Ward Nurses’ Resuscitation of Critical Patients

Abstract

Little is known about the current training and barriers in resuscitation skills among practicing ward nurses. A convenience sample of 459 ward nurses, recruited from 11 academic teaching hospitals in Korea, were surveyed to assess current training and barriers to optimal resuscitation performance on the wards. The Perceived Barriers scale was developed, refined, and its psychometric properties were assessed. Approximately 36% of nurses had received simulation-based resuscitation skills training. Exploratory factor analysis identified four barriers accounting for 58.4% of the variance: insufficient training (37.7%), lack of competence (9.8%), lack of self-confidence (5.9%), and workload and tension (5.1%). Strategic planning and resuscitation skills training should be incorporated into staff development programs to reduce barriers to optimal resuscitation performance and cope with work demands for ward nurses.

Keywords

resuscitation barrier simulation nurse training

Introduction

The risk of a potentially avoidable cardiac arrest for patients in general wards is more than 5 times that of patients in critical care areas (Hodgetts et al., 2002). Acutely ill patients in general wards often show signs of clinical deterioration before an adverse event (Kause et al., 2004). However, studies have demonstrated a marked lack of awareness and management of critical patients among ward nurses (Franklin & Mathew, 1994; Fuhrmann, Lippert, Perner, & Østergaard, 2008). Underpreparedness of nurses in an in-hospital resuscitation event may delay intervention and consequently decrease a patient’s chance of survival (Ranse & Arbon, 2008).

Barriers for best practice resuscitation in hospital wards are common, but little is known of current training and perceived barriers in resuscitation among practicing ward nurses. Recent training is the main factor associated with better quality of basic life support (Nyman & Sihvonen, 2000; Verplancke et al., 2008). Identified barriers to effective resuscitation for nurses include inexperience (Dennison, Mendez-Tellez, Wang, Pronovost, & Needham, 2007; Hemming, Hudson, Durham, & Richuso, 2003), stress (Hemming et al., 2003), and communication gaps between disciplines (Hicks, Bandiera, & Denny, 2008). Other factors include suboptimal structure in observational practice, insufficient measurement and documentation of vital signs, insufficient knowledge of signs of deterioration, and lack of analytic tools and guidelines in decision making about deteriorating patients (Franklin & Mathew, 1994; Fuhrmann et al., 2008; Strzyzewski, 2006).

However, as these results are mostly derived from interviews with a relatively small number of nurses, the results can impede generalization. The extent of perceived barriers in resuscitation by ward nurses is not yet fully understood and a large-scale empirical study focusing on these issues is required.

To identify these barriers, the research team developed and administered a needs assessment survey for ward nurses. The survey was carried out to define specific training objectives that can be linked to the competence required for the recognition and resuscitation of patients. Using this knowledge, nurse administrators can design education and support systems that will lead to improving nurses’ competence in resuscitation.

Purpose

The purpose of this study was to explore current training experiences and identify barriers to optimal resuscitation performance in Korean hospital ward nurses.

Method

Design

This was a cross-sectional descriptive survey study.

Measures

The questionnaire consisted of three parts: 4-item Current Training Experiences Assessment tool, 24-item Perceived Barrier scale, and a set of demographic questions.

Assessment of current training experience

The instrument included 1 item on current experiences in clinically deteriorating patient events and 3 items measuring the experience of simulation-based resuscitation training over the past 12 months.

Perceived barriers

The survey development was guided by the conceptual framework proposed by Dwyer and Mosel Williams (2002) for understanding nurses’ behavior regarding cardiopulmonary resuscitation (CPR). Instruments were developed by the authors using the following steps (DeVellis, 2012; Pett, Lackey, & Sullivan, 2003): (a) defining the construct of perceived barriers in resuscitation based on a literature review (Hicks et al., 2008; Odell, Victor, & Oliver, 2009; Strzyzewski, 2006), (b) generating items and establishing content validity by a panel of four experts who had expertise in emergency medicine or nursing, and (c) testing construct validity using exploratory factor analysis with Direct Oblimin rotation and internal consistency reliability. In this study, perceived barriers in resuscitation were defined as the factors in nurses’ personal experiences that impede then from functioning at their best during resuscitation.

Participants were asked to respond on a 5-point Likert-type scale which assessed the nurses’ perceived importance of barriers to performing resuscitation tasks. Scores range from 1 (strongly disagree) to 5 (strongly agree), with high scores indicating greater importance as a barrier. The Cronbach’s α for the final 24-item scale was .926.

Sample

The sample size was estimated based on the suggestion that there be at least 10–15 subjects per item for factor analysis (Pett et al., 2003). The target population for the survey was registered nurses from noncritical care areas who were employed at the time of sampling. The authors contacted the nursing departments/divisions of 25 academic teaching hospitals in Seoul, Korea, to request their participation in the research. Permission to do the study was obtained from 11 of these hospitals (44%). A convenience sample of 511 hospital nurses from noncritical care areas was recruited from the 11 hospitals. Noncritical care areas were selected to tap experiences of nurses who were relatively unlikely to face resuscitation on a daily basis. Of the 511 structured questionnaires distributed to the hospitals, 502 were returned, accounting for a response rate of 98.2%. Forty-three questionnaires were excluded due to incomplete data leaving 459 questionnaires for the final analysis. Therefore, the minimum sample size requirement for factor analysis was satisfied.

Procedures

The study protocol and procedures were reviewed and approved by the Institutional Review Board of the College of Nursing, Yonsei University. A self-administered questionnaire was sent via mail to the 11 hospitals with a letter describing the study. Nurses in the nursing departments of these hospitals were contacted in advance, informed about the purpose and nature of the study, and asked to assist with coordination, administration, and collection of the survey as a research assistant. Using a convenience sampling method, lists of eligible participants who met the sampling criteria were made based on the judgment of the nursing unit manager in each unit, and then a research assistant distributed and collected the questionnaires from the eligible nurses in each nursing unit of the 11 hospitals. Informed consent was obtained from each participant who volunteered. Respondent anonymity was maintained throughout the data collection and analysis. The data were collected from April 11 to May 20, 2011.

Data Analysis

Descriptive and t-test statistics were calculated to summarize the quantitative data using Statistical Package for the Social Sciences (SPSS) version 20.0 program (SPSS Inc, Chicago, IL). To explore the underlying structure, an exploratory factor analysis was performed and factor scores were calculated. Factor loadings were calculated using principal axis factoring (PAF) and Direct Oblimin rotation to investigate the construct validity of the Perceived Barrier scale. The reason for using Oblimin rotation was that the factors were conceptualized as interrelated aspects of perceived barriers. In the PAF solution, factors were extracted with Eigenvalues greater than 1.0. In the extraction phase, items were used, if they had a factor loading of at least .40 (Pett et al., 2003). Cronbach’s α coefficients were calculated to estimate the internal consistency for the items in each factor and for the total scale. Comparison of the mean of the Perceived Barrier scale and its subscale scores between new graduates and experienced nurses was performed using t-test.

Results

Demographics of Ward Nurses

Table 1 shows the demographics characteristics of the ward nurses. All 459 nurses were women, their ages ranged from 22 to 59 years with a mean age of 29.2 ± 5.78 years, and 54% had baccalaureate degrees. The proportion of new graduate nurses with less than 12 months hospital experience was 27% and 48% of the nurses worked in a medical ward.

Table 1.

Baseline Characteristics.

Variable	Category	N (%)/M ± SD	Range
Gender	Women	459 (100)
Gender	Women	29.2 ± 5.78	22–59
Age (years)	≤30	314 (68.4)
	31–40	128 (27.9)
	>40	17 (3.7)
Work duration (months)		78.04 ± 67.59	1–396
	≤12	125 (27.2)
	>12	334 (72.8)
Workplace specialty	Medical ward	218 (47.5)
	Surgical ward	208 (45.3)
	Mixed	33 (7.2)
Educational background	Associate degree	213 (46.4)
Educational background	Baccalaureate degree	246 (53.6)

Note. N = 459.

Current Training Experiences in Resuscitation

Table 2 lists the current experiences with clinically deteriorating patient events during the past 12 months. Although experiences were diverse among the ward nurses, the three most frequent clinically deteriorating patient events on the wards during the past 12 months were respiratory failure (78%), hypotension (76%), and electrolyte imbalance (69%).

Table 2.

Experiences With Deteriorating Patient Events During Past Year.

Category	N (%)^a
Respiratory failure	359 (78.2)
Hypotension	348 (75.8)
Electrolyte imbalance	315 (68.6)
Loss of consciousness due to non-neurologic etiology	280 (61.0)
Loss of consciousness due to neurologic etiology	274 (59.7)
Oliguria	255 (55.6)
Sepsis	240 (52.3)
Chest pain	224 (48.8)
Dysrhythmia	212 (46.2)
Cardiac arrest	209 (45.5)

Note. N = 459.

^aMultiple responses.

Table 3 lists the current experiences of simulation-based resuscitation training. Approximately 36% of nurses had simulation-based resuscitation training, and the most frequent training content was CPR (93%).

Table 3.

Current Experiences of Simulation-Based Resuscitation Training.

Variable	Category	N (%)
Training experiences	Yes	164 (35.7)
Training experiences	No	295 (64.3)
Time since resuscitation training	1 month ago	25 (14.6)
	3 months ago	23 (14.0)
	6 months ago	46 (28.1)
	1 year ago	46 (28.1)
	More than 1 year	24 (14.6)
	Total	164 (100)
Main content^a	Cardiopulmonary resuscitation	152 (92.7)
	Communication	37 (22.6)
	Psychomotor skills	36 (22.0)
	Team work	34 (20.7)
	Patient monitoring	32 (19.5)
	Patient safety	26 (15.9)
	Cognitive training	15 (9.1)
	Crisis resource management	7 (4.3)

Note. N = 459.

^aMultiple responses.

Perceived Barriers to Optimal Resuscitation Performance

The Kaiser–Meyer–Olkin Measure of Sampling Adequacy score was .95 and Bartlett’s test of sphericity was significant (χ² = 12710.2, p = <.001). These results suggest that factor analysis was appropriate and could be expected to yield common factors.

An exploratory factor analysis identified four factors: insufficient training (37.7%), lack of competence (9.8%), lack of self-confidence (5.9%), and workload and tension (5.1%). These four components accounted for 58.4% of the variance. Internal consistency reliability estimates for the 4-factor subscales were acceptable and ranged from 0.826 to 0.893, except for the “Workload and Tension” subscale, which was 0.536, likely because it contained only 2 items.

On a 5-point scale, “excessive workloads and multiple patients” (4.16 ± 0.73), “stress and anxiety” (4.03 ± 0.74), and “no exposure to training education in the management of deteriorating patients” (3.79 ± 0.76) were ranked high, whereas “lack of knowledge and skills regarding vital signs” (3.00 ± 1.08) was ranked the lowest (Table 4).

Table 4.

Perceived Barriers to Optimal Resuscitation Performance.

Abbreviated Barriers Item (% of Variance)	Factor Loadings	M ± SD
Factor 1: Insufficient training (37.7%)
No exposure to nursing skills training required to manage deteriorating patients	.85	3.67 ± 0.78
No exposure to training education in the management of deteriorating patients	.83	3.79 ± 0.76
Lack of training education about intuitive reasoning or clinical decision making to cope with a deteriorating patient effectively	.80	3.73 ± 0.75
Lack of financial or other administrative support for staff education in hospital	.71	3.69 ± 0.79
Lack of physical examination skills	.61	3.49 ± 0.74
Lack of interpretation skills for laboratory results	.60	3.54 ± 0.77
Factor 2: Lack of competence (9.8%)
Lack of required skill and knowledge regarding vital signs	−.84	3.00 ± 1.08
Absent or infrequent vital sign recording	−.83	3.10 ± 1.07
Problems in communication of large volumes of complex information between nurses and doctors	−.76	3.51 ± 0.84
Failure to locate and manage the crash cart and necessary equipment	−.76	3.46 ± 1.00
Unclear as to roles and goals of fellow team members	−.70	3.61 ± 0.85
Technical problems with equipment	−.69	3.50 ± 0.91
Delays in calling the doctor	−.67	3.58 ± 1.04
Failure in attaching patient monitoring equipment	−.62	3.31 ± 0.97
Lack of guidelines in decision making about deteriorating patients	−.61	3.68 ± 0.82
Failure to debrief after the event	−.55	3.64 ± 0.84
Factor 3: Lack of self-confidence (5.9%)
Lack of confidence in managing a deteriorating patient	.80	3.71 ± 0.80
Lack of timely response to deteriorating patients	.79	3.72 ± 0.77
Lack of knowledge in early recognition of a deteriorating patient	.71	3.70 ± 0.73
Inexperienced nurses	.70	3.69 ± 0.88
Stress and anxiety	.61	4.03 ± 0.74
Lack of access to knowledge resources to consult during times of critical care events	.60	3.64 ± 0.72
Factor 4: Workload and tension (5.1%)
Excessive workloads, multiple patients	.71	4.16 ± 0.73
Tensions within professional hierarchies that obstruct communication or information flow	.52	3.67 ± 0.78

Note. N = 459.

Comparison of Perceived Barrier Scores Between New Graduate and Experienced Nurses

New graduate nurses with less than 12 months of experience reported significantly higher barriers in the lack of self-confidence factor compared to experienced nurses with more than 12 months of experience (3.89 ± 0.50 vs. 3.70 ± 0.58, t = 3.407, p = .001). There were no significant differences in the total Perceived Barrier scale (t = .829, p = .408) or the subscales: insufficient training (t = 1.065, p = .288), lack of competence (t = −.552, p = .581), workload and tension (t = −1.246, p = 213).

Discussion

This multicenter survey had a high overall response rate, and acceptable psychometric tests were demonstrated for its theoretically derived scale. The results demonstrate that current experiences in resuscitation training are suboptimal and that perceived barriers to optimal resuscitation performance are evident and vary with experience, especially self-confidence.

In this study, only 36% of ward nurses had simulation-based resuscitation training experiences, and the main training content was a single professional education event in CPR management. Continual resuscitation training is necessary for practicing nurses to decrease decay of knowledge and skills and to gain proficiency and improve self-efficacy in resuscitation (Roh, Lee, Chung, & Park, 2011). Currently, simulation-based team training focuses largely upon intra-/interprofessional team work, highlighting patient safety, human factors, crisis resource management (CRM), and team-based behaviors (Eppich, Howard, Vozenilek, & Curran, 2011). Despite widespread support, there is little evidence to support the efficacy of interprofessional resuscitation education and this deficit requires further study (Lapkin, Levett-Jones, & Gilligan, 2011).

The results of the factor analysis show that ward nurses regard insufficient resuscitation training as an important barrier to optimal resuscitation performance. Similarly, the main factor associated with better quality of Basic Life Support (BLS) is reported as recent BLS training (Nyman & Sihvonen, 2000; Verplancke et al., 2008). However, the results of one survey show that although BLS is a core skill, there is a great deal of variation in training provided at the undergraduate level in terms of training hours, composition of training modalities, frequency of refresher training, and assessment time (Jordan & Bradley, 2000). Health care providers trained in resuscitation are reported to perform well in real code situations, and the result is an increase in return of spontaneous circulation, higher rates of survival and hospital discharge for patients, as well as an increase in 30-day and 1-year survival rates (Moretti et al., 2007). Therefore, staff education is an essential part of the “chain of prevention” to assist hospitals in structuring their care processes to prevent and detect patient deterioration and cardiac arrests (Smith, 2010). Although many hospitals provide resuscitation training programs, there is need to introduce more rigorous and standardized education programs based on need assessment of ward nurses because they are often responsible for direct implementation of resuscitation skills.

The results of our study demonstrate that “excessive workloads and multiple patients” is the most frequently cited barriers to optimal resuscitation performance by ward nurses and a heavy workload was reported as a key barrier to improving pain management in Australian emergency departments (Bennetts, Campbell-Brophy, Huckson, & Doherty, 2012). The results of another study show that for “excessive workloads and multiple patients,” patient acuity has increased, even in general wards, and that has increased the workload and stress for nurses (Chellel et al., 2002; Cutler, 2002). There is a need to set action strategies, planning and prioritizing tasks, assumptions, and allocation of resources, which all influence how patients on general wards are assessed and monitored (Fuhrmann, Perner, Klausen, Østergaard, & Lippert, 2009). Therefore, contextual factors should be considered in designing a resuscitation curriculum to improve ward nurses’ performance in hospital settings.

Further, in our study, “stress and anxiety” is shown to be the second most frequently cited barrier to optimal resuscitation performance. This result is similar to that of a previous study that found stress was the most frequently cited specific emotion as a perceived barrier to effective resuscitation (Hemming et al., 2003). Nurses also report a decrease in anxiety regarding participation in future CPR events after participation in a multidisciplinary CRM training course (Allan et al., 2010). Although simulation-based training may empower nurses and contribute to decreasing stress and anxiety, there are relatively few studies that demonstrate the effectiveness of resuscitation training on these psychological variables and should be the focus of future research.

Our results also demonstrate that new graduate nurses, compared to experienced nurses, report significantly higher perceived barrier mean scores for lack of self-confidence. This result is similar to that of a study showing that compared to nurses with more than 10 years of experience, nurses with less than 10 years of ICU experience reported higher overall and attitude-related barriers and organizational barriers to low tidal volume ventilation in acute respiratory distress syndrome (Dennison et al., 2007). New graduate nurses report tasks in critical care as the most stressful (Yeh & Yu, 2009), and this can often lead to nurse turnover (Laschinger, Grau, Finegan, & Wilk, 2010). Therefore, new graduate nurses should be prioritized as target learners because they represent an at-risk population about to start practice, and there is need to develop and strengthen their competence in resuscitation as practicing nurses.

The limitation of this study is that the sample in this survey consisted of nurses from noncritical clinical areas. It is unknown whether these findings also apply to nurses in other clinical areas including critical care and emergency departments. The use of a nonprobability survey sampling method is also a limitation, but demographic patterns of the nurses were similar to a recent survey (Cho et al., 2012), which indicates that this sample could be representative of the target population in Korea. However, the use of a convenience sample from one geographical location limits the generalizability of the study findings.

Conclusion

Nurses are key providers and often first responders in detecting and initiating resuscitation in patients in ward settings. Our results reveal suboptimal training experiences in resuscitation among ward nurses and identify four important barriers to optimal resuscitation performance including insufficient training, lack of competence, lack of self-confidence, and workload and tension. These results indicate a need to introduce and evaluate the outcomes of a resuscitation training curriculum, while at the same time giving consideration to organizational factors to reduce perceived barriers and improve optimal resuscitation performance among ward nurses.

Footnotes

Acknowledgments

We thank our colleagues who provided critical feedback on the draft survey, nurses who assisted data collection, and all nurses who completed the survey.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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