Perceptions of patient safety culture among healthcare employees in tertiary hospitals of Heilongjiang province in northern China: a cross-sectional study

Perceptions of patient safety culture among healthcare employees in tertiary hospitals of... Abstract Objective Assessing the patient safety culture is necessary for improving patient safety. Research on patient safety culture has attracted considerable attention. Currently, there is little research on patient safety culture in China generally, and in Heilongjiang in northern China specifically. The aim of the study is to explore the perception of healthcare employees about patient safety culture and to determine whether perception differs per sex, age, profession, years of experience, education level and marital status. Design Cross-sectional study. Setting Thirteen tertiary hospitals in Heilongjiang, northern China. Participants About 1024 healthcare employees. Main Outcome Measure The perception of healthcare employees was measured using the safety attitude questionnaire, which include six dimensions. Higher scores represented more positive attitudes. An analysis of variance was used to compare socio-demographic differences per position, marital status and education; t-tests were used for sex, age and experience. Results A total of 1024 (85.33%) valid questionnaires were returned. The mean score of the six dimensions was 73.74/100; work conditions (80.19) had the highest score of all the dimensions, and safety climate (70.48) had the lowest. Across distinct dimensions, there were significant differences in perceptions of patient safety culture per sex, age, years of experience, position, marital status and education level (P < 0.05). Conclusions The findings can help in assessing perceived patient safety culture among healthcare employees and identifying dimensions that require improvement. Interventions aimed at specific socio-demographic groups are necessary to improve patient safety culture. patient safety culture, tertiary hospital, healthcare employee Introduction Security is one of the human needs related to survival and development. Patients in hospitals seek medical safety; hence, patient safety is a widespread concern. The US Institute of Medicine defines patient safety as enabling patients to avoid accidental injury [1]. A well-known report points to the abundance of people who die from preventable medical errors, which highlights the growing concern for patient safety [1]. According to a World Health Organization (WHO) report, the incidence of adverse medical events in various countries ranges from 3.5% to 16.6% and about one-tenth of hospitalised patients in the world have experienced unnecessary injuries due to medical malpractice [2]. In addition, according to a survey at Harvard University, 34% of Americans believe that they or their family had experienced medical errors [3]. Although patient safety problems occur globally, they are more common in developing countries, and there is a lack of discussion about this crisis [2]. Patient safety is a key part of medical quality [4–6] and it is increasingly recognised as a global health concern [1, 7, 8]. Improving patient safety is critical to preventing adverse events [9]. Previous studies generally agree that to ensure patient safety and improve the quality of care, medical institutions must establish a patient safety culture [10–12]. Patient safety culture was defined by the British Health and Safety Commission as ‘the product of individual and group values, attitudes, perceptions, competencies, and patterns of behaviour that determine the commitment to, and the style and proficiency of an organization’s safety management’ [13, 14]. Foreign evaluation of the patient safety culture has gradually developed since 1980. From the beginning of 2000, the US’ investment in patient safety culture research has notably increased. In recent years, the amount of relevant research has grown. At present, the patient safety culture in China has gained the attention of hospital managers, and creating a positive patient safety culture has become a vital measure to enhance the level of patient safety management. Safety culture measurement is a key strategy to improve patient safety culture [15–17]. Medical institutions abroad have made substantial progress in the evaluation of patient safety culture; however, in China, this culture is still in its initial stages. Scales concerning patient safety culture assessment have been published abroad; for example, the Manchester Patient Safety Framework [18], the Hospital Survey on Patient Safety culture [19], the Culture of Safety Survey [20], and the Safety Attitudes Questionnaire (SAQ) [21]. The SAQ is the most widely used safety culture evaluation tool in medical institutions, and it has good face and content validity [21]. In recent years, it has been widely used in the USA [22], Turkey [23], Switzerland [24], Norway [25], Taiwan (China) [16] and other countries. Assessing the status quo of patient safety culture is a critical first step to improving the safety culture [9]. Some previous studies used the SAQ to study the status quo across six dimensions of patient safety culture [26–30], and found that healthcare employees’ perceptions of patient safety culture differ depending on demographic factors [12, 31–33]. To date, most patient safety culture studies have focused on nurses and doctors. Additionally, there is still limited research on the status quo of the six dimensions of patient safety culture in China, and there have been fewer studies in the Heilongjiang region. In China, hospitals can be classed, depending on their technical and service levels, into primary, secondary and tertiary hospitals. Among these classes, tertiary hospitals are considered the best, as they have advanced medical equipment and highly skilled healthcare employees, and many patients are served each year in these hospitals. Hence, measuring the patient safety culture in these hospitals is vital. Specifically, we examined the patient safety culture in tertiary hospitals in Heilongjiang, northern China to determine whether perception differed per sex, age, profession, years of experience, education level and marital status. It is hoped that this study will serve as a reference for follow-up studies. Methods A cross-sectional study using a questionnaire survey was conducted in Heilongjiang, northern China. The total population of Heilongjiang in 2014 was 38.33 million. According to ‘Statistical yearbook of health and family planning in China (2014)’, there are 82 tertiary hospitals in Heilongjiang province. Due to the geographical distribution, human resources, and time and resource limitations, we did not investigate all the hospitals. Purposive sampling was used in the study. Four cities (Harbin, Daqing, Qiqihar and Mudanjiang) were selected based on the comprehensive rankings of their Gross Domestic Product in 2014 and the populations’ health levels. Sixteen hospitals were selected based on hospital scale and geographical location. However, only 13 hospitals agreed to participate in the study. These hospitals are public hospitals and have strong medical skills and good reputations. Permission to administer the survey was obtained from all 13 tertiary hospitals. Data collection The survey was conducted from July to August 2014. With the assistance of hospital managers, the questionnaire was distributed during staff meetings at the hospital outpatient departments, inpatient departments, medical technology departments and some administrative departments. The inclusion criteria were as follows: (1) a formal employee, (2) fluent in Chinese, (3) willing to participate in the study and (4) worked in their present position for at least 1 year. The exclusion criteria were as follows: (1) people who were not on duty during our survey (e.g. illness, vacation, business trip), (2) in training, (3) interns or (4) newly employed. All respondents were hospital workers and could influence and be influenced by the hospital’s patient safety culture. Invitees were informed that participation was voluntary and anonymous, that all answers would be treated confidentiality, and that no individual responses would be available to local management. Hospital managers were asked to request the healthcare workers to complete any outstanding questionnaires. Completed questionnaires were collected 7 days after they had been distributed. Questionnaires were collected and stored by the management team. In total, 1200 questionnaires were distributed, and 1024 valid questionnaires were obtained (response rate = 85.33%). Questionnaire We used the SAQ, which was developed in 2000 by Sexton, and has several versions depending on diverse healthcare settings [21]. All versions consist of 30 identical core questions; we decided to base our survey on the 30 core items alone. We obtained permission from Dr Jochen to translate the questionnaire. To examine consistency between versions, the content validity of the translated version was examined by five healthcare-related experts throughout China, who were asked to assess the questionnaire regarding clarity, relevance and comprehensiveness to China’s culture. Upon revision by an expert committee, we administered the questionnaire to 50 participants as a pre-test (all were subsequently excluded from the study). Per these individuals’ feedback, further modifications were undertaken. For all questions, the Cronbach’s alpha coefficient was 0.91. We chose the SAQ as an evaluation tool because it is one of the most commonly used and rigorously validated tools for measuring the safety climate in healthcare [34]. The SAQ includes six dimensions, each consisting of several items: teamwork climate (e.g. the perceived quality of collaboration between personnel), safety climate (e.g. perceptions of a strong and proactive organisational commitment to safety), job satisfaction (e.g. positivity about the work experience), perception of management (e.g. approval of managerial action), stress recognition (e.g. acknowledgement of how performance is influenced by stressors) and working conditions (e.g. the perceived quality of the work environment and logistical support). A study conducted in Switzerland introduced the SAQ and expanded the 5-point Likert scale by adding a ‘not applicable’ option [24]. Our study adopted this modification; therefore, all items were rated on a 5-point Likert scale (1 = ‘disagree strongly’, 2 = ‘disagree slightly’, 3 = ‘neutral’, 4 = ‘agree slightly’ and 5 = ‘agree strongly’) and a ‘not applicable’ option was included for each item. Standardised algorithms were used to aggregate individual items to a 0–100 scale for each dimension (1 = 0, 2 = 25, 3 = 50, 4 = 75 and 5 = 100). Lower scores represent less favourable perception on that dimension and higher scores represent more favourable perceptions. Additional questions were added to assess respondents’ demographic information (i.e. sex, age, years of experience, position, marital status and education level). Data analyses EpiData version 3.1 was used for data entry, and we asked another member of our team to verify all entered data. SAS 9.3 was used for data analyses. All analyses began with basic descriptive statistics of the participants’ demographics. We used frequency and percentage for descriptive statistics analyses, and mean and standard deviation for description of the attitudes towards distinct dimensions in patient safety culture. Differences in perceptions of safety culture per participants’ demographic characteristics were analysed with t-tests and an analysis of variance. The Student–Newman–Keuls q-test was used for further multiple comparisons. The level of statistical significance was set as P < 0.05. Ethical approval The Institutional Review Board of Harbin Medical University Ethical granted approval before data collection commenced (project identification code: HMUIRB20170016). The administrators of the 13 hospitals approved the research protocol, including the purpose, method and use of the data collected. All participants participated voluntarily, anonymously and provided written informed consent. Results Participants’ demographics Among respondents, 716 (70.1%) were women. The ratio of doctors and nurses was close to 1:1. Of the respondents, 826 (81.3%) had completed undergraduate education and above. More than half of the respondents were married. Participants’ demographics are shown in Table 1. Table 1 Participants’ demographics Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Table 1 Participants’ demographics Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Attitude to patient safety culture Participants’ perceptions to dimensions of patient safety culture are shown in Table 2. The mean of the overall score of patient safety culture was 73.74 ± 12.43. The score of work conditions dimension (80.19 ± 17.54) was the highest in the six dimensions followed by teamwork climate (76.73 ± 14.52). Our results are compared with past results in Fig. 1. Table 2 Participants’ perceptions of patient safety culture Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Table 2 Participants’ perceptions of patient safety culture Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Figure 1 View largeDownload slide Comparison of the means of patient safety culture across six dimensions between our study and past research. Figure 1 View largeDownload slide Comparison of the means of patient safety culture across six dimensions between our study and past research. Responses by dimensions As shown in Table 3, perception of job satisfaction significantly differed depending on healthcare employees’ age, years of experience and marital status. Unmarried participants had more favourable perceptions of job satisfaction than did married participants. Perception of management differed depending on healthcare employees’ sex and years of experience. Perception of safety climate differed depending on healthcare employees’ sex and position. There was no significant difference between participants depending on marital status in the dimensions of perception of management and safety climate. Table 3 Scores of dimensions distributed by participants’ characteristics Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Note: Analysis of variance: position, marital status, and education; t-tests: sex, age, and experience. The Student–Newman–Keuls q-test was used for further multiple comparisons. Table 3 Scores of dimensions distributed by participants’ characteristics Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Note: Analysis of variance: position, marital status, and education; t-tests: sex, age, and experience. The Student–Newman–Keuls q-test was used for further multiple comparisons. Discussion We examined healthcare employees’ attitudes across six dimensions of patient safety culture in tertiary hospitals in Heilongjiang, northern China. We revealed significant differences depending on sex, position, years of experiences, marital status, education level and age. The valid response rate was satisfactory and higher than those reported in similar studies (52–79%) [28, 30, 33, 35], which shows that the translated SAQ statements were acceptable. Participants’ total mean scores were between ‘neutral’ and ‘agree slightly’ and their attitudes to patient safety culture were generally positive. This is consistent with some previous studies [36, 37]. However, hospital managers, health employees, the people who conduct patient safety culture education and other stakeholders require improvements in this area. Like other studies [30, 35, 38], healthcare employees generally have a good understanding of teamwork climate and job satisfaction. An interesting finding of the present study is that the highest scoring dimension was working conditions, which differs from most studies [29, 36–38], except for the study by Kristensen et al. [30]. Additionally, in other studies, mean perception scores were lower [29, 30, 37] than those in our study. This may be because we only investigated tertiary hospitals, which have state support, and compared with other hospitals, have relatively better management, hardware and software facilities. Most previous studies have focused on differences in sex, age, position and years of experience; however, in our study, we also examined education level and marital status, which makes our research more comprehensive. All six patient safety dimensions showed significant differences in a univariate analysis of differences in socio-demographic characteristics. The dimensions of job satisfaction, teamwork climate and work condition showed that people who have fewer working years and who are younger have more positive attitudes. However, the dimension of stress recognition showed the opposite pattern. Further, nurses had higher scores than did physicians in all dimensions except stress recognition. Similar to the findings in Palestinian hospitals, nurses and doctors have a different understanding of patient safety culture, and our nurses had more favourable perceptions of safety climate and work condition than doctors did [26]. Medical technology staff had less favourable perceptions of stress recognition than doctors and nurses. Differences in patient safety culture between diverse medical staff may be because of variations their work. Nurses often have contact with patients, and are very experienced in diverse aspects. Doctors usually undergo rigorous training and prolonged exposure to high-pressure environments that are more sensitive to stress. Another interesting finding is that we found that significant differences related to education level in perceptions of stress recognition and work conditions. Highly educated participants had more favourable perceptions of stress recognition, but less favourable perceptions of work condition. A possible explanation is that participants with higher education are more sensitive to pressure and they have more responsibility at work than do less-educated participants. In addition to the dimensions of perception of management and safety climate, there were differences in the other four dimensions depending on marital status. Married participants had a more favourable view of stress recognition than did unmarried participants; however, for the other three dimensions, married participants had less favourable views than did unmarried participants. The reason for this remains to be discovered. Moreover, similar to the research in the Gaza Strip, women had more favourable perceptions of management than did men [27]. In previous studies, there were no significant sex differences in the dimensions of safety climate and stress recognition [27, 28, 30]. However, in our study, women had more favourable perceptions of safety climate, whereas men had more favourable perceptions of stress recognition. Concerning the work conditions, women had more favourable perceptions than did men. These findings are not in line with those typically recorded in the literature [12, 16]. The differences may be attributable to general sex differences [12]. The reason the Heilongjiang results differ from the literature is unknown; further studies including larger samples and in-depth qualitative analysis are recommended to investigate this finding. Our research has laid the foundations for these future studies. Our study has several limitations. Due to time and resource limitations, we chose only 13 tertiary hospitals in Heilongjiang. Since healthcare employees in other types of hospitals were excluded, the findings are not generalisable to all healthcare employees. Furthermore, the analyses were limited to the results obtained from a questionnaire. Other qualitative methods should be used for further study. However, our findings can provide a guide for further research on patient safety culture in Heilongjiang hospitals. The results revealed the attitudes of healthcare employees across six dimensions of patient safety culture in 13 tertiary hospitals in the Heilongjiang province. The average scores on the six dimensions were higher than those of previous studies, especially in the dimensions of work conditions and perception of management. However, there is still room for improvement and to build a better safety culture. Differences in patient safety culture attitudes may exist in hospitals. This study not only confirms previously reported differences related to sex, age, years of experience and position in healthcare employees’ perceptions of patient safety attitudes, but also that it is related to education and marital status, which have been studied less often. The results showed that there were varying degrees of differences in perceptions of patient safety culture related to socio-demographic characteristics. Possible reasons for these findings need to be further explored. Assessing the status quo is a critical first step to improving the safety culture. Our results provide baseline data about the patient safety culture in Heilongjiang province, northern China. The findings contribute to the understanding of safety culture and provide a useful reference for the development of policies related to patient safety; however, further study is needed. Acknowledgements We are grateful for Dr Jochen’s agreement to translate the SAQ into Chinese. Funding This study was funded by the Natural Science Foundation of China (grant nos. 71273002, 71473064 and 71673073); the New Century Excellent Talents of University from the Ministry of Education, China (grant no. 1252-NCET02), the China Postdoctoral Science Foundation (grant nos. 2015M570211 and 2016T90181), the Heilongjiang Provincial Association of Social Sciences (grant no. 15058) and the Collaborative Innovation Centre of Social Risks Governance in Health. Authors’ Contributions Y.L., Y.Z. and Y.H. drafted the manuscript; M.J., T.S. and Q.W. designed the study; H.Q., Q.W. and H.M. collected the data; M.J., Q.W., K.Y. and B.T. analysed the data and Y.H. contributed to the manuscript’s revision. All authors approved the final manuscript for publication. References 1 Kohn LT, Corrigan JM, Donaldson MS. To Err is Human: Building a Safer Health System, 2000; 453– 4. 2 Anon. Quality of care: patient safety. Qual Lett Healthc Lead  2002; 16: 165– 6. 3 Foundation KF, Health HSoP. 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Safety culture perceptions of pharmacists in Malaysian hospitals and health clinics: a multicentre assessment using the Safety Attitudes Questionnaire. BMJ Open  2015; 5: e008889. © The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal for Quality in Health Care Oxford University Press

Perceptions of patient safety culture among healthcare employees in tertiary hospitals of Heilongjiang province in northern China: a cross-sectional study

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
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1353-4505
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1464-3677
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10.1093/intqhc/mzy084
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Abstract

Abstract Objective Assessing the patient safety culture is necessary for improving patient safety. Research on patient safety culture has attracted considerable attention. Currently, there is little research on patient safety culture in China generally, and in Heilongjiang in northern China specifically. The aim of the study is to explore the perception of healthcare employees about patient safety culture and to determine whether perception differs per sex, age, profession, years of experience, education level and marital status. Design Cross-sectional study. Setting Thirteen tertiary hospitals in Heilongjiang, northern China. Participants About 1024 healthcare employees. Main Outcome Measure The perception of healthcare employees was measured using the safety attitude questionnaire, which include six dimensions. Higher scores represented more positive attitudes. An analysis of variance was used to compare socio-demographic differences per position, marital status and education; t-tests were used for sex, age and experience. Results A total of 1024 (85.33%) valid questionnaires were returned. The mean score of the six dimensions was 73.74/100; work conditions (80.19) had the highest score of all the dimensions, and safety climate (70.48) had the lowest. Across distinct dimensions, there were significant differences in perceptions of patient safety culture per sex, age, years of experience, position, marital status and education level (P < 0.05). Conclusions The findings can help in assessing perceived patient safety culture among healthcare employees and identifying dimensions that require improvement. Interventions aimed at specific socio-demographic groups are necessary to improve patient safety culture. patient safety culture, tertiary hospital, healthcare employee Introduction Security is one of the human needs related to survival and development. Patients in hospitals seek medical safety; hence, patient safety is a widespread concern. The US Institute of Medicine defines patient safety as enabling patients to avoid accidental injury [1]. A well-known report points to the abundance of people who die from preventable medical errors, which highlights the growing concern for patient safety [1]. According to a World Health Organization (WHO) report, the incidence of adverse medical events in various countries ranges from 3.5% to 16.6% and about one-tenth of hospitalised patients in the world have experienced unnecessary injuries due to medical malpractice [2]. In addition, according to a survey at Harvard University, 34% of Americans believe that they or their family had experienced medical errors [3]. Although patient safety problems occur globally, they are more common in developing countries, and there is a lack of discussion about this crisis [2]. Patient safety is a key part of medical quality [4–6] and it is increasingly recognised as a global health concern [1, 7, 8]. Improving patient safety is critical to preventing adverse events [9]. Previous studies generally agree that to ensure patient safety and improve the quality of care, medical institutions must establish a patient safety culture [10–12]. Patient safety culture was defined by the British Health and Safety Commission as ‘the product of individual and group values, attitudes, perceptions, competencies, and patterns of behaviour that determine the commitment to, and the style and proficiency of an organization’s safety management’ [13, 14]. Foreign evaluation of the patient safety culture has gradually developed since 1980. From the beginning of 2000, the US’ investment in patient safety culture research has notably increased. In recent years, the amount of relevant research has grown. At present, the patient safety culture in China has gained the attention of hospital managers, and creating a positive patient safety culture has become a vital measure to enhance the level of patient safety management. Safety culture measurement is a key strategy to improve patient safety culture [15–17]. Medical institutions abroad have made substantial progress in the evaluation of patient safety culture; however, in China, this culture is still in its initial stages. Scales concerning patient safety culture assessment have been published abroad; for example, the Manchester Patient Safety Framework [18], the Hospital Survey on Patient Safety culture [19], the Culture of Safety Survey [20], and the Safety Attitudes Questionnaire (SAQ) [21]. The SAQ is the most widely used safety culture evaluation tool in medical institutions, and it has good face and content validity [21]. In recent years, it has been widely used in the USA [22], Turkey [23], Switzerland [24], Norway [25], Taiwan (China) [16] and other countries. Assessing the status quo of patient safety culture is a critical first step to improving the safety culture [9]. Some previous studies used the SAQ to study the status quo across six dimensions of patient safety culture [26–30], and found that healthcare employees’ perceptions of patient safety culture differ depending on demographic factors [12, 31–33]. To date, most patient safety culture studies have focused on nurses and doctors. Additionally, there is still limited research on the status quo of the six dimensions of patient safety culture in China, and there have been fewer studies in the Heilongjiang region. In China, hospitals can be classed, depending on their technical and service levels, into primary, secondary and tertiary hospitals. Among these classes, tertiary hospitals are considered the best, as they have advanced medical equipment and highly skilled healthcare employees, and many patients are served each year in these hospitals. Hence, measuring the patient safety culture in these hospitals is vital. Specifically, we examined the patient safety culture in tertiary hospitals in Heilongjiang, northern China to determine whether perception differed per sex, age, profession, years of experience, education level and marital status. It is hoped that this study will serve as a reference for follow-up studies. Methods A cross-sectional study using a questionnaire survey was conducted in Heilongjiang, northern China. The total population of Heilongjiang in 2014 was 38.33 million. According to ‘Statistical yearbook of health and family planning in China (2014)’, there are 82 tertiary hospitals in Heilongjiang province. Due to the geographical distribution, human resources, and time and resource limitations, we did not investigate all the hospitals. Purposive sampling was used in the study. Four cities (Harbin, Daqing, Qiqihar and Mudanjiang) were selected based on the comprehensive rankings of their Gross Domestic Product in 2014 and the populations’ health levels. Sixteen hospitals were selected based on hospital scale and geographical location. However, only 13 hospitals agreed to participate in the study. These hospitals are public hospitals and have strong medical skills and good reputations. Permission to administer the survey was obtained from all 13 tertiary hospitals. Data collection The survey was conducted from July to August 2014. With the assistance of hospital managers, the questionnaire was distributed during staff meetings at the hospital outpatient departments, inpatient departments, medical technology departments and some administrative departments. The inclusion criteria were as follows: (1) a formal employee, (2) fluent in Chinese, (3) willing to participate in the study and (4) worked in their present position for at least 1 year. The exclusion criteria were as follows: (1) people who were not on duty during our survey (e.g. illness, vacation, business trip), (2) in training, (3) interns or (4) newly employed. All respondents were hospital workers and could influence and be influenced by the hospital’s patient safety culture. Invitees were informed that participation was voluntary and anonymous, that all answers would be treated confidentiality, and that no individual responses would be available to local management. Hospital managers were asked to request the healthcare workers to complete any outstanding questionnaires. Completed questionnaires were collected 7 days after they had been distributed. Questionnaires were collected and stored by the management team. In total, 1200 questionnaires were distributed, and 1024 valid questionnaires were obtained (response rate = 85.33%). Questionnaire We used the SAQ, which was developed in 2000 by Sexton, and has several versions depending on diverse healthcare settings [21]. All versions consist of 30 identical core questions; we decided to base our survey on the 30 core items alone. We obtained permission from Dr Jochen to translate the questionnaire. To examine consistency between versions, the content validity of the translated version was examined by five healthcare-related experts throughout China, who were asked to assess the questionnaire regarding clarity, relevance and comprehensiveness to China’s culture. Upon revision by an expert committee, we administered the questionnaire to 50 participants as a pre-test (all were subsequently excluded from the study). Per these individuals’ feedback, further modifications were undertaken. For all questions, the Cronbach’s alpha coefficient was 0.91. We chose the SAQ as an evaluation tool because it is one of the most commonly used and rigorously validated tools for measuring the safety climate in healthcare [34]. The SAQ includes six dimensions, each consisting of several items: teamwork climate (e.g. the perceived quality of collaboration between personnel), safety climate (e.g. perceptions of a strong and proactive organisational commitment to safety), job satisfaction (e.g. positivity about the work experience), perception of management (e.g. approval of managerial action), stress recognition (e.g. acknowledgement of how performance is influenced by stressors) and working conditions (e.g. the perceived quality of the work environment and logistical support). A study conducted in Switzerland introduced the SAQ and expanded the 5-point Likert scale by adding a ‘not applicable’ option [24]. Our study adopted this modification; therefore, all items were rated on a 5-point Likert scale (1 = ‘disagree strongly’, 2 = ‘disagree slightly’, 3 = ‘neutral’, 4 = ‘agree slightly’ and 5 = ‘agree strongly’) and a ‘not applicable’ option was included for each item. Standardised algorithms were used to aggregate individual items to a 0–100 scale for each dimension (1 = 0, 2 = 25, 3 = 50, 4 = 75 and 5 = 100). Lower scores represent less favourable perception on that dimension and higher scores represent more favourable perceptions. Additional questions were added to assess respondents’ demographic information (i.e. sex, age, years of experience, position, marital status and education level). Data analyses EpiData version 3.1 was used for data entry, and we asked another member of our team to verify all entered data. SAS 9.3 was used for data analyses. All analyses began with basic descriptive statistics of the participants’ demographics. We used frequency and percentage for descriptive statistics analyses, and mean and standard deviation for description of the attitudes towards distinct dimensions in patient safety culture. Differences in perceptions of safety culture per participants’ demographic characteristics were analysed with t-tests and an analysis of variance. The Student–Newman–Keuls q-test was used for further multiple comparisons. The level of statistical significance was set as P < 0.05. Ethical approval The Institutional Review Board of Harbin Medical University Ethical granted approval before data collection commenced (project identification code: HMUIRB20170016). The administrators of the 13 hospitals approved the research protocol, including the purpose, method and use of the data collected. All participants participated voluntarily, anonymously and provided written informed consent. Results Participants’ demographics Among respondents, 716 (70.1%) were women. The ratio of doctors and nurses was close to 1:1. Of the respondents, 826 (81.3%) had completed undergraduate education and above. More than half of the respondents were married. Participants’ demographics are shown in Table 1. Table 1 Participants’ demographics Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Table 1 Participants’ demographics Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Participants  n  %  Sex   Male  305  29.9   Female  716  70.1  Age (years)   <35  626  61.4   ≥35  394  38.6  Years of experience       <10  627  61.7   ≥10  389  38.3  Position       Doctor  456  44.6   Nurse  441  43.2   Medical technology  56  5.5   Management  51  5   Other  17  1.7  Education level       High school/secondary school  27  2.7   College  163  16   Undergraduate and above  826  81.3  Marital status   Unmarried  309  30.3   Married  694  68   Divorced  12  1.2   Other (including widowed)  5  0.5  Attitude to patient safety culture Participants’ perceptions to dimensions of patient safety culture are shown in Table 2. The mean of the overall score of patient safety culture was 73.74 ± 12.43. The score of work conditions dimension (80.19 ± 17.54) was the highest in the six dimensions followed by teamwork climate (76.73 ± 14.52). Our results are compared with past results in Fig. 1. Table 2 Participants’ perceptions of patient safety culture Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Table 2 Participants’ perceptions of patient safety culture Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Dimension  X¯±S  Sort  Teamwork climate  76.73 ± 14.52  2  Safety climate  70.48 ± 15.69  6  Job satisfaction  73.14 ± 20.71  3  Stress recognition  70.73 ± 24.13  5  Perception of management  71.04 ± 19.42  4  Work condition  80.19 ± 17.54  1  Total  73.74 ± 12.43    Figure 1 View largeDownload slide Comparison of the means of patient safety culture across six dimensions between our study and past research. Figure 1 View largeDownload slide Comparison of the means of patient safety culture across six dimensions between our study and past research. Responses by dimensions As shown in Table 3, perception of job satisfaction significantly differed depending on healthcare employees’ age, years of experience and marital status. Unmarried participants had more favourable perceptions of job satisfaction than did married participants. Perception of management differed depending on healthcare employees’ sex and years of experience. Perception of safety climate differed depending on healthcare employees’ sex and position. There was no significant difference between participants depending on marital status in the dimensions of perception of management and safety climate. Table 3 Scores of dimensions distributed by participants’ characteristics Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Note: Analysis of variance: position, marital status, and education; t-tests: sex, age, and experience. The Student–Newman–Keuls q-test was used for further multiple comparisons. Table 3 Scores of dimensions distributed by participants’ characteristics Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Participants  Job satisfaction X¯±S  Perception of management X¯±S  Safety climate X¯±S  Stress recognition X¯±S  Teamwork climate X¯±S  Work condition X¯±S  Sex   Male  71.6 ± 19.52  68.41 ± 19.83  68.33 ± 16.2  74.04 ± 22.96  76.04 ± 15.2  76.95 ± 19.12   Female  73.75 ± 21.19  72.06 ± 19.13  71.39 ± 15.41  69.26 ± 24.52  76.97 ± 14.21  81.59 ± 16.63   P-value  0.1301  0.0061  0.0044  0.0038  0.3502  0.0001  Age (years)   <35  74.26 ± 21.29  71.8 ± 20.06  70.92 ± 16.16  68.94 ± 25.25  77.97 ± 14.38  82.04 ± 17.08   ≥35  71.3 ± 19.69  69.66 ± 18.27  69.74 ± 14.92  73.54 ± 22.05  74.76 ± 14.53  77.12 ± 17.87   P-value  0.0265  0.0811  0.2423  0.0023  0.0006  <0.0001  Years of experience   <10  74.29 ± 20.62  72.02 ± 19.89  70.81 ± 15.96  69.06 ± 24.93  78.22 ± 14.26  81.93 ± 16.98   ≥10  71.17 ± 20.84  69.32 ± 18.6  69.75 ± 15.22  73.47 ± 22.71  74.18 ± 14.6  77.26 ± 18.13   P-value  0.0197  0.0313  0.2961  0.0041  <0.0001  <0.0001  Position   Doctor  71.35 ± 19.85  69.19 ± 18.96  68.78 ± 15.62  72.92 ± 23.44  76.96 ± 14.11  77.71 ± 18.44   Nurse  74.48 ± 21.52  72.15 ± 19.84  72.4 ± 15.51  70.78 ± 24.62  77.1 ± 13.98  83.08 ± 15.97   Medical technology  76.79 ± 20.35  72.58 ± 19.72  68.62 ± 16.7  58.41 ± 26.17  75.89 ± 17.27  77.01 ± 18.0   Management  72.77 ± 20.01  74.8 ± 17.81  71.44 ± 15.32  66.67 ± 20.72  74.43 ± 15.99  80.51 ± 18.01   Other  75.59 ± 24.61  76.47 ± 22.59  70.52 ± 17.11  63.97 ± 21.37  74 ± 22.39  81.25 ± 19.26   P-value  0.1256  0.0577  0.0118  0.0003  0.6515  0.0001  Marital status   Unmarried  76.1 ± 20.3  71.82 ± 19.82  71.39 ± 16.03  63.69 ± 26.36  78.92 ± 13.77  83.84 ± 15.84   Married  71.86 ± 20.83  70.61 ± 19.28  70.08 ± 15.49  73.74 ± 22.62  75.94 ± 14.66  78.51 ± 18.06   Divorced  70.91 ± 18  67.61 ± 17.64  72.08 ± 16.66  75 ± 13.98  70.69 ± 13.54  79.17 ± 16.71   Other (including widowed)  63 ± 21.68  78.75 ± 21.01  60.24 ± 20.65  70 ± 22.27  66.67 ± 28.26  80 ± 18.43   P-value  0.0162  0.5809  0.2934  <0.0001  0.0034  0.0002  Education level   High school/secondary school  75.93 ± 22.96  73.3 ± 21.01  73.83 ± 16.72  59.62 ± 27.05  80.71 ± 13.39  88.19 ± 14.22   College  75.38 ± 19.27  72.16 ± 18.87  70.63 ± 15.18  64.08 ± 24.25  76.94 ± 15.03  82.52 ± 15.61   Undergraduate and above  72.54 ± 20.88  70.64 ± 19.45  70.33 ± 15.74  72.4 ± 23.77  76.56 ± 14.47  79.44 ± 17.9   P-value  0.214  0.5365  0.5174  <0.0001  0.3379  0.0066  Note: Analysis of variance: position, marital status, and education; t-tests: sex, age, and experience. The Student–Newman–Keuls q-test was used for further multiple comparisons. Discussion We examined healthcare employees’ attitudes across six dimensions of patient safety culture in tertiary hospitals in Heilongjiang, northern China. We revealed significant differences depending on sex, position, years of experiences, marital status, education level and age. The valid response rate was satisfactory and higher than those reported in similar studies (52–79%) [28, 30, 33, 35], which shows that the translated SAQ statements were acceptable. Participants’ total mean scores were between ‘neutral’ and ‘agree slightly’ and their attitudes to patient safety culture were generally positive. This is consistent with some previous studies [36, 37]. However, hospital managers, health employees, the people who conduct patient safety culture education and other stakeholders require improvements in this area. Like other studies [30, 35, 38], healthcare employees generally have a good understanding of teamwork climate and job satisfaction. An interesting finding of the present study is that the highest scoring dimension was working conditions, which differs from most studies [29, 36–38], except for the study by Kristensen et al. [30]. Additionally, in other studies, mean perception scores were lower [29, 30, 37] than those in our study. This may be because we only investigated tertiary hospitals, which have state support, and compared with other hospitals, have relatively better management, hardware and software facilities. Most previous studies have focused on differences in sex, age, position and years of experience; however, in our study, we also examined education level and marital status, which makes our research more comprehensive. All six patient safety dimensions showed significant differences in a univariate analysis of differences in socio-demographic characteristics. The dimensions of job satisfaction, teamwork climate and work condition showed that people who have fewer working years and who are younger have more positive attitudes. However, the dimension of stress recognition showed the opposite pattern. Further, nurses had higher scores than did physicians in all dimensions except stress recognition. Similar to the findings in Palestinian hospitals, nurses and doctors have a different understanding of patient safety culture, and our nurses had more favourable perceptions of safety climate and work condition than doctors did [26]. Medical technology staff had less favourable perceptions of stress recognition than doctors and nurses. Differences in patient safety culture between diverse medical staff may be because of variations their work. Nurses often have contact with patients, and are very experienced in diverse aspects. Doctors usually undergo rigorous training and prolonged exposure to high-pressure environments that are more sensitive to stress. Another interesting finding is that we found that significant differences related to education level in perceptions of stress recognition and work conditions. Highly educated participants had more favourable perceptions of stress recognition, but less favourable perceptions of work condition. A possible explanation is that participants with higher education are more sensitive to pressure and they have more responsibility at work than do less-educated participants. In addition to the dimensions of perception of management and safety climate, there were differences in the other four dimensions depending on marital status. Married participants had a more favourable view of stress recognition than did unmarried participants; however, for the other three dimensions, married participants had less favourable views than did unmarried participants. The reason for this remains to be discovered. Moreover, similar to the research in the Gaza Strip, women had more favourable perceptions of management than did men [27]. In previous studies, there were no significant sex differences in the dimensions of safety climate and stress recognition [27, 28, 30]. However, in our study, women had more favourable perceptions of safety climate, whereas men had more favourable perceptions of stress recognition. Concerning the work conditions, women had more favourable perceptions than did men. These findings are not in line with those typically recorded in the literature [12, 16]. The differences may be attributable to general sex differences [12]. The reason the Heilongjiang results differ from the literature is unknown; further studies including larger samples and in-depth qualitative analysis are recommended to investigate this finding. Our research has laid the foundations for these future studies. Our study has several limitations. Due to time and resource limitations, we chose only 13 tertiary hospitals in Heilongjiang. Since healthcare employees in other types of hospitals were excluded, the findings are not generalisable to all healthcare employees. Furthermore, the analyses were limited to the results obtained from a questionnaire. Other qualitative methods should be used for further study. However, our findings can provide a guide for further research on patient safety culture in Heilongjiang hospitals. The results revealed the attitudes of healthcare employees across six dimensions of patient safety culture in 13 tertiary hospitals in the Heilongjiang province. The average scores on the six dimensions were higher than those of previous studies, especially in the dimensions of work conditions and perception of management. However, there is still room for improvement and to build a better safety culture. Differences in patient safety culture attitudes may exist in hospitals. This study not only confirms previously reported differences related to sex, age, years of experience and position in healthcare employees’ perceptions of patient safety attitudes, but also that it is related to education and marital status, which have been studied less often. The results showed that there were varying degrees of differences in perceptions of patient safety culture related to socio-demographic characteristics. Possible reasons for these findings need to be further explored. Assessing the status quo is a critical first step to improving the safety culture. Our results provide baseline data about the patient safety culture in Heilongjiang province, northern China. The findings contribute to the understanding of safety culture and provide a useful reference for the development of policies related to patient safety; however, further study is needed. Acknowledgements We are grateful for Dr Jochen’s agreement to translate the SAQ into Chinese. Funding This study was funded by the Natural Science Foundation of China (grant nos. 71273002, 71473064 and 71673073); the New Century Excellent Talents of University from the Ministry of Education, China (grant no. 1252-NCET02), the China Postdoctoral Science Foundation (grant nos. 2015M570211 and 2016T90181), the Heilongjiang Provincial Association of Social Sciences (grant no. 15058) and the Collaborative Innovation Centre of Social Risks Governance in Health. Authors’ Contributions Y.L., Y.Z. and Y.H. drafted the manuscript; M.J., T.S. and Q.W. designed the study; H.Q., Q.W. and H.M. collected the data; M.J., Q.W., K.Y. and B.T. analysed the data and Y.H. contributed to the manuscript’s revision. All authors approved the final manuscript for publication. References 1 Kohn LT, Corrigan JM, Donaldson MS. To Err is Human: Building a Safer Health System, 2000; 453– 4. 2 Anon. Quality of care: patient safety. Qual Lett Healthc Lead  2002; 16: 165– 6. 3 Foundation KF, Health HSoP. 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Safety culture perceptions of pharmacists in Malaysian hospitals and health clinics: a multicentre assessment using the Safety Attitudes Questionnaire. BMJ Open  2015; 5: e008889. © The Author(s) 2018. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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International Journal for Quality in Health CareOxford University Press

Published: Apr 19, 2018

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