EWS for Decreasing the Rates of Adverse Events

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21st Sep 2017 Health Reference this

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Ilinka Risteska-Budzhakovska

INTRODUCTION

Acute health care facilities are faced with the considerable challenge of providing effective and efficient care for the increased number of patients that are suffering from complex co-morbidities (Massey, Aitken, & Wendy, 2008). . In addition, research found that this can be a challenge for inexperienced staff that are less able to recognise signs of deterioration in a timely manner. As a result, unrecognised clinical deterioration of acute ward patients continues to be one of the crucial issues in the health care sector (M. Odell, Victor, & Oliver, 2009; Preston & Flynn, 2010; Waldie, Day, & Tee, 2016; Zimlichman et al., 2012).

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The problem of unrecognised clinical deterioration leads to increased number adverse events such as: avoidable cardiac arrests, unnecessary re-admissions to emergency wards and morbidity and mortality. The problem also results in an increased financial burden to the health care sector and loss of efficiency(Ansell, Meyer, & Thompson, 2015; Kyriacos, Jelsma, & Jordan, 2011; Rattray et al., 2011; Waldie et al., 2016; Wood et al., 2015a).

The National Safety and Quality Health Service Standards(NSQHS) by the Australian Commission on Safety and Quality in Health Care (ACSQHC) were designed with a main goal to improve the health care outcomes for the patients of health care services through the provision of best possible care. Standard 9 of the NSQHS outlines the importance of timely identification and response to clinical deterioration of acutely unwell patients (Australian Commission on Safety and Quality in Health Care, 2012).

BACKGROUND

Many adverse events in the healthcare can be avoided once human errors are minimised (Georgaka, Mparmparousi, & Vitos, 2012). Various policies, procedures and systems have been established around the world for the timely detection of acutely deteriorating patients and improved survival rates (Duncan, McMullan, & Mills, 2012; Freebairn, 2013; Mullany, Ziegenfuss, Goleby, & Ward, 2016). One of the systems in use is Early Warning Scores (EWS). EWS systems were developed to provide set parameters for the physiological changes that take place during acute patient deterioration (Higgins, Maries-Tillott, Quinton, & Richmond, 2008; McCallum, Duffy, Hastie, Ness, & Price, 2013; Morris & Davies, 2010). The original EWS system was created in Liverpool, Australia (McCallum et al., 2013). Not long after variations began being used in many countries including: New Zealand (Freebairn, 2013), England (Morris & Davies, 2010), Ireland (McGaughey, Blackwood, O’Halloran, Trinder, & Porter, 2010), and USA (Stark, Maciel, Sheppard, Sacks, & Hines, 2015). EWS system used in Australia incorporates parameters of: respiratory rate, temperature, blood pressure, heart rate, urine output, pain and conscious level. All parameters are colour coded so as to provide guidance for the necessity of staff intervention once abnormal values are detected (Christofidis, Hill, Horswill, & Watson, 2015).

AIM: To evaluate the effect of EWS systems on decreasing the rates of fatal adverse events among deteriorating patients as well as potential factors that inhibit or facilitate effectiveness of these systems. This will be accomplished by reviewing the available literature on these topics

REVIEW OF THE LITERATURE

Number of studies were analysed as part of the literature review. All relevant findings were then classified according to the following themes: effectiveness of EWS for decreasing the rates of adverse events, level of staff compliance with the EWS systems, failure to recognise abnormal values, not actioning escalation of care.

Effectiveness of EWS for decreasing the rates of adverse events

The literature is divided on whether these systems are beneficial to the health care. Some of the studies found that EWS did not decrease mortality rates or hospital stay (Freebairn, 2013; Johnstone, Rattray, & Myers, 2007; Mohammed, Hayton, Clements, Smith, & Prytherch, 2009). According to Freebairn (2013) evaluation of 73 000 in hospital deaths, two years post implementation of EWS systems in Victoria did not show any decrease of the mortality rate. Among these studies the main reason for failure was found to be variable errors in implementing the system (Johnstone et al., 2007; Mohammed et al., 2009).

On the other hand, ten of the studies found that routine use of an adequate EWS system was an effective way to detect deviations in patients’ health condition(Ansell et al., 2015; Cherry & Jones, 2015; Drower, McKeany, Jogia, & Jull, 2013; Georgaka et al., 2012; Groarke et al., 2008; Kyriacos et al., 2011; Massey et al., 2008; Rattray et al., 2011; Salt, 2013; Wood et al., 2015b). Cherry and Jones, (2015) concluded that if the system guidelines were followed as recommended this would result in prompt recognition in 66% of the deteriorating patients. This is supported by another study (Groarke et al., 2008) that found that signs of deterioration are present in 85% of the ward patients and adequate use of EWS can be highly beneficial for these patients. Furthermore, study by Drower et al., (2013) compared the results of cardiac arrests pre and post implementation of EWS in New Zealand hospital. This showed 60% decrease in cardiac arrest cases post implementation of EWS systems.

Level of staff compliance with the EWS system

A number of studies found that EWS systems which were potentially highly beneficial were compromised due to nurses’ inability to recognise their importance (Ansell et al., 2015; Cherry & Jones, 2015; Groarke et al., 2008; Wood et al., 2015b). The main reason found in the studies for this lack of recognition was nurses believing that their critical thinking skills were sufficient for the detection of relevant changes in patient health status (Ansell et al., 2015). Moreover, nurses were found to be reluctant to use the EWS systems because they considered them to not be beneficial for improving patients’ outcomes. Study by Wood et al., (2015b) outlined that 45% of the interviewed nurses were finding the systems impractical and unnecessary increase in their workload. In addition, some nurses stated that fatigue and lack of time is the main reason behind partial compliance with the system (Georgaka et al., 2012). It was also found that a significant proportion of the healthcare workers were failing to completely follow the prescribed protocols (Cherry & Jones, 2015; Higgins et al., 2008; McGaughey et al., 2010). As a result, crucial physiological observation was being only partially recorded or not being added to the final score (Johnstone et al., 2007; Mandy Odell, 2015; Preston & Flynn, 2010). Research by Morris and Davis (2010) including 12 patients on an acute ward, found that the heart rate was the only physiological parameter from EWS measured for all patients. In comparison, neurological observation was recorded only for 42% of the patients.

Failure to recognise abnormal values

Nurses’ ability to recognise and act upon changes in patients’ health status is essential for providing appropriate level of care (Chua, Mackey, Ng, & Liaw, 2013; M. Odell et al., 2009). Detectable signs of decline in patients’ health are present at least 6 to 8 hours before an adverse event occurs (Osborne, Douglas, Reid, Jones, & Gardner, 2015; Zimlichman et al., 2012). This provides sufficient time-frame for adequate intervention (Duncan et al., 2012; Pantazopoulos et al., 2012). Although EWS were designed to assist nurses in recognising abnormal values, studies have found that in practice there are many instances where nurses used the system without interpreting the values (Cherry & Jones, 2015; Higgins et al., 2008; Morris & Davies, 2010). Some of the reasons behind this were: lack of knowledge (Johnstone et al., 2007; Massey et al., 2008) , skills (M. Odell et al., 2009) and confidence (Morris & Davies, 2010). All this led to missed warning signs (Kyriacos et al., 2011; Mandy Odell, 2015). One sensitive but often excluded pathophysiological parameter was respiratory rate. Nurses were found to underestimate the value of this often first indicator of deterioration (Ansell et al., 2015). Georgaka et al., (2012) revealed that interviewed nurses believed that intuition and critical thinking skills were more beneficial for recognising clinical deterioration than EWS systems in place. On contrary, one study by Rattray et al., (2011)found that nurses were able to recognise signs of deterioration promptly once they combined the results gained from EWS systems with their acquired knowledge and critical thinking skills.

Escalation of care

Failing to report abnormal vital signs and escalate the care will most likely lead to major adverse events (Higgins et al., 2008; M. Odell et al., 2009). Studies show a treatment delay of between 1 and 3 hours, which is an extremely dangerous length of time for fragile patients (Kyriacos et al., 2011). In addition, study by Wood et al. (2015b) identified that nurses actioned escalation of care in only 22% of deteriorating patients on the ward. This was supported in two other studies that also found that nursing staff was hesitant to report the deterioration and initiate escalation of care (M. Odell et al., 2009; Preston & Flynn, 2010). Nurses reported barriers to reaching medical officers to review the patient (Cherry & Jones, 2015). Meanwhile, junior nurses reported having their concerns dismissed by senior staff (Wood et al., 2015a). Miscommunication amongst staff members (Mandy Odell, 2015) and imbalance between scoring system results and the clinical presentation of the patient (Preston & Flynn, 2010) were other reasons given. On the other hand, study by Rattray et al., (2011) found that prompt escalation of care for deteriorating patients is possible. This requires precisely defined guidelines for actioning an escalation of care and time frame in which senior medical staff is required to respond to the call.

RELEVANCE TO THE CLINICAL PRACTICE

This literature review paper demonstrated several relevant implications for the clinical practice and nursing profession. It was found that effectiveness of EWS systems is determined by the human factor using these systems. Collecting and documenting the physiological parameters in a routine manner was not sufficient enough to improve patients’ outcomes (Georgaka et al., 2012). Furthermore, critical thinking skills and relevant knowledge regarding the pathophysiological changes in the human body were imperative. Obtaining the information but not understanding its value or not escalating the care in adequate time frame can lead to catastrophic results (Mullany et al., 2016).

In order to maximise the benefits of EWS systems several interventions could be developed. Health care workers using the EWS can be consulted and allowed to express their concerns or present the challenges they face while using the system. Literature review determined that there is a higher instance of compliance with the system once staff members understand the necessity and benefits of the current EWS system in use (Wood et al., 2015b) Continuous education sessions that will improve the gaps in the knowledge among nursing staff can be highly beneficial. This is substantial for junior nurses and nursing students (Higgins et al., 2008; McCallum et al., 2013). Quite often they are the ones struggling to interpret the correlation between the recorded observation (McGaughey et al., 2010). Competency testing post education will provide more information about further areas of improvement (Morris & Davies, 2010). Regular evaluation and audits of the practice and can also provide further directions for improvement (Hammond et al.). Consistency in documentation process can increase compliance and limit potential confusion. Health care sector should focus on universal EWS systems used on national level (Christofidis et al., 2015). Another suggestion that literature review provided was implementing electronic EWS system as more efficient and effective tool in the workplace (Mohammed et al., 2009).

Finally, there is necessity of improving communication between junior and senior staff members. Nurses should be encouraged to report any concerns they have without the fear of being judged (Hammond et al.). All members of the multidisciplinary health care team need to work together to provide best possible care to their patients.

CONCLUSION

The EWS systems were designed and implemented in the health care sector to support both nursing and medical staff in early detection of clinically deteriorating patients. Presented literature review outlined that there are different views regarding the benefits of EWS and its positive correlation to decreased mortality in the hospital settings. Several obstacles are recognised across most of the studies and all involve the human factor as a main barrier for effectiveness of the EWS systems. Some of the hurdles restricting the benefits of the EWS systems can be decreased by nurses’ compliance with the system and combination of routing observation and critical thinking skills. This will enable timely escalation of care once deterioration is needed. It is necessary that all members of the multidisciplinary team work together for greater benefits of the patient. This can be achieved by regular audit and modification of the systems and continuous education for the staff members.

Ansell, H., Meyer, A., & Thompson, S. (2015). Technology and the issues facing nursing assessment. British Journal of Nursing, 24(17), 886-889. doi:10.12968/bjon.2015.24.17.886

Australian Commission on Safety and Quality in Health Care. (2012). National Safety and Quality Health Service Standards. Sydney.

Cherry, P. G., & Jones, C. P. (2015). Attitudes of nursing staff towards a Modified Early Warning System. British Journal of Nursing, 24(16), 812-818. doi:10.12968/bjon.2015.24.16.812

Christofidis, M. J., Hill, A., Horswill, M. S., & Watson, M. O. (2015). Less is more: the design of early-warning scoring systems affects the speed and accuracy of scoring. Journal of Advanced Nursing, 71(7), 1573-1586. doi:10.1111/jan.12618

Chua, W. L., Mackey, S., Ng, E. K. C., & Liaw, S. Y. (2013). Front line nurses’ experiences with deteriorating ward patients: a qualitative study. International Nursing Review, 60(4), 501-509. doi:10.1111/inr.12061

Drower, D., McKeany, R., Jogia, P., & Jull, A. (2013). Evaluating the impact of implementing an early warning score system on incidence of in-hospital cardiac arrest. New Zealand Medical Journal, 126(1385), 26-34.

Duncan, K., McMullan, C., & Mills, B. (2012). Early warning systems. Nursing, 42(2), 38.

Freebairn, R. (2013). ‘Easy to cure but difficult to detect’–the case for early warning systems in the acute hospital. New Zealand Medical Journal, 126(1385), 9-12.

Georgaka, D., Mparmparousi, M., & Vitos, M. (2012). Early Warning Systems. Hospital Chronicles, 7(1 Sup), 37-43.

Groarke, J. D., Gallagher, J., Stack, J., Aftab, A., Dwyer, C., McGovern, R., & Courtney, G. (2008). Use of an admission early warning score to predict patient morbidity and mortality and treatment success. Emergency Medicine Journal, 25(12), 803-806. doi:10.1136/emj.2007.051425

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Hammond, N. E., Spooner, A. J., Barnett, A. G., Corley, A., Brown, P., & Fraser, J. F. The effect of implementing a modified early warning scoring (MEWS) system on the adequacy of vital sign documentation. Australian Critical Care, 26(1), 18-22. doi:10.1016/j.aucc.2012.05.001

Higgins, Y., Maries-Tillott, C., Quinton, S., & Richmond, J. (2008). Promoting patient safety using an early warning scoring system. Nursing Standard, 22(44), 35-40.

Johnstone, C. C., Rattray, J., & Myers, L. (2007). Physiological risk factors, early warning scoring systems and organizational changes. Nursing in Critical Care, 12(5), 219-224.

Kyriacos, U., Jelsma, J., & Jordan, S. (2011). Monitoring vital signs using early warning scoring systems: a review of the literature. Journal of Nursing Management, 19(3), 311-330. doi:10.1111/j.1365-2834.2011.01246.x

Massey, D., Aitken, L. M., & Wendy, C. (2008). What factors influence suboptimal ward care in the acutely ill ward patient? Australian critical care : official journal of the Confederation of Australian Critical Care Nurses, 21(3), 127. doi:10.1016/j.aucc.2008.05.051

McCallum, J., Duffy, K., Hastie, E., Ness, V., & Price, L. (2013). Developing nursing students’ decision making skills: Are early warning scoring systems helpful? Nurse Education in Practice, 13(1), 1-3. doi:10.1016/j.nepr.2012.09.011

McGaughey, J., Blackwood, B., O’Halloran, P., Trinder, T. J., & Porter, S. (2010). Realistic evaluation of early warning systems and the acute life-threatening events — recognition and treatment training course for early recognition and management of deteriorating ward-based patients: research protocol. Journal of Advanced Nursing, 66(4), 923-932. doi:10.1111/j.1365-2648.2009.05257.x

Mohammed, M. A., Hayton, R., Clements, G., Smith, G., & Prytherch, D. (2009). Improving accuracy and efficiency of early warning scores in acute care. British Journal of Nursing, 18(1), 18-24.

Morris, A., & Davies, K. (2010). Early warning scoring systems: observation of care in practice. British Journal of Nursing, 19(18), 1180-1184.

Mullany, D. V., Ziegenfuss, M., Goleby, M. A., & Ward, H. E. (2016). Improved hospital mortality with a low MET dose: the importance of a modified early warning score and communication tool. Anaesthesia & Intensive Care, 44(6), 734-741.

Odell, M. (2015). Detection and management of the deteriorating ward patient: an evaluation of nursing practice. Journal of Clinical Nursing, 24(1/2), 173-182. doi:10.1111/jocn.12655

Odell, M., Victor, C., & Oliver, D. (2009). Nurses’ role in detecting deterioration in ward patients: systematic literature review. Journal of Advanced Nursing, 65(10), 1992-2006. doi:10.1111/j.1365-2648.2009.05109.x

Osborne, S., Douglas, C., Reid, C., Jones, L., & Gardner, G. (2015). The primacy of vital signs – Acute care nurses’ and midwives’ use of physical assessment skills: A cross sectional study. International Journal of Nursing Studies, 52(5), 951-962. doi:10.1016/j.ijnurstu.2015.01.014

Pantazopoulos, I., Tsoni, A., Kouskouni, E., Papadimitriou, L., Johnson, E. O., & Xanthos, T. (2012). Factors influencing nurses’ decisions to activate medical emergency teams. Journal of Clinical Nursing, 21(17/18), 2668-2678. doi:10.1111/j.1365-2702.2012.04080.x

Preston, R., & Flynn, D. (2010). Observations in acute care: evidence-based approach to patient safety. British Journal of Nursing, 19(7), 442-447.

Rattray, J. E., Lauder, W., Ludwick, R., Johnstone, C., Zeller, R., Winchell, J., . . . Smith, A. (2011). Indicators of acute deterioration in adult patients nursed in acute wards: a factorial survey. Journal of Clinical Nursing, 20(5/6), 723-732. doi:10.1111/j.1365-2702.2010.03567.x

Salt, L. (2013). EVALUATING CRITICAL CARE OUTREACH AND THE EARLY WARNING SCORE TOOL — THE WARD NURSE’S VIEWPOINT. Kai Tiaki Nursing Research, 4(1), 17-24.

Stark, A. P., Maciel, R. C., Sheppard, W., Sacks, G., & Hines, O. J. (2015). An Early Warning Score Predicts Risk of Death after In-hospital Cardiopulmonary Arrest in Surgical Patients. American Surgeon, 81(10), 916-921.

Waldie, J., Day, T., & Tee, S. (2016). Patient safety in acute care: are we going around in circles? British Journal of Nursing, 25(13), 747-751.

Wood, S. D., Candeland, J. L., Dinning, A., Dow, S., Hunkin, H., McHale, S., . . . Taylor, N. (2015a). Our approach to changing the culture of caring for the acutely unwell patient at a large UK teaching hospital: A service improvement focus on Early Warning Scoring tools. Intensive & Critical Care Nursing, 31(2), 106-115. doi:10.1016/j.iccn.2014.11.006

Wood, S. D., Candeland, J. L., Dinning, A., Dow, S., Hunkin, H., McHale, S., . . . Taylor, N. (2015b). Our approach to changing the culture of caring for the acutely unwell patient at a large UK teaching hospital: A service improvement focus on Early Warning Scoring tools. Intensive & Critical Care Nursing, 31(2), 106-115. doi:10.1016/j.iccn.2014.11.006

Zimlichman, E., Szyper-Kravitz, M., Shinar, Z., Klap, T., Levkovich, S., Unterman, A., . . . Shoenfeld, Y. (2012). Early recognition of acutely deteriorating patients in non-intensive care units: Assessment of an innovative monitoring technology. Journal of Hospital Medicine, 7(8), 628-633. doi:10.1002/jhm.1963

Ilinka Risteska-Budzhakovska

INTRODUCTION

Acute health care facilities are faced with the considerable challenge of providing effective and efficient care for the increased number of patients that are suffering from complex co-morbidities (Massey, Aitken, & Wendy, 2008). . In addition, research found that this can be a challenge for inexperienced staff that are less able to recognise signs of deterioration in a timely manner. As a result, unrecognised clinical deterioration of acute ward patients continues to be one of the crucial issues in the health care sector (M. Odell, Victor, & Oliver, 2009; Preston & Flynn, 2010; Waldie, Day, & Tee, 2016; Zimlichman et al., 2012).

The problem of unrecognised clinical deterioration leads to increased number adverse events such as: avoidable cardiac arrests, unnecessary re-admissions to emergency wards and morbidity and mortality. The problem also results in an increased financial burden to the health care sector and loss of efficiency(Ansell, Meyer, & Thompson, 2015; Kyriacos, Jelsma, & Jordan, 2011; Rattray et al., 2011; Waldie et al., 2016; Wood et al., 2015a).

The National Safety and Quality Health Service Standards(NSQHS) by the Australian Commission on Safety and Quality in Health Care (ACSQHC) were designed with a main goal to improve the health care outcomes for the patients of health care services through the provision of best possible care. Standard 9 of the NSQHS outlines the importance of timely identification and response to clinical deterioration of acutely unwell patients (Australian Commission on Safety and Quality in Health Care, 2012).

BACKGROUND

Many adverse events in the healthcare can be avoided once human errors are minimised (Georgaka, Mparmparousi, & Vitos, 2012). Various policies, procedures and systems have been established around the world for the timely detection of acutely deteriorating patients and improved survival rates (Duncan, McMullan, & Mills, 2012; Freebairn, 2013; Mullany, Ziegenfuss, Goleby, & Ward, 2016). One of the systems in use is Early Warning Scores (EWS). EWS systems were developed to provide set parameters for the physiological changes that take place during acute patient deterioration (Higgins, Maries-Tillott, Quinton, & Richmond, 2008; McCallum, Duffy, Hastie, Ness, & Price, 2013; Morris & Davies, 2010). The original EWS system was created in Liverpool, Australia (McCallum et al., 2013). Not long after variations began being used in many countries including: New Zealand (Freebairn, 2013), England (Morris & Davies, 2010), Ireland (McGaughey, Blackwood, O’Halloran, Trinder, & Porter, 2010), and USA (Stark, Maciel, Sheppard, Sacks, & Hines, 2015). EWS system used in Australia incorporates parameters of: respiratory rate, temperature, blood pressure, heart rate, urine output, pain and conscious level. All parameters are colour coded so as to provide guidance for the necessity of staff intervention once abnormal values are detected (Christofidis, Hill, Horswill, & Watson, 2015).

AIM: To evaluate the effect of EWS systems on decreasing the rates of fatal adverse events among deteriorating patients as well as potential factors that inhibit or facilitate effectiveness of these systems. This will be accomplished by reviewing the available literature on these topics

REVIEW OF THE LITERATURE

Number of studies were analysed as part of the literature review. All relevant findings were then classified according to the following themes: effectiveness of EWS for decreasing the rates of adverse events, level of staff compliance with the EWS systems, failure to recognise abnormal values, not actioning escalation of care.

Effectiveness of EWS for decreasing the rates of adverse events

The literature is divided on whether these systems are beneficial to the health care. Some of the studies found that EWS did not decrease mortality rates or hospital stay (Freebairn, 2013; Johnstone, Rattray, & Myers, 2007; Mohammed, Hayton, Clements, Smith, & Prytherch, 2009). According to Freebairn (2013) evaluation of 73 000 in hospital deaths, two years post implementation of EWS systems in Victoria did not show any decrease of the mortality rate. Among these studies the main reason for failure was found to be variable errors in implementing the system (Johnstone et al., 2007; Mohammed et al., 2009).

On the other hand, ten of the studies found that routine use of an adequate EWS system was an effective way to detect deviations in patients’ health condition(Ansell et al., 2015; Cherry & Jones, 2015; Drower, McKeany, Jogia, & Jull, 2013; Georgaka et al., 2012; Groarke et al., 2008; Kyriacos et al., 2011; Massey et al., 2008; Rattray et al., 2011; Salt, 2013; Wood et al., 2015b). Cherry and Jones, (2015) concluded that if the system guidelines were followed as recommended this would result in prompt recognition in 66% of the deteriorating patients. This is supported by another study (Groarke et al., 2008) that found that signs of deterioration are present in 85% of the ward patients and adequate use of EWS can be highly beneficial for these patients. Furthermore, study by Drower et al., (2013) compared the results of cardiac arrests pre and post implementation of EWS in New Zealand hospital. This showed 60% decrease in cardiac arrest cases post implementation of EWS systems.

Level of staff compliance with the EWS system

A number of studies found that EWS systems which were potentially highly beneficial were compromised due to nurses’ inability to recognise their importance (Ansell et al., 2015; Cherry & Jones, 2015; Groarke et al., 2008; Wood et al., 2015b). The main reason found in the studies for this lack of recognition was nurses believing that their critical thinking skills were sufficient for the detection of relevant changes in patient health status (Ansell et al., 2015). Moreover, nurses were found to be reluctant to use the EWS systems because they considered them to not be beneficial for improving patients’ outcomes. Study by Wood et al., (2015b) outlined that 45% of the interviewed nurses were finding the systems impractical and unnecessary increase in their workload. In addition, some nurses stated that fatigue and lack of time is the main reason behind partial compliance with the system (Georgaka et al., 2012). It was also found that a significant proportion of the healthcare workers were failing to completely follow the prescribed protocols (Cherry & Jones, 2015; Higgins et al., 2008; McGaughey et al., 2010). As a result, crucial physiological observation was being only partially recorded or not being added to the final score (Johnstone et al., 2007; Mandy Odell, 2015; Preston & Flynn, 2010). Research by Morris and Davis (2010) including 12 patients on an acute ward, found that the heart rate was the only physiological parameter from EWS measured for all patients. In comparison, neurological observation was recorded only for 42% of the patients.

Failure to recognise abnormal values

Nurses’ ability to recognise and act upon changes in patients’ health status is essential for providing appropriate level of care (Chua, Mackey, Ng, & Liaw, 2013; M. Odell et al., 2009). Detectable signs of decline in patients’ health are present at least 6 to 8 hours before an adverse event occurs (Osborne, Douglas, Reid, Jones, & Gardner, 2015; Zimlichman et al., 2012). This provides sufficient time-frame for adequate intervention (Duncan et al., 2012; Pantazopoulos et al., 2012). Although EWS were designed to assist nurses in recognising abnormal values, studies have found that in practice there are many instances where nurses used the system without interpreting the values (Cherry & Jones, 2015; Higgins et al., 2008; Morris & Davies, 2010). Some of the reasons behind this were: lack of knowledge (Johnstone et al., 2007; Massey et al., 2008) , skills (M. Odell et al., 2009) and confidence (Morris & Davies, 2010). All this led to missed warning signs (Kyriacos et al., 2011; Mandy Odell, 2015). One sensitive but often excluded pathophysiological parameter was respiratory rate. Nurses were found to underestimate the value of this often first indicator of deterioration (Ansell et al., 2015). Georgaka et al., (2012) revealed that interviewed nurses believed that intuition and critical thinking skills were more beneficial for recognising clinical deterioration than EWS systems in place. On contrary, one study by Rattray et al., (2011)found that nurses were able to recognise signs of deterioration promptly once they combined the results gained from EWS systems with their acquired knowledge and critical thinking skills.

Escalation of care

Failing to report abnormal vital signs and escalate the care will most likely lead to major adverse events (Higgins et al., 2008; M. Odell et al., 2009). Studies show a treatment delay of between 1 and 3 hours, which is an extremely dangerous length of time for fragile patients (Kyriacos et al., 2011). In addition, study by Wood et al. (2015b) identified that nurses actioned escalation of care in only 22% of deteriorating patients on the ward. This was supported in two other studies that also found that nursing staff was hesitant to report the deterioration and initiate escalation of care (M. Odell et al., 2009; Preston & Flynn, 2010). Nurses reported barriers to reaching medical officers to review the patient (Cherry & Jones, 2015). Meanwhile, junior nurses reported having their concerns dismissed by senior staff (Wood et al., 2015a). Miscommunication amongst staff members (Mandy Odell, 2015) and imbalance between scoring system results and the clinical presentation of the patient (Preston & Flynn, 2010) were other reasons given. On the other hand, study by Rattray et al., (2011) found that prompt escalation of care for deteriorating patients is possible. This requires precisely defined guidelines for actioning an escalation of care and time frame in which senior medical staff is required to respond to the call.

RELEVANCE TO THE CLINICAL PRACTICE

This literature review paper demonstrated several relevant implications for the clinical practice and nursing profession. It was found that effectiveness of EWS systems is determined by the human factor using these systems. Collecting and documenting the physiological parameters in a routine manner was not sufficient enough to improve patients’ outcomes (Georgaka et al., 2012). Furthermore, critical thinking skills and relevant knowledge regarding the pathophysiological changes in the human body were imperative. Obtaining the information but not understanding its value or not escalating the care in adequate time frame can lead to catastrophic results (Mullany et al., 2016).

In order to maximise the benefits of EWS systems several interventions could be developed. Health care workers using the EWS can be consulted and allowed to express their concerns or present the challenges they face while using the system. Literature review determined that there is a higher instance of compliance with the system once staff members understand the necessity and benefits of the current EWS system in use (Wood et al., 2015b) Continuous education sessions that will improve the gaps in the knowledge among nursing staff can be highly beneficial. This is substantial for junior nurses and nursing students (Higgins et al., 2008; McCallum et al., 2013). Quite often they are the ones struggling to interpret the correlation between the recorded observation (McGaughey et al., 2010). Competency testing post education will provide more information about further areas of improvement (Morris & Davies, 2010). Regular evaluation and audits of the practice and can also provide further directions for improvement (Hammond et al.). Consistency in documentation process can increase compliance and limit potential confusion. Health care sector should focus on universal EWS systems used on national level (Christofidis et al., 2015). Another suggestion that literature review provided was implementing electronic EWS system as more efficient and effective tool in the workplace (Mohammed et al., 2009).

Finally, there is necessity of improving communication between junior and senior staff members. Nurses should be encouraged to report any concerns they have without the fear of being judged (Hammond et al.). All members of the multidisciplinary health care team need to work together to provide best possible care to their patients.

CONCLUSION

The EWS systems were designed and implemented in the health care sector to support both nursing and medical staff in early detection of clinically deteriorating patients. Presented literature review outlined that there are different views regarding the benefits of EWS and its positive correlation to decreased mortality in the hospital settings. Several obstacles are recognised across most of the studies and all involve the human factor as a main barrier for effectiveness of the EWS systems. Some of the hurdles restricting the benefits of the EWS systems can be decreased by nurses’ compliance with the system and combination of routing observation and critical thinking skills. This will enable timely escalation of care once deterioration is needed. It is necessary that all members of the multidisciplinary team work together for greater benefits of the patient. This can be achieved by regular audit and modification of the systems and continuous education for the staff members.

Ansell, H., Meyer, A., & Thompson, S. (2015). Technology and the issues facing nursing assessment. British Journal of Nursing, 24(17), 886-889. doi:10.12968/bjon.2015.24.17.886

Australian Commission on Safety and Quality in Health Care. (2012). National Safety and Quality Health Service Standards. Sydney.

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