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. 2024 May 10;81(9):5342–5352. doi: 10.1111/jan.16235

Nurse by numbers: The impact of early warning systems on nurses' higher‐order thinking, a quantitative study

Marie Danielle Le Lagadec 1,✉, Deb Massey 2, Amy‐Louise Byrne 1, Justine Connor 1, Tracy Flenady 1
PMCID: PMC12371781  PMID: 38733070

Abstract

Aim

To evaluate registered nurses' perceptions of whether the mandated use of the early warning system vital signs tool impacts the development of nurses' higher‐order thinking skills.

Design

A concurrent mixed methods study design.

Method

Using an online survey, registered nurses' perceptions were elucidated on whether early warning system algorithmic tools affected the development of their higher‐order thinking. Likert‐type matrix questions with additional qualitative fields were used to obtain information on nurse's perceptions of the tool's usefulness, clinical confidence in using the tool, compliance with escalation protocols, work environment and perceived compliance barriers.

Results

Most of the 305 (91%) participants included in the analysis had more than 5 years of nursing experience. Most nurses supported the early warning tool and were happy to comply with escalation protocols if the early warning score concurred with their assessment of the patient (63.6%). When the score and the nurse's higher‐order thinking did not align, some had the confidence to override the escalation protocol (40.0%), while others omitted (69.4%) or inaccurately documented vital signs (63.3%) to achieve the desired score. Very few nurses (3.6%) believe using early warning tools did not impede the development of higher‐order thinking.

Conclusion

Although experienced nurses appreciate the support of early warning tools, most value patient safety above the tools and rely on their higher‐order thinking. The sustained development and use of nurses' higher‐order thinking should be encouraged, possibly by adding a critical thinking criterion to existing algorithmic tools.

Impact

The study has implications for all nurses who utilize algorithmic tools, such as early warning systems, in their practice. Relying heavily on algorithmic tools risks impeding the development of higher‐order thinking. Most experienced nurses prioritize their higher‐order thinking in decision‐making but believe early warning tools can impede higher‐order thinking.

Patient or Public Contribution

Registered nurses participated as survey respondents.

Keywords: critical thinking, decision‐making tools, early warning system, higher‐order thinking, nurses

1. INTRODUCTION

By recognizing and responding to patient deterioration, nurses play a pivotal role in driving clinical excellence and patient safety (Considine & Currey, 2015). Patient safety is a key indicator of healthcare services' performance; therefore, recognizing and responding to acute deterioration has been included as one of the Australian National Safety and Quality in Health Standards, Standard 8 (Australian Commission on Safety and Quality in Health Care, 2017). Healthcare organizations must provide staff with appropriate education and support to ensure adequate care for deteriorating patients (Australian Commission on Safety and Quality in Health Care, 2017) and most have opted to adopt early warning systems (EWSs). EWSs are algorithmic decision‐making tools that provide healthcare workers with an objective, quantifiable means of identifying and responding to deteriorating patients (Australian Commission on Safety and Quality in Health Care, 2017). Using standardized protocols, the EWS guides nursing actions based on patient's level of vital sign derangement, which is numerically categorized (Le Lagadec & Dwyer, 2017).

Becoming a safe clinical nurse requires proficient patient assessment skills and well‐developed higher‐order thinking skills, such as clinical judgement, critical thinking and clinical reasoning (Connor et al., 2022). Benner et al. (2008) elaborate by stating that nurses require multiple thinking strategies, including critical thinking, clinical judgement, diagnostic reasoning, deliberative rationality, scientific reasoning, dialogue, argument and creative thinking, to be effective practitioners. Nurses are required to make safe, accurate and timely decisions to ensure patient safety (Reay et al., 2016). Higher‐order thinking develops over time with clinical exposure. Tanner (2006) describes ‘thinking like a nurse’ as noticing, interpreting, responding and reflecting. Developing higher‐order thinking skills is complex and requires a supportive environment, clinical exposure and time. For this study, higher‐order thinking refers to the complex cognitive skills that include but are not limited to, clinical judgement, critical thinking, clinical reasoning and clinical decision‐making.

Recognizing deteriorating patients is a complex learned skill that requires clinical exposure and education (Grant, 2019). Concerns have been raised that overreliance on a numerical score generated by an EWS may impact nurses' ability to develop higher‐order thinking skills (Elliott et al., 2015; Kellett & Sebat, 2017), resulting in a nursing‐by‐number culture. However, there is a paucity of research on the impact of EWS on the development of higher‐order thinking skills. This is a distinct gap in knowledge given the ever‐increasing use of algorithmic tools in healthcare coupled with the expectation that all nurses possess well‐developed higher‐order thinking skills, creating tension and conflict in relation to nurses' scope of practice.

1.1. Background

With the ageing global population and the acuity of hospitalized patients, nursing practices are becoming increasingly complex. Many algorithmic tools, such as the EWS, have been implemented in healthcare settings to enhance patient safety. The EWS supports and guides nurses in their clinical decision‐making by promoting the recognition of deterioration and appropriate escalation of care. Since their introduction over three decades ago, EWSs have been internationally accepted and are mandated in all Australian healthcare facilities (Australian Commission on Safety and Quality in Health Care, 2017). Despite conflicting evidence about their effectiveness, EWSs have become a core component of contemporary nursing practice and are introduced to novice nurses during their undergraduate studies (Saab et al., 2017). The EWS, based on patients' vital signs, relies on pattern recognition to help nurses recognize the deteriorating patient (Elliott et al., 2015). This is arguably a limitation of the EWS since the pattern of vital sign derangement during a deterioration event has not been well researched (Massey et al., 2010). An aggregated score based on the level of vital signs derangement is linked to an EWS escalation protocol, which guides the nursing action (Le Lagadec & Dwyer, 2017). Nurses are expected to comply with the EWS guidelines and escalation protocol per hospital policies and the Australian National Safety and Quality in Health Standards, Standard 8 (Australian Commission on Safety and Quality in Health Care, 2017).

Since the introduction of EWS, studies have shown that the incidence of preventable in‐hospital mortality and severe adverse events has decreased significantly (Credland et al., 2021). However, there is much speculation that using algorithmic tools, such as the EWS, will lead to a box‐ticking, task‐focused nursing culture (Nielsen et al., 2020). To be safe practitioners, nurses must employ various skills involving physical patient assessments and applying their higher‐order thinking to fully assimilate the information gathered and plan appropriate nursing interventions (Connor et al., 2022). Since algorithmic tools are introduced to novice nurses in their undergraduate studies, there are concerns that the next generation of nurses will not be encouraged to develop their higher‐order thinking skills. This may dilute the nurses' scope of practice, negatively impacting patient safety (Elliott et al., 2015). Therefore, investigating the relationship between EWSs and higher‐order thinking in nursing is essential. Several studies have focused on how nurses utilize the EWS and, in so doing, have explored clinical reasoning and critical thinking (Elliott et al., 2015; Fox & Elliott, 2015). These studies utilize qualitative methodologies, providing valuable insights into the nuances of nursing practice. Our paper extends this knowledge by affording statistically significant associations that may inform evidence‐based practice and healthcare policy. We provide statistical data on the nurses' perceptions of how using EWSs impacts their and their peers' higher‐order thinking skills. The knowledge generated from our study may help to inform existing nursing practice and the undergraduate nursing curriculum. Since the healthcare industry is increasingly relying on algorithmic tools, the results of our study may extend beyond EWS and find application in other areas of healthcare.

2. METHOD

2.1. Study aim

We aim to evaluate registered nurses' perceptions of whether the mandated use of EWS vital signs tools impacts the development of higher‐order thinking.

2.2. Study design

This concurrent mixed methods study elicited Australian nurses' perceptions of the impact of the mandated use of EWS tools on the development of higher‐order thinking skills. The self‐rated Qualtrics survey collected qualitative and quantitative data using a tool designed by a human factors specialist. To ensure the quality of the study, we followed the ‘STROBE checklist of items that should be included in reports of cross‐sectional studies’ (http://www.plosmedicine.org).

2.3. Participants

Australian registered nurses who were university‐trained or similar and utilized EWS tools in their clinical practice were invited to participate in the study. Unlicensed nursing assistants and enrolled nurses with a diploma in nursing were excluded from the study. Although unlicensed nursing assistants and enrolled nurses utilize EWS tools, their scope of practice is limited, and the decision‐making responsibility resides with the registered nurse (Nursing and Midwifery Board of Australia, 2022). Participation was open to public and private sector nurses in metropolitan, regional and rural healthcare facilities. Purposive sampling using a snowballing method was employed, and recruitment was executed via nurse‐focused social media, Facebook and Twitter.

Approximately 361,350 nurses are registered in Australia, of which about 60% work in acute care settings (Department of Health and Aged Care, 2022). A sample size of approximately 384 online survey participants is required to provide statistical rigour (5% margin of error, 95% CI; Calculator.net, 2024). However, previous similar studies have utilized sample sizes of 100 to 150 participants and were thought to provide sufficient rigour for descriptive statistics (Ebert et al., 2022; Fox & Elliott, 2015). We aim to achieve a sample size of 300 participants, resulting in a 5.5% margin of error at a 95% confidence interval (Calculator.net, 2024).

2.4. Data collection

The online survey, hosted on Qualtrics, was developed by a human factors specialist and successfully used in previous studies (Dwyer et al., 2019; Ebert et al., 2022). The anonymous survey was open for 3 months, from January to March 2023, and included 11 demographic questions and ten 5‐point matrix Likert‐type questions related to the use of the EWS tool. Each matrix question comprised a series of sub‐questions and a qualitative field allowing nurses to record their thoughts and perceptions. The survey focused on the nurses' perceptions of the usefulness of the EWS tool, their clinical confidence in using the tool, compliance with the EWS protocol, their work environment and perceived barriers to EWS protocol compliance. The underlying intention of the survey was to evaluate if nurses believed the EWS tools encouraged them to utilize higher‐order thinking skills. The survey did not focus on any specific EWS tool, given that Australia does not have a standardized national EWS. The survey was pilot tested by 10 registered nurses, and the questions were reviewed for content validation and refined before the survey's launch.

2.5. Survey tool internal reliability

The original survey tool (Dwyer et al., 2019) was employed in our study in a slightly different context than originally intended. Therefore, it required internal reliability testing. Each of the 10 matrix Likert‐type questions focused on a separate sociocultural aspect of employing EWS and were therefore independently tested for internal reliability using the Cronbach alpha test. Since some sub‐questions were negatively phrased, reverse coding was required before analysis. Nine of the matrixes had Cronbach alpha scores ranging between 0.76 and 0.936. An alpha score above 0.7 is regarded as reliable (Tavakol & Dennick, 2011). One of the matrix questions (Q24, Appendix 1) produced a poor internal reliability score (0.513) and was not reported on in the study.

2.6. Data analysis

The survey generated 1200 responses. In the first screening, 207 participants were eliminated (four did not consent to participate, 87 did not use EWS in their clinical practice, 17 were not registered nurses, and 99 completed less than 50% of the survey). Many of the 993 remaining participants demonstrated factors consistent with bot‐generated responses: high similarity in qualitative phrasing, rapid completion time and reCAPTCHA score <0.5. This led to a further 688 eliminations, resulting in 305 participants being included in the study. Since the survey was anonymous, it was impossible to verify the participants' credentials. The total number of responses and the resulting participants included in the data analysis are disclosed in the interest of research transparency since selective reporting may be considered academic misconduct (Noyes, 2023).

The data were analysed using IBM SPSS v 26 software. Missing data was not inferred but was omitted from the analysis. Descriptive statistics was used to analyse the demographic data, using means (M), standard deviations (SD) and frequency tables. Since Likert‐type data are always ordinal, descriptive statistics were presented as medians and frequencies. Means and standard deviation were also included to allow comparison with other similar studies (Ebert et al., 2022). Wilcoxon signed‐rank test was used to compare the median of related categorical variables at a 0.05 significance level. Since the data derived from the 305 participants were not normally distributed, the association between the responses and the respondents' demographic variables was ascertained using Spearman's rank‐order correlation. A p‐value ≤.05 was considered statistically significant.

2.7. Ethical considerations

Ethical approval for this study was obtained through the university HREC, application 0023987. Participant consent was conditional to completing the survey.

3. RESULTS

3.1. Demographics

Most of the participants identified as female (94.8%), had postgraduate qualifications (65.1%) and were directly responsible for patient care (clinical ward nurses, 70.3%; Table 1). Most were experienced nurses, with 90.8% having more than 5 years of nursing and 21.3% having been in the nursing workforce for more than 15 years (M = 12.76 years, SD = 8.98, median = 10 years, range = 1–47 years). More than half of the participants worked in metropolitan hospitals (62.3%), reflective of the Australian nursing workforce (Australian Institute of Health and Welfare, 2022). Approximately half of the participants nursed in medical and surgical wards (53.4%).

TABLE 1.

Demographics of participants (n = 305).

Variable Frequency (n) Percentage (%)
Gender (female) 289 94.8
Country of nurse training
Australia 271 88.9
Other 32 10.5
Highest qualification
Undergraduate 104 34.9
Postgraduate 131 43.0
Master degree 66 21.6
PhD 4 0.1
Years of nursing experience
1–5 years 28 9.2
6–10 years 143 46.9
>10 years 134 43.9
Clinical role
Clinical ward nurse 213 70.3
Nurse educator/manager 92 30.4
Work environment
Medical 87 28.5
Surgical 57 18.7
Medical/surgical 19 6.2
Emergency 58 19.0
Other 84 27.6
Employment status
Fulltime 167 54.8
Parttime 73 23.9
Casual/agency 65 21.3
Hospital location
Metropolitan 190 62.3
Regional 103 33.8
Rural/remote 12 3.9
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3.2. EWS education/training belief and work environment

Most participants agreed that they understood the purpose of the EWS (99.3%, n = 298/300), they had received appropriate EWS training (92.7%, n = 280/302), and they valued the training received (88.3%, n = 265/300). The ward nurses had a greater appreciation for the EWS training they received than the managers and clinical educators (Χ 2(2, n = 298) = 13.913, p < .001). However, there were no significant differences in the training satisfaction score between participants from rural, regional and metropolitan hospitals (Χ 2(2, n = 298) = 5.95, p = .203) or between years of experience (r(296) = 0.040, p = .491). Positive staff attitudes are often an indicator of a good work environment (Peyton & Zigarmi, 2021), and in our study, 75.9% (n = 230/303) of participants stated they enjoyed their work (M = 4.09, SD = 0.907, median = 4) and felt part of the team (76.5%, n = 232/303, M = 4.11, SD = 0.878, median = 4). Yet, only 67.9% (n = 206/303) of participants felt valued (M = 3.86, SD = 0.981, median = 4), supported (67.3%, n = 204/303, M = 3.88, SD = 0.681, median = 4) and respected (70.7%, n = 114/303, M = 3.92, SD = 0912, median = 4).

3.3. Participants' view of EWS tools

The participant's opinion of the EWS tool was overwhelmingly positive. Most thought the EWS was an excellent tool that assisted them in identifying deteriorating patients (63.6%, n = 192/302), but they did not perceive that their peers had the same high opinion of the tool (Table 2). When asked if the tool added value to their clinical thinking skills, less than half agreed (47.9%, n = 144/301), the rest were ambivalent (M = 3.39, SD = 1.19, median = 3). There was a negative but significant correlation between the participants' years of experience and their perceptions that EWS valued their clinical thinking skills (r(297) = −0.1432, p = .013). Also, the more experienced nurses responded negatively when asked whether they thought the EWS was just more paperwork (r(294) = −0.117, p = .045).

TABLE 2.

Participants' views and perceptions of peers' views of EWS.

I believe My peers believe p a
Agree/strongly agree (%, n) M SD Median Agree/strongly agree (%) M SD Median
Cronbach alpha coefficient α = 0.84 α = 0.823
The EWS charting system is
1. An excellent tool that aids in the detection of clinical deterioration 63.6% (192/302) 3.71 1.13 4 54.0% (156/289) 3.54 1.06 4 .078
2. A waste of time 32.3% (97/300) 2.70 1.41 2 41.1% (116/282) 3.08 1.24 4 <.001
3. A means of valuing nurses' clinical thinking skills 47.9% (144/301) 3.39 1.19 3 31.8% (90/283) 2.77 1.27 3 <.001
4. Just more paperwork 36.5% (109/299) 2.88 1.40 3 43.3% (122/282) 3.07 1.32 4 .032
5. Clear and concise – easy to use 65.8% (197/301) 3.79 1.06 4 37.7% (106/281) 2.96 1.29 2 <.001
6. Should be accurately completed at each round of observations 74.5% (224/301) 4.08 106 5 64.8% (182/281) 3.86 1.08 4 <.001
7. Something that can be ticked and flicked 13.5% (41/301) 2.17 1.05 2 42.4% (119/281) 3.14 1.21 4 <.001
8. Is important for patients whose condition is deteriorating 70.8% (213/301) 3.99 1.10 4 43.7% (123/281) 3.15 1.29 3 <.001
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Note: Based on a 5‐point Likert scale, 1 = strongly disagree and 5 = strongly agree, for comparative purposes, reverse coding was applied to negatively phrased survey questions.

Abbreviations: EWS, early warning systems; M, mean; SD, standard deviation.

a

p derived from the Wilcoxon signed‐rank test establishing differences between responses for ‘I believe’ and ‘My peers believe’.

3.4. EWS compliance and documentation

Most participants stated that they always, or nearly always (60.0% n = 177/295), comply with EWS documentation requirements (M = 3.41, SD = 1.41, median = 4). However, around two‐thirds of the participants admitted to occasionally omitting vital signs because either they did not think it was necessary or because they judged that including certain vital signs would result in an unwarranted medical patient review (Table 3). Pain score was the most frequently omitted vital signs, with 20.4% (59/288) of respondents saying they rarely charted the pain score. According to participants, the more frequently documented vital signs included blood pressure (58.1%, n = 169/291 of participants stated they always document this vital sign), heart rate (56.5%, n = 165/292) and oxygen saturation (56.2%, n = 164/292). Also, 51.2% (n = 150/293) of participants stated that they always accurately record the respiration rate. The more experienced nurse appeared to have a greater appreciation of the value of accurately documenting respiration rate (r(289) = 0.221, p < .001). Some participants admitted to purposefully recording inaccurate vital sign values either by estimating a value or repeating a previous value without monitoring the vital sign (Table 3). Many respondents did not feel it was necessary to complete a full set of vital signs at every patient monitoring occasion. Although 75.1% (n = 214/285) of participants said they always total up the EWS score, more than two thirds stated that they have, on occasion, totalled the EWS score despite not documenting all vital signs (69.6%, n = 197/284).

TABLE 3.

Participants perceived behaviour when completing EWS documentation.

Never (%) Sometimes (%) M SD Median
Cronbach alpha coefficient α = 0.791
1. I did not document one particular vital sign accurately because it would have raised the total score to an unreasonable number 36.7% (106/289) 21.8% (63/289) 2.45 1.43 2
2. I repeated a previously recorded vital sign without reassessing the patient 40.1% (116/289) 19.4% (56/289) 2.45 1.51 2
3. I recorded one or more values higher than it should have been to trigger a clinical review 41.0% (119/290) 17.9% (52/290) 2.44 1.49 2
4. I estimated a vital sign value rather than reassessing the patient 40.1% (116/289) 18.3% (53/289) 2.46 1.50 2
5. I didn't include a value for ALL the vital signs but still calculated a total score 30.6% (87/284) 27.1% (77/284) 2.51 1.38 2
6. I didn't believe the patient required a FULL set of observations, so left one or more values empty when repeating the one I thought was important 18.6% (54/290) 36.6% (106/290) 2.68 1.30 2
7. I recorded a particular vital sign inaccurately on purpose 43.3% (125/259) 17.3% (50/259) 2.35 1.47 2
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Note: Based on a 5‐point Likert scale, 1 = never, 2 = sometimes, 3 = about half the time, 4 = most of the time, 5 = always.

Abbreviations: EWS, early warning systems; M, mean; SD, standard deviation.

3.4.1. Perceived barriers to compliance

Participants were asked what they perceived as the barriers to EWS guideline compliance. Most stated that the extra workload resulting from an EWS‐triggered escalation of care was rarely a barrier to compliance (Table 4). However, more than 75% perceived time constraints did, at least occasionally, affect compliance. Over 60% of respondents stated that they were, on occasion, reluctant to follow EWS guidelines because it would result in notifying a medical officer, and they felt they would be chastised or made to feel that they were overreacting. A few participants stated they never allow their clinical judgement to prevent them from following the EWS guidelines (Table 4). However, most respondents value their clinical judgement, given that approximately 70% stated that they do not comply with the EWS guidelines if they do not think the patient's condition warrants an escalation of care or when they believe the situation can be managed on the ward. Most participants stated that although their peers have a relatively low opinion of the EWS (Table 2), they do not allow their peers' actions to influence their own EWS compliance. Overall, participants viewed their clinical decision‐making/clinical judgement (Table 4, Questions 2, 3, 4, 9, 12) as having a greater influence on not complying with EWS guidelines than the impact that escalation of care would have on their workload (Table 4, Questions 1, 5, 6, 8).

TABLE 4.

Participants perceived barriers to EWS guideline compliance.

Never (%) Sometimes (%) M SD Median
Cronbach alpha coefficient α = 0.936
How often do any of the following situations make it difficult for you to comply with EWS guidelines
1. When I didn't have enough time to complete the documentation properly 24.1% (70/291) 36.1% (105/291) 2.52 1.301 2
2 When I didn't think it would make any difference to the patient's outcome or care delivered 32.8% (95/290) 25.2% (73/290) 2.43 1.34 2
3. When I chose to rely on my clinical judgement 11.3% (33/291) 38.1% (111/291) 2.85 1.25 3
4. When I was worried that the score/colour code would have triggered a response that I didn't believe was warranted 29.6% (86/291) 29.6% (86/291) 2.51 1.37 2
5. When the correct score/colour would have triggered an escalation of care that would involve phoning a medical officer 36.4% (106/291) 19.9% (58/291) 2.49 1.45 2
6. When the correct score/colour would have triggered a response that increased my workload 39.7% (115/290) 18.3% (53/290) 2.46 1.48 2
7. When the correct score/colour would have triggered an escalation of care that would have made me look like I was overreacting 36.2% (105/290) 21.4% (62/290) 2.43 1.40 2
8. When I was feeling fatigued 36.7% (106/289) 23.9% (69/289) 2.39 1.38 2
9. When I did not think it was necessary 26.9% (78/290) 31.4% (91/290) 2.50 1.31 2
10. When I could not access the equipment 33.1% (96/290) 28.6% (83/290) 2.39 1.34 2
11. When I was concerned about being chastised 38.3% (111/290) 20.0% (58/290) 2.46 1.46 2
12. When I felt our ward could manage the situation 31.3% (90/288) 27.4% (79/288) 2.43 1.32 2
13. My peers don't escalate based on EWS, therefore I don't 42.7% (122/286) 15.4% (44/286) 2.41 1.48 2
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Note: Based on a 5‐point Likert scale, 1 = never, 2 = sometimes, 3 = about half the time, 4 = most of the time, 5 = always; M = mean, SD = standard deviation.

Abbreviations: EWS, early warning systems; M, mean; SD, standard deviation.

3.5. Participants perceived confidence

Many of the participants agreed or strongly agreed that they advocate for their patients when dealing with peers (66.9%, n = 186/278, M = 3.74, SD = 1.377, median = 4) or with senior colleagues (64.0%, n = 178/278, M = 3.59, SD = 1.369, median = 4). Although 66.5% (n = 184/284) of the participants agree or strongly agree that they think about what can go wrong (M = 3.64, SD = 1.288, median = 4) and vigilantly monitor patients for deterioration (69.7%, n = 193/277, M = 3.92, SD = 1.256, median = 4), only 48.0% (n = 133/277) agree or strongly agree that they feel they can override the EWS guidelines in favour of their critical thinking (M = 3.18, SD = 1.403, median = 3).

3.6. The EWS guidelines and participants' higher‐order thinking

The responses indicated that at least some of the time, nurses allow their clinical judgement to override the EWS guidelines (59.9%, n = 166/277, M = 3.18, SD = 1.403, median = 3). Although most participants stated they comply with EWS guidelines (60.0%, n = 177/295, M = 3.14, SD = 1.41, median = 4), several admit to either omitting certain vital signs (69.4%, n = 197/284, M = 2.51, SD = 1.38, median = 2) or recording vital signs inaccurately (63.3%, n = 183/289, M = 245, SD = 1.45, median = 2) in order to arrive at an EWS score that they deem better reflected the patient's condition. Approximately half the participants said they did not always comply with the EWS guidelines because they did not think a high score was warranted and believed the ward could handle the situation. Less than half of the participants believe that EWS added value to their clinical thinking skills (47.9%, n = 144/301, M = 3.39, SD = 1.190, median = 3), and this was confirmed in that the majority stated that they found it challenging to comply with the EWS guidelines if the EWS score did not support their clinical judgement (88.7%, n = 258/291, M = 2.85, SD = 1.251, median = 3). Only 3.6% (10/278) of participants believe that the mandated use of EWS does not impede the development of higher‐order thinking, 35.3% (98/278) agreed or strongly agreed that using the EWS impedes the development of higher‐order thinking, and the remaining (61.1%, n = 170/278), were ambivalent (M = 4.65, SD = 1.625, median = 5, Likert scale: 1 = strongly disagree, 7 = strongly agree).

In summary, most nurses were satisfied with the EWS training and greatly valued the tool supporting their recognition of deteriorating patients. However, the more experienced nurses did not think the EWS supported their higher‐order thinking or added value to patient care. Although nurses recognized the importance of complying with the EWS protocols and documentation, they only did so if the EWS score aligned with their assessment of the patient's condition. More than half of the participants either had the confidence to override the EWS guidelines in favour of their critical thinking, or they omitted or inaccurately documented vital signs to achieve a score aligned with their patient assessment. Most participants believed that the mandated use of EWS tools impedes nurses' development of higher‐order thinking.

4. DISCUSSION

Our study aimed to ascertain whether registered nurses believe the mandated use of EWS vital signs tools impacts the development of higher‐order thinking. We have provided quantitative data showing that nurses overwhelmingly value the support offered by the EWS, but many nurses only comply with the EWS protocols if the score concurs with the nurses' assessment of the patient's condition. Many nurses in our study appear to value their clinical judgement, thus their higher‐order thinking skills, more highly than the EWS. Given the increased reliance on EWSs in healthcare facilities, we believe this is an important study adding to the body of knowledge on the benefits and limitations of the mandated use of EWSs.

The introduction of EWSs in healthcare more than a decade ago was met with some trepidation with speculations that these algorithmic decision‐making tools would negatively impact nursing autonomy (Jensen et al., 2019). Through ongoing education and the implementation of the EWS tools in everyday clinical practice, nurses have grown to appreciate the support provided by the EWS in recognizing and responding to deteriorating patients (Badr et al., 2021; Langkjaer et al., 2023). Studies have shown that the introduction of the EWS has significantly decreased the incidence of preventable in‐hospital adverse events not only by improving the recognition of patient deterioration but also through the establishment of well‐coordinated response teams (Credland et al., 2021; Downey et al., 2017). The EWS provides nurses with a quantifiable means of raising concerns for a deteriorating patient (Langkjaer et al., 2023). This is particularly prudent amongst inexperienced nurses who utilize EWS as a safety net (Elliott et al., 2015; Jensen et al., 2019).

Our study has shown that nurses greatly value the support offered by the EWS in their patient care decision‐making and appreciate the EWS education provided by their employers. As with other studies (Ebert et al., 2022), a few respondents thought the EWS added to their workload and was no more than a box‐ticking exercise. In a similar study, Ebert et al. (2022) reported that midwives' EWS compliance was influenced by their peers, and they sometimes failed to escalate care because they believed they could deal with the patient's deterioration on the ward. Our study showed that nurses' EWS compliance was not influenced by peers but by their clinical judgement. The nurses recognized the importance of complying with the EWS guidelines and protocols and were happy to do so when the EWS score concurs with their assessment of the patient.

Current EWS tools leave little scope for flexibility and do not accommodate the complexity of inter‐patient variability. The ‘one‐size‐fits‐all’ nature of EWSs is a recognized shortcoming of these tools (Langkjaer et al., 2023). Nurses are expected to follow the EWS guidelines and respond to the EWS score per protocol. In the early stages of patient deterioration, there are sometimes few changes in vital signs, yet the nurse may instinctively know something is wrong (Douw et al., 2017). Ede et al. (2021) refer to this as ‘soft signs’ of deterioration. To accommodate such circumstances and compensate for the rigidity of the EWS tool, a ‘nurse worried’ criterion has been added to some EWS tools (Douw et al., 2017; Romero‐Brufau et al., 2019). The ‘worried’ criterion allows nurses to escalate patient care unsupported by the EWS score (Romero‐Brufau et al., 2019). The ‘worried’ criterion can potentially optimise patient safety (Douw et al., 2017). Unfortunately, given doctors' preference for quantifiable data, the use of the ‘worried’ criterion is inconsistent, with many nurses showing reluctance for fear of being ridiculed by peers and superiors (Douw et al., 2017).

With the ageing population, there is an increasing number of hospital patients with chronic conditions whose baseline vital signs are outside the EWS tool's normal range (Chester & Rudolph, 2011). These patients risk triggering frequent unwarranted alerts. To compensate for this, specialized EWSs have been created for patients with certain chronic conditions, such as NEWS2 for patients with chronic respiratory disorders (Royal College of Physicians, 2017). Other EWS tools allow the medical officer to modify the trigger range for a limited period to accommodate patients with chronic conditions (Flenady et al., 2020). The impact of the trigger range modification feature on patient safety has not been investigated, which may account for the inconsistency in its use. Some medical officers have embraced the opportunity to modify the vital sign trigger ranges, while others rarely apply modifications (Elliott et al., 2015; Flenady et al., 2020). Without documented vital sign modifications, nurses are left with the dilemma of escalating care despite the patient showing no visible sign of deterioration.

Our study shows that when the EWS score does not concur with the nurse's assessment of the patient, many nurses prioritize their higher‐order thinking over the EWS score. Some nurses reported a reluctance to override the EWS protocol but were willing to manipulate the EWS score to evoke an action that they believed enhanced patients' safety. They did so by omitting or inaccurately documenting vital signs to achieve an EWS score that supported their higher‐order thinking. These findings are not new and have been reported in other studies (Elliott et al., 2015; Langkjaer et al., 2023). This indicates that although the nurses in our study value the EWS, many recognize that the tools are not always suitable and prioritize their higher‐order thinking over the EWS score.

Higher‐order thinking is essential in ensuring patient safety in clinical practice (Connor et al., 2022). Current EWS do not actively encourage clinical assessment or critical thinking (Nielsen et al., 2020). However, EWSs were not designed to replace higher‐order thinking but to complement it (Royal College of Physicians, 2017). Higher‐order thinking skills such as clinical judgement, critical thinking and decision‐making develop with time and experience (Benner, 2019). There is speculation that an overreliance on algorithmic decision‐making tools, such as EWSs, will deprive novice nurses of the opportunity to develop their higher‐order thinking skills (Elliott et al., 2015; Jensen et al., 2019). Although our study produced little evidence that EWS negatively impacts the development of higher‐order thinking, experienced nurses participating in the study voiced concerns that this was the case. Nurses value using the EWS score as it facilitates multidisciplinary communication and supports their subjective assessment of the patient (Augutis et al., 2023; Burns et al., 2018). However, EWS is more than just a number used to guide patient care; it is one of many tools that nurses should use to ensure the best outcomes for the patient. Öhlén et al. (2021) refer to a holistic approach to patient care as ‘clinical gaze’, which involves a physical assessment of the patient, a deep understanding of the patient's medical condition in the current context, the nurse's experience, and utilizing higher‐order thinking skills. Vital signs are fundamental indicators of patient wellness but must be monitored, documented and interpreted accurately to be valuable (Kellett & Sebat, 2017). Studies have shown that vital signs assessment, risks becoming a ritualistic task delegated to junior staff members who may not appreciate their significance in relation to physiological deterioration (Grant, 2019; Nielsen et al., 2020). Most nurses in our study stated that they recognize the significance of vital sign monitoring and the resulting EWS score and use them in their decision‐making regarding patient care. Despite this, vital sign assessment continues to be delegated to the most inexperienced members of the team.

Our study has shown that many experienced nurses prioritize patient safety over compliance with EWS guidelines and protocols. Since hospital policy dictates that clinical staff be mandated to follow the EWS guidelines, this indicates a distinct limitation in the existing rigid EWSs. A possible solution is incorporating an EWS criterion that encourages nurses to utilize their higher‐order thinking and still produce a quantifiable EWS score. One such EWS, the individual‐early warning score (I‐EWS), was recently introduced in Danish hospitals and found to be very effective and well‐received by clinical staff (Langkjaer et al., 2023; Nielsen et al., 2022). The I‐EWS allows nurses to change the EWS score to align with their clinical judgement. In a large multicentred randomized control trial, Nielsen et al. (2022) found that although only 6% of nurses used the opportunity to alter the EWS score, the I‐EWS resulted in significantly fewer unnecessary emergency medical reviews without compromising patient safety. The I‐EWS appears to be a potential solution to the rigidity of the ‘one‐size‐fits‐all’ EWS, allowing experienced nurses to legitimately change the EWS score by applying their higher‐order thinking rather than using inaccurate documentation to achieve the same goal.

Several studies investigating nurses' perceptions of EWS have discussed higher‐order thinking (Burns et al., 2018; Jensen et al., 2019). Most of these studies are qualitative and produce a rich understanding of what nurses truly think of EWS. Our study aimed to ascertain whether nurses believe that EWS impacted the development of higher‐order thinking. However, since experienced nurses with well‐developed higher‐order thinking skills chose to participate in our study, we have not fully achieved this aim. We have provided statistical data showing that many nurses value their higher‐order thinking above the EWS score, and some are willing to manipulate the score to match their clinical judgement. We have also provided evidence that many experienced nurses believe the EWS inhibit the development of higher‐order thinking in novice nurses. It would be beneficial to repeat this study targeting beginner nurses whose higher‐order thinking is not yet well developed. The study has revealed that although few nurses are willing to override the EWS protocol, some are willing to manipulate the score to align with their assessment of the patient. This indicates an important limitation in the existing EWS, an inflexibility that may be addressed by including a critical thinking component in existing EWSs.

4.1. Limitations and strengths of the research

Although this study aimed to attract novice, intermediate and well‐experienced nurse participants, most respondents were experienced nurses with more than 10 years of clinical experience. Novice nurses in their first 2 years of nursing practice were noticeably absent from the study cohort. It is possible that more experienced nurses feel strongly about the impact of EWS on higher‐order thinking or appreciate the value of research in clinical practice. Either way, the dominance of well‐experienced nurses in this study could have biased the results. It would be beneficial to repeat the survey targeting inexperienced nurses and compare their responses to those of the participants in the current study. Additionally, our sampling strategy meant that we may have recruited nurses interested in patient deterioration or who support and value EWS, which could also have biased the results. One of the strengths of this study is that it provides quantitative evidence of the nurses' perceptions of the impact of EWS on higher‐order thinking. Quantitative evidence is greatly valued in evidence‐based practice and is used to inform clinical practices and policy. We believe that the evidence presented in our study may be used to inform future nursing practice.

5. CONCLUSION

Nurses value the support offered by EWS when responding to the deteriorating patient. Our study has shown that nurses recognize the significance of accurate vital signs documentation and most nurses abide by the EWS guidelines if the EWS score concurs with their assessment of the patient's condition. However, when the EWS score does not align with the nurses' clinical judgement, some are reluctant to override the EWS protocol, but may be willing to manipulate the EWS score to achieve a score that they believe best represents the patient's condition. This indicates that most nurses prioritize patient safety and many value their higher‐order thinking above the EWS. This supports existing recommendations that EWS be used in conjunction with higher‐order thinking and that the rigidity of the EWS tool does not accommodate inter‐patient variability. It is suggested that the use of higher‐order thinking in patient care may be promoted by including a critical thinking criterion in existing EWS tools.

AUTHOR CONTRIBUTIONS

MDLL, TF, DM and JC conceptualized and designed the study. All authors were responsible for participant recruitment, and MDLL collected and analysed the resulting quantitative data. All the authors made a substantial contribution to interpreting the data. A‐LB and MDLL drafted the manuscript, and DM, TF and JC critically reviewed the manuscript.

FUNDING INFORMATION

This work was supported by a CQUniversity Internal Grant, RHS6503. The funding body was not involved in the planning or execution of this study and did not contribute to this manuscript.

CONFLICT OF INTEREST STATEMENT

The authors have no conflict of interest to declare.

PEER REVIEW

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/jan.16235.

STATISTICS

(a) The authors confirm that this submission conforms to the Journal's statistical guidelines. (b) The statistics were checked prior to submission by an expert statistician, Prof Lukman Thalib, Edith Cowen University.

Supporting information

Appendix 1.

JAN-81-5342-s002.pdf (277.9KB, pdf)

Data S1.

JAN-81-5342-s001.docx (33KB, docx)

ACKNOWLEDGEMENTS

We would like to thank the participants for their contribution to our study. We are most grateful to Prof Lukman Thalib, Edith Cowen University, for his statistical review of the manuscript. Open access publishing facilitated by Central Queensland University, as part of the Wiley ‐ Central Queensland University agreement via the Council of Australian University Librarians.

Le Lagadec, M. D. , Massey, D. , Byrne, A.‐L. , Connor, J. , & Flenady, T. (2025). Nurse by numbers: The impact of early warning systems on nurses' higher‐order thinking, a quantitative study. Journal of Advanced Nursing, 81, 5342–5352. 10.1111/jan.16235

DATA AVAILABILITY STATEMENT

The data supporting this study is available from the corresponding author on request. The data are not publicly available for ethical reasons.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix 1.

JAN-81-5342-s002.pdf (277.9KB, pdf)

Data S1.

JAN-81-5342-s001.docx (33KB, docx)

Data Availability Statement

The data supporting this study is available from the corresponding author on request. The data are not publicly available for ethical reasons.

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