and day 3, the post-acute care discharge (PACD) score facilitates discharge planning. A PACD score of ≥8 points on day 3 of hospitalization was accurate to predict discharge to a post-acute care facility (area under the curve [AUC]: 0.82). Data from our institution showed a significant relation between biopsychosocial risk and discharge to a post-acute care facility. The "Selbstpflegeindex" (SPI) is a simple and commonly used nursing and geriatric tool to assess functional dependence in activities of daily life. A SPI score of <32 points indicates a risk for post-acute care deficit. Nurse led care and nurse led units (NLC and NLU) are defined as institutional settings, typically within acute care hospitals, which provide independent specialized nursing service for post-acute care patients, who need predominantly nursing care. They constitute a possible model of care for patients with low medical yet high nursing risk and are characterized and operationalized by five factors: 1) inpatient environment offering active treatment; 2) case mix based on care needs; 3) nursing leadership of the (multidisciplinary) clinical team; 4) nursing conceptualized as the predominant active therapy; 5) nurses' authority to admit and discharge patients. There are indications that post-acute care patients discharged from NLUs have a better functional status and greater psychological well-being, are more often discharged home than to another institution and less often readmitted to the hospital than patients receiving usual care. There are also indications that these patients are more satisfied with care. Within the proposed TRIAGE study we aim to validate and further improve these nursing/care scores to enable more wide-spread adoption for optimized patient management.
Discharge planning has to begin on admission. We and others have previously investigated the utility of different blood biomarkers for an optimized prognostic assessment in patients presenting to the ED with respiratory infections, sepsis, acute heart failure and myocardial infarction and other important medical conditions. Among different markers, pro-adrenomedullin (proADM) has generated interest as an accurate prognostic marker for adverse outcome with high validity across different medical situations. We also investigated biopsychosocial factors, which influence admission and discharge decision and are thus prerequisites for clinically meaningful site-of-care decision making. Reducing the number of in-hospital days is important not only for cost issues. Hospital-acquired disability is an emerging issue in health care and older, frail medical patients at high risk for allegedly premature referral to a nursing home with consecutive depression and further deterioration of mental and physical independence. To improve hospital management of patients with lower respiratory tract infections, we have developed a biomarker-enhanced clinical risk score (combining the CURB65 score and proADM). The efficacy and safety of this score was recently tested in a randomized controlled trial at the Kantonsspital Aarau. Based on these studies focusing on respiratory infections, we hypothesize that adding clinical parameters and prognostic biomarkers to an established triage risk score, such as the MTS, at the very proximal time point of ED admission, has a substantial and clinically relevant potential to improve its performance and translate into better triage of patients on admission and during hospitalization. This will help to identify both, high risk patients in need of urgent care and inhospital management and low risk patients where longer waiting times have no detrimental consequences and who can potentially be treated in outpatient, NLC, post-acute or nursing home settings.
Importantly, previous efforts to validate and improve current triage scores in unselected patients across different medical diagnoses presenting to the ED were limited by the isolated focus on the ED, a small sample size and/or small spectrum of medical conditions, and observational "hypothesis-generating" designs only. In addition, no study has investigated whether initial measurement of blood biomarkers and/or clinical parameters has the potential to improve patient triage. Thus, a large-scale comprehensive study is warranted to validate previous findings, investigate whether prognostic markers and clinical parameters could improve patient triage from admission to discharge and translate these findings into a new, improved initial triage system for use in routine clinical care throughout the hospital stay. Importantly, we aim to not only focus on medical risk, but also include biopsychological risk scores for post-acute care/nursing needs to enable a more comprehensive assessment of a patient's situation.
Such an enhanced initial patient assessment that supports a clinician's ability to accurately triage and risk stratify patients has the potential to facilitate early and appropriate therapeutic interventions and prevent unnecessary waiting times, improve important initial triage decisions in regard to site-of-care decisions, help recognize and plan post-acute care needs early for immediate social worker involvement, reduce duration of hospital stays and, overall, optimize allocation of health-care resources, and at the same time decrease mortality and morbidity by focusing the medical attention to high risk subjects. As part of an ongoing prospective and large-scale research effort, we plan to later evaluate the efficacy and safety of this new triage algorithm in a second cluster-randomized controlled trial (comparing the new algorithm with an usual care control group).
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