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NS-2333; No. of Pages 9 International Journal of Nursing Studies xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
International Journal of Nursing Studies journal homepage: www.elsevier.com/ijns
The relationship between patient safety culture and adverse events: A questionnaire survey Xue Wang a, Ke Liu b,*, Li-ming You b, Jia-gen Xiang c, Hua-gang Hu d, Li-feng Zhang b, Jing Zheng b, Xiao-wen Zhu e a
Department of Orthopaedics, The First Affiliated Hospital of Chongqing Medical University, China School of Nursing, Sun Yat-sen University, China School of Nursing, Guangzhou University of Chinese Medicine, China d School of Nursing, Soochow University, China e Department of Nursing, School of Medicine, Jinan University, China b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 17 April 2013 Received in revised form 10 December 2013 Accepted 18 December 2013
Background: Patient safety culture is an important factor in the effort to reduce adverse events in the hospital and improve patient safety. A few studies have shown the relationship between patient safety culture and adverse events, yet no such research has been reported in China. Objectives: This study aimed to describe nurses’ perception of patient safety culture and frequencies of adverse events, and examine the relationship between them. Design: This study was a descriptive, correlated study. Setting and participants: We selected 28 inpatient units and emergency departments in 7 level-3 general hospitals from 5 districts in Guangzhou, China, and we surveyed 463 nurses. Methods: The Hospital Survey on Patient Safety Culture was used to measure nurses’ perception of patient safety culture, and the frequencies of adverse events which happened frequently in hospital were estimated by nurses. We used multiple logistic regression models to examine the relationship between patient safety culture scores and estimated frequencies of each type of adverse event. Results: The Positive Response Rates of 12 dimensions of the Hospital Survey on Patient Safety Culture varied from 23.6% to 89.7%. There were 47.8–75.6% nurses who estimated that these adverse events had happened in the past year. After controlling for all nurse related factors, a higher mean score of ‘‘Organizational Learning-Continuous Improvement’’ was significantly related to lower the occurrence of pressure ulcers (OR = 0.249), prolonged physical restraint (OR = 0.406), and complaints (OR = 0.369); a higher mean score of ‘‘Frequency of Event Reporting’’ was significantly related to lower the occurrence of medicine errors (OR = 0.699) and pressure ulcers (OR = 0.639). Conclusions: The results confirmed the hypothesis that an improvement in patient safety culture was related to a decrease in the occurrence of adverse events. ß 2013 Elsevier Ltd. All rights reserved.
Keywords: Adverse events Patient safety Patient safety culture Chinese hospital Nursing
* Corresponding author at: School of Nursing, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou 510089, China. Tel.: +86 20 87334850. E-mail address: [email protected] (K. Liu). 0020-7489/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
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NS-2333; No. of Pages 9 2
X. Wang et al. / International Journal of Nursing Studies xxx (2014) xxx–xxx
What is already known about the topic? Theoretically, patient safety culture (PSC) is regarded as an important factor in the prevention of adverse events (AEs) in healthcare settings, but the relationship lacks quantitative evidence. Few studies have examined the relationship between PSC and AEs. Although some studies have investigated the rates of some AEs and nurses’ perception of PSC, no study had examined the relationship between them in Chinese hospitals. What this paper adds Nurses’ perception of PSC was not satisfactory and the nurse-estimated AEs were high in Chinese hospitals. Improvement in nurses’ perception of PSC was related to a decrease in the occurrence of patient AEs. 1. Introduction 1.1. Background The Institute of Medicine (IOM) emphasized that it was important for healthcare organizations to establish a safety culture to ensure that patients were not inadvertently harmed by errors in the care which was supposed to heal them (Stefl, 2001). PSC in healthcare organizations, specifically hospitals, includes communication founded on mutual trust, good information flow, shared perception of the importance of safety, organizational learning, commitment from management and leadership, and the presence of a non-punitive approach to incident and error reporting (Sanders and Cook, 2007). AEs have become a global problem; they are an important indicator of patient safety (Baker et al., 2004). The IOM pointed out that preventable AEs happen not only due to individual factors such as inadequate skills or knowledge of nurses or doctors; it claimed that system errors due to problems in areas such as management, work environment and staffing are a more important aspect of preventable AEs (Stefl, 2001). It is therefore urgent to build a safety system, and building a safety culture is the first step towards it (Maurette, 2002). There are several methods of collection of AEs data, such as reviews of medical or nursing records, direct observation, reporting systems, nurses’ estimates, patient interviews and so on (Cina-Tschumi et al., 2009; Flynn et al., 2002; Olsen et al., 2007). Each method has its strengths and weaknesses. For example, a review of medical or nursing records and direct observation can provide accurate information of antecedents and outcomes of AEs, but implementing it may cost more time and staffing (Flynn et al., 2002). A reporting system is an accepted useful method to collect information about AEs, but the high missed report rate is its weakness (GrenierSennelier et al., 2002). Many hospitals have a reporting system, but most of them do not work well in China (Dai et al., 2009). Nurses’ estimates can not only collect mass of data in a short amount of time with little money and staffing, but also collect more accurate information
without fear of punishment (Stratton et al., 2004). Although this method of data collection may be subject to respondent bias and recall bias (Manojlovich and DeCicco, 2007), Cina-Tschumi et al. (2009) showed that nurses’ estimated ‘‘patient fall’’ frequencies over the period of one year were concordant with continuously and systematically assessed data and more accurate than the latter over one month. This method has showed usefulness in other studies (Aiken et al., 2001; Sochalski, 2004). For these reasons, we have chosen to use nurses’ estimates to collect data about the frequencies of AEs over a period of one year. It has been suggested that establishing a good safety culture can help prevent an error chain from causing a real error (Reason, 1995), but the relationship between PSC and AEs lacks quantitative evidence. Some researches (Hansen et al., 2011; Singer et al., 2009; Zohar et al., 2007) found that PSC was negatively correlated with some AEs (medicine error, acute myocardial infarction, heart failure or Patient Safety Indicators which monitored AEs). Another study (Ausserhofer et al., 2012) found that none of the AEs it looked at (medication administration error, pressure ulcer, patient fall, urinary tract infection, bloodstream infection and pneumonia) was significantly correlated with PSC, while rationing of nursing care was significantly correlated with patient satisfaction, medicine errors, bloodstream infection and pneumonia; this indicated that nurse-related organizational factors may have affected AEs. Studies that examined the relationship between PSC and a single type of AE employed controls for nurse-related factors such as staffing ratio and education (Hansen et al., 2011; Vogus and Sutcliffe, 2007). We deduced from this that for our examination of the relationship between PSC and AEs, we would need to take account of nurse-related factors. To our knowledge, a few researches have been conducted to explore the relationship between PSC and AEs, yet none examined the relationship between PSC and AEs in China. 1.2. Objectives The objectives of this study were to describe nurses’ perception of PSC and their estimate of the frequencies of AEs and to examine the relationship between PSC and AEs in Chinese hospitals. 2. Methods 2.1. Design This study was a descriptive, correlated study. 2.2. Sample and setting Eight out of Guangzhou’s twelve districts are described as main urban areas due to high population density. Based on stratified sampling, we sampled seven level-3 hospitals (the large, high-tech hospitals with 1000–2500 beds) in five main urban areas of Guangzhou, covering 1 in 3 of Guangzhou’s total count of level-3 hospitals and 5 in
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
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NS-2333; No. of Pages 9 X. Wang et al. / International Journal of Nursing Studies xxx (2014) xxx–xxx
8 of all its main urban areas. One medical unit, one surgical unit, one Intensive Care Unit (ICU) and one emergency department from each hospital were selected, 28 units in total. The study surveyed all of the nurses working in these units from October 2010 to January 2011. The inclusion criteria of nurse were as follows: registered nurses who had worked at least one year in the current hospital. Totally, 640 questionnaires were delivered, 539 (84.2%) nurses returned the questionnaires and 463 (72.3%) questionnaires were valid. 2.3. Measuring instrument The Hospital Survey on Patient Safety Culture (HSOPSC) and AE questionnaires were used to collect data. The HSOPSC was pilot tested, revised and then released by the Agency for Healthcare Research and Quality (AHRQ) (Sorra and Nieva, 2004). The HSOPSC contains 42 items to measure 12 patient safety culture dimensions. The items used 5-point Likert response scales of agreement (‘‘strongly disagree’’ to ‘‘strongly agree’’) or frequency (‘‘never’’ to ‘‘always’’), so the mean score of each dimension could be calculated. In addition, a Positive Response Rate (PRR) could be calculated for each item from responses of ‘‘strongly agree/agree’’ or ‘‘always/most of the time’’. To calculate the PRR of one dimension, first step is to compute the PRR for each item and then calculate the mean PRR across all items of this dimension. Similarly, the mean PRRs of overall HSOPSC can be calculated. If the PRR is over 75%, this dimension is defined as ‘‘patient safety strength’’. The HSOPSC was translated into Chinese by this research team and content validity was established, and the reliability test showed a good internal consistency: Cronbach’s a (Xiang et al., 2012) was 0.853. We investigated the following 7 AEs which occurred frequently in hospitals and considered to be sensitive to nursing care as the indicators to report (Aiken et al., 2001; Flynn et al., 2002; Yang et al., 2010): medicine error (ME), pressure ulcer (PU), patient falls (PF), physical restraints for more than 8 h (PR 8 h), surgical wound infection (SWI), infusion or transfusion reaction (IR/TR) and patients or their family complaints (PC/FC). The frequencies of AEs were scored as ‘‘never happen = 0’’, ‘‘several times a year = 1’’, ‘‘once a month or less = 2’’, ‘‘several times a month = 3’’, ‘‘once a week = 4’’, ‘‘several times a week = 5’’, ‘‘everyday = 6’’ in the past year using a 7-level rating scale estimated by nurses. Additionally, nurses’ demographic data were collected, including gander, age, the highest education in nursing, current work unit, hospital working years and hours worked per week. 2.4. Statistical analysis We used SPSS (Version 17.0) to perform the statistical analysis. Descriptive statistics, including frequencies, percentages and tables were used for nurses’ demographic data, the HSOPSC and AEs. We used a series of Chi-square tests to confirm that the samples came from a same statistical mass. We calculated intra-class correlation coefficient (ICC) both within unit and hospital and in the
3
same unit of different hospitals to examine the validity of this method of measuring AEs. To examine the relationship between PSC and AEs, we used bivariate regression models for each AE and 12 HSOPSC dimensions at first; then we performed multiple logistic regression models with one type of AE as the dependent variable and 12 HSOPSC dimensions as independent variables with control for all nurse related factors. The standard of significance was set at a < 0.05. Considering that the main purpose of our research was to explore whether PSC levels related to rates of AE’s, we checked that no data was lost after collapsing the reports of AEs into a binary none/some variable. In those models, we combined 7 categories of frequencies of AEs into a binomial variable named ‘‘never happened = 0’’ (responded ‘‘never happened’’) and ‘‘had happened = 1’’ (responses of ‘‘several times a year’’, ‘‘once a month or less’’, ‘‘several times a month’’, ‘‘once a week’’, ‘‘several times a week’’ or ‘‘everyday’’). Since the explanatory and response variables came from the same investigated nurses, we performed split half analysis (Van den Heede et al., 2013) to test our findings. Half of the random sample from all the participating nurses was used to recreate HSOPSC dimensions as the explanatory variables, whereas the other half of the sample was used to recreate the AEs as the response variables. We conducted the split half analysis five times using SPSS (Version 17.0). These results showed negligible difference from the total sample results which reinforced our findings. Therefore, it was used in both of bivariate regression models and multiple logistic regression models. 2.5. Ethical considerations The research proposal was approved by Ethical Committee of School of Nursing, Sun Yat-sen University. Informed consents were obtained from all sampled hospitals and nurses. The survey was strictly anonymous to ensure nurses’ privacy. 3. Results 3.1. Participants There were 463 nurses in our sample and they came from a same statistical mass as confirmed by Chi-square tests. Most of the nurses were female (95.1%). They were between 21 and 53 years old, and the mean age was 30.67 5.92. More than half of them (57.0%) were in their twenties. More than half of nurses (54.1%) did not hold a baccalaureate degree. These nurses worked in medical units (17.7%), surgical units (18.4%), ICU (21.0%) and emergency departments (43.0%). There were 43.5% nurses working for more than 10 years in their current hospital. About 41% nurses worked over 40 h per week (see Table 1). 3.2. Patient safety culture The PRRs and mean scores of 12 HSOPSC dimensions and overall score were calculated (see Table 2). The PRRs ranged from 23.6% to 89.7%, and mean scores ranged from
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
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4 Table 1 Demographic information of nurses. Nurse factors Gender – % Female Male Age (in years) – % 21–25 26–30 31–35 36–40 41–53 Highest education in nursing Secondary & Advanced diploma Baccalaureate & Master degree Current work unit – % Medical unit Surgical unit ICU Emergency department Hospital working years – % 1–10 11–20 21–31 Hours worked per week – % 30–40 41–60
Total-n (%) Mean SD
Hospital 1 Hospital 2 Hospital 3 Hospital 4 Hospital 5 Hospital 6 Hospital 7 P-values
425(95.1) 22(4.9)
97.1 2.9
94.3 5.7
102(23.4) 146(33.6) 100(23.0) 63(14.5) 24(5.5) –% 248(54.1)
24.6 35.5 20.0 12.3 7.5
28.6 32.8 20.3 11.3 7.0
49.3
202(45.9)
82(17.7) 85(18.4) 97(21.0) 199(43.0)
92.9 7.1
96.4 3.6
90.2 9.8
95.8 4.2
0.281
24.7 31.1 22.2 16.2 5.8
24.2 22.6 32.3 14.5 6.5
25.7 30.0 23.7 13.7 5.9
26.7 22.4 24.1 21.1 5.7
25.7 24.3 22.9 20.0 7.1
0.136
57.4
59.2
57.6
59.3
62.1
62.5
0.238
50.7
42.6
40.8
42.4
40.7
37.9
37.5
21.1 19.7 11.3 47.9
14.1 26.8 18.3 40.8
14.5 20.0 27.3 38.2
20.0 15.7 22.9 41.4
21.3 11.5 26.2 41.0
19.4 16.1 38.7 25.8
13.7 17.8 6.8 61.6
0.206
58.7 32.9 8.4
56.5 32.1 11.5
52.0 38.5 9.6
49.7 40.0 10.3
53.9 37.5 8.6
54.3 35.6 10.1
52.9 38.6 8.6
0.224
83.3 16.2
87.7 12.3
90.8 9.2
87.3 12.7
90.6 9.4
88.6 11.4
85.4 14.6
0.205
30.67 5.92
9.60 6.90 247(56.5) 161(36.8) 29(6.6) 38.14 3.58 264(58.7) 186(41.3)
2.58 0.60 to 4.10 0.47. The overall PRR was 57.4%. The PRR of ‘‘Organizational Learning-Continuous Improvement’’ (PRR = 89.7%) was the highest followed by ‘‘Teamwork within Units’’ (PRR = 86.5%). The PRR of ‘‘Staffing’’ (PRR = 23.6%) was the lowest. The PRRs of ‘‘Non-punitive Response to Error’’, ‘‘Communication Openness’’ and ‘‘Frequency of Event Reporting’’ were all less than 50%. 3.3. Adverse events To examine the validity of this method of measuring AEs, we calculated intra-class correlation coefficient (ICC) Table 2 Descriptive statistics of the HSOPSC. HSOPSC
PRRa (%)
Mean SD
Organizational Learning-Continuous Improvementb Teamwork Within Unitsb Supervisor/Manager Expectations & Action Promoting Safety Feedback and Communication About Error Hospital Handoffs and Transitions Hospital Management Support for Patient Safety Overall Perceptions of Safety Teamwork Across Hospital Units Frequency of Event Reporting Communication Openness Non-punitive Response to Error Staffing Overall
89.7
4.10 0.47
86.5 73.8
4.09 0.56 3.81 0.52
69.4
3.88 0.67
68.1 59.6
3.37 0.58 3.55 0.67
53.0 50.1 44.2 38.5 32.0 23.6 57.4
3.35 0.53 3.38 0.58 3.40 0.87 3.18 0.67 2.82 0.70 2.58 0.60 3.46 0.34
a b
100 0
Positive Response Rate (PRR). PRR > 75% was defined as patient safety strength.
both within unit (average measure ICC from 0.514 to 0.854, P-values
NS-2333; No. of Pages 9 International Journal of Nursing Studies xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
International Journal of Nursing Studies journal homepage: www.elsevier.com/ijns
The relationship between patient safety culture and adverse events: A questionnaire survey Xue Wang a, Ke Liu b,*, Li-ming You b, Jia-gen Xiang c, Hua-gang Hu d, Li-feng Zhang b, Jing Zheng b, Xiao-wen Zhu e a
Department of Orthopaedics, The First Affiliated Hospital of Chongqing Medical University, China School of Nursing, Sun Yat-sen University, China School of Nursing, Guangzhou University of Chinese Medicine, China d School of Nursing, Soochow University, China e Department of Nursing, School of Medicine, Jinan University, China b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 17 April 2013 Received in revised form 10 December 2013 Accepted 18 December 2013
Background: Patient safety culture is an important factor in the effort to reduce adverse events in the hospital and improve patient safety. A few studies have shown the relationship between patient safety culture and adverse events, yet no such research has been reported in China. Objectives: This study aimed to describe nurses’ perception of patient safety culture and frequencies of adverse events, and examine the relationship between them. Design: This study was a descriptive, correlated study. Setting and participants: We selected 28 inpatient units and emergency departments in 7 level-3 general hospitals from 5 districts in Guangzhou, China, and we surveyed 463 nurses. Methods: The Hospital Survey on Patient Safety Culture was used to measure nurses’ perception of patient safety culture, and the frequencies of adverse events which happened frequently in hospital were estimated by nurses. We used multiple logistic regression models to examine the relationship between patient safety culture scores and estimated frequencies of each type of adverse event. Results: The Positive Response Rates of 12 dimensions of the Hospital Survey on Patient Safety Culture varied from 23.6% to 89.7%. There were 47.8–75.6% nurses who estimated that these adverse events had happened in the past year. After controlling for all nurse related factors, a higher mean score of ‘‘Organizational Learning-Continuous Improvement’’ was significantly related to lower the occurrence of pressure ulcers (OR = 0.249), prolonged physical restraint (OR = 0.406), and complaints (OR = 0.369); a higher mean score of ‘‘Frequency of Event Reporting’’ was significantly related to lower the occurrence of medicine errors (OR = 0.699) and pressure ulcers (OR = 0.639). Conclusions: The results confirmed the hypothesis that an improvement in patient safety culture was related to a decrease in the occurrence of adverse events. ß 2013 Elsevier Ltd. All rights reserved.
Keywords: Adverse events Patient safety Patient safety culture Chinese hospital Nursing
* Corresponding author at: School of Nursing, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou 510089, China. Tel.: +86 20 87334850. E-mail address: [email protected] (K. Liu). 0020-7489/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
G Model
NS-2333; No. of Pages 9 2
X. Wang et al. / International Journal of Nursing Studies xxx (2014) xxx–xxx
What is already known about the topic? Theoretically, patient safety culture (PSC) is regarded as an important factor in the prevention of adverse events (AEs) in healthcare settings, but the relationship lacks quantitative evidence. Few studies have examined the relationship between PSC and AEs. Although some studies have investigated the rates of some AEs and nurses’ perception of PSC, no study had examined the relationship between them in Chinese hospitals. What this paper adds Nurses’ perception of PSC was not satisfactory and the nurse-estimated AEs were high in Chinese hospitals. Improvement in nurses’ perception of PSC was related to a decrease in the occurrence of patient AEs. 1. Introduction 1.1. Background The Institute of Medicine (IOM) emphasized that it was important for healthcare organizations to establish a safety culture to ensure that patients were not inadvertently harmed by errors in the care which was supposed to heal them (Stefl, 2001). PSC in healthcare organizations, specifically hospitals, includes communication founded on mutual trust, good information flow, shared perception of the importance of safety, organizational learning, commitment from management and leadership, and the presence of a non-punitive approach to incident and error reporting (Sanders and Cook, 2007). AEs have become a global problem; they are an important indicator of patient safety (Baker et al., 2004). The IOM pointed out that preventable AEs happen not only due to individual factors such as inadequate skills or knowledge of nurses or doctors; it claimed that system errors due to problems in areas such as management, work environment and staffing are a more important aspect of preventable AEs (Stefl, 2001). It is therefore urgent to build a safety system, and building a safety culture is the first step towards it (Maurette, 2002). There are several methods of collection of AEs data, such as reviews of medical or nursing records, direct observation, reporting systems, nurses’ estimates, patient interviews and so on (Cina-Tschumi et al., 2009; Flynn et al., 2002; Olsen et al., 2007). Each method has its strengths and weaknesses. For example, a review of medical or nursing records and direct observation can provide accurate information of antecedents and outcomes of AEs, but implementing it may cost more time and staffing (Flynn et al., 2002). A reporting system is an accepted useful method to collect information about AEs, but the high missed report rate is its weakness (GrenierSennelier et al., 2002). Many hospitals have a reporting system, but most of them do not work well in China (Dai et al., 2009). Nurses’ estimates can not only collect mass of data in a short amount of time with little money and staffing, but also collect more accurate information
without fear of punishment (Stratton et al., 2004). Although this method of data collection may be subject to respondent bias and recall bias (Manojlovich and DeCicco, 2007), Cina-Tschumi et al. (2009) showed that nurses’ estimated ‘‘patient fall’’ frequencies over the period of one year were concordant with continuously and systematically assessed data and more accurate than the latter over one month. This method has showed usefulness in other studies (Aiken et al., 2001; Sochalski, 2004). For these reasons, we have chosen to use nurses’ estimates to collect data about the frequencies of AEs over a period of one year. It has been suggested that establishing a good safety culture can help prevent an error chain from causing a real error (Reason, 1995), but the relationship between PSC and AEs lacks quantitative evidence. Some researches (Hansen et al., 2011; Singer et al., 2009; Zohar et al., 2007) found that PSC was negatively correlated with some AEs (medicine error, acute myocardial infarction, heart failure or Patient Safety Indicators which monitored AEs). Another study (Ausserhofer et al., 2012) found that none of the AEs it looked at (medication administration error, pressure ulcer, patient fall, urinary tract infection, bloodstream infection and pneumonia) was significantly correlated with PSC, while rationing of nursing care was significantly correlated with patient satisfaction, medicine errors, bloodstream infection and pneumonia; this indicated that nurse-related organizational factors may have affected AEs. Studies that examined the relationship between PSC and a single type of AE employed controls for nurse-related factors such as staffing ratio and education (Hansen et al., 2011; Vogus and Sutcliffe, 2007). We deduced from this that for our examination of the relationship between PSC and AEs, we would need to take account of nurse-related factors. To our knowledge, a few researches have been conducted to explore the relationship between PSC and AEs, yet none examined the relationship between PSC and AEs in China. 1.2. Objectives The objectives of this study were to describe nurses’ perception of PSC and their estimate of the frequencies of AEs and to examine the relationship between PSC and AEs in Chinese hospitals. 2. Methods 2.1. Design This study was a descriptive, correlated study. 2.2. Sample and setting Eight out of Guangzhou’s twelve districts are described as main urban areas due to high population density. Based on stratified sampling, we sampled seven level-3 hospitals (the large, high-tech hospitals with 1000–2500 beds) in five main urban areas of Guangzhou, covering 1 in 3 of Guangzhou’s total count of level-3 hospitals and 5 in
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
G Model
NS-2333; No. of Pages 9 X. Wang et al. / International Journal of Nursing Studies xxx (2014) xxx–xxx
8 of all its main urban areas. One medical unit, one surgical unit, one Intensive Care Unit (ICU) and one emergency department from each hospital were selected, 28 units in total. The study surveyed all of the nurses working in these units from October 2010 to January 2011. The inclusion criteria of nurse were as follows: registered nurses who had worked at least one year in the current hospital. Totally, 640 questionnaires were delivered, 539 (84.2%) nurses returned the questionnaires and 463 (72.3%) questionnaires were valid. 2.3. Measuring instrument The Hospital Survey on Patient Safety Culture (HSOPSC) and AE questionnaires were used to collect data. The HSOPSC was pilot tested, revised and then released by the Agency for Healthcare Research and Quality (AHRQ) (Sorra and Nieva, 2004). The HSOPSC contains 42 items to measure 12 patient safety culture dimensions. The items used 5-point Likert response scales of agreement (‘‘strongly disagree’’ to ‘‘strongly agree’’) or frequency (‘‘never’’ to ‘‘always’’), so the mean score of each dimension could be calculated. In addition, a Positive Response Rate (PRR) could be calculated for each item from responses of ‘‘strongly agree/agree’’ or ‘‘always/most of the time’’. To calculate the PRR of one dimension, first step is to compute the PRR for each item and then calculate the mean PRR across all items of this dimension. Similarly, the mean PRRs of overall HSOPSC can be calculated. If the PRR is over 75%, this dimension is defined as ‘‘patient safety strength’’. The HSOPSC was translated into Chinese by this research team and content validity was established, and the reliability test showed a good internal consistency: Cronbach’s a (Xiang et al., 2012) was 0.853. We investigated the following 7 AEs which occurred frequently in hospitals and considered to be sensitive to nursing care as the indicators to report (Aiken et al., 2001; Flynn et al., 2002; Yang et al., 2010): medicine error (ME), pressure ulcer (PU), patient falls (PF), physical restraints for more than 8 h (PR 8 h), surgical wound infection (SWI), infusion or transfusion reaction (IR/TR) and patients or their family complaints (PC/FC). The frequencies of AEs were scored as ‘‘never happen = 0’’, ‘‘several times a year = 1’’, ‘‘once a month or less = 2’’, ‘‘several times a month = 3’’, ‘‘once a week = 4’’, ‘‘several times a week = 5’’, ‘‘everyday = 6’’ in the past year using a 7-level rating scale estimated by nurses. Additionally, nurses’ demographic data were collected, including gander, age, the highest education in nursing, current work unit, hospital working years and hours worked per week. 2.4. Statistical analysis We used SPSS (Version 17.0) to perform the statistical analysis. Descriptive statistics, including frequencies, percentages and tables were used for nurses’ demographic data, the HSOPSC and AEs. We used a series of Chi-square tests to confirm that the samples came from a same statistical mass. We calculated intra-class correlation coefficient (ICC) both within unit and hospital and in the
3
same unit of different hospitals to examine the validity of this method of measuring AEs. To examine the relationship between PSC and AEs, we used bivariate regression models for each AE and 12 HSOPSC dimensions at first; then we performed multiple logistic regression models with one type of AE as the dependent variable and 12 HSOPSC dimensions as independent variables with control for all nurse related factors. The standard of significance was set at a < 0.05. Considering that the main purpose of our research was to explore whether PSC levels related to rates of AE’s, we checked that no data was lost after collapsing the reports of AEs into a binary none/some variable. In those models, we combined 7 categories of frequencies of AEs into a binomial variable named ‘‘never happened = 0’’ (responded ‘‘never happened’’) and ‘‘had happened = 1’’ (responses of ‘‘several times a year’’, ‘‘once a month or less’’, ‘‘several times a month’’, ‘‘once a week’’, ‘‘several times a week’’ or ‘‘everyday’’). Since the explanatory and response variables came from the same investigated nurses, we performed split half analysis (Van den Heede et al., 2013) to test our findings. Half of the random sample from all the participating nurses was used to recreate HSOPSC dimensions as the explanatory variables, whereas the other half of the sample was used to recreate the AEs as the response variables. We conducted the split half analysis five times using SPSS (Version 17.0). These results showed negligible difference from the total sample results which reinforced our findings. Therefore, it was used in both of bivariate regression models and multiple logistic regression models. 2.5. Ethical considerations The research proposal was approved by Ethical Committee of School of Nursing, Sun Yat-sen University. Informed consents were obtained from all sampled hospitals and nurses. The survey was strictly anonymous to ensure nurses’ privacy. 3. Results 3.1. Participants There were 463 nurses in our sample and they came from a same statistical mass as confirmed by Chi-square tests. Most of the nurses were female (95.1%). They were between 21 and 53 years old, and the mean age was 30.67 5.92. More than half of them (57.0%) were in their twenties. More than half of nurses (54.1%) did not hold a baccalaureate degree. These nurses worked in medical units (17.7%), surgical units (18.4%), ICU (21.0%) and emergency departments (43.0%). There were 43.5% nurses working for more than 10 years in their current hospital. About 41% nurses worked over 40 h per week (see Table 1). 3.2. Patient safety culture The PRRs and mean scores of 12 HSOPSC dimensions and overall score were calculated (see Table 2). The PRRs ranged from 23.6% to 89.7%, and mean scores ranged from
Please cite this article in press as: Wang, X., et al., The relationship between patient safety culture and adverse events: A questionnaire survey. Int. J. Nurs. Stud. (2014), http://dx.doi.org/10.1016/j.ijnurstu.2013.12.007
G Model
NS-2333; No. of Pages 9 X. Wang et al. / International Journal of Nursing Studies xxx (2014) xxx–xxx
4 Table 1 Demographic information of nurses. Nurse factors Gender – % Female Male Age (in years) – % 21–25 26–30 31–35 36–40 41–53 Highest education in nursing Secondary & Advanced diploma Baccalaureate & Master degree Current work unit – % Medical unit Surgical unit ICU Emergency department Hospital working years – % 1–10 11–20 21–31 Hours worked per week – % 30–40 41–60
Total-n (%) Mean SD
Hospital 1 Hospital 2 Hospital 3 Hospital 4 Hospital 5 Hospital 6 Hospital 7 P-values
425(95.1) 22(4.9)
97.1 2.9
94.3 5.7
102(23.4) 146(33.6) 100(23.0) 63(14.5) 24(5.5) –% 248(54.1)
24.6 35.5 20.0 12.3 7.5
28.6 32.8 20.3 11.3 7.0
49.3
202(45.9)
82(17.7) 85(18.4) 97(21.0) 199(43.0)
92.9 7.1
96.4 3.6
90.2 9.8
95.8 4.2
0.281
24.7 31.1 22.2 16.2 5.8
24.2 22.6 32.3 14.5 6.5
25.7 30.0 23.7 13.7 5.9
26.7 22.4 24.1 21.1 5.7
25.7 24.3 22.9 20.0 7.1
0.136
57.4
59.2
57.6
59.3
62.1
62.5
0.238
50.7
42.6
40.8
42.4
40.7
37.9
37.5
21.1 19.7 11.3 47.9
14.1 26.8 18.3 40.8
14.5 20.0 27.3 38.2
20.0 15.7 22.9 41.4
21.3 11.5 26.2 41.0
19.4 16.1 38.7 25.8
13.7 17.8 6.8 61.6
0.206
58.7 32.9 8.4
56.5 32.1 11.5
52.0 38.5 9.6
49.7 40.0 10.3
53.9 37.5 8.6
54.3 35.6 10.1
52.9 38.6 8.6
0.224
83.3 16.2
87.7 12.3
90.8 9.2
87.3 12.7
90.6 9.4
88.6 11.4
85.4 14.6
0.205
30.67 5.92
9.60 6.90 247(56.5) 161(36.8) 29(6.6) 38.14 3.58 264(58.7) 186(41.3)
2.58 0.60 to 4.10 0.47. The overall PRR was 57.4%. The PRR of ‘‘Organizational Learning-Continuous Improvement’’ (PRR = 89.7%) was the highest followed by ‘‘Teamwork within Units’’ (PRR = 86.5%). The PRR of ‘‘Staffing’’ (PRR = 23.6%) was the lowest. The PRRs of ‘‘Non-punitive Response to Error’’, ‘‘Communication Openness’’ and ‘‘Frequency of Event Reporting’’ were all less than 50%. 3.3. Adverse events To examine the validity of this method of measuring AEs, we calculated intra-class correlation coefficient (ICC) Table 2 Descriptive statistics of the HSOPSC. HSOPSC
PRRa (%)
Mean SD
Organizational Learning-Continuous Improvementb Teamwork Within Unitsb Supervisor/Manager Expectations & Action Promoting Safety Feedback and Communication About Error Hospital Handoffs and Transitions Hospital Management Support for Patient Safety Overall Perceptions of Safety Teamwork Across Hospital Units Frequency of Event Reporting Communication Openness Non-punitive Response to Error Staffing Overall
89.7
4.10 0.47
86.5 73.8
4.09 0.56 3.81 0.52
69.4
3.88 0.67
68.1 59.6
3.37 0.58 3.55 0.67
53.0 50.1 44.2 38.5 32.0 23.6 57.4
3.35 0.53 3.38 0.58 3.40 0.87 3.18 0.67 2.82 0.70 2.58 0.60 3.46 0.34
a b
100 0
Positive Response Rate (PRR). PRR > 75% was defined as patient safety strength.
both within unit (average measure ICC from 0.514 to 0.854, P-values
