Emergency response team to critically ill medical patients in the Emergency Department
Evaluation of patient characteristics, calling criteria and effect
Thesis for the degree of Philosophia Doctor Stine Engebretsen
Division of Emergencies and Critical Care Emergency Department
Faculty of Medicine Institute of Clinical Medicine
© Stine Engebretsen, 2022
Series of dissertations submitted to the Faculty of Medicine, University of Oslo
ISBN 978-82-8377-971-4
All rights reserved. No part of this publication may be
reproduced or transmitted, in any form or by any means, without permission.
Cover: Hanne Baadsgaard Utigard.
Print production: Reprosentralen, University of Oslo.
III
Table of contents
Acknowledgements ... V Abbreviations ... VII About this thesis ... VIII Summary ... IX Sammendrag ... XI List of papers ... XIII
1. Introduction ... 1
1.1 Historical background ... 2
1.2 Detection of critical illness ... 4
1.2.1 Single-parameter systems (SPSs) ... 4
1.2.2 Early warning scores systems (EWSSs) ... 5
1.3 Response to critical illness... 8
1.3.1 Standard care ... 8
1.3.2 Emergency response team ... 8
1.4 Outcomes of critical illness ... 9
1.5 Current knowledge gaps... 10
2. Aims of study ... 11
3. Material and methods ... 12
3.1 Study setting ... 12
3.1.1 Norway ... 12
3.1.2 Oslo University Hospital Ullevål ... 13
3.1.3 The emergency response team ... 14
3.2 Population and registers ... 15
3.3 Study design ... 16
3.4 Variables ... 18
3.4.1 Patient characteristics variables ... 18
3.4.2 ED management and process variables ... 21
3.4.3 Patient outcome variables ... 23
3.4.4 Study outcome variables ... 23
3.5 Statistical methods ... 24
3.5.1 Analyses of association ... 25
3.5.2 Analyses of prediction... 27
IV
4. Summary of results ... 29
4.1 Paper I ... 29
4.2 Paper II ... 31
4.3 Paper III... 33
5. General discussion ... 36
5.1 Discussion of the main findings ... 36
5.1.1 Patient status, ED management and patient outcome ... 36
5.1.2 Factors associated with ICU admission ... 38
5.1.3 The NEWS2-scale for identification ... 39
5.1.4 NEWS2 cut-offs and the OUH-criteria for identification ... 41
5.1.5 Quality of care, resource use and outcome by team versus standard care ... 43
5.1.6 Overall evaluation ... 45
5.2 Methodological considerations ... 45
5.2.1 Preconception ... 46
5.2.2 Selection bias ... 46
5.2.3 Information bias ... 48
5.2.4 Data quality ... 49
5.2.5 Confounding ... 52
5.2.6 Causality ... 53
5.2.7 Statistical methods ... 55
5.2.8 Validity ... 56
5.3 Ethical considerations ... 57
5.4 Strengths and limitations ... 57
6. Conclusions and implications ... 59
6.1 Conclusions ... 59
6.2 Implications for practice ... 60
6.3 Implications for future research ... 61
7. References ... 63
Appendix (Paper I-III) ... 77
V
Acknowledgements
This study was conducted with data from the Emergency Department at Oslo University Hospital, Ullevål. My gratitude goes to all my colleagues managing the patient group investigated in this study.
They do a tremendous effort in assessing, treating and caring for these patients and their next-of-kin every day. It is a great teamwork! Thank you also to the big group of patients that, without
knowledge, has contributed with data from their medical records.
The conduction of this study was only possible thanks to the head of the Emergency Department, and my leader, Inger Larsen. She has not only granted me the possibility to use 50% of my work time to do this study, but also cheered and supported me along the way. She has numerous times
emphasized how important this work is and how important increased research competency is for the department. A big thank you for that, and for being a great leader and person.
I could not have asked for better supervisors than Rune Rimstad, Stig Tore Bogstrand and Dag Jacobsen. All easy-going, supportive, positive and with good knowledge of the setting and population of the study. All have been involved in all aspects of this work, to which I am grateful.
My main supervisor, Rune, has been available for discussion and advice on short notice throughout the project, often with new perspectives, to which I am truly thankful! In addition, he has a great sense of humor and a perfect amount of compassion, which has made the supervisions something to look forward to. Thank you, Rune!
Stig Tore has patiently helped me through many of the statistical discussions, always calm and with a laughter to accompany his knowledge. Dag is a nestor in acute medicine, and has willingly shared his expertise. Thank you, both, for encouragement and advices.
Thank you also to the Department of Research and Development at Division of Emergencies and Critical Care, Oslo University Hospital. The grant from you allowed me to gradually start this project in 2016, by buying time to write a project plan and applications.
This study would not be possible without the project group initiating the emergency response team for critically ill medical patients. Thank you to this group, and especially the head-physician in the ED at the time, Helle Midtgaard; your enthusiasm spread to all of us.
Thank you to the nurses and medical secretaries who have performed registration in the two registers from which this study retrieved data. A special thanks to Annika Ueland and Bente Løkken for the effort you both have put into the registration.
VI For part of the statistics in paper 2, expert help was needed. Thank you so much to statistician Valeria Vitelli for giving us this help and being a co-author, and also for statistical advice for paper 1.
My closest colleagues at work must also be thanked, helping me keep track of my ‘other’ work, and ensuring a professional and social arena that I love being a part of due to all of you. I hope you know who you are.
My gratitude also goes to my friends, who, in a good way, have distracted me from this study.
Undoubtedly such distractions are needed to keep sane, and I am so happy that this has also been possible, yet in restricted ways, during the last period now with a pandemic. A special thank you to my friend Sasja, who took the time to read the thesis and gave advices on how to optimize the English language.
Last, but not least, thank you to my partner Jann, who has been patient, supportive and interested all the way. Also thank you to the rest of my family, who have supported me in their own ways.
Together you have made me always remember what’s important in life.
Oslo, august 2021 Stine Engebretsen
VII
Abbreviations
ABCDE: Airway, Breathing, Circulation, Disability, Exposure ABG: Arterial blood gas
AUC: Area under the curve CCA: Complete case analysis CCI: Charlson Comorbidity Index CI: Confidence interval
CT: Computed Tomography
ECG: Electrocardiogram
ED: Emergency Department
EWS(S): Early Warning Score (System) GCS: Glasgow Coma Scale
GP: General Practitioner ICU: Intensive Care Unit
LOMT: Limitation of Medical Treatment LOS: Length of Stay
MTS: Manchester Triage System NEWS(2): National Early Warning Score (2)
OR: Odds ratio
OUH(-U): Oslo University Hospital (- Ullevål) RCP: Royal College of Physicians
REC: Regional Committees for Medical and Health Research Ethics ROC: Receiver-operating characteristics curve
RRS: Rapid Response System SPS: Single Parameter System
STEMI: ST-elevation myocardial infarction
VIII
About this thesis
The overall topic of this study is the use of emergency response team for critically ill undifferentiated medical patients in the emergency department (ED). It has been found that critically ill patients may receive suboptimal care in the ED, and that this may impact patient on outcomes such as mortality and morbidity. Despite this, the literature examining the identification and management of these patients in the ED is limited, as is the use of emergency response team. The topic of the study includes characteristics of patients and ED management, comparison of two systems for
identification of critically ill patients and comparison of care by an emergency response team and standard care.
In the introduction the historical background is summarized, followed by an elaboration of identification of critically ill patients and then their management. Outcome-measures are also explored, before knowledge gaps are highlighted.
Triage 1 and 2 patients were selected to participate due to their potential for critical illness. The first received team management, the latter standard care. All were referred to the internal medicine subspecialties. Trauma patients, patients with surgical complaints, patients with cardiac arrest and patients with ST-elevation myocardial infarction (STEMI) were not included. All data were retrieved from two registers, containing mainly ED data from medical records. The register for triage 1 patients was an existing quality register, the register for triage 2 patients was established for the purpose of this study. There was no intervention included in this study, it is observational of nature. The patients were followed from an entry point in the ED to 30 days or discharge later than 30 days.
IX
Summary
Background and aims
Critically ill and injured patients is an increasing group in EDs, and many have prolonged ED stay. This can cause increased ventilator time, hospital length of stay and mortality. Different types of
management have been investigated; targeting the waiting time from intensive care unit (ICU) admission is decided until transfer to ICU takes place. For patients with specific conditions such as trauma, stroke and sepsis, management with emergency response teams starting at patient arrival, have shown promising effect. For critically ill patients with undifferentiated medical conditions, however, such management is scarcely investigated. The overall aim of this study was therefore to evaluate the use of an emergency response team for critically ill undifferentiated medical patients in the ED. This was done by evaluating characteristics of team patients, the team criteria and the effect of team compared to standard care.
Methods
The study was conducted in the ED of Oslo University Hospital Ullevål (OUH-U). Data from two registers were used. These contained data on the two groups of medical patients assumed to have the most urgent conditions; triage 1 and triage 2. The first group received team management, the latter standard care. We investigated characteristics of triage 1 patients, and factors associated with ICU admission. The ability of the existing team criteria and National Early Warning Score 2 (NEWS2) to predict unfavorable outcomes, and their association with these outcomes, were also investigated.
Furthermore, we investigated how team management was associated with quality of care, resource use and patient outcome, compared to standard care.
Results
Triage 1 patients were young and with little somatic comorbidity, and about half had NEWS2 < 7 at arrival. About half received critical care in the ED, and a little more than half needed ICU admission.
One in four was diagnosed with acute poisoning, and mortality rate was low. Factors associated with ICU admission were male gender and lower age, as well as higher NEWS2 at arrival and receiving critical care in the ED.
Neither the existing criteria nor NEWS2 cut-offs predicted the outcomes well. The existing team criteria showed the best association with the outcomes critical care in the ED and mortality. NEWS2 >
4 showed the best association with the outcome ICU admission.
X Compared to standard care, team management showed better association with three of the four outcomes for quality of care. It was also associated with more critical care in the ED and shorter ED stay; two of the outcomes for ED resource use. For patient outcome, team management was associated with ICU admission and mortality.
Conclusions
The findings that many patients were not admitted to ICU and that mortality rate was low, along with the poor ability of both the existing team criteria and NEWS2 to predict unfavorable outcomes, indicates that more research on identification of patients for team management is needed. Until more information is available, the existing criteria can be considered safe to use, due to their association with the outcomes. The findings also suggest that team management provides better quality of care compared to standard care, and that team management better ensures delivery of critical care in the ED and identification of patients needing ICU admission.
XI
Sammendrag
Bakgrunn og formål
I akuttmottak er det et økende antall av pasienter som er kritisk syke og skadde. Mange har lang oppholdstid i akuttmottak før de overflyttes til intensivavdeling, noe som kan ha en negativ påvirkning på for eksempel hvor lenge de må være tilkoblet respirator og på dødelighet. Flere løsninger er testet for å unngå dette. Disse retter seg mot ventetiden for ledig plass på
intensivavdelingen. For alvorlig skadde pasienter og pasienter med hjertestans, hjerneslag eller sepsis har bruk av akutteam vist lovende resultater. Slike akutteam behandler pasienten allerede fra ankomst til akuttmottaket. Bruk av akutteam for kritisk syke pasienter med uavklarte
indremedisinske tilstander er derimot lite utbredt og lite undersøkt. Hovedformålet med denne studien var derfor å undersøke dette nærmere ved å kartlegge kjennetegn ved pasienter som fikk slikt teammottak, ved å evaluere kriteriene for å ta i bruk team, og å undersøke effekt av
teammottak sammenlignet med standard mottak av pasientene.
Metoder
Studien ble gjennomført ved Avdeling for akuttmottak, Oslo Unviseristetssykehus Ullevål. Vi brukte data fra to registre som hadde opplysninger om de antatt mest kritisk syke indremedisinske pasientene; de som hadde hastegrad 1 og 2. Den første gruppen fikk teammottak, den andre fikk standard mottak. Først undersøkte vi kjennetegn ved pasientene som hadde hastegrad 1 og teammottak. Vi analyserte også om det var noen av disse kjennetegnene som gav høyere
sannsynlighet for å bli innlagt på intensivavdeling. Dernest undersøkte vi om de kriteriene vi brukte for å tilkalle teamet kunne predikere eller ga høyre sannsynlighet for om pasientene trengte
akuttmedisinske tiltak i akuttmottaket, innleggelse på intensivavdeling eller om de døde i løpet av 30 dager eller sykehusoppholdet. Vi testet også et skåringssystem for vitale parametre; NEWS2, og om ulike skår av NEWS2 kunne predikere eller ga høyere sannsynlighet for de samme utkommene. Til slutt undersøkte vi om teammottak eller standard mottak gav høyest sannsynlighet for god kvalitet, ressursbruk og ulike pasientutkomme.
Resultater
Pasienter med hastegrad 1 var unge og relativt friske fra før, og omtrent halvparten hadde NEWS2- skår < 7 ved ankomst. Cirka halvparten fikk akuttmedisinske tiltak i akuttmottaket, og litt over halvparten ble innlagt på intensivavdeling. En fjerdedel av pasientene hadde akutt forgiftning, og
XII dødeligheten var lav. Faktorer som ga høyere sannsynlighet for å bli lagt inn på intensivavdeling var å være mann, yngre alder, å ha høyere NEWS2-skår og å få akuttmedisinske tiltak i akuttmottaket.
Hverken de eksisterende team-kriteriene eller ulike NEWS2-skår klarte å predikere utkommene godt.
De eksisterende team-kriteriene ga høyest sannsynlighet for å få akuttmedisinske tiltak i akuttmottak og for død i løpet av 30 dager eller sykehusoppholdet. NEWS2 > 4 ga høyest sannsynlighet for
innleggelse på intensivavdeling.
Teammottak gav høyere sannsynlighet for god kvalitet enn standard mottak. Det gav også høyere sannsynlighet for å få akuttmedisinske tiltak og for kortere oppholdstid i akuttmottaket. Teammottak gav i tillegg høyere sannsynlighet for innleggelse på intensivavdeling og for død i løpet av 30 dager eller sykehusoppholdet.
Konklusjon
Mange pasienter med hastegrad 1 trengte ikke innleggelse på intensivavdeling, og dødeligheten var lav. Dette, sammen med funnet om at både de eksisterende teamkriteriene og ulike NEWS2-skår predikerte utkommene dårlig, tyder på at det trengs mer informasjon om hvordan man best identifiserer pasienter som har nytte av akutteam. Inntil videre kan de eksisterende teamkriteriene brukes, fordi de fanget sannsynligheten for utkommene. Funnene indikerer også at teammottak gir bedre kvalitet enn standard mottak. I tillegg virker det som teammottak bedre enn standard mottak sikrer at pasientene får akuttmedisinske tiltak i akuttmottak, og bedre identifiserer pasienter som trenger innleggelse på intensivavdeling.
XIII
List of papers
Paper I:
Engebretsen S, Bogstrand ST, Jacobsen D, Rimstad R.
Characteristics, management and outcome of critically ill general medical patients in the Emergency Department: An observational study.
International Emergency Nursing. 2021;54:100939. Doi: 10.1016/j.ienj.2020.100939
Paper II:
Engebretsen S, Bogstrand ST, Jacobsen D, Vitelli V, Rimstad R.
NEWS2 versus a single-parameter system to identify critically ill medical patients in the emergency department.
Resuscitation Plus. 2020;3:100020. Doi: 10.1016/j.resplu.2020.100020
Paper III:
Engebretsen S, Bogstrand ST, Jacobsen D, Rimstad R.
Quality of care, resource use and patient outcome by use of emergency response team compared to standard care for critically ill medical patients in the Emergency Department: A retrospective single- center cohort study from Norway.
BMJ Open. 2021;11:e047264. Doi: 10.1136/bmjopen-2020-047264
XIV
1. Introduction
For patients with acute illness or injury the ED is the gateway to specialized treatment in the hospital.
Here they receive initial assessment, diagnostic testing and initial management or resuscitation, before they are transferred to the department that can offer definitive and specialized care.1 Within the group of patients in the ED, there is a specter of acuteness. Most patients do not have life-threatening conditions needing immediate management, and can safely tolerate some waiting in the ED. A small group of patients, however, appear so critically ill or injured that swift management and escalated resource use is necessary to avoid fatal or serious outcomes, if at all possible. Many need admittance to an ICU. These patients are increasing in numbers,2 and possible explanations include increasing rates of sepsis and chronic medical conditions such as diabetes, and an aging population.2
The group of critically ill and injured patients can be divided into two subgroups. One group consists of patients with specific conditions where initial management is standardized, such as severe injuries, cardiac arrest, sepsis, stroke and myocardial infarction. The other group consists of patients who appear critically ill, but have undifferentiated conditions that need more investigation, and initial management is less standardized.3
Over the years it has been acknowledged that critically ill and injured patients could receive suboptimal care in the ED due to prolonged stay, leading to adverse events such as prolonged ventilator time in the ICU, prolonged length of stay (LOS) and increased risk of mortality.4, 5 Different types of strategies have been investigated to improve outcomes, mostly targeting what is
denominated the boarding time; the time spent in the ED from ICU admission is decided until transfer takes place.6 These strategies focus on either ED or hospital solutions, and include medical emergency team, education of ED intensivists, resuscitation care units and different collaborations between ED and ICU. 4-8
For patients with specific conditions, management by specialized emergency response teams have existed and been promoted for several years.9-12 Such team management starts when the patients arrive in the ED, and shows promising effect on outcomes such as time to treatment, mortality and morbidity.13-16 For patients with undifferentiated conditions, however, management by an
emergency response team is scarcely investigated. The use of such a team for critically ill undifferentiated medical patients is therefore the topic of this study.
1
2 Correct identification and management of patients with potentially life-threatening conditions in the ED is imperative in order to allocate resources where they are most needed. Due to little knowledge of management by emergency response teams for undifferentiated medical patients, and the resource-demanding character of such teams, evaluation is necessary. This has also been
acknowledged in other settings than the ED, and a conceptual framework used for rapid response systems (RRS) to evaluate identification and management of deteriorating ward patients can easily be adapted to the current study (figure 1).17, 18
Figure 1. Conceptual framework for RRS and current study.
With this framework as a base, the current study focuses on the detection of, response to and outcomes of critically ill undifferentiated medical patients in the ED. These components will be further explored in the following subchapters, followed by an identification of knowledge gaps. First a brief historical background about EDs will be given.
1.1 Historical background
The first EDs opened after World War 2, as a result of developments in trauma care due to wartime experiences.19 In the 50s and 60s EDs often were casualty rooms, where injured patients could be seen by junior medical staff.20 In the same period EDs in the USA implemented triage; also used in wartime, as a tool for sorting patients due to overflowing of patients compared to capacity.21 In the 60ies there were advances in coronary care, as well as new technologies such as computed tomography (CT) and cardiac monitoring, that facilitated rapid diagnosis.19 Physicians started working full-time in the ED, and specialties in Emergency Medicine were introduced in the USA and the United Kingdom.22 There was a growing understanding that acutely ill and injured patients could be
3 saved if receiving rapid treatment.19 Trauma teams and -systems were established, as were codes or teams for cardiac arrest. In the 70ies emergency nursing specialties also appeared.23
In the 90ies triage was further developed, and five-level triage scales were introduced.21, 24-26 Along with medical development, the EDs evolved further. For many critical conditions the “golden hour”
became an expression of time-critical management that should be initiated within the first hour of hospital arrival. Teams or management guidelines were introduced for conditions like myocardial infarction, stroke and sepsis. Lately many have also implemented early warning score systems (EWSS) to detect patients in deterioration or patients with subtle signs of critical illness.
In Europe, two models of emergency care appeared. One was based on the caregiver coming to the patient, performing resuscitation and then making a disposition, often with delivery directly to the specific hospital department. In the other, the patients came to the hospital for treatment, and were then either discharged or admitted to specific departments.22 The introduction of an Emergency Medicine specialty varied from country to country, and it was acknowledged as a specialty by the European Union in 2011.22
In Norway the ED was initially a place called “the bathroom”, where patients underwent a bath before being admitted to the wards.27 The role of the EDs slowly expanded, and trauma teams and cardiac arrest teams appeared. The introduction of triage first happened around 2004.28 A
comprehensive review by the health authorities in 2007 urged the development forward, as they concluded that patient safety was threatened due to lack of triage and senior personnel.1
Implementation of triage expedited, and plans for a specialty in Emergency Medicine began and were established in 2017.29 Emergency nursing specialization already existed, but the need was also emphasized in the review, resulting in more universities offering the education.
From being a room in the hospital where injured patients could receive help from physicians
normally working elsewhere, EDs internationally and in Norway today are a central part of hospitals.
Patients with a full range of conditions undergo complex assessments, diagnostic procedures and time-critical management,27 often by senior staff specialized in emergency care20. It is acknowledged that some conditions need a quicker response than others, some with a whole team managing the patient. EDs have become the heart of the emergency care system, but due to continuous medical progress, an aging population and patients with more complex complaints, ongoing evaluation and development is imperative.
4
1.2 Detection of critical illness
Before a type of management such as an emergency response team can be offered, it is necessary to identify the patients that would benefit from it; patients who are critically ill.
Several definitions of critical illness exist. One states that it “acutely impairs one or more vital organ systems such that there is a high probability of imminent or life-threatening deterioration in the patient’s condition”30. In Norway, an intensive care patient is defined as a patient with acute life- threatening illness characterized by potentially reversible failure in vital organ systems.31 In both definitions one or more organ systems have to be impaired for the patient to be defined as critically ill or needing intensive care.
Although some patients have unmistaken signs of organ failure and thus critical illness, the
impairment of organ systems can be difficult to affirm when the patient arrives in the ED. This may take some time and involve further diagnostic procedures, assessment of response to interventions and ongoing observation. This could however delay time-critical management, and as a result vital signs are often used as proxies for failure of organ systems.
EDs have traditionally used triage as a tool to sort patients based on clinical urgency at arrival, and most triage systems are based on symptoms or a combination of symptoms and vital signs.32 There has however been concern that triage systems may be provider-dependent,33 and that they do not identify patients who deteriorate later in the ED stay. The later years ED-specific RRS for recognizing and responding to deteriorating ED patients has thus been investigated.34-36
Unlike triage, RRSs for deteriorating ward patients mostly use vital signs as triggers, either single- parameter systems (SPSs) or EWSSs.17 Both are used to identify patient deterioration and trigger escalation of care, with the goal of preventing adverse events.37, 38 The development of both types started over 20 years ago, as a response to research showing preventable deaths and adverse events in deteriorating ward patients.37, 38 These vital sign triggers are explored in the next subchapter.
1.2.1 Single-parameter systems (SPSs)
SPSs typically consist of a set of extreme values of vital signs (e.g. pulse rate < 40 beats per minute) or other physiological parameters (e.g. threatened airway). Presence of one or more of these triggers
5 the response, often an emergency response team.39 The first system was described in 199540, and in the following years numerous systems appeared.38, 39
SPSs are mostly used for admitted adult patients, only a few SPSs seem to have been developed specifically for ED use.35 Validation studies of SPSs are scarce, and few is performed in the ED setting.41 Most studies show that SPSs have low sensitivity or high specificity, or both.38, 42-44 One study found excellent prediction of survival and association with other outcomes, but used summarized scores, similar to an EWSS.41 When comparing SPSs to EWSSs, the latter show better outcomes.39, 45
1.2.2 Early warning scores systems (EWSSs)
EWSSs typically consist of a set of vital signs or other physiological parameters, to which points are allocated to different levels of the vital signs / parameters. The points are then summarized to give a total score which triggers the response. There is often a stepwise escalation as the score gets higher, with an emergency response team as the highest response.46 After what was probably the first EWSS developed in 1997,47 several EWSSs have been developed, targeting hospitalized adult general patients, children or pregnant women37, 48, 49 ED-specific EWSSs also exist, either as part of a triage system, or as a stand-alone EWSS.50-53 One of the most tested and used EWSS today is NEWS.37 NEWS was developed by the Royal College of Physicians (RCP) in 2012, with an update called NEWS2 in 2017.37, 54 It consists of the parameters respiration rate, oxygen saturation, systolic blood pressure, pulse rate, level of consciousness and temperature,54 and the allocation of points are shown in table 1. The RCP recommends that a total score of five or more should trigger urgent assessment by a clinician or team competent in care of acutely ill patients, and that a score of seven or more should trigger emergency assessment by a team competent in critical care including advanced airway management.54 In Norway the use of NEWS was recommended by the Ministry of Health and Care Services through a patient safety campaign from 2014-2018.55
6 Table 1. NEWS2 with allocation of points54
Points 3 2 1 0 1 2 3
RR per minute ≤8 9-11 12-20 21-24 ≥25
SpO2 1 (%) ≤91 92-93 94-95 ≥96
SpO2 2* (%) ≤83 84-85 86-87 88-92 or
≥93 on air
93-94 on O2
95-96 on O2
≥97 on O2
Air/O2 O2 Air
SBP (mmHg) ≤90 91-100 101-110 111-219 ≥220
Pulse per minute ≤40 41-50 51-90 91-110 111-130 ≥131
Consciousness Alert CVPU
Temperature (°C) ≤35.0 35.1-36.0 36.1-38.0 38.1-39.0 ≥39.1
RR: respiration rate, SpO2: oxygen saturation, O2: oxygen, SBP: systolic blood pressure, CVPU: confusion, verbal, pain, unresponsive, *For patients with hypercapnic respiratory failure
Validation studies of NEWS/NEWS2 are numerous, also in the ED setting, finding good performance in different patient groups (table 2). No validation studies target critically ill undifferentiated medical patients in the ED, but some target potential subgroups such as sepsis.
7 Table 2. Overview of NEWS/NEWS2 validation-studies in ED setting
Patient group Outcome Results
Sepsis*56 ICU adm 2d Mortality 30d Combined
Poor prediction ICU adm Acceptable other outcomes Associated with all outcomes Triage 2+3*57 Hospital adm
ICU adm LOS
Mortality 30d
Poor prediction hospital and ICU adm Acceptable mortality at arrival and transfer, excellent at 1h after arrival
Correlation with all outcomes
Sepsis*58 Septic shock diagnosis Excellent prediction, NEWS≥3 optimal cut-off Respiratory
distress*59
Survival 90d Excellent prediction
Decreasing NEWS associated with survival Pneumonia*60 Mortality 30d, 180d, 6years
ICU adm
Empyema, ICU adm or readm 30d
Poor prediction mortality and empyema/read Acceptable ICU adm
Associated with mortality, ICU adm and empyema/readm
Sepsis*61 Mortality in-hospital ICU/MCU adm 2d Combined
Poor prediction mortality > 70y, acceptable <
70y
Acceptable ICU/MCU > 70y, excellent < 70y Admitted
patients*62
Mortality 30d, in-hospital Acceptable prediction mortality Associated with mortality
Sepsis*63 Mortality 10d, 30d Excellent prediction 10d, acceptable 30d Elderly*64 Adm
Mortality in-hospital
Poor prediction adm Acceptable mortality General ED
population*65
Mortality 2d Hospital adm
Deterioration or ICU adm 2d
Excellent prediction mortality 2d Poor other outcomes
Sepsis*66 Severe sepsis Septic shock
Mortality in-hospital, sepsis- related
Excellent prediction mortality in-hospital Outstanding other outcomes
Infection**67 Composite (ICU, mortality or organ dysfunction, 3d) Mortality 30d
Excellent prediction composite outcome cohort A
Acceptable other outcomes Covid-19**68 Severe disease (ICU or death)
Mortality in-hospital
NEWS2 ≥5 acceptable, NEWS2 ≥6 excellent prediction of severe disease
Both acceptable mortality Elderly**69 Mortality 30d
Hospital adm HDU/ICU readm
Acceptable prediction mortality and HDU adm Poor hospital adm and readm
Covid-19**70 Severe outcome (ICU or death) 14d
Poor to acceptable prediction in different cohorts
Covid-19**71 Mortality in-hospital Excellent prediction Covid-19#72 ICU adm 48h, 7d
Mortality 48h, 7d
NEWS2 acceptable prediction all outcomes NEWS acceptable 7d, excellent 48h
ICU: intensive care unit, adm: admission, d: days, readm: readmission, LOS: length of stay, MCU: medical intensive care unit, ED: emergency department, HDU: high dependency unit, *NEWS, **NEWS2, #NEWS + NEWS2
8
1.3 Response to critical illness
The following will focus on management starting at patient arrival, alternatively patient
deterioration, not on specific management in the earlier mentioned boarding time. Two types of management is identified for critically ill patients. The most common seem to be management in a resuscitation area of the ED, without a team alert. This will in the following be denominated
‘standard care’. The other involves alert of and management by an emergency response team.
1.3.1 Standard care
The World Health Organization recommends that the sickest patients, triaged as ‘red’, are cared for in a designated resuscitation area of the ED, with the equipment needed to manage critical illness.
They also recommend staff to be designated and trained in resuscitation.73 ED physicians and nurses care for the patients, sometimes with predefined roles.74 Other physician subspecialty involvement happens after the initial management of the patients, in order to refer the patient to a particular department in the hospital. ED personnel also commonly manage the patients in the boarding time.5 The number of ED personnel involved in this type of management for critically ill medical patients probably varies depending on the clinical status of the patient. Standard care may involve critical care interventions such as intubation, central venous catheter, arterial line, vasopressors, non- invasive ventilation and chest tube.3, 75-77 Management according to an Airway, Breathing,
Circulation, Disability, Exposure (ABCDE) approach is used by some.77 The ED LOS, ICU admission rate and mortality rate of patients vary.3, 75-77
1.3.2 Emergency response team
Emergency response teams are commonly used for patients with trauma, cardiac arrest, STEMI, sepsis and stroke, 9-12, 78 with promising effect on time to treatment, morbidity and mortality.13-16, 79 Other specialized teams, such as respiratory care team and pulmonary embolism team, have also been implemented with good results.80, 81
9 Such teams tend to be multidisciplinary, i.e. involving personnel from different disciplines and
subspecialties in addition to ED personnel, and often there are predefined criteria deciding when to call the team. In addition, predefined management guidelines are common, as are predefined tasks for each team member. Some have common training, often simulation-based. Type and number of personnel in the different teams varies depending on the type of patients they respond to, type of hospital and type of health system.
The literature about team management for critically ill medical patients is scarce, and such
management is thus probably not that common. A study from Denmark showed that only 5 of 16 EDs had such a team, while all had trauma team and cardiac arrest teams.82 Some EDs created ad-hoc teams depending on diagnosis or symptoms.82 Existing literature reveals that the teams investigated are triggered either using locally developed SPSs,83, 84 or by decision of the ED physician.85 Teams are multidisciplinary, and critical care interventions similar to those described for standard care are performed.83, 85 As for standard care patients, ED LOS, ICU admission rate and mortality rate vary.83-85
1.4 Outcomes of critical illness
Outcomes are used to evaluate if what we do is useful for the patients and of good quality. In the field of RRS, use of patient outcomes such as mortality, cardiac arrest and unplanned ICU admission is recommended, with an assumption that they can be prevented.17 This is however not always the case,86 and other outcomes such as goals of care, patient/provider satisfaction and cost are also suggested.17
Already in 1966 Donabedian argued that patient outcomes such as recovery, restoration of function and survival have limits as measures of quality of care.87 He argued that other factors than medical care could influence these outcomes, or that the outcomes could be irrelevant. To investigate quality of care he suggested to also evaluate the process of care and the structure in which the care takes place.87
In emergency medicine several quality indicators have been suggested, in which structure, process and outcome is represented.88-90 Some are general for the whole ED population, and focus on time- processes, such as time to first physician assessment or administration of analgesics.89-91 Others are specific for subgroups of critically ill patients, such as time to CT scan for stroke, and time to
antibiotics for sepsis.
10 The most commonly used patient outcomes in validation studies of SPSs and NEWS/NEWS2 include ICU admission at different time points, cardiac arrest and mortality at different time points (table 2, subchapter 1.2.2).42-45 Also in studies of management, mortality is commonly used,5, 76 along with process outcomes such as ED LOS and time to different interventions in the ED.5, 84
1.5 Current knowledge gaps
In Norway there is a lack of studies investigating characteristics, identification and management of critically ill medical patients in the ED.
Internationally a few single-center studies have investigated characteristics of this patient group, but mostly with small number of participants.3, 75, 76, 83-85
Only one of these investigated association with ICU admission, in a center with restricted ICU bed capacity.76 Another investigated association with 30 day mortality.85 The remaining studies were descriptive in nature.
Several international studies have examined identification of subgroups of patients by use of single- parameter systems or early warning score systems in the ED (table 2, subchapter 1.2.2).45 Some subgroups, e.g. sepsis, could be a part of the group of critically ill medical patients, but no study investigated the latter group as a whole.
Internationally three single-center studies investigating the use of an emergency response team for this patient group were found. Two were descriptive,83, 85 and the third was a practice improvement study.84 The latter was the only one comparing team to standard care, with descriptive analyses of time-processes before and -after. All had a small number of participants.
11
2. Aims of study
The overall aim of this study was to evaluate the use of a multidisciplinary emergency response team for critically ill undifferentiated medical patients in the ED, by investigating patient characteristics, calling criteria and effect.
The objectives were:
1. To investigate the emergency response team patients’ status before the critical illness and at ED arrival, the ED management and the patients’ outcome (paper I)
2. To investigate which parameters were associated with ICU admission for emergency response team patients (paper I)
3. To test the ability of NEWS2 to identify critically ill medical patients for emergency response team (paper II)
4. To compare the ability of different NEWS2 cut-offs and the single parameter system in use to identify critically ill medical patients for emergency response team (paper II)
5. To investigate how management by an emergency response team was associated with ED quality of care, ED resource use and patient outcome, compared to standard care (paper III)
12
3. Material and methods
3.1 Study setting
3.1.1 Norway
In Norway, unlike what is common internationally, the primary care services include emergency services by general practitioners (GPs) during working hours as well as after-hours. After-hours services are offered by on-call GPs or in emergency care centers, and patients self-refer. Hospital emergency care is considered specialized care, and is provided in EDs. Here acute patients are referred by a primary care physician or brought in by ambulance if ambulance personnel consider the complaint to need specialist care.92 Self-referral is rare. Figure 2 gives an overview of pathways to ED care in Norway.
Figure 2. Overview of pathways to ED care in Norway
‘Acute’ is defined by the health authorities as patients needing review in the ED within 24 hours from the first contact with the primary health services.1 Less acute patients or those not needing
specialized care are managed in the primary care system. As a result, Norwegian EDs have fewer patients, but with a higher degree of acuity, than many international EDs, as well as higher admittance rate. The EDs are thus normally not organized in different areas such as resuscitation,
13 monitor, minor and major injury etc; which are common internationally, but consist of resuscitation rooms and/or trauma bays, and standard rooms.
Due to no emergency medicine specialty, the different on-call specialists have traditionally reviewed their own patients in the ED. Which specialist should review each patient is decided when the patients are referred by telephone prior to arrival. In 2017 a specialty in emergency medicine was established also in Norway, and the first specialist was approved in 2019. The specialty is a sub- specialty of internal medicine, and thus different than international specialties.29 Nurses, on the other hand, have been employed in the EDs, and constitute what have been considered ED specific personnel. An emergency nursing specialty has existed for several years.
3.1.2 Oslo University Hospital Ullevål
The study was conducted in the ED of Oslo University Hospital Ullevål (OUH-U), a local hospital for 265 000 inhabitants in Oslo (2018), and a tertiary referral hospital for selected medical services, included trauma. All subspecialties in internal medicine are represented, and the hospital has 213 medical beds, including a Medical Intensive Care Unit with 10 beds and a Coronary Intensive Care Unit with 13 beds. In 2015 the ED saw 28 053 patients, with admittance rate of 90% and a mean LOS of 3.4 hours. Adult medical patients constituted 49% of the admitted patients. The ED is considered a large-volume ED in Norway.
In the study period, 2015-2016, emergency response teams existed for trauma patients, cardiac arrest patients and critically ill children, in addition to critically ill adult medical patients. An emergency response team for patients considered for thrombolysis was implemented in January 2016. A team response with direct pathway to coronary angiography existed for patients with STEMI.
All patients fulfilling criteria for team management were categorized as triage 1, and managed in resuscitation rooms or trauma bays. All other patients were triaged according to the Manchester Triage System (MTS), and managed by on-call subspecialists and ED nurses in standard ED rooms.
These patients received primary nursing care. At the time no emergency medicine specialty existed.
Figure 3 gives an overview of ED management and patient flow.
14 Figure 3. Overview of ED management and patient flow of triage 1 (red arrow) and triage 2-5 (blue arrow) patients. All patients could change pathway throughout the ED stay.
ED: Emergency department, MTS: Manchester Triage System, ABCDE: Airway, Breathing, Circulation, Disability, Exposure, ICU: Intensive care unit
3.1.3 The emergency response team
In 2012 our ED initiated a project aiming at introducing an emergency response team for critically ill medical patients. A working group consisting of representatives from the ED, division of medicine, anesthesiology department, radiology department and laboratory department was established. The project resulted in a proposal for composition of the team and definition of the tasks of each team member, criteria to call the team and a plan for training the team. The proposal was accepted by all stakeholders, and following a period of information and training, the team was implemented in March 2013.
Alongside the implementation process, the working group also recommended to establish a quality register for patients treated by the team, in order to monitor the patient group, quality of care and patient outcome. This register was established in 2016, and started registration of patients admitted from January 2015.
The team managed adult medical patients who meet one or more of the predefined criteria. The team leader was an experienced registrar in internal medicine with easy access to medical ICU beds, and the team consisted of altogether eight persons with predefined tasks. The team criteria,
15 hereafter called the OUH-criteria, and team members are shown in table 3. Management of the patients were done in resuscitation rooms and followed an ABCDE approach.
Table 3. The OUH-criteria and members of emergency response team
OUH-criteria Team members
Threatened airway Respiratory arrest
Respiration rate < 8 or > 40 Oxygen saturation < 85 %
Systolic blood pressure < 90 mmHg Pulse < 35 or > 130
GCS < 9
Persistent/continuous fitting Temperature < 32 °C
Clinical concern by prehospital personnel, ED doctor or ED nurse
Registrar in internal medicine (team leader) Registrar in anesthesiology
ED nurses (3) Nurse anesthetist Phlebotomist Radiographer
If needed supplemented by:
Registrar in cardiology Registrar in neurology Registrar other subspecialty
OUH: Oslo University Hospital, GCS: Glasgow Coma Scale, ED: Emergency Department
3.2 Population and registers
The population consisted of potentially critically ill medical patients. This included triage 1 patients managed by the team, which was the sole population when investigating objective 1 and 2. For objective 3, 4 and 5 triage 2 patients were also included. As seen in figure 3, these patients received what is denominated ‘standard care’ in our ED and in this study, which differ some from what is defined as ‘standard care’ in chapter 1.3.1. They were seen immediately by one or two ED nurses, and within 10 minutes by a registrar in internal medicine. They could be managed in resuscitation rooms or in standard ED rooms, depending on their clinical status. Care was supplemented by additional ED nurses or physicians if needed.
The quality register for team patients included all patients managed by the team, with an exception of patients not holding a Norwegian social security number. At the time it was not technically possible to register these patients in the selected platform of the register; eReg. In the study period this applied to 44 patients.
The register contained data from medical records, including patient characteristics, comorbidity, prehospital status and management, ED status and management and results from selected diagnostic tests performed in the ED. Also administrative data were included, such as data on team activation,
16 LOS, level of care and discharge diagnoses. The register had no data on management after the ED stay. Three nurses with training and myself performed registration.
After application to the board of the register, selected deidentified data on all registered patients from 2015 and 2016 were retrieved (n=1294). The quality register will in the following be referred to as register 1.
For the purpose of this study a register for triage 2 patients was also established. This was an anonymous register, which included every 5th admitted medical patient from 2015 and 2016 (n=1426). Every 5th patient was selected in order to get a spread in time of day and week, and to have a similar number of patients as in register 1 from the study period. The variables in the register were similar to those in register 1, and the register platform was the same. Data was registered by three trained medical secretaries and myself. This register will in the following be referred to as register 2. Triage 2 patients who deteriorated and thus had a team response later in the ED stay were only included in register 1.
3.3 Study design
The study was a historic cohort study, and used data from 2015 and 2016. Medical triage 1 and 2 patients from the two registers were considered to be potentially critically ill, and were eligible for inclusion. Data were retrospective, but followed the patients prospectively from an entry point in the ED until 30 days or hospital discharge later than 30 days. The entry points were start of team
management for triage 1 patients and arrival in the ED for triage 2 patients.
In order to investigate the overall aim and the five objectives, and in line with the theoretical framework presented in chapter 1, three part-studies were performed, resulting in three papers; in the following referred to as paper I - III. In paper I, covering objective 1 and 2, we investigated characteristics of patients managed by the team and factors associated with ICU admission. In paper II, covering objective 3 and 4, we investigated the identification of patients eligible for team
management, by assessing the NEWS2 scale and comparing NEWS2 cut-offs to the OUH-criteria. In paper III, covering objective 5, we investigated quality of care, resource use and patient outcome in management by team versus standard care. Figure 4 gives an overview of the present study by using the earlier mentioned conceptual framework.
17 Figure 4. Overview of present study using the conceptual framework shown in figure 1
OUH: Oslo University Hospital, NEWS2: National Early Warning Score 2, ED: Emergency department, ICU: Intensive care unit
In paper I all patients from register 1 were included. In paper II patients from both registers were included. Patients with incomplete NEWS2 and < 18 years were excluded (n=1124). For the outcome
‘ICU admission’ patients with a Not for ICU order were excluded (n=31), and for ‘mortality’ patients with a Not for ICU and/or Not for resuscitation order were excluded (n=109). In paper III patients from both registers were included. Patients with NEWS2 < 5 or > 10, patients < 18 years and patients missing three or more NEWS2 part-scores were excluded (n=1600). Figure 5 gives an overview of included and excluded patients in the three papers.
18 Figure 5. Flowchart of included and excluded patients
NEWS2: National Early Warnings Score 2, ICU: Intensive Care Unit
3.4 Variables
The variables used in analyses were limited to the ones present in the two registers. Most variables were used in two or all three papers, and can be grouped into variables about patient characteristics, ED management or processes and patient outcomes.
3.4.1 Patient characteristics variables
Patient characteristics are factors describing the patient, such as age, sex, education, ethnicity, family situation, economic status and health status.93 In the following patient characteristic variables are divided into characteristics before the illness, and characteristics or status at ED arrival.
The characteristics before the illness included ‘age’, ‘gender’, comorbidity and ‘living in care home or institution’. ‘Age’ was continuous and ‘gender’ dichotomous. For comorbidity three variables were
19 used; ‘Charlson comorbidity index (CCI)’,94' ‘history of substance abuse’ and ‘psychiatric history’. ‘CCI’
was used as a continuous variable in paper I, and as a categorical variable with categories 0p, 1-2p, 3- 4p and >4p in paper II and III.95 ‘History of substance abuse’ and ‘psychiatric history’ were used as separate dichotomous variables in paper I, and combined into one dichotomous variable in paper II and III. ‘Living in a care home or institution’ was used as a dichotomous variable. All patient
characteristics variables were based on data available at admittance.
The status at ED arrival included ‘seen by doctor prior to arrival’, ‘presenting complaint’, ‘time of day and week at arrival’, ‘OUH-criteria present’, ‘NEWS2’, ‘Glasgow Coma Scale (GCS)’, ‘deranged vital signs’ and ‘blood tests outside of reference range’. ‘Seen by doctor prior to arrival’ was dichotomous, and included primary care physician, ambulance physician or other physician. ‘Presenting complaint’
was text-data, and was grouped into seven categories based on the most frequent complaints (table 4). ‘Time of day and week at arrival’ was categorized into weekday 08-20, weekday 20-08, weekend 08-20 and weekend 20-08. Weekend was defined as between 15:00 Friday and 07:00 Monday.
‘OUH-criteria at arrival’ was used as a dichotomous variable. It included presence of any of
respiration rate < 8 or > 40, oxygen saturation < 85 %, systolic blood pressure < 90 mmHg, pulse < 35 or > 130, GCS < 9 or temperature < 32 at arrival. ‘NEWS2’ was calculated retrospectively based on vital signs at arrival. It was used as a continuous variable and dichotomous with cut-off > 6 in paper I and II. In paper II it was also used with cut-offs > 5, > 4 and > 3. In paper III it was used categorical with the categories 5, 6, 7, 8, 9 and 10p. ‘GCS’ was categorized as 13-15, 9-12 and < 9p. ‘Deranged vital signs’ was a dichotomous variable, and was a combination of ‘OUH-criteria at arrival’ or NEWS 7- 10p or GCS < 15p. The variable ‘blood tests outside of reference range’ was dichotomous. It included any of lactate, creatinine, platelets, white blood cells or bilirubin outside of reference range.
Table 5 gives an overview of patient characteristic variables used in the different papers.
20 Table 4. Categorization of presenting complaint and primary discharge diagnosis
Categories Presenting complaints Primary discharge diagnoses (ICD-10) Cardiac /
circulatory
Arrhythmia/block Myocardial infarction Chest pain
Heart failure
All I-diagnoses except infections R00, R01, R02, R07
Acute poisoning
Intoxication Poisoning
F10-19 T4n-T50 T51-65 Respiratory Asthma/COPD
Pulmonary oedema Pulmonary embolism Shortness of breath
All J-diagnoses except infections R04, R05, R06
Conscious- ness / neurological
Stroke
Decreased / altered consciousness Syncope
Seizures / epilepsy
I60-69 G40-47
Other relevant G-diagnoses Abdominal GI-bleed
Abdominal pain Urology
All K- and N-diagnoses R10-19
R30-39 Infection All types of infection, independent
of site Sepsis
All A- and B-diagnoses J00-22, J40, J44.0, J98.7 G00-09
I01.0-2, I30, I32, I33, I38, I40, I41, I51.4, I52, I77.6, I79.1, I80, I88
K20, K29, K65, K81 L00-08
N30, N41, N45, N70-77
Other Other complaints Other diagnoses
COPD: Chronic obstructive pulmonary disease, GI: gastrointestinal
21 Table 5. Overview of patient characteristic variables used in the papers
Variables Paper I Paper II Paper III
Age X X X
Gender X X X
CCI X X X
History of substance abuse X X X
Psychiatric history X X X
Living in care home or institution X
Seen by doctor before arrival X
Presenting complaint X X X
Time of day and week at arrival X
OUH criteria at arrival X X
NEWS2 at arrival X X X
GCS at arrival X
Deranged vital signs X
Blood tests outside of reference range X
CCI: Charlson Comorbidity Index, OUH: Oslo University Hospital, NEWS2: National Early Warning Score 2, GCS: Glasgow Coma Scale
3.4.2 ED management and process variables
ED management variables are variables describing the management given in the ED, such as different types of interventions. Process variables are variables describing different processes in the ED, such as time-processes describing the time from arrival to different interventions.
ED management variables were ‘team response’, ‘diagnostic interventions’, ‘critical care in the ED’
and’ limitation of medical treatment (LOMT)’. ‘Team response’ was dichotomous, and included patients managed by the team. ‘Diagnostic interventions’ consisted of several specific dichotomous variables in paper I; ‘CT-scan’ (any), ‘ultrasound’ (any), ‘x-ray’ (any), ‘electrocardiogram (ECG)’ and
‘arterial blood gas (ABG)’. In paper III it was both categorical, describing the number of interventions performed; 0, 1, 2, 3, 4, 5 or >5, and dichotomous; ‘> 3 diagnostic interventions’. Interventions included in paper III were ECG, ABG, blood culture, other microbiological investigation, lumbar puncture, chest x-ray, other x-ray, CT of head, other CT, cardiac ultrasound or other ultrasound.
‘Critical care in the ED’ was dichotomous. In paper I it was divided into ‘critical care interventions’
and ‘critical care medications’, both dichotomous. Interventions included any of intubation, other airway interventions, non-invasive ventilation, arterial line, central venous line, pacing, cardioversion,
22 cardiopulmonary resuscitation, pleural catheter or administration of blood products. Medications included any of sedatives, anesthetic agents, antiarrhythmics or vasopressors.96
‘LOMT’ was dichotomous, consisting of any of the following decided in the ED: not for respirator, not for ICU or not for resuscitation. In paper II and III the variables ‘not for ICU’ and ‘not for
resuscitation’ were used as separate variables to exclude patients.
ED process variables included ‘complete set of vital signs’,97 ‘pain assessment documented’,89
‘analgesics given within 20 minutes’98, ‘antibiotics given within 60 minutes if sepsis’,99 and ‘ED LOS’.
‘Complete set of vital signs’ was dichotomous, and included complete documentation of respiration rate, oxygen saturation, pulse, blood pressure, temperature and GCS at arrival.97 ‘Pain assessment documented’ was dichotomous, and included the documentation of pain score. ‘Analgesics given within 20 minutes’ was also dichotomous, and included any analgesics given within 20 minutes of arrival. ‘Antibiotics given within 60 minutes if sepsis’ was dichotomous, and sepsis was defined as having infection as main discharge diagnosis and the presence of ≥ 2 quick Sequential Organ Failure Assessment (qSOFA) score or ≥ 2 Systemic Inflammatory Response Syndrome (SIRS) score at arrival.100
‘ED LOS’ was both continuous and dichotomous in paper I, the latter had cut-off > 3.3 hours made by using the 75th percentile from historical hospital data. In paper III it was dichotomous, the cut off <
180 minutes was made using the 75th percentile of ED LOS data for patients included in the paper.
Table 6 gives an overview of ED management and process variables.
Table 6. Overview of ED management and process variables used in the papers
Variables Paper I Paper II Paper III
Team response X X
Diagnostic interventions X X
Critical care in the ED X X X
LOMT X X X
Complete set of vital signs X
Pain assessment documented X
Analgesics within 20 minutes X
Antibiotics within 60 minutes if sepsis X
ED LOS X X
ED: Emergency Department, LOMT: limitation of medical treatment, LOS: length of stay
23 3.4.3 Patient outcome variables
Patient outcome variables are variables describing the outcome for the patients or the end result.
Traditionally it has included death, disability, dissatisfaction, disease and discomfort. It may also involve factors related to functional status, quality of life and health.101
The variables ‘ICU admission’, ‘ICU LOS’, ‘hospital LOS’, ‘mortality’ and ‘primary discharge diagnosis’
was defined as patient outcome variables. ‘ICU admission’ was dichotomous and included admission to any ICU in the hospital directly from the ED. ‘ICU LOS’ was both continuous and dichotomous. The latter had a cut-off of < 66 hours, made by using the 75th percentile of ICU LOS data for patients included in the paper. ‘Hospital LOS’ was both continuous and dichotomous. In paper I the dichotomous variable had a cut-off of > 167 hours, made using the 75th percentile of LOS from historic hospital data. In paper III the cut-off was < 194 hours, made using the 75th percentile of hospital LOS data for patients included in the paper.
‘Mortality’ was dichotomous and defined as mortality at 30 day or at hospital discharge after 30 days. ‘Primary discharge diagnosis’ was categorical, and based on ICD-10 diagnosis. The categories were made to be as equal as possible to the seven categories for presenting complaint (table 4, subchapter 3.4.1).
Table 7 gives an overview of patient outcome variables.
Table 7. Overview of patient outcome variables used in the papers
Variables Paper I Paper II Paper III
ICU admission X X X
ICU LOS X
Hospital LOS X X
Mortality X X X
Primary discharge diagnosis X X X
ICU: Intensive Care Unit, LOS: Length of stay
3.4.4 Study outcome variables
The study outcome variables were a combination of ED management or process variables and patient outcome variables. The first were included because it is recommended to investigate
24 processes when investigating quality of care,88-90 and to investigate goals of care when investigating outcomes for RRS.17
In paper I only one outcome variable was used; ‘ICU admission’. In paper II three outcome variables were used; ‘mortality’, ‘ICU admission’ and ‘critical care in the ED’. Paper III had 11 outcome
variables, covering the themes ED quality of care, ED resource use and patient outcome. ED quality of care included the variables ‘complete set of vital signs’, ‘pain assessment documented’, ‘analgesics given within 20 minutes’ and ‘antibiotics given within 60 minutes if sepsis’. ED resource use variables included ‘> 3 diagnostic interventions’, ‘critical care in the ED’ and ‘ED LOS < 180 minutes’. Patient outcome variables included ‘ICU admission’, ‘ICU LOS < 66 hours’, ‘hospital LOS < 194 hours’ and
‘mortality’.
Table 8 gives an overview of the outcome variables used in the papers.
Table 8. Overview of study outcome variables used in the papers
Variables Paper I Paper II Paper III
Complete set of vital signs X
Pain assessment documented X
Analgesics within 20 minutes X
Antibiotics within 60 minutes if sepsis X
> 3 diagnostic interventions X
Critical care in the ED X X
ED LOS < 180 minutes X
ICU admission X X X
ICU LOS < 66 hours X
Hospital LOS < 194 hours X
Mortality X X
ED: Emergency Department, LOS: Length of stay, ICU: Intensive care unit
3.5 Statistical methods
Statistical analyses were performed using IBM SPSS version 25.0 for Windows (Armonk, NY, USA) and R software for statistical computing.102 Univariate analyses, analyses of association and analyses of prediction were performed.
25 In univariate analyses categorical variables are presented as number (n) and percentage. Continuous variables are presented as mean with confidence interval (CI) if normally distributed and median with interquartile range if not. Group comparisons were two-sided, and used Chi-square test or exact test for categorical variables and t-test or Mann-Whitney rank sum test for continuous variables.
Comparisons are presented as p-values and p<0.05 was considered statistically significant.
3.5.1 Analyses of association
Due to dichotomous outcome variables and the observational nature of the study, multivariate logistic regression analyses were performed. This allowed investigation of associations and reduction of confounding.
Paper I was explorative in nature, and all factors considered to potentially contribute to the study outcome ‘ICU admission’ were included in the model; ‘age’, ‘gender’, ‘living in care home or institution’, ‘CCI’ (categorical), ‘history of substance abuse’, ‘psychiatric history’, ‘NEWS2’
(continuous), ‘blood tests outside of reference range’, ‘critical care intervention’, ‘critical care medication’ and ‘LOMT-decision’. Two factors showing significant difference between ICU and non- ICU patients in univariate analyses were also included, namely ‘seen by doctor before arrival’ and
‘arriving weekday 20-08’. Forward wald regression was used to arrive at the final model, and data are presented as unadjusted and adjusted odds ratios (ORs) with CIs and p-values.
In paper II and III graphical models were made to get a better overview of the factors potentially influencing the exposure variable and/or outcome variable. Clinical rational was used to build the models. Figure 6 shows one of the graphical models for paper III, the remaining models can be viewed in supplement 1 in paper II and supplement 1 in paper III.
In all models the blue box to the left is the exposure variable. The red arrow is the timeline from exposure to outcome. The outcomes are in the blue boxes to the right. Factors considered to influence exposure and/or outcome; confounders, are in white boxes, and arrows represent the direction of influence. In both papers some of the variables could be outcome variables in one model, and a variable adjusted for; confounder, in another model. The function of these variables depended on the length of the timeline and how far away in time from the ED stay the outcome variable was.
