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An evaluation of an early warning clinical marker referral tool
Intensive and Critical Care Nursing (2006) 22, 274—282
ORIGINAL ARTICLE
An evaluation of an early warning clinical marker referral tool Anna Louise Green a,∗, Allison Williams b a b
Western Hospital, Gordon Street, Footscray, 3011, Vic., Australia University of Melbourne, Vic., Australia
Accepted 23 April 2006
KEYWORDS Critical Care; Early warning scores; Unplanned ICU admission; Critical Illness mortality
∗
Summary Objectives: The purpose of this study was to evaluate the introduction of a clinical marker tool using a pre- and post-test design in a tertiary university-affiliated hospital. The clinical marker tool was designed to assist in the early identification of unstable patients in the general surgical and medical ward environment based on abnormal vital signs. Methods: A pre- and post-test design of the clinical marker tool was undertaken over a 3-year period. All unstable ward patients who were admitted to the Intensive Care Unit (ICU) from 1 February 2002 to 31 January 2003 (pre- implementation period) and from 1 February 2003 to 31 January 2005 (post-implementation period) were included in the study. A secondary analysis was performed on annual medical emergency calls made to the resuscitation team and mortality from such events from 1 January 2002 to 31 December 2004. Results: Prior to implementing the clinical marker tool, 63 (41.2%) unplanned ICU admissions from the ward had clinical markers present for ≥6 h. Following implementation of the clinical marker tool, 101 (24.5%) patients had clinical markers present for ≥6 h (p = 0.0002). There was no difference in ICU or hospital length of stay or hospital mortality for unplanned admissions to the ICU following implementation of the clinical marker tool. The number of patients found to be still breathing with a pulse on arrival of the resuscitation team was significantly increased from 56 (47.9%) patients to 181 (64.6%) patients post-implementation of the clinical marker tool (p = 0.0024). Additionally, we found an associated increase in survival of this group of patients discharged home from 33 (59%) patients to 136 (75.1%) patients post-implementation of the clinical marker tool (p = 0.0003). Conclusions: The clinical marker tool implemented by an ICU Liaison Team improved the management of patients in the ward environment, including proactive admission of patients to the ICU. Additionally, implementation of the clinical marker tool was
Corresponding author. Tel.: +61 3 8345 6588; fax: +61 3 8345 6336. E-mail address: [email protected] (A.L. Green).
0964-3397/$ — see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.iccn.2006.04.004
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associated with a reduction in the number of cardiac arrests and improvement in hospital mortality for patients experiencing a medical emergency call. The timeframe of instability on the ward prior to the ICU admission may be used as a quality indicator to measure ICU Liaison Team performance. Further research is required to substantiate these findings. © 2006 Elsevier Ltd. All rights reserved.
Introduction Over the last 15 years there has been an increase in the number of intensive care teams providing assessment, advice and treatment for patients in the ward environment (Coad and Haines, 1999; Daly et al., 1998; Green and Edmonds, 2004; Lee et al., 1995). Two distinct teams have become very prominent in the literature and these are the Australian medically led Medical Emergency Teams (MET), and the nurse-led teams known as the Outreach Teams of the United Kingdom (UK). The MET and some of the Outreach Teams use abnormal vital signs (also referred to as clinical markers) to identify ward patients who are deteriorating and may be at risk of suffering a cardiac arrest (Goldhill et al., 1999a; Lee et al., 1995). The significance of abnormal vital signs originated from research that reported clinical deterioration in patients occurring within 8 h prior to cardiac arrest (Schein et al., 1990) and/or admission to the ICU (Goldhill et al., 1999b). The nurse-led Intensive Care Unit (ICU) Liaison Teams in Australia have typically not used abnormal vital signs to trigger a referral to the team but rather to rely on ward staff to determine when assistance is required. A recent trend in Australia has seen the introduction of a collaborative arrangement between the MET and the ICU Liaison Team (Barbetti and Choate, 2003) where the ICU Liaison Team responds to the MET calls. The Outreach Teams that respond to patients with abnormal physiology use a variety of alert systems. The simplest system is where ward nurses are instructed to call the Outreach Team when patients reach one or more abnormal vital signs (Ball et al., 2003). Another system is where ward nurses are instructed to call the registrar and the Outreach Team when two abnormal vital signs are reached (DHMA, 2003). The most complex of these alert systems is the assignment of weighted scores awarded to abnormal vital signs and then calculated to give a total score (Garcea et al., 2004; Odell et al., 2002). The score determines the level of response required ranging from ward staff observing the patient to calling the medical regis-
trar and the Outreach Team (DHMA, 2003; Pittard, 2003). Outcome measures of unplanned ICU admissions, cardiac arrests and hospital mortality rates have all been used in researching the effectiveness of the METs (Bristow et al., 2000; Buist et al., 2002; Hillman et al., 2005; Hourihan et al., 1995; Salamonson et al., 2001). In contrast, the nurse-led teams have used reduction in ICU readmission rates, ICU and ward patient mortality rates as indicators in evaluating their effectiveness (Ball et al., 2003; Garcea et al., 2004; Green and Edmonds, 2004; Leary and Ridley, 2003; Priestley et al., 2004; Russell, 1999). The divergent results obtained in evaluating the effectiveness of nurse-led and medical-led teams suggest further studies are required using different outcomes measures. The ICU Liaison Team was pioneered at a tertiary university-affiliated hospital in Melbourne, Victoria, Australia, in 1996 and implemented in 1998. The ICU Liaison Team case manages patients following discharge from the ICU and provides assessment and advice for other patients at risk within the ward environment. In order to improve the appropriate and timely management of unstable patients in the wards, the ICU Liaison Team modified the MET criteria to refer patients at the first signs of deterioration rather than at the ‘pre’ cardiac arrest stage. The modified tool was called the clinical marker tool and was implemented by the ICU Liaison Team in 2003. This ICU Liaison Team model is the first nurse-led team to introduce abnormal vital sign criteria in the assessment and management of deteriorating patients in Australia. The aim of this research was to assess in a preand post-study design the effects of the ICU Liaison Team in responding to clinical marker referrals made for ward patients exhibiting early signs of deterioration. Specifically, the study investigated whether the clinical marker tool assisted with the early identification of patients with abnormal vital signs at risk of cardiac arrest and whether the clinical marker tool could reduce the length of time patients remained on the ward with abnormal vital signs.
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Methods Setting This study was undertaken at a tertiary universityaffiliated hospital in Melbourne, Australia. It has 323 beds, of which 11 are allocated to the high dependency unit (HDU) and the ICU. It is one of three hospitals and two nursing homes situated in Melbourne’s western suburbs that form the Western Health Service. Western Health treats over 100,000 emergency presentations annually.
Ethics The hospital ethics committee viewed the implementation of the clinical marker tool as a quality assurance project and therefore ethics approval was not warranted. However, ethics approval was obtained from the university’s human research ethics committee overseeing the project.
Study design This study was a quasi-experimental, prospective design (LoBiondo-Wood and Haber, 2002). A singlegroup pre- and post-test study was conducted. The intervention was a nurse-led clinical marker tool. The timeframe of the project was between February 2002 and January 2005. The 12-month pre- and 24-month post-test design was chosen to allow comparisons to be made following the introduction of an experimental treatment (LoBiondo-Wood and Haber, 2002). A true experimental design was not feasible as nursing staff at the participating hospital had been utilising the ICU Liaison Team to review unstable patients on the ward for more than 5 years. Removal of this service for some patients may have been inappropriate and unethical. A control hospital was not enlisted, as the executive team at the participating hospital believed that any further delay in implementation of the clinical marker tool would disadvantage patient outcomes. The outcome measures chosen were ‘unplanned ICU admissions’, ‘cardiac arrests’, and ‘mortality following cardiac arrest’. Additionally, data were collected on the ICU Liaison Team workload and the number of patients who required not for resuscitation (NFR) orders to be implemented following implementation of the clinical marker tool.
A.L. Green, A. Williams son Team and any patient who had an unplanned admission to the ICU from the wards or who suffered a cardiac arrest/medical emergency between February 2002 and January 2005 at the participating hospital.
Inclusion and exclusion criteria All wards where patients were admitted as inpatients within the participating hospital were included in the implementation of the clinical marker tool. The ICU Liaison Team decided that the day procedure unit, outpatients and the emergency department be excluded due to the patients short length of stay and therefore were less likely to require ICU Liaison Team involvement. Furthermore, the ICU Liaison Team’s previous experience found that involvement with unstable patients in these areas was uncommon. Patients admitted to the ICU from theatre following elective surgery were also excluded as these patients were considered to be planned admissions. Any other surgical or medical admissions from the wards to the ICU were defined as unplanned and were included in the study.
Development of the clinical marker parameters The clinical marker tool used for identifying ‘at-risk patients’ was based upon the MET model but modified to capture patients at an earlier stage of deterioration. The modifications were made following a three-month retrospective study conducted in 1999 of all unplanned admissions to the ICU to assess what clinical markers were reached 6 h before their admission. Modifications to the criteria included the following: lowering the ranges of heart rate from 140 beats/min to 120 beats/min and the respiratory rate from 36 breaths/min to 30 breaths/min. Additional criteria included oxygen saturations (<90% on oxygen) and urine output <30 ml/h for two consecutive hours. These changes reflected the criteria reached for patients admitted into the HDU at an earlier stage of the disease process. Accordingly, this 6-h timeframe was selected by the Intensivists and the ICU Liaison Team as an appropriate target time for patients to be admitted into the HDU from the ward with unresolved physiological criteria.
Intervention Study sample The study included all ward patients with abnormal vital signs who were referred to the ICU Liai-
The ICU Liaison Team is led by an ICU Nurse Practitioner and consists of one other senior ICU nurse who has a minimum of 5 years critical care experi-
An evaluation of an early warning clinical marker referral tool ence. The clinical marker tool enabled the referral of any patient displaying abnormal vital sign parameters or other criteria such as ‘worried nurse’ or ‘difficulty in breathing’ to the medical registrar treating the patient. If the medical registrar was unable to attend to the patient within 15 min or the clinical markers were unresolved despite treatment, then the ICU Liaison Team were contacted. The ICU Liaison Team provided the service between the hours of 08:00 and 18:00 h, 7 days a week. After hours, the ICU registrar continued to review those patients on the wards who the ICU Liaison Team were concerned about and accepted new clinical marker referrals from the ward staff during the night. The ICU Liaison Team provided extensive education sessions consisting of over 40 1-h interactive sessions for nursing and medical staff. The hospital’s Chief Executive Officer promoted the project via the hospital bulletins and weekly newsletters. Ongoing promotion of the project was via visual reminders that included the display of posters, wearing of ‘flip cards’ around the neck and attaching printouts to the patient’s bedside charts, all of which listed the reportable clinical markers. Other promotional measures included monthly reports to the nurse unit managers and the executive team with graphs illustrating the wards the unplanned ICU admissions came from. Adverse event forms were completed and discussed with the relevant nurse unit managers for all patients with clinical markers present for longer than 6 h prior to their ICU admission. All these measures assisted to maintain awareness and support of the project.
Data collection All unplanned admissions (including readmissions) from the ward to the ICU were identified from 1 February 2002 to 31 January 2005. This represented 12 months pre- (February 2002 to January 2003) and 24 months post-implementation (February 2003 to January 2005) of the clinical marker tool. On a daily basis the ICU Liaison Team prospectively collected data on all new admissions into the ICU from the ward. Each patient’s medical record and bedside charts were examined for the presence of clinical markers preceding the ICU admission. Analysis of these data identified the length of time the patient was on the ward in an unstable condition prior to their ICU admission. The switchboard operator activated the resuscitation team via a ‘code blue’ announcement and documented all calls into a logbook. The resuscitation team recorded the details of the ‘code blue’ events on specially designed forms.
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Both the switchboard logbook and the ‘code blue’ forms were subsequently analysed and entered into a database by the Cardiopulmonary Resuscitator (CPR) Coordinator. The CPR Coordinator removed the ‘false alarm calls’ from the data, for example when the resuscitation team was activated for patients who had fainted. Code blue data and outcomes following the event were collected from 1 January 2002 to 31 December 2004, allowing for approximately 12 months pre- and 24 months postdata collection. The routine collection of ‘code blue’ data for audit purposes, rather than specifically collected for this study meant that the dates did not coincide completely with the period when the study was undertaken. The ICU Liaison Team documented all clinical marker referrals made over a 24-month period into a logbook, including if patients were admitted to the ICU or if NFR orders were documented. Also, the ICU Liaison Team collected data on the number of patients admitted onto their caseload as a measure of monitoring workload levels.
Data analysis Descriptive statistics, including frequencies and percentages were used to identify the number of clinical marker referrals made and in evaluating for differences in the demographic data of patients admitted to the ICU. Data analysis was performed using Analyse-it for Microsoft Excel. The Mann—Whitney U test was used for evaluating differences in the median length of stay (LOS) for unplanned admissions/readmissions. Chi square was used for evaluating the number of ‘code blue’ calls, the number of unplanned admissions/readmissions including the time delays in admitting patients to the ICU, and the outcomes following these events.
Results In the first 24 months following the implementation of the clinical marker tool there were 415 clinical marker referrals (average of 17 referrals per month) to the ICU Liaison Team during working hours (08:00—18:00 h). Patients may have had several clinical markers present and referrals relating to the respiratory and the cardiovascular system were the most prevalent (Table 1). Three hundred and forty-seven (84%) patient referrals resulted in a change to the patient’s treatment following ICU Liaison Team referral, including referral to and consultation with medical staff, ordering of diagnostic
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A.L. Green, A. Williams
Table 1 Frequency of clinical markers during the period February 2003 to January 2005 (n = 415) Clinical marker category
Number of patients with the marker
Decrease in CNS Blood pressure <90 systolic Heart rate >120 Respiratory rate >30 SaO2 <90% on oxygen Difficulty in breathing Urine output <5 ml/kg for 2 h a Other
91 107 104 131 145 73 76 9
a Other: failure to respond to treatment or any patient staff are worried about.
tests and changes to medication management. One hundred and eleven patients (27%) were transferred to the ICU or the coronary care unit (CCU) following ICU Liaison Team involvement and a further 49 (12%) resulted in NFR orders being made as further treatment was considered futile. The remaining 68 (16%) of referrals required an assessment only with ICU Liaison Team support of the ward staff. Between February 2002 and January 2005, 2226 patients were admitted to the ICU. Of these 612 patients were admitted before implementation of the clinical marker tool. Following implementation of the clinical marker tool unplanned admissions
Table 2 tool
to the ICU from the ward increased on average by 34.6% per annum without a notable increase in ICU readmissions (Table 2). No significant difference between age, sex, ICU and hospital length of stay and outcome for unplanned admissions to the ICU from the ward was found. With the introduction of the clinical marker tool there was a significant decrease in the length of time unstable patients on the ward were admitted to the ICU (Table 3). Prior to implementing the tool, 63 (41.2%) unplanned ICU admissions had clinical markers present for ≥6 h on the ward prior to their ICU admission compared to 101 (24.5%) patients in the period following implementation of the tool. A comparative review of ‘code blue’ calls for 12 months prior to implementation of the clinical marker tool in 2002 and for 24 months postimplementation in 2003/2004 is demonstrated in Table 4. There was a decrease in the percentage of ‘code blue’ calls being made for patients who had suffered a cardiac arrest following implementation of the tool; from 61 (52.1%) patients in 2002 to 98 (35%) patients in 2003/2004. Conversely, there was an increase in ‘code blue’ calls being made for patients who were still breathing and had a palpable pulse following implementation of the tool; from 56 (47.9%) patients in 2002 to 181 (64.6) patients in 2003/2004. No significant difference was
Characteristics of unplanned ward admissions to ICU, before and after introduction of the clinical marker
Unplanned ICU admits, n (%) ICU Readmissions, n (%) Male, n (%) Mean age (years) ICU LOS; days Median (25th—75th percentiles) Hospital LOS (days) Median (25th—75th percentiles) Hospital mortality, n (%)
Pre-clinical marker (n = 153)
Post-clinical marker (n = 412)
111 (18.1)
320 (19.8)
42 (6.9) 87 (54) 63.2 3.0 (1.3—6.9)
19 (9—39)
52 (33.9)
92 (5.7) 236 (57) 61.8 2.6 (1.2—6.4)
16 (8—33.7)
142 (34.5)
LOS, length of stay.
Table 3 Frequency of unplanned ward admissions (including readmissions) into the ICU and duration of clinical marker presence (P = <0.0002) Clinical markers present for ≤6 h, n (%) Clinical markers present for ≥6 h, n (%)
Pre-clinical marker (n = 153)
Post-clinical marker (n = 412)
90 (58.8) 63 (41.2)
311 (75.4) 101 (24.5)
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Table 4 Comparison of cardiac arrest/medical emergency responses pre- (2002) and post-implementation (2003 and 2004) (P = 0.0024)
Code Blue announcements Code Blue forms, n (%) Cardiac arrest, n (%) Medical emergency, n (%)
Pre-clinical marker
Post-clinical marker
182 117 (64) 61 (52.1) 56 (47.9)
428 280 (65) 98 (35) 181 (64.6)
N.B. For 2003, 1 patient excluded as details unknown.
Table 5 Comparison of cardiac arrest/medical emergency outcomes pre- (2002) and post-implementation (2003 and 2004) Patients who survived to go home, n (%) Pre-clinical marker
Significance (Pre vs. Post)
Post-clinical marker
Cardiac arrest
11 (18)
18 (18.4)
Medical emergency
33 (59)
136 (75.1)
NS X2 = 13.18 (P = 0.0003)
NS, not significant.
found in the survival of patients following a ‘code blue’ call for cardiac arrests; however there was a significant difference in survival for patients following a ‘code blue’ call for medical emergencies (Table 5). In the 12 months prior to implementation of the clinical marker tool, the ICU Liaison Team had 630 patients on their caseload requiring a total of 1958 visits. The number of patients on their caseload increased to 1889 patients with a corresponding increase in the number of visits to 4586 in the 24 months post-implementation of the clinical marker tool. This resulted in a dramatic increase in the ICU Liaison Team workload.
Discussion This study has described the successful implementation of a clinical marker tool by the ICU Liaison Team in a tertiary Australian hospital. The major findings of this study demonstrated that expanding the role of the ICU Liaison Team to include a clinical marker tool improved the timely management of complex care patients in the ward. The clinical marker tool in conjunction with the ICU Liaison Team provided earlier intervention and aided in the timely transfer of patients to the ICU or identification of patients where an NFR order was considered more appropriate. The clinical marker tool allowed for referral of patients to the ICU Liaison Team at an earlier stage of deterioration rather than at the pre-arrest stage where admission to the ICU was imminent. Earlier referral of patients to the ICU Liaison Team allowed
for ongoing monitoring and timely management of problems in the ward environment, where the patient’s condition improved and admission to the ICU was averted. Additionally, the earlier referral enabled discussion to occur on the suitability for resuscitation and ICU admission in a less urgent manner. As with many nurse-led services, this model responds to referrals and provides a one-off visit (as per MET) but, if warranted, will continue to case-manage unstable ward patients until they are stable or an ICU admission is arranged. The clinical markers were chosen to capture patients at an earlier stage of the disease process but could also capture patients where ICU Liaison Team referral was not required. The inclusion of ‘seriously worried’ as one of the clinical marker criteria may have resulted in some patients being inappropriately referred to the team. Similar to the study by Cioffi (2000) the ICU Liaison Team found the ‘seriously worried’ criteria often identified the critically ill patient before the reportable vital sign parameters were reached. In some cases junior nurses used the ‘seriously worried’ and the ‘difficulty in breathing’ criteria to obtain prompt assistance when not being able to articulate their concerns. Furthermore, if the referral was inappropriate then this situation was transformed into a teaching opportunity whereby the ICU Liaison Team would conduct a complete patient assessment with the ward staff, which reassured the nurse that the patient was clinically stable. The benefit of the ‘worried nurse’ and the ‘difficulty in breathing’ criteria outweighed the number of times inappropriate referrals may have been received.
280 Another major finding of the study was an increase in the total number of unplanned admissions into the ICU with a reduction in the timeframe patients remained on the ward in an unstable condition prior to being admitted to the ICU. In many instances patients were identified for an ICU admission following a clinical marker referral to the ICU Liaison Team, who otherwise may have had a delayed admission that risked health outcomes. This is a similar finding to the study by Parr et al. (2001) where 45% of patients required an ICU admission following a MET call. These findings suggest that the clinical marker tool and expert ICU nurse support is effective in identifying ward patients warranting an ICU admission. However, the increase in ICU admissions may have resulted from unexpected influences such as the closure of an ICU and surgical ward at a nearby hospital with a subsequent increase in the utilisation of the beds at the participating hospital. Additionally, patients in the ward environment who required an ICU admission may have been a more complex group of patients that could not have been controlled for, although the characteristics between the pre- and post-groups were similar. Regardless of the reasons for the increase in unplanned admissions, the aim should be admitting patients to the ICU at the first signs of deterioration where a HDU admission was required rather than at the later stages of deterioration where an ICU admission occurred. This study is the only study that reported on the timeframe of instability prior to ICU admission and readmission as a quality indicator. It would be expected that patients who were admitted to the ICU at the first signs of deterioration would have a decreased ICU and hospital stay with improved outcomes (Pittard, 2003). However, this study found no significant differences in the lengths of stays and outcomes for unplanned admissions to the ICU following implementation of the clinical marker tool. This finding is inconsistent with other recent publications that have demonstrated reduced mortality following implementation of an Outreach Team (Ball et al., 2003; Garcea et al., 2004; Priestly et al., 2004). Recently ward beds have been allocated to patients in the emergency department as a priority over patients waiting for discharge to a ward bed from the ICU in the study hospital. It is not uncommon to find patients in the ICU waiting several days for a ward bed to become available, which may have contributed to these untoward findings. This has been reported elsewhere in the UK (Pittard, 2003). Another explanation is an increase in the number of seriously ill patients admitted to the ICU who previously remained on the ward. This may explain why no
A.L. Green, A. Williams improvement in length of stay and mortality was seen in this study. Overall, this project clearly demonstrated that the number of ‘code blue’ calls for patients suffering a cardiac arrest decreased after the introduction of the clinical marker tool. Coinciding with this decrease was an increase in ‘code blue’ calls for patients to be still breathing and with a pulse. This would suggest that nurses are being more proactive in calling for expert assistance and patients are being identified earlier and treatment initiated prior to the patient deteriorating to the point where a cardiac arrest occurs. Occasionally, ward staff utilised the ICU Liaison Team as an intermediary to determine the need for a ‘code blue’ call. These outcomes are similar to studies where the incidence of cardiac arrests decreased by half to two thirds after implementation of an MET (Bellomo et al., 2003; Buist et al., 2002). However, this study found no significant difference in survival for patients who had a cardiac arrest, although there was a significant difference in outcome for patients who were still breathing with a pulse following a ‘code blue’ call, supporting the notion that the clinical marker tool improves patient outcomes. Interestingly, the number of NFR orders initiated by the ICU Liaison Team increased following implementation of the clinical marker tool. Parr et al. (2001) found the MET identified patients for whom an NFR order should be considered. This would suggest the clinical marker tool identified unstable patients and in some cases allowed time for discussions to take part with the family on the suitability of resuscitation or an ICU admission to enable an informed decision to be made. The increase in patients being made NFR may have contributed to a reduction in the number of recorded cardiac arrests. A reduction in readmission rates is commonly utilised to evaluate the effectiveness of nurse-led teams and to assist in the justification for the establishment of nurse-led teams. A few studies have demonstrated a reduction in readmission rates following the introduction of an Outreach Team (Ball et al., 2003; Pittard, 2003). However, other studies have found no difference in readmission rates (Leary and Ridley, 2003; Russell, 1999). Readmission rates for this study have ranged from 6.9% to 5.7% and have failed to show a significant reduction following implementation of the clinical marker tool. Consequently, this raises questions as to whether readmission rates should be utilised to measure performance of the nurse-led teams (Leary and Ridley, 2003). A reason why the majority of nurse-led teams are unable to demonstrate a
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reduction in readmission rates may relate to the role these nurses have in early identification and fast-tracking of patients to the ICU. Finally, the implementation of the clinical marker tool resulted in a considerable increase in clinical workload for the ICU Liaison Team. This study recommends organisational support for 24-h ICU Liaison staffing before nurse-led teams expand their services incorporating a clinical marker tool. The educational opportunities for ward staff provide additional incentives for this service.
pital. Additionally, the ICU Liaison Team provided extensive and ongoing education and feedback of the clinical marker project, which may have led to an increase in referrals to the team. Both the pre-existing establishment of the role and the ongoing feedback provided to staff may have resulted in a ‘‘Hawthorne Effect’’ (LoBiondo-Wood and Haber, 2002).
Limitations
In summary this study demonstrated that the clinical marker tool in conjunction with an ICU Liaison Team can improve the timely management of acutely ill patients in the ward including fasttracking patients in need of an ICU admission, identifying patients where an NFR order should be considered, reducing the number of cardiac arrest calls and improving patient outcomes for medical emergencies. This research recommends that the length of time clinical markers are present prior to an ICU admission may be an improved alternative in evaluating the effectiveness of nurse-led teams. These findings suggest that this type of proactive care utilising the clinical marker tool in conjunction with the ICU Liaison Team provides strong support for the implementation of this service into other health care organisations.
The major limitation of this study was the use of a pre- and post-test design where changes between the two study periods occurred. Some of these changes included an increase in ICU and ward beds at the participating hospital and a change in bed allocation with emergency patients receiving ward beds as a priority over ICU patients during the postimplementation phase of the clinical marker tool. Both of these major changes would have impacted on the number of admissions to the ICU and the length of stay. The more obvious deficit with preand post-test design relates to differing populations between the two periods. A further limitation of our study was the use of ‘code blue’ data, which was already collected for audit purposes where the dates did not coincide completely with the study period and may have produced erroneous results. However, the extended period of the study and the statistically significant results obtained suggest that it was due to the implementation of a clinical marker tool. Additionally, not all ward patients requiring ICU admission were referred to the ICU Liaison Team. Medical staff treating the patient may have been the first to be contacted, instigating the patient’s admission to the ICU and some of the unplanned admissions to the ICU occurred after-hours when the ICU Liaison Team were unavailable. Both these scenarios may have assisted with the fast-tracking of patients to the ICU. It was out of the scope of this study to identify the number of clinical marker referrals made to the medical staff, including afterhours when the ICU registrar responded to the clinical marker referrals when the ICU Liaison Team was not on duty. This project was implemented in a hospital where the ICU Liaison Team has been established for more than 5 years. Ward staff were already accustomed to referring unstable patients to the ICU Liaison Team in an ‘ad-hoc’ fashion. Therefore, the implementation of the clinical marker tool was not a totally new concept at the participating hos-
Summary
Recommendations for further research This study provides evidence for nurse-led teams to implement a clinical marker tool in similar settings and recommends the timeframe of instability on the ward prior to the ICU admission be used as a major quality indicator. An interesting, but not unexpected finding of this study was a deficit in NFR orders being made by the ward medical staff, that resulted in the ICU Liaison Team and the ICU medical staff identifying and writing NFR orders for this group of patients. Further investigation is required to determine adequate staffing levels for the ICU Liaison Team and to support 24-h cover.
Acknowledgements The authors gratefully acknowledge Julie Daniels and Sandra Niklaus (members of the ICU Liaison Team) for their assistance in data collection. Also, Craig French (Director of ICU) who provided advice on the analysis and interpretation of the data and in combination with Lydia Dennett (Divisional
282 Director CCVT & ICU) critically reviewed drafts of the manuscript and approved the final version of the paper.
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A.L. Green, A. Williams Goldhill DA, White SA, Sumner A. Physiological values and procedures in the 24 h before ICU admission from the ward. Anaesthesis 1999b;54(6):529—34. Green A, Edmonds L. Bridging the gap between the intensive care unit and general wards—–the ICU Liaison Nurse. Intens Crit Care Nurs 2004;20(3):133—43. Hillman K, Chen J, Cretikos M, Bellomo R, Brown D, Doig G, Finfer S, Flabouris A. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet 2005;365(9477):2091—7. Hourihan F, Bishop G, Hillman KM, Lee A. The medical emergency team: a new strategy to identify and intervene in High-risk patients. Clin Intens Care 1995;6(6):269—72. Leary T, Ridley S. Impact of an Outreach team on readmission to a critical care unit. Anaesthesia 2003;58(4): 328—32. Lee A, Bishop G, Hillman KM, Daffurn K. The medical emergency team. Anaesth Intens Care 1995;23(2):183—6. LoBiondo-Wood G, Haber J. Nursing Research. Mosby: United States of America; 2002. Odell M, Forster A, Rudman K, Bass F. The critical care outreach service and the early warning system on surgical wards. Nurs Crit Care 2002;7(3):132—5. Parr MJA, Hadfield A, Flabouris G, Bishop K, Hillman K. The medical emergency team: 12 month analysis of reasons for activation, immediate outcome and not-for-resuscitation orders. Resuscitation 2001;50(1):39—44. Pittard AJ. Out of our reach? Assessing the impact of introducing a critical care outreach service. Anaesthesia 2003;58: 882—5. Priestley G, Watson W, Rashidian A, Mozley C, Russell D, Wilson J, Cope J, Hart D, Kay D, Cowley K, Pateraki J. Introducing critical care outreach: a ward-randomised trial of phased introduction in a general hospital. Intens Care Med 2004;30(7):1398—404. Russell S. Reducing readmissions to the intensive care unit. Heart Lung 1999;28(5):365—72. Salamonson Y, Kariyawasam A, van Heere B, O’Connor C. The evolutionary process of Medical Emergency Team (MET) implementation: reduction in unanticipated ICU transfers. Resuscitation 2001;49(2):135—41. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest 1990;98(6):1388—92.
ORIGINAL ARTICLE
An evaluation of an early warning clinical marker referral tool Anna Louise Green a,∗, Allison Williams b a b
Western Hospital, Gordon Street, Footscray, 3011, Vic., Australia University of Melbourne, Vic., Australia
Accepted 23 April 2006
KEYWORDS Critical Care; Early warning scores; Unplanned ICU admission; Critical Illness mortality
∗
Summary Objectives: The purpose of this study was to evaluate the introduction of a clinical marker tool using a pre- and post-test design in a tertiary university-affiliated hospital. The clinical marker tool was designed to assist in the early identification of unstable patients in the general surgical and medical ward environment based on abnormal vital signs. Methods: A pre- and post-test design of the clinical marker tool was undertaken over a 3-year period. All unstable ward patients who were admitted to the Intensive Care Unit (ICU) from 1 February 2002 to 31 January 2003 (pre- implementation period) and from 1 February 2003 to 31 January 2005 (post-implementation period) were included in the study. A secondary analysis was performed on annual medical emergency calls made to the resuscitation team and mortality from such events from 1 January 2002 to 31 December 2004. Results: Prior to implementing the clinical marker tool, 63 (41.2%) unplanned ICU admissions from the ward had clinical markers present for ≥6 h. Following implementation of the clinical marker tool, 101 (24.5%) patients had clinical markers present for ≥6 h (p = 0.0002). There was no difference in ICU or hospital length of stay or hospital mortality for unplanned admissions to the ICU following implementation of the clinical marker tool. The number of patients found to be still breathing with a pulse on arrival of the resuscitation team was significantly increased from 56 (47.9%) patients to 181 (64.6%) patients post-implementation of the clinical marker tool (p = 0.0024). Additionally, we found an associated increase in survival of this group of patients discharged home from 33 (59%) patients to 136 (75.1%) patients post-implementation of the clinical marker tool (p = 0.0003). Conclusions: The clinical marker tool implemented by an ICU Liaison Team improved the management of patients in the ward environment, including proactive admission of patients to the ICU. Additionally, implementation of the clinical marker tool was
Corresponding author. Tel.: +61 3 8345 6588; fax: +61 3 8345 6336. E-mail address: [email protected] (A.L. Green).
0964-3397/$ — see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.iccn.2006.04.004
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associated with a reduction in the number of cardiac arrests and improvement in hospital mortality for patients experiencing a medical emergency call. The timeframe of instability on the ward prior to the ICU admission may be used as a quality indicator to measure ICU Liaison Team performance. Further research is required to substantiate these findings. © 2006 Elsevier Ltd. All rights reserved.
Introduction Over the last 15 years there has been an increase in the number of intensive care teams providing assessment, advice and treatment for patients in the ward environment (Coad and Haines, 1999; Daly et al., 1998; Green and Edmonds, 2004; Lee et al., 1995). Two distinct teams have become very prominent in the literature and these are the Australian medically led Medical Emergency Teams (MET), and the nurse-led teams known as the Outreach Teams of the United Kingdom (UK). The MET and some of the Outreach Teams use abnormal vital signs (also referred to as clinical markers) to identify ward patients who are deteriorating and may be at risk of suffering a cardiac arrest (Goldhill et al., 1999a; Lee et al., 1995). The significance of abnormal vital signs originated from research that reported clinical deterioration in patients occurring within 8 h prior to cardiac arrest (Schein et al., 1990) and/or admission to the ICU (Goldhill et al., 1999b). The nurse-led Intensive Care Unit (ICU) Liaison Teams in Australia have typically not used abnormal vital signs to trigger a referral to the team but rather to rely on ward staff to determine when assistance is required. A recent trend in Australia has seen the introduction of a collaborative arrangement between the MET and the ICU Liaison Team (Barbetti and Choate, 2003) where the ICU Liaison Team responds to the MET calls. The Outreach Teams that respond to patients with abnormal physiology use a variety of alert systems. The simplest system is where ward nurses are instructed to call the Outreach Team when patients reach one or more abnormal vital signs (Ball et al., 2003). Another system is where ward nurses are instructed to call the registrar and the Outreach Team when two abnormal vital signs are reached (DHMA, 2003). The most complex of these alert systems is the assignment of weighted scores awarded to abnormal vital signs and then calculated to give a total score (Garcea et al., 2004; Odell et al., 2002). The score determines the level of response required ranging from ward staff observing the patient to calling the medical regis-
trar and the Outreach Team (DHMA, 2003; Pittard, 2003). Outcome measures of unplanned ICU admissions, cardiac arrests and hospital mortality rates have all been used in researching the effectiveness of the METs (Bristow et al., 2000; Buist et al., 2002; Hillman et al., 2005; Hourihan et al., 1995; Salamonson et al., 2001). In contrast, the nurse-led teams have used reduction in ICU readmission rates, ICU and ward patient mortality rates as indicators in evaluating their effectiveness (Ball et al., 2003; Garcea et al., 2004; Green and Edmonds, 2004; Leary and Ridley, 2003; Priestley et al., 2004; Russell, 1999). The divergent results obtained in evaluating the effectiveness of nurse-led and medical-led teams suggest further studies are required using different outcomes measures. The ICU Liaison Team was pioneered at a tertiary university-affiliated hospital in Melbourne, Victoria, Australia, in 1996 and implemented in 1998. The ICU Liaison Team case manages patients following discharge from the ICU and provides assessment and advice for other patients at risk within the ward environment. In order to improve the appropriate and timely management of unstable patients in the wards, the ICU Liaison Team modified the MET criteria to refer patients at the first signs of deterioration rather than at the ‘pre’ cardiac arrest stage. The modified tool was called the clinical marker tool and was implemented by the ICU Liaison Team in 2003. This ICU Liaison Team model is the first nurse-led team to introduce abnormal vital sign criteria in the assessment and management of deteriorating patients in Australia. The aim of this research was to assess in a preand post-study design the effects of the ICU Liaison Team in responding to clinical marker referrals made for ward patients exhibiting early signs of deterioration. Specifically, the study investigated whether the clinical marker tool assisted with the early identification of patients with abnormal vital signs at risk of cardiac arrest and whether the clinical marker tool could reduce the length of time patients remained on the ward with abnormal vital signs.
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Methods Setting This study was undertaken at a tertiary universityaffiliated hospital in Melbourne, Australia. It has 323 beds, of which 11 are allocated to the high dependency unit (HDU) and the ICU. It is one of three hospitals and two nursing homes situated in Melbourne’s western suburbs that form the Western Health Service. Western Health treats over 100,000 emergency presentations annually.
Ethics The hospital ethics committee viewed the implementation of the clinical marker tool as a quality assurance project and therefore ethics approval was not warranted. However, ethics approval was obtained from the university’s human research ethics committee overseeing the project.
Study design This study was a quasi-experimental, prospective design (LoBiondo-Wood and Haber, 2002). A singlegroup pre- and post-test study was conducted. The intervention was a nurse-led clinical marker tool. The timeframe of the project was between February 2002 and January 2005. The 12-month pre- and 24-month post-test design was chosen to allow comparisons to be made following the introduction of an experimental treatment (LoBiondo-Wood and Haber, 2002). A true experimental design was not feasible as nursing staff at the participating hospital had been utilising the ICU Liaison Team to review unstable patients on the ward for more than 5 years. Removal of this service for some patients may have been inappropriate and unethical. A control hospital was not enlisted, as the executive team at the participating hospital believed that any further delay in implementation of the clinical marker tool would disadvantage patient outcomes. The outcome measures chosen were ‘unplanned ICU admissions’, ‘cardiac arrests’, and ‘mortality following cardiac arrest’. Additionally, data were collected on the ICU Liaison Team workload and the number of patients who required not for resuscitation (NFR) orders to be implemented following implementation of the clinical marker tool.
A.L. Green, A. Williams son Team and any patient who had an unplanned admission to the ICU from the wards or who suffered a cardiac arrest/medical emergency between February 2002 and January 2005 at the participating hospital.
Inclusion and exclusion criteria All wards where patients were admitted as inpatients within the participating hospital were included in the implementation of the clinical marker tool. The ICU Liaison Team decided that the day procedure unit, outpatients and the emergency department be excluded due to the patients short length of stay and therefore were less likely to require ICU Liaison Team involvement. Furthermore, the ICU Liaison Team’s previous experience found that involvement with unstable patients in these areas was uncommon. Patients admitted to the ICU from theatre following elective surgery were also excluded as these patients were considered to be planned admissions. Any other surgical or medical admissions from the wards to the ICU were defined as unplanned and were included in the study.
Development of the clinical marker parameters The clinical marker tool used for identifying ‘at-risk patients’ was based upon the MET model but modified to capture patients at an earlier stage of deterioration. The modifications were made following a three-month retrospective study conducted in 1999 of all unplanned admissions to the ICU to assess what clinical markers were reached 6 h before their admission. Modifications to the criteria included the following: lowering the ranges of heart rate from 140 beats/min to 120 beats/min and the respiratory rate from 36 breaths/min to 30 breaths/min. Additional criteria included oxygen saturations (<90% on oxygen) and urine output <30 ml/h for two consecutive hours. These changes reflected the criteria reached for patients admitted into the HDU at an earlier stage of the disease process. Accordingly, this 6-h timeframe was selected by the Intensivists and the ICU Liaison Team as an appropriate target time for patients to be admitted into the HDU from the ward with unresolved physiological criteria.
Intervention Study sample The study included all ward patients with abnormal vital signs who were referred to the ICU Liai-
The ICU Liaison Team is led by an ICU Nurse Practitioner and consists of one other senior ICU nurse who has a minimum of 5 years critical care experi-
An evaluation of an early warning clinical marker referral tool ence. The clinical marker tool enabled the referral of any patient displaying abnormal vital sign parameters or other criteria such as ‘worried nurse’ or ‘difficulty in breathing’ to the medical registrar treating the patient. If the medical registrar was unable to attend to the patient within 15 min or the clinical markers were unresolved despite treatment, then the ICU Liaison Team were contacted. The ICU Liaison Team provided the service between the hours of 08:00 and 18:00 h, 7 days a week. After hours, the ICU registrar continued to review those patients on the wards who the ICU Liaison Team were concerned about and accepted new clinical marker referrals from the ward staff during the night. The ICU Liaison Team provided extensive education sessions consisting of over 40 1-h interactive sessions for nursing and medical staff. The hospital’s Chief Executive Officer promoted the project via the hospital bulletins and weekly newsletters. Ongoing promotion of the project was via visual reminders that included the display of posters, wearing of ‘flip cards’ around the neck and attaching printouts to the patient’s bedside charts, all of which listed the reportable clinical markers. Other promotional measures included monthly reports to the nurse unit managers and the executive team with graphs illustrating the wards the unplanned ICU admissions came from. Adverse event forms were completed and discussed with the relevant nurse unit managers for all patients with clinical markers present for longer than 6 h prior to their ICU admission. All these measures assisted to maintain awareness and support of the project.
Data collection All unplanned admissions (including readmissions) from the ward to the ICU were identified from 1 February 2002 to 31 January 2005. This represented 12 months pre- (February 2002 to January 2003) and 24 months post-implementation (February 2003 to January 2005) of the clinical marker tool. On a daily basis the ICU Liaison Team prospectively collected data on all new admissions into the ICU from the ward. Each patient’s medical record and bedside charts were examined for the presence of clinical markers preceding the ICU admission. Analysis of these data identified the length of time the patient was on the ward in an unstable condition prior to their ICU admission. The switchboard operator activated the resuscitation team via a ‘code blue’ announcement and documented all calls into a logbook. The resuscitation team recorded the details of the ‘code blue’ events on specially designed forms.
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Both the switchboard logbook and the ‘code blue’ forms were subsequently analysed and entered into a database by the Cardiopulmonary Resuscitator (CPR) Coordinator. The CPR Coordinator removed the ‘false alarm calls’ from the data, for example when the resuscitation team was activated for patients who had fainted. Code blue data and outcomes following the event were collected from 1 January 2002 to 31 December 2004, allowing for approximately 12 months pre- and 24 months postdata collection. The routine collection of ‘code blue’ data for audit purposes, rather than specifically collected for this study meant that the dates did not coincide completely with the period when the study was undertaken. The ICU Liaison Team documented all clinical marker referrals made over a 24-month period into a logbook, including if patients were admitted to the ICU or if NFR orders were documented. Also, the ICU Liaison Team collected data on the number of patients admitted onto their caseload as a measure of monitoring workload levels.
Data analysis Descriptive statistics, including frequencies and percentages were used to identify the number of clinical marker referrals made and in evaluating for differences in the demographic data of patients admitted to the ICU. Data analysis was performed using Analyse-it for Microsoft Excel. The Mann—Whitney U test was used for evaluating differences in the median length of stay (LOS) for unplanned admissions/readmissions. Chi square was used for evaluating the number of ‘code blue’ calls, the number of unplanned admissions/readmissions including the time delays in admitting patients to the ICU, and the outcomes following these events.
Results In the first 24 months following the implementation of the clinical marker tool there were 415 clinical marker referrals (average of 17 referrals per month) to the ICU Liaison Team during working hours (08:00—18:00 h). Patients may have had several clinical markers present and referrals relating to the respiratory and the cardiovascular system were the most prevalent (Table 1). Three hundred and forty-seven (84%) patient referrals resulted in a change to the patient’s treatment following ICU Liaison Team referral, including referral to and consultation with medical staff, ordering of diagnostic
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A.L. Green, A. Williams
Table 1 Frequency of clinical markers during the period February 2003 to January 2005 (n = 415) Clinical marker category
Number of patients with the marker
Decrease in CNS Blood pressure <90 systolic Heart rate >120 Respiratory rate >30 SaO2 <90% on oxygen Difficulty in breathing Urine output <5 ml/kg for 2 h a Other
91 107 104 131 145 73 76 9
a Other: failure to respond to treatment or any patient staff are worried about.
tests and changes to medication management. One hundred and eleven patients (27%) were transferred to the ICU or the coronary care unit (CCU) following ICU Liaison Team involvement and a further 49 (12%) resulted in NFR orders being made as further treatment was considered futile. The remaining 68 (16%) of referrals required an assessment only with ICU Liaison Team support of the ward staff. Between February 2002 and January 2005, 2226 patients were admitted to the ICU. Of these 612 patients were admitted before implementation of the clinical marker tool. Following implementation of the clinical marker tool unplanned admissions
Table 2 tool
to the ICU from the ward increased on average by 34.6% per annum without a notable increase in ICU readmissions (Table 2). No significant difference between age, sex, ICU and hospital length of stay and outcome for unplanned admissions to the ICU from the ward was found. With the introduction of the clinical marker tool there was a significant decrease in the length of time unstable patients on the ward were admitted to the ICU (Table 3). Prior to implementing the tool, 63 (41.2%) unplanned ICU admissions had clinical markers present for ≥6 h on the ward prior to their ICU admission compared to 101 (24.5%) patients in the period following implementation of the tool. A comparative review of ‘code blue’ calls for 12 months prior to implementation of the clinical marker tool in 2002 and for 24 months postimplementation in 2003/2004 is demonstrated in Table 4. There was a decrease in the percentage of ‘code blue’ calls being made for patients who had suffered a cardiac arrest following implementation of the tool; from 61 (52.1%) patients in 2002 to 98 (35%) patients in 2003/2004. Conversely, there was an increase in ‘code blue’ calls being made for patients who were still breathing and had a palpable pulse following implementation of the tool; from 56 (47.9%) patients in 2002 to 181 (64.6) patients in 2003/2004. No significant difference was
Characteristics of unplanned ward admissions to ICU, before and after introduction of the clinical marker
Unplanned ICU admits, n (%) ICU Readmissions, n (%) Male, n (%) Mean age (years) ICU LOS; days Median (25th—75th percentiles) Hospital LOS (days) Median (25th—75th percentiles) Hospital mortality, n (%)
Pre-clinical marker (n = 153)
Post-clinical marker (n = 412)
111 (18.1)
320 (19.8)
42 (6.9) 87 (54) 63.2 3.0 (1.3—6.9)
19 (9—39)
52 (33.9)
92 (5.7) 236 (57) 61.8 2.6 (1.2—6.4)
16 (8—33.7)
142 (34.5)
LOS, length of stay.
Table 3 Frequency of unplanned ward admissions (including readmissions) into the ICU and duration of clinical marker presence (P = <0.0002) Clinical markers present for ≤6 h, n (%) Clinical markers present for ≥6 h, n (%)
Pre-clinical marker (n = 153)
Post-clinical marker (n = 412)
90 (58.8) 63 (41.2)
311 (75.4) 101 (24.5)
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Table 4 Comparison of cardiac arrest/medical emergency responses pre- (2002) and post-implementation (2003 and 2004) (P = 0.0024)
Code Blue announcements Code Blue forms, n (%) Cardiac arrest, n (%) Medical emergency, n (%)
Pre-clinical marker
Post-clinical marker
182 117 (64) 61 (52.1) 56 (47.9)
428 280 (65) 98 (35) 181 (64.6)
N.B. For 2003, 1 patient excluded as details unknown.
Table 5 Comparison of cardiac arrest/medical emergency outcomes pre- (2002) and post-implementation (2003 and 2004) Patients who survived to go home, n (%) Pre-clinical marker
Significance (Pre vs. Post)
Post-clinical marker
Cardiac arrest
11 (18)
18 (18.4)
Medical emergency
33 (59)
136 (75.1)
NS X2 = 13.18 (P = 0.0003)
NS, not significant.
found in the survival of patients following a ‘code blue’ call for cardiac arrests; however there was a significant difference in survival for patients following a ‘code blue’ call for medical emergencies (Table 5). In the 12 months prior to implementation of the clinical marker tool, the ICU Liaison Team had 630 patients on their caseload requiring a total of 1958 visits. The number of patients on their caseload increased to 1889 patients with a corresponding increase in the number of visits to 4586 in the 24 months post-implementation of the clinical marker tool. This resulted in a dramatic increase in the ICU Liaison Team workload.
Discussion This study has described the successful implementation of a clinical marker tool by the ICU Liaison Team in a tertiary Australian hospital. The major findings of this study demonstrated that expanding the role of the ICU Liaison Team to include a clinical marker tool improved the timely management of complex care patients in the ward. The clinical marker tool in conjunction with the ICU Liaison Team provided earlier intervention and aided in the timely transfer of patients to the ICU or identification of patients where an NFR order was considered more appropriate. The clinical marker tool allowed for referral of patients to the ICU Liaison Team at an earlier stage of deterioration rather than at the pre-arrest stage where admission to the ICU was imminent. Earlier referral of patients to the ICU Liaison Team allowed
for ongoing monitoring and timely management of problems in the ward environment, where the patient’s condition improved and admission to the ICU was averted. Additionally, the earlier referral enabled discussion to occur on the suitability for resuscitation and ICU admission in a less urgent manner. As with many nurse-led services, this model responds to referrals and provides a one-off visit (as per MET) but, if warranted, will continue to case-manage unstable ward patients until they are stable or an ICU admission is arranged. The clinical markers were chosen to capture patients at an earlier stage of the disease process but could also capture patients where ICU Liaison Team referral was not required. The inclusion of ‘seriously worried’ as one of the clinical marker criteria may have resulted in some patients being inappropriately referred to the team. Similar to the study by Cioffi (2000) the ICU Liaison Team found the ‘seriously worried’ criteria often identified the critically ill patient before the reportable vital sign parameters were reached. In some cases junior nurses used the ‘seriously worried’ and the ‘difficulty in breathing’ criteria to obtain prompt assistance when not being able to articulate their concerns. Furthermore, if the referral was inappropriate then this situation was transformed into a teaching opportunity whereby the ICU Liaison Team would conduct a complete patient assessment with the ward staff, which reassured the nurse that the patient was clinically stable. The benefit of the ‘worried nurse’ and the ‘difficulty in breathing’ criteria outweighed the number of times inappropriate referrals may have been received.
280 Another major finding of the study was an increase in the total number of unplanned admissions into the ICU with a reduction in the timeframe patients remained on the ward in an unstable condition prior to being admitted to the ICU. In many instances patients were identified for an ICU admission following a clinical marker referral to the ICU Liaison Team, who otherwise may have had a delayed admission that risked health outcomes. This is a similar finding to the study by Parr et al. (2001) where 45% of patients required an ICU admission following a MET call. These findings suggest that the clinical marker tool and expert ICU nurse support is effective in identifying ward patients warranting an ICU admission. However, the increase in ICU admissions may have resulted from unexpected influences such as the closure of an ICU and surgical ward at a nearby hospital with a subsequent increase in the utilisation of the beds at the participating hospital. Additionally, patients in the ward environment who required an ICU admission may have been a more complex group of patients that could not have been controlled for, although the characteristics between the pre- and post-groups were similar. Regardless of the reasons for the increase in unplanned admissions, the aim should be admitting patients to the ICU at the first signs of deterioration where a HDU admission was required rather than at the later stages of deterioration where an ICU admission occurred. This study is the only study that reported on the timeframe of instability prior to ICU admission and readmission as a quality indicator. It would be expected that patients who were admitted to the ICU at the first signs of deterioration would have a decreased ICU and hospital stay with improved outcomes (Pittard, 2003). However, this study found no significant differences in the lengths of stays and outcomes for unplanned admissions to the ICU following implementation of the clinical marker tool. This finding is inconsistent with other recent publications that have demonstrated reduced mortality following implementation of an Outreach Team (Ball et al., 2003; Garcea et al., 2004; Priestly et al., 2004). Recently ward beds have been allocated to patients in the emergency department as a priority over patients waiting for discharge to a ward bed from the ICU in the study hospital. It is not uncommon to find patients in the ICU waiting several days for a ward bed to become available, which may have contributed to these untoward findings. This has been reported elsewhere in the UK (Pittard, 2003). Another explanation is an increase in the number of seriously ill patients admitted to the ICU who previously remained on the ward. This may explain why no
A.L. Green, A. Williams improvement in length of stay and mortality was seen in this study. Overall, this project clearly demonstrated that the number of ‘code blue’ calls for patients suffering a cardiac arrest decreased after the introduction of the clinical marker tool. Coinciding with this decrease was an increase in ‘code blue’ calls for patients to be still breathing and with a pulse. This would suggest that nurses are being more proactive in calling for expert assistance and patients are being identified earlier and treatment initiated prior to the patient deteriorating to the point where a cardiac arrest occurs. Occasionally, ward staff utilised the ICU Liaison Team as an intermediary to determine the need for a ‘code blue’ call. These outcomes are similar to studies where the incidence of cardiac arrests decreased by half to two thirds after implementation of an MET (Bellomo et al., 2003; Buist et al., 2002). However, this study found no significant difference in survival for patients who had a cardiac arrest, although there was a significant difference in outcome for patients who were still breathing with a pulse following a ‘code blue’ call, supporting the notion that the clinical marker tool improves patient outcomes. Interestingly, the number of NFR orders initiated by the ICU Liaison Team increased following implementation of the clinical marker tool. Parr et al. (2001) found the MET identified patients for whom an NFR order should be considered. This would suggest the clinical marker tool identified unstable patients and in some cases allowed time for discussions to take part with the family on the suitability of resuscitation or an ICU admission to enable an informed decision to be made. The increase in patients being made NFR may have contributed to a reduction in the number of recorded cardiac arrests. A reduction in readmission rates is commonly utilised to evaluate the effectiveness of nurse-led teams and to assist in the justification for the establishment of nurse-led teams. A few studies have demonstrated a reduction in readmission rates following the introduction of an Outreach Team (Ball et al., 2003; Pittard, 2003). However, other studies have found no difference in readmission rates (Leary and Ridley, 2003; Russell, 1999). Readmission rates for this study have ranged from 6.9% to 5.7% and have failed to show a significant reduction following implementation of the clinical marker tool. Consequently, this raises questions as to whether readmission rates should be utilised to measure performance of the nurse-led teams (Leary and Ridley, 2003). A reason why the majority of nurse-led teams are unable to demonstrate a
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reduction in readmission rates may relate to the role these nurses have in early identification and fast-tracking of patients to the ICU. Finally, the implementation of the clinical marker tool resulted in a considerable increase in clinical workload for the ICU Liaison Team. This study recommends organisational support for 24-h ICU Liaison staffing before nurse-led teams expand their services incorporating a clinical marker tool. The educational opportunities for ward staff provide additional incentives for this service.
pital. Additionally, the ICU Liaison Team provided extensive and ongoing education and feedback of the clinical marker project, which may have led to an increase in referrals to the team. Both the pre-existing establishment of the role and the ongoing feedback provided to staff may have resulted in a ‘‘Hawthorne Effect’’ (LoBiondo-Wood and Haber, 2002).
Limitations
In summary this study demonstrated that the clinical marker tool in conjunction with an ICU Liaison Team can improve the timely management of acutely ill patients in the ward including fasttracking patients in need of an ICU admission, identifying patients where an NFR order should be considered, reducing the number of cardiac arrest calls and improving patient outcomes for medical emergencies. This research recommends that the length of time clinical markers are present prior to an ICU admission may be an improved alternative in evaluating the effectiveness of nurse-led teams. These findings suggest that this type of proactive care utilising the clinical marker tool in conjunction with the ICU Liaison Team provides strong support for the implementation of this service into other health care organisations.
The major limitation of this study was the use of a pre- and post-test design where changes between the two study periods occurred. Some of these changes included an increase in ICU and ward beds at the participating hospital and a change in bed allocation with emergency patients receiving ward beds as a priority over ICU patients during the postimplementation phase of the clinical marker tool. Both of these major changes would have impacted on the number of admissions to the ICU and the length of stay. The more obvious deficit with preand post-test design relates to differing populations between the two periods. A further limitation of our study was the use of ‘code blue’ data, which was already collected for audit purposes where the dates did not coincide completely with the study period and may have produced erroneous results. However, the extended period of the study and the statistically significant results obtained suggest that it was due to the implementation of a clinical marker tool. Additionally, not all ward patients requiring ICU admission were referred to the ICU Liaison Team. Medical staff treating the patient may have been the first to be contacted, instigating the patient’s admission to the ICU and some of the unplanned admissions to the ICU occurred after-hours when the ICU Liaison Team were unavailable. Both these scenarios may have assisted with the fast-tracking of patients to the ICU. It was out of the scope of this study to identify the number of clinical marker referrals made to the medical staff, including afterhours when the ICU registrar responded to the clinical marker referrals when the ICU Liaison Team was not on duty. This project was implemented in a hospital where the ICU Liaison Team has been established for more than 5 years. Ward staff were already accustomed to referring unstable patients to the ICU Liaison Team in an ‘ad-hoc’ fashion. Therefore, the implementation of the clinical marker tool was not a totally new concept at the participating hos-
Summary
Recommendations for further research This study provides evidence for nurse-led teams to implement a clinical marker tool in similar settings and recommends the timeframe of instability on the ward prior to the ICU admission be used as a major quality indicator. An interesting, but not unexpected finding of this study was a deficit in NFR orders being made by the ward medical staff, that resulted in the ICU Liaison Team and the ICU medical staff identifying and writing NFR orders for this group of patients. Further investigation is required to determine adequate staffing levels for the ICU Liaison Team and to support 24-h cover.
Acknowledgements The authors gratefully acknowledge Julie Daniels and Sandra Niklaus (members of the ICU Liaison Team) for their assistance in data collection. Also, Craig French (Director of ICU) who provided advice on the analysis and interpretation of the data and in combination with Lydia Dennett (Divisional
282 Director CCVT & ICU) critically reviewed drafts of the manuscript and approved the final version of the paper.
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