The effect of patient safety culture on nurses’ near-miss reporting intention: the moderating role of perceived severity of near misses

Abstract

Background

Reporting near misses is a practical approach to improve the confounding challenge of patient safety. Evidence suggests that patient safety culture and the characteristics of errors might have important impacts on reporting. No studies, however, have examined the relationships among patient safety culture, perceived severity of near misses and near-miss reporting.

Aims

To explore the relationship between patient safety culture and nurses’ near-miss reporting intention, and examine the potential moderating effect the perceived severity of near misses might have on this relationship.

Methods

Using a cross-sectional survey, data were collected with three validated survey instruments completed by 920 Registered Nurses in eight tertiary hospitals in China. Multiple regression analysis tested relationships among the variables.

Results

Nurses reported a moderate–high level of near-miss reporting intention. Patient safety culture was positively associated with nurses’ near-miss reporting intention. Perceived severity of near misses did not significantly moderate the relationship between patient safety culture and reporting intention.

Conclusions

Nurses generally showed a positive willingness to report near misses. A specific near-miss management and education system within a learning, supportive working environment are key components to improve reporting intention among nurses which could significantly improve patient safety.

Keywords

near misses nurses patient safety culture reporting intention severity

Introduction

Despite decades of focus, patient safety remains a primary health care concern due to the high rate of errors (Makary and Daniel, 2016). Beyond the negative aspect of patient harm, errors can serve as valuable resources for learning and improving safety. Among optimal approaches to learn from errors, developing incident reporting systems has been recognised as a globally effective and efficient strategy. The World Health Organization (WHO, 2005) indicated that reporting errors is the mark of a highly reliable learning organisation and should be strengthened to improve safety.

Numerous healthcare error reporting tools have been constructed locally or nationally; however, the learning effect is still limited. Most reporting systems have focused on incidents as actual adverse events and neglected potential adverse events, commonly known as near misses (Ladner and Baker, 2013). A near miss is defined as an incident which did not reach the patient by chance or timely intervention (WHO, 2009). Compared with actual adverse events, near misses present more learning opportunities to strengthen safety as they occur more frequently than actual errors and highlight system vulnerabilities without causing patient harm. Reporting near misses could increase awareness and performance of patient safety, lessening the risk of safety issues (Sheikhtaheri, 2014; Spall et al., 2015).

Despite efforts to establish reporting systems across all of healthcare, underreporting of errors persists worldwide. For near misses, reporting is much more challenging because they are less visible and cause no harm to patients. Several managerial and individual factors affect reporting healthcare errors, such as uncertainty of what and how to report, lack of feedback, and fear-related factors (Archer et al., 2017; Chiang et al., 2019). However, the factors that specially contribute to near-miss reporting have rarely been explored.

A reliable and effective reporting system is part of an organisation’s safety culture. Patient safety culture is the product of individual and group beliefs, values, attitudes, perceptions, competencies and patterns of behaviour that determine the organisation’s commitment to quality and safety (The Joint Commission, 2016). The Agency for Healthcare Research and Quality (AHRQ) reported that patient safety culture included 12 composites, such as staffing, teamwork, management support, non-punitive response, Organisational learning (OL), etc. (Sorra and Dyer, 2010). Patient safety culture is universal as foundational to improve safety attitudes and performance. Nurses had more agreement on reporting errors positively if their work conditions featured a patient safety culture and a system-driven approach to handle errors (Richter et al., 2014). However, the exact relationship between patient safety culture and near-miss reporting remains largely unexplored. Given the positive effect of patient safety culture, we, therefore, proposed that:

Hypothesis One: patient safety culture relates positively to nurses’ near-miss reporting intention.

Error characteristics, particularly the severity of consequences, have been reported to be a critical element affecting safety performance (Chuang et al., 2007; Homsma et al., 2009; Kodama and Kanda, 2010). A study among resident physicians showed that 58.1% of respondents were more inclined to report serious errors compared with near misses (Singal et al., 2018). Most previous studies focused on actual adverse events, making it reasonable that the greater the severity of the event, the more necessary the report. However, because near misses cause no harm to patients, the effect of severity of consequences on near-miss reporting intention remains unclear. Moreover, studies on organisational culture suggest that the effect of individual and organisational factors on employees’ specific behaviours might be affected by a mediator or moderator (Fischer et al., 2018). Employees’ safety awareness increases with the strengthening of a safety-centred working environment and over time could develop into safety performance. Accordingly, clinical safety issues that arouse individuals’ awareness (i.e. high-severity near misses) are thought to be important in strengthening the effect of a safety-centred working environment (i.e. patient safety culture) and positively influence the safety performance, such as reporting. Therefore, we hypothesised that:

Hypothesis Two: perceived severity of near misses moderates the relationship between patient safety culture and nurses’ near-miss reporting intention.

As the last line of defence in preventing patients from being harmed, frontline nurses experience more near misses (Cohoon, 2011), making them an indispensable part in reporting near misses. Understanding nurses’ intention to report near misses and the impact of patient safety culture and the severity of near misses can greatly contribute to patient safety.

The Study

Aims

The aims of the study were to explore the relationship between patient safety culture and nurses’ near-miss reporting intention (NMRI), and examine the potential moderating effect the perceived severity of near misses has on this relationship.

Design

A cross-sectional survey design was employed.

Participants and setting

A sample of 920 nurses were recruited from eight tertiary hospitals in six convenient administrative regions in east China ranging in size from 1100 beds to 2500 beds. The inclusion criteria were registered nurse with at least one-year's work experience who provided direct nursing care. Nurse managers and nurses who were not officially employed in the selected hospitals, such as the on-the-job training nurses or interns, were excluded from the study. A multi-stage random sampling approach was used. First, eight hospitals were randomly selected from the 23 tertiary hospitals in the six regions. Proportional stratified random sampling was then used to select individual nurses from each hospital. As personnel should be accounted one by one, when the calculation identified the number of personnel as less than one, it was counted as one.

Data collection

Data were collected using three questionnaires. First, the researcher explained the study to nurse managers in each hospital to obtain permission. Second, the researcher went to each unit and distributed the survey packets to selected eligible nurses based on the estimated number. The purpose, methods, significance and assurance of the anonymity and confidentiality of the study was explained to participants. It was emphasised that if they agreed to participate, they should complete the questionnaires, seal them in a pre-prepared envelope and then place them in a reserved space in the head nurse office or give them to the research assistant. Those not wishing to participate sealed the uncompleted questionnaires and likewise returned them. The researcher collected survey packets from each unit after 72 hours. A total of 1100 survey packets were distributed, with 920 completed packets retrieved giving a response rate of 83.64%.

Instruments

Three instruments were used. A demographic form recorded nurses’ age, gender, education, work experience, employment status and work department.

NMRI

Nurses’ intention to report near misses was measured by the Near-Miss Reporting Intention Scale (NMRIS). NMRIS is an investigator-designed scale with three items (e.g. ‘when a near miss occurs, I would like to actively report to my manager’). Items were developed from a modified version of the second-order problem solving scale (Tucker, 2003) with a literature review to define error reporting. We also conducted individual interviews among 19 nurses with six to 21 years of work experience and used the Delphi method among nine experts with an expert authority score of 0.82. Items were rated on a five-step Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) and summed up; higher scores indicated a higher level of NMRI. The NMRIS was validated with the panel of experts and tested among 582 nurses. The content validity (S-CVI/Ave) was 1, the Cronbach’s alpha was 0.85. The exploratory factor analysis supported a one-dimensional structure (explained variance: 76.94%). The confirmatory factor analysis verified the factorial structure, with the factor loadings of 0.59–0.87. The floor and ceiling effects were observed in 0.8% and 10.7% of cases (valid n = 920), which was considered not to be present in this study (Terwee et al., 2007).

The perceived severity of near misses

The perceived severity of near misses (PSNM) was measured by an investigator-designed instrument, ‘Near-miss severity assessment form’ (NMSAF). The NMSAF consists of two parts: the description of 16 hypothetical near-miss events and the Risk Assessment Index (RAI) to evaluate the severity of each event.

To develop an inventory of near-miss events, we used content analysis to examine the two-year near-miss database of a 2500-bed tertiary hospital together with interviews among 19 nurses from three general tertiary hospitals to determine 551 specific near-miss events. Combined with a literature review and several discussions within our research group, we developed 33 hypothetical near-miss events. Through consensus with our expert panel, 16 applicable hypothetical near-miss events were determined, including medications, transfusion, laboratory, infection, working procedure, document, communication, et cetera. For each event, we used the RAI to determine the potential severity of the near miss (Hoppes and Mitchell, 2013). The severity score was rated on a five-point scale ranging from 1 (no harm) to 5 (extremely severe or fatal). Participants’ responses were averaged, with higher scores indicating a higher level of perceived severity of near misses.

Patient safety culture

A Chinese version of the Hospital Survey on Patient Safety Culture (HSOPSC) (Liang, 2014) was used in this study. Developed by AHRQ, the HSOPSC is a valid, widely-used instrument to assess hospital staff opinions about patient safety culture from 12 aspects (Sorra and Dyer, 2010). The items were rated on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), higher average scores indicating a better safety culture. In this study, three subscales of HSOPSC were used. ‘Non-punitive response to errors’ subscale included three items measuring whether the person who committed an error was punished. The original Cronbach’s alpha was 0.78; this study showed a Cronbach’s alpha of 0.79. ‘Organisational learning’ (OL) subscale included three items measuring the positive change or improvement efforts led by mistakes. The original Cronbach’s alpha was 0.71; this study showed a Cronbach’s alpha of 0.78. ‘Management support for patient safety’ (MSPS) subscale included three items measuring the prioritisation and interest that hospital management placed on safety. The original Cronbach’s alpha was 0.79; this study showed a Cronbach’s alpha of 0.81.

Data analysis

SPSS version 19.0 and AMOS version 24.0 (IBM Corp., NY, USA) were used. Frequency, percentage, mean and standard deviation (SD) described participants’ demographic characteristics and major variables. Pearson’s correlation was used to determine the associations between patient safety culture, perceived severity of near misses and NMRI. Multiple stepwise regression analysis was performed to examine whether patient safety culture relates positively to NMRI. Hierarchical stepwise regression was used to test whether the perceived severity of near misses moderated the relationship between patient safety culture and NMRI. Independent t-test, analysis of variance measured the relationship between the NMRI and demographic characteristics.

Results

Participant characteristics

The study participants ranged in age from 19 to 53 years old, with a mean age of 30.11 (SD 5.93). The majority were female (96.09%). The median years of work experience was seven years (4, 12) with more than half reporting less than 10 years’ experience (66.63%). Nearly half of the participants held a bachelor’s degree or above (45.98%) (Table 1).

Table 1.

Participants’ demographic characteristics.

Variable	Frequency	Percentage*
Age (years)
≤25	218	23.70
26–35	540	58.70
36–45	132	14.35
≥46	20	2.17
Gender
Female	884	96.09
Male	31	3.37
Education
Master’s degree or above	18	1.96
Bachelor’s degree	405	44.02
Associate degree	446	48.48
Secondary technical	44	4.78
Work experience (years)
≤5	357	38.80
6–10	256	27.83
11–15	151	16.41
16–20	84	9.13
≥21	55	5.98
Employment status
Contract	286	31.09
Permanent	625	67.93
Work departments
Surgical	323	35.11
Medical	280	30.43
Gynaecology and Obstetrics	68	7.39
Paediatric	58	6.30
Emergency Room	122	13.26
Intensive Care Unit	57	6.20
EENT	10	1.09

*The missing rate is between 0.22% to 1.85%. EENT: eye, ear, nose and throat.

Descriptive statistics and correlations of NMRI, patient safety culture and PSNM

In this study, participants reported a moderate–high level of NMRI (mean = 10.95, SD 2.76) with no significant difference between age, gender, education, work experience, departments and employment status. The mean score of patient safety culture was non-punitive response to error (mean = 3.08, SD 0.69), OL (mean = 4.01, SD 0.52) and management support for safety (mean = 3.78, SD 0.68). The mean score of perceived severity of near misses was 1.56 (SD 0.43).

Except for the non-punitive response to error (r = 0.04, p = 0.29), OL (r = 0.15, p < 0.001) and management support for safety (r = 0.14, p < 0.001) were significantly positively correlated with NMRI. The perceived severity of near misses (r = –0.11, p < 0.001), however, was significantly negatively correlated with NMRI (Table 2).

Table 2.

Mean, standard deviation and variable correlations.

	M	SD	NMRI	NPRE	OL	MSPS	PSNM
NMRI	10.95	2.76	1
NPRE	3.08	0.69	0.04	1
OL	4.01	0.52	0.15**	0.23**	1
MSPS	3.78	0.68	0.14**	0.30**	0.48**	1
PSNM	1.56	0.43	−0.11**	−0.04	−0.07*	−0.01	1

p < 0.05.

p < 0.01.

NMRI: near-miss reporting intention; NPRE: non-punitive response to error; OL: organisational learning; MSPS: management support for patient safety; PSNM: perceived severity of near misses.

Hypothesis testing

The multiple regression analysis showed that OL (β = 0.56, p < 0.01), and management support for safety (β = 0.35, p < 0.05) significantly predicted NMRI. Therefore, Hypothesis One was partially supported.

The hierarchical regression analysis showed that whilst OL (β = 0.52, p < 0.01), management support for safety (β = 0.36, p < 0.05) and PSNM (β = –0.63, p < 0.01) were all significant predictors of NMRI, the effect of the interaction variables was statistically insignificant: OL × PSNM (β = 0.67, p = 0.11), MSPS × PSNM (β = –0.20, p = 0.57); therefore the PSNM did not moderate the relationship between patient safety culture and NMRI. Hypothesis Two was therefore not supported (Table 3).

Table 3.

Results of regression analysis.

Hypothesis One		Hypothesis Two
Predictors	NMRI	Predictors	NMRI
	β (95% CI)	Step one	β (95% CI)
OL	0.56** (0.18, 0.95)	OL	0.52** (0.14, 0.91)
MSPS	0.35* (0.05, 0.64)	MSPS	0.36* (0.06, 0.65)
R ²	0.03	PSNM	–0.63** (–1.03, −0.22)
F	12.96***	R ²	0.04
		F	11.73***
		Step two	β (95% CI)
		OL	0.50* (0.12, 0.89)
		MSPS	0.36* (0.07, 0.66)
		PSNM	–0.63* (–1.04, −0.22)
		OL × PSNM	0.67 (–0.15, 1.50)
		MSPS × PSNM	–0.20 (–0.87, 0.48)
		R ²	0.04
		F	7.57***

p < 0.05.

**p < 0.01.

***p < 0.001.

CI: confidence interval; NMRI: near-miss reporting intention; OL: organisational learning; MSPS: management support for patient safety; PSNM: perceived severity of near misses.

Discussion

The study examined the influence of patient safety culture on nurses’ intention to report near misses, incorporating the moderating role of PSNM. In this study, the NMRI score was 10.95 (SD 2.76), showing a moderate–high level of willingness to report near misses among nurses, which differs slightly from other studies’ findings that healthcare workers generally hold a passive attitude towards error reporting (Rutledge et al., 2018). This difference might depend on the type of event. While previous studies included both adverse events and near misses in one system, the events in this study were all near misses. In contrast to adverse events, the no-harm feature of near misses helps to reduce nurses’ fear of blame, the main barrier of event reporting. Also, that this study selected participants in tertiary teaching hospitals might be another explanation, because these organisations viewed near misses more positively and placed a higher value on near-miss education. Given the evidence that ‘doing a quick fix and not reporting’ was a common response to near misses (Hewitt and Chreim, 2017; Jeffs et al., 2012), this study demonstrated that education on near misses may have already worked. Since the behavioural intention is assumed to be an immediate antecedent of behaviour (Ajzen, 1991), this study emphasised that managers should embed near-miss education into the regular staff training to further strengthen the NMRI, thus to promote the shift to actual reporting behaviour.

Previous studies have indicated that the degree to which employees believed safety was valued in their organisational culture had an impact on safety performance. Here, patient safety culture, specifically OL and management support for safety, positively influenced NMRI. This finding is consistent with Gemmel et al. (2018), that a LEAN organisation, one characterised by learning and continuous improvement, showed more reporting behaviour by nurses. The positive effect of OL may be attributed to its role in creating a shared group norm that explicates the positive aspects of near misses and encourages learning from one’s experiences. According to Chuang et al. (2007), while heterogeneity of group members’ knowledge and experience with errors produced more in-depth investigations, the learning group norm could shape the propensity of members to engage in collective effort of learning from errors. Also, in contrast to a blame culture that inhibits reporting, an organisation with a learning culture is more likely to view reporting as a chance to prevent recurrence of errors (Manapragada, 2018) and in turn increases nurses’ intention to report near misses. Therefore, it is important to provide an organisation-wide training to create a collective understanding of near misses and a new set of standards for assessing reporting.

This study demonstrated that when management was committed to safety and provided support, nurses were more likely to report near misses, which is consistent with earlier studies (Manapragada, 2018; Richter et al., 2014; Tucker, 2003). When managers provide resources and opportunities, nurses are able to better participate in hospital safety affairs. According to the theory of planned behaviour, an individual’s perceived ease or difficulty in performing a behaviour influences behaviour intention (Ajzen, 1991). For Chinese nurses, who have long been regarded as passive performers of physicians’ orders and have limited authority in management work, management support is a major factor in reporting near misses. This result highlights the importance of nurse managers’ consistent role modelling of a safety-prioritised attitude and actions.

This study found that the effect of non-punitive response to error on NMRI was not significant, whereas prior studies reported that blame culture was a deterrent to employees’ participation in error reporting (Archer et al., 2017; Chiang et al., 2019). The difference may result from the characteristics of near misses. While most studies managed both adverse events and near misses in one system, we focused specifically on near misses that caused no actual harm and were sometimes regarded as a sign of successful recovery of incidents and thus decreased nurses’ concern regarding punitive responses to reporting. Furthermore, previous studies focused on the non-punitive response directed towards the person who committed errors while the present study did not specify for whom the responses of near misses were intended. Richter et al. (2014) pointed out that only when the staff believed that they were directly affected by a punitive environment would they consider whether to report or not. This new finding suggests that for near misses, new strategies other than the traditional non-punitive policy should be developed to promote reporting intention.

In the present study, although the perceived severity of near misses was not found to have a moderating effect as predicted, it is potentially important for developing strategies to promote reporting since it did exhibit a significant main effect on NMRI. However, in contrast to prior studies reporting that high-risk or severe events were positively associated with learning behaviour (Chuang et al., 2007; Hewitt and Chreim, 2017; Kodama and Kanda, 2010), this study showed a negative effect of the perceived severity of near misses on NMRI. This finding may be attributed to an incomplete error management system. At present, managers generally lack a clear understanding of the difference between near misses and adverse events. Most near misses, especially those with more severe potential consequences, are commonly incorporated into the adverse events system, in which the punishment remains the primary management means and inhibits nurses’ willingness to report near misses. This finding further indicates a need for culture change and, more importantly, to develop a specific near-miss management system. The current focus on efficiency in healthcare organisations means individuals tend to deal with events that appear repeatedly in their work. Ramanujam and Goodman (2003) reported that events with higher probability were more likely to gain attention whereas most of the events had minor consequences. Moreover, the failure of the perceived severity of near misses to act as a significant moderator is perhaps not surprising. According to McClelland and Judd (1993), significant moderation effects were infrequently found in field-based studies that had non-optimal distributions of variables. In the present study, the perceived severity of near-miss variables had a restricted range, with participants’ scores truncated at the lower end of the instrument (1.56 out of 5). This restriction of range in one of the interaction variables lowered the power of the test for moderation.

There are limitations that ought to be considered. First, the cross-sectional design limits the extent to which causal relationships can be inferred from this study. Future research should take a longitudinal approach to understand this relationship. Second, this study collected data through self-report surveys, which makes common method bias a possible limitation. It would be beneficial for future research to replicate our findings using more objective measures or ‘other-report’ data. Third, this study selected participants in tertiary hospitals, which might influence the findings’ automatic extrapolation to lower-level hospitals. Recruiting samples from multilevel healthcare settings is suggested for future research. Last, since two instruments in this study are newly developed, although we applied a rigorous questionnaire development procedure, it is recommended to further validate and improve these instruments with other, larger, representative samples.

Conclusion

Reporting near misses is a critical but challenging aspect of patient safety. This study presents an overview of the effect that OL, management support for safety and PSNM have on NMRI. To further encourage reporting on near misses, managers should recognise the nurses’ positive intention and develop a specific near-miss management system to transform the intention into actual behaviour. Also, hospitals should review their policies to ensure a learning and supportive environment to avoid relying solely on a traditional non-punitive response. Moreover, this study extends our knowledge that while paying attention to near misses that are actively reported, managers should focus consciously on underreported events since these near misses might be more serious from the perspective of frontline nurses.

Key points for policy, practice and/or research

Clinical teachers should integrate near-miss education into staff training to increase nurses’ awareness of the value of near misses.

It is important for healthcare organisations to develop a supportive, learning and safety-centred culture to enhance nurses’ willingness to report near misses.

Managers need a specific management system for near misses that develops new reporting strategies rather than relying on a non-punitive incentive system.

Nurse managers need to pay attention to near misses that are actively reported as well as underreported events, since these near misses usually have more severe consequences.

Footnotes

Acknowledgements

The authors gratefully acknowledge the managers and nurses in eight hospitals who support this research. Our thanks also to Prof. Xinjuan WU for her professional assistance in conducting this research.

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.

Ethics

The study was a part of the Doctoral dissertation, which was approved by the PhD research review board in School of Nursing, Peking Union Medical College on March 2015. Permission to perform the interviews and questionnaire survey was obtained from the selected hospitals. Nurses who agreed to participate were informed that the survey was anonymous, confidential and that they could elect to not answer any of the individual questions.

Funding

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

ORCID iD

Yi Yang

Yi Yang, RN, PhD candidate. Her research area concerns the nurse’s roles in improving nursing quality and patient safety.

Huaping Liu, RN, PhD, FAAN, Professor. Her research interests include nursing management, clinical nursing.

References

Ajzen

(1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes 50(2): 179–211.

Archer

Hull

Soukup

, et al.(2017) Development of a theoretical framework of factors affecting patient safety incident reporting: A theoretical review of the literature. BMJ Open 7: e017155.

Chiang H, Lee H, Lin S, et al. (2019) Factors contributing to voluntariness of incident reporting among hospital nurses. Journal of Nursing Management 27: 806–814.

Chuang

Ginsburg

Berta

(2007) Learning from preventable adverse events in health care organizations: Development of a multilevel model of learning and propositions. Health Care Management Review 32(4): 330–340.

Cohoon

(2011) Causes of near misses: Perceptions of perioperative nurses. AORN Journal 93(5): 551–565.

Fischer

Jones

Verran

(2018) Consensus achievement of leadership, organizational and individual factors that influence safety climate: Implications for nursing management. Journal of Nursing Management 26(1): 50–58.

Gemmel

Beveren

Landry

, et al.(2018) Problem-solving behavior of nurses in a lean environment. Journal of Nursing Management 27(1): 35–41.

Hewitt

Chreim

(2017) Fix and forget or fix and report: A qualitative study of tensions at the front line of incident reporting. BMJ Quality & Safety 24(5): 303–310.

Homsma

Dyck

Gilder

(2009) Learning from error: The influence of error incident characteristics. Journal of Applied Business Research 62: 115–122.

10.

Hoppes M and Mitchell J (2013) Serious safety events: A focus on harm classification: Deviation in care as link. Getting to Zero White Paper Series – edition no. 2. American Society for Healthcare Risk Management. Available at: https://www.ashrm.org/sites/default/files/ashrm/SSE-2_getting_to_zero-9-30-14.pdf (accessed 10 August 2017).

11.

Jeffs

Berta

Lingard

, et al.(2012) Learning from near misses: From quick fixes to closing off the Swiss-cheese holes. BMJ Quality & Safety 21(4): 287–294.

12.

Kodama

Kanda

(2010) Nurse risk managers’ criteria for dealing with near-miss events. BioScience Trends 4(5): 231–238.

13.

Ladner

Baker

(2013) Near-miss events: A vastly missed opportunity. Liver Transplantation 19(5): 467–469.

14.

Liang

(2014) Hospital Survey on Patient Safety Culture in Tertiary General Hospital in Beijing, Beijing: Peking Union Medical College.

15.

McClelland

Judd

(1993) Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin 114(2): 376–390.

16.

Makary

Daniel

(2016) Medical error—the third leading cause of death in the US. BMJ 353: i2139.

17.

Manapragada

(2018) When safety climate is not enough: Examining the moderating effects of psychosocial hazards on nurse safety performance. Journal of Advanced Nursing 75(6): 1207–1218.

18.

Ramanujam

Goodman

(2003) Latent errors and adverse organizational consequences: A conceptualization. Journal of Organizational Behavior 24: 815–836.

19.

Richter

McAlearney

Pennell

(2014) Evaluating the effect of safety culture on error reporting: A comparison of managerial and staff perspectives. American Journal of Medical Quality 30(6): 550–558.

20.

Rutledge

Retrosi

Ostrowski

(2018) Barriers to medication error reporting among hospital nurses. Journal of Clinical Nursing 27(9–10): 1941–1949.

21.

Sheikhtaheri

(2014) Near misses and their importance for improving patient safety. Iranian Journal of Public Health 43(6): 853–854.

22.

Singal

Zafar

Tbakhi

, et al.(2018) Assessment of knowledge and attitudes towards safety events reporting among residents in a community health system. Journal of Community Hospital Internal Medicine Perspectives 8(5): 253–259.

23.

Sorra

Dyer

(2010) Multilevel psychometric properties of the AHRQ hospital survey on patient safety culture. BMC Health Services Research 10: 199.

24.

Spall

Kassam

Tollefson

(2015) Near-misses are an opportunity to improve patient safety. Otolaryngology & Head and Neck Surgery 23(4): 292–296.

25.

Terwee

Bot

de Boer

, et al.(2007) Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology 60(1): 34.

26.

The Joint Commission (2016) Comprehensive Accreditation Manual for Hospitals: The Patient Safety Systems Chapter, Update 2. Available at: www.jointcommission.org/assets/1/18/PSC_for_web.pdf (accessed 23 May 2017).

27.

Tucker

(2003) Organizational Learning from Operational Failure, Boston: Harvard University.

28.

World Health Organization (2005) World Alliance for Patient Safety: WHO Draft Guidelines for Adverse Event Reporting and Learning Systems: From information to action, Geneva: World Health Organization.

29.

World Health Organization (2009) World Alliance for Patient Safety: The Conceptual Framework for the International Classification for Patient Safety, Geneva: World Health Organization.