Background

Over the last decades, there has been an increasing interest in patient safety and learning from medical errors. Traditionally, these issues have to a large degree been addressed in hospital settings [1,2,3,4,5,6,7]. However, during recent years, there has been a stronger emphasis on investigating factors related to patient safety in primary care as well, as the largest volume of health care is provided outside the hospitals.

Patient safety culture involves leader and staff interaction, routines, attitudes, practices and awareness that influence risks of adverse events in patient care [8]. The concept is developed within organizational psychology, and is regarded as a group phenomenon. The safety culture in the health service near the patients is of particular interest, as a substantial variation across wards has been shown [9]. This variation is associated with risk of medical errors [10,11,12].

Nursing homes may be among the primary care services with the highest risks of adverse events. Nursing home patients are vulnerable due to their complex multiple diseases, cognitive impairment and unclear presentation of illnesses [13]. There is a risk of medication errors and fall injuries [14, 15]. In nursing homes there commonly are many health care providers with short or no formal training, like auxiliary nurses and untrained assistants. There might also be challenges with staffing ratios to meet the needs of the patients. In nursing homes, physicians are usually present only a few hours per week.

Compared to hospitals, the patient safety culture in nursing homes has been shown to be considerably poorer [16,17,18]. Therefore, nursing home patients might be at increased risk of harm related to medical errors. An association between patient safety culture in nursing homes and poor clinical outcomes has been reported [14, 15]. Nursing home administrators and managers seem to rate the safety culture in their institutions higher than do direct caregivers, who might be more aware of safety concerns [18, 19]. For this reason, the practice of leadership walkarounds has been recommended.

Assessment of patient safety climate in nursing homes provides an opportunity to identify improvement targets [20]. However, introducing safety projects may be challenging. An Ohio study showed that nearly half of the nursing staff found it difficult to make needed quality changes in nursing homes [21]. A “blame and shame” culture has also been observed in nursing homes [20, 22]. Patient safety climate assessment affords an opportunity to involve leadership in improving culture, as well as to set targets for improvement and divert resources if necessary [8].

There are several instruments to measure safety attitudes among health care professionals [1, 23,24,25,26,27]. These have traditionally been made for clinical settings within hospitals, like the Hospital Survey of Patient Safety Culture (HSOPSC) [25]. Over the last years, questionnaires have also been adapted to settings outside hospitals. This includes the Nursing Home Survey on Patient Safety Culture (NHSOPSC), which was developed by the Agency for Healthcare Research and Quality [18, 28]. A study describing the psychometric properties of the Norwegian NHSOPSC version has been published [29].

Another commonly used instrument is the Safety Attitudes Questionnaire (SAQ). It includes six major patient safety factors: Teamwork climate, Safety climate, Job satisfaction, Perceptions of management, Working conditions, and Stress recognition [30].

A number of studies have shown an association between SAQ scores and patient outcome [10,11,12, 26, 31,32,33]. The SAQ identifies areas with poor patient care and can motivate leaders to implement quality improvement strategies, whereby the risk of adverse events may be reduced [34,35,36]. The Safety Attitudes Questionnaire - Ambulatory Version (SAQ-A) has been developed and adjusted to the primary care setting [1] (Additional file 1). It provides the possibility of measuring effect of safety improvement interventions and change in safety attitudes [37]. The SAQ has also been used in nursing home settings [38, 39].

The SAQ-A has previously been adapted and validated for Norwegian General Practitioner (GP) practices and out-of-hours casualty clinics [40,41,42]. As the instrument has proved to be a useful tool for measuring safety climate in these parts of Norwegian primary care, we wanted to validate it in the nursing home setting as well. This will enable safety culture comparisons across sectors of the health services.

The aim of the present study was to develop a tool for measuring patient safety climate in nursing homes. We present the psychometric properties of the Norwegian translated version of the SAQ-A for nursing homes. We aimed to study whether the factor structure in this Norwegian version was the same as in the original questionnaire. Finally, we wanted to investigate whether the SAQ-A might be an appropriate instrument for measuring patient safety climate in the Norwegian nursing home setting.

Methods

Sample

The study was done in five nursing homes in Tønsberg, Norway. The total number of wards in the five nursing homes was 34, varying from three to 13 wards. In all, the five nursing homes cared for 366 patients, varying from 38 to 101 patients in each nursing home. There were totally 765 health care professionals working in the nursing homes. We did not include in the analyses employees that were working less than/equal to 20% (equivalent to one working day per week), or those being on leave during the study period (n = 302). Out of the remaining 463 employees, 288 (62.2%) answered the questionnaire (Table 1). The response rates varied between 56.9 and 72.2% across the five nursing homes.

Table 1 Patients, employees and response rates in five nursing homes in Tønsberg, Norway, 2016
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The characteristics of the 288 respondents have previously been published in another paper [43] and are presented in Table 2.

Table 2 Characteristics of 288 employees in five nursing homes, Norway, responding to the SAQ-A, 2016
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Translation procedures

The original SAQ-A was translated according to the principles adapted from Beaton et al. [44]. The procedures with translation, back-translation and adaptation by an expert committee with clinicians and researchers are described in another paper [43]. Completing the SAQ-A takes approximately 15 min.

Scoring

The SAQ-A has 62-items where the health care workers give their responses using a 5-point Likert scale: 1 = disagree strongly, 2 = disagree slightly, 3 = neutral, 4 = agree slightly, 5 = agree strongly. The category “Not applicable” was recoded into missing values in the data analyses. We reversed scores of negatively worded items. Factor scores were calculated by summing scores on items hypothesized to belong to each factor.

Hypothesized factor structure

The original SAQ, developed at the University of Texas at Austin [30], described six factors: Teamwork climate, Safety climate, Working conditions, Job satisfaction, Perceptions of management and Stress recognition (Table 3). Not all the items in the original SAQ were covered by these six factors. The remaining items were included to provide information considered useful for local quality improvement interventions.

Table 3 The six factors and corresponding items in the original Safety Attitudes Questionnaire (SAQ) version (Sexton et al, 2006)
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For Teamwork climate in the present study, two items (Q35: It is easy for personnel in this nursing home ward to ask questions when there is something that they do not understand; and Q38: The physicians and nurses here work together as a well-coordinated team) were removed from the hypothesized factor structure model. One of these items (Q38) referred to cooperation with physicians, and was removed since physicians are more seldom present in nursing homes than in hospitals and GP practices. The other item (Q35) was removed as the need to ask questions may be perceived less prevalent in nursing home care. Based on the previously validated factor structure of the Norwegian SAQ-A [40], we hypothesized that Q18 (The levels of staffing in this nursing home ward are sufficient to handle the number of patients) should be moved from Perceptions of management to Working conditions, and that Q17 (The nursing home ward management does not knowingly compromise the safety of patients) in Perceptions of management should be exchanged with Q9 (Senior management of this nursing home ward is doing a good job).

Data collection

The data were collected in the five nursing homes in February 2016. Paper versions of the SAQ-A were distributed by administrative contact persons to the health care workers. Filled-in questionnaires were returned anonymously in boxes. Questionnaires were scanned into an SPSS data file for analysis.

Reports with the SAQ-A results were sent to nursing home wards with at least five responders. The employees were recommended to discuss local patient safety factors, and to develop strategies for improvement in their own nursing home ward.

Statistical analysis

To reduce loss of cases by listwise deletion of cases with missing data, imputation of missings were done by multiple regression analysis with SPSS v.24. Values were imputed for the “real missing”s (but not for those who failed to return a valid value by ticking the box “Not applicable”). For each variable with missing values imputed scores were predicted by the five answers (among the answers to the 28 questions in the confirmatory factor analysis) most strongly correlated to the variable in question.

SPSS was used to estimate the Cronbach alphas, corrected item-total correlation, item-to-other-factor correlations and item-descriptive statistics. An indicator of an item not belonging where it was hypothesized to sit is whether its removal would markedly improve the variable set’s Cronbach’s alpha, a measure of the extent to which the responses of items within a factor correlated pairwise. Cronbach alpha scores were considered good if between 0.70 and 0.90, and acceptable if above 0.60 [45]. Corrected item-total correlations were checked and compared to item-to-other-factor correlations to see if the items correlated more strongly with the factor they were hypothesized to belong to than with the other factors.

The hypothesized six factor model was tested by confirmatory factor analysis (CFA) in AMOS, using data from respondents answering all of the items, including the imputed responses. As factors reflect the correlation structure in the item responses, valid factors should reflect a thematic logic that is coherent with the purpose of the questionnaire. CFA provides goodness-of-fit indices which show how the survey responses comply with the pre-hypothesized factor model.

The following goodness-of-fit indices (indicators of how well the factor pattern in the survey responses conforms with the hypothesized factor model) were calculated: the chi-square/degrees of freedom ratio (χ2/d.f.), the p, the Root Mean Square Error of Approximation (RMSEA), the pclose, the Comparative Fit Index (CFI) and the Hoelter 0.05. Acceptable goodness-of-fit values indicate that the SAQ-A measures patient safety climate by the hypothesized factors. The χ2/d.f. should be below 2.5 [46,47,48], the p value should exceed 0.05, the RMSEA should not exceed 0.08, the pclose value should exceed 0.05 [49], the CFI should exceed 0.90 [50]. The Hoelter 0.05 - an estimate of the largest sample for which a data set with these intercorrelations among the variables would confirm the model – should exceed 200 [51].

Ethical considerations

This was a study on patient safety climate among employees in nursing homes, conducted in compliance with the Helsinki Declaration. The participants received written information about the purpose of the study, that data would be collected anonymously and treated in confidence. As this study did not involve patients, it was not regarded as a medical and health research project - and was thereby not affected by the Norwegian Health Research Act. Approval from the Committee for medical and health research ethics was therefore not needed. The study was approved by the Norwegian Social Science Data Services: the governmental agency for protecting survey research respondent privacy according to the Norwegian Personal Data Act (Ref. No. 2015/42892).

Results

Table 4 presents median and mean scores with standard deviations for each of the 62 items, expressing the degree of agreement with the statements in the questionnaire. The proportions of missing values/not applicable at item levels are also shown in the table, and were on average 9.4%, ranging from 1.0 to 44.1%. 169 respondents answered all items in the hypothesized model. After imputation of missings by multiple regression analysis, 288 health care providers had responses to all items.

Table 4 Median and mean scores for the 62 items in the Safety Attitudes Questionnaire – Ambulatory Version (SAQ-A) among 288 health care providers in five nursing homes in Tønsberg, Norway, 2016
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The strongest disagreement was found in the statements “Abnormal test results are frequently lost or overlooked”, mean score (SD) 1.9 (1.1), and “I have made errors that had the potential to harm patients”, mean score (SD) 1.9 (1.3). The highest mean scores reflecting agreement were reported for the statements “I like my job”, mean score (SD) 4.7 (0.7), “Briefing other personnel before a procedure (e.g., wound care) is important for patient safety”, mean score (SD) 4.6 (0.8), “High levels of workload are common in this nursing home ward”, mean score (SD) 4.5 (0.9), and “Attending health care providers in this nursing home ward are doing a good job”, mean score (SD) 4.5 (0.9).

The confirmatory factor analysis showed that the hypothesized total model of six factors Teamwork climate, Safety climate, Job satisfaction, Perceptions of management, Working conditions, and Stress recognition fitted the data adequately. The goodness-of-fit indices for the model are presented in Table 5.

Table 5 Goodness-of-fit indices for the entire model among 288a health care providers in five nursing homes, Tønsberg, Norway, 2016
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The hypothesized six-factor model is presented in Figure 1.

Fig. 1
figure 1

The hypothesized six-factor model, Tønsberg, Norway, 2016

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The Cronbach’s alpha was 0.886 for the total model and ranged from 0.655 to 0.786 for the single-factor subscales: Teamwork climate, Safety climate, Working conditions, Perceptions of management, Job satisfaction and Stress recognition (Table 6).

Table 6 Item variation and internal consistency of the total confirmed model and of the model’s six safety factors based on data from 288a respondents in five nursing homes, Tønsberg, Norway, 2016
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Half (14) of the 28 items in the confirmed model correlated higher with the factor it was related to in the hypothesized factor model than with any other factor. Fourteen items correlated higher with a different factor, however, several only slightly higher. For example, Q6 correlated 0.503 to Perceptions of management and 0.497 to own factor (Working conditions).

Explained variance by factor and communality by item are presented in Table 7.

Table 7 Explained variance by factor, communality by item, Tønsberg, Norway, 2016
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Discussion

Our study showed that the hypothesized total factor model of six factors Teamwork climate, Safety climate, Job satisfaction, Perceptions of management, Working conditions, and Stress recognition had acceptable goodness-of-fit values to be used for climate measurements in the nursing home setting.

In a recent study, SAQ was shown to be a reliable tool to measure safety climate also in nursing homes in the Netherlands [38]. The authors in that study encouraged nursing homes to avoid focusing on all safety factors at the same time. Their report showed that improving one factor may have a positive influence also on other safety climate factors.

Cappelen et al. have studied the psychometric properties of the Nursing Home Survey on Patient Safety Culture (NHSOPSC) in Norwegian nursing homes [29]. This is an alternative instrument to measure safety climate. The authors identified ten factors: teamwork, staffing, compliance with procedures, training and skills, nonpunitive response to mistakes, handoffs, feedback and communication about incidents, communication openness, supervisor expectations, and management and organizational learning. Some of these factors overlap with the SAQ factors, but the NHSOPSC factors are described in more detail. Both instruments are useful tools for measuring patient safety in the Norwegian nursing home setting.

The degree of consensus amongst staff in a nursing home ward is a measure of the organizational climate’s strength. In order to describe the degree to which staff share perceptions within the same nursing home ward, we aimed to obtain a response rate of 70%. The response rate of 62.2% in our study was suboptimal. However, it was higher than the response rates in a Dutch nursing home study (53%) [38] and a study in Norwegian GP practices and out-of-hours clinics (52.2%) [40]. The large number of nursing home employees working part-time may have a higher degree of uncertainty about patient safety. This could possibly affect the willingness to participate in the study. There was no clear association between number of employees and response rates across the participating nursing homes. The actual response rates for the five nursing homes were 56.9, 60.4, 62.5, 63.3 and 72.2, respectively. This gives us the opportunity to explore the variation in organizational climate measurements across nursing home wards.

Among those responding to the questionnaire, there were moderate instances of items with missing values/not applicable, on average 9.4%. In 15 out of 62 items, the proportion of missing values/not applicable was > 10%. However, only two of these 15 items belonged to any of the safety factors. These were items Q5 (Medical errors are handled appropriately in this nursing home ward) and Q20 (I am encouraged by my colleagues to report any patient safety concerns I may have), both belonging to the factor Safety climate, and with a proportion of 10.4 and 10.1% missing values/not applicable, respectively. A high proportion of missing values/not applicable may indicate that the respondents regard the specific item as being less relevant for their nursing home setting. However, 24 out of 28 items belonging to one of the six safety factors had < 10% missing values/not applicable.

Both the size and the organization of Norwegian nursing homes vary a lot, some of them being large institutions with teaching responsibilities of health profession students, others being small with limited numbers of patients and staff. For these reasons, it is not surprising that employees may have regarded some of the 62 items as being less relevant for their particular nursing home setting. This also reflects the diversity in the included nursing homes. In addition, the included health professions have different responsibilities in nursing home care. For instance, nursing assistants are not involved in test results, and health workers have no responsibility for medication. This means that certain items are highly relevant for some of the health professions and less to others.

In our study, we chose to use the full SAQ-A version – and not the short form of SAQ. This increased the possibility of including items that staff found less appropriate – with a correspondingly larger proportion of missing responses to these items. However, this nursing home study is part of a larger patient safety climate study in different services of Norwegian primary care, and we have decided to use the full SAQ-A version in all the services.

We have to recognize that the 17% of employees who were not Norwegian native speakers may have had difficulties understanding the statements in the questionnaire. We do not know the country of origin for these respondents; language problems would probably be less among those coming from other Scandinavian countries.

As far as we know, this is the first systematic study of the psychometric properties of the SAQ-A in Norwegian nursing homes. It is a strength that the study was done in both small and large nursing homes. Comparisons of safety cultures are now possible as the SAQ-A instrument has been validated and adapted to different sectors of the primary healthcare services.

The Cronbach alphas for the total model (0.873) and for two of the six factors, Safety climate (0.700) and Job satisfaction (0.754), were considered good (≥ 0.70). For the remaining four factors, Teamwork climate (0.626), Stress recognition (0.672), Working conditions (0.673) and Perceptions of management (0.695), the Cronbach alphas were acceptable (≥0.60) [45]. These values demonstrate the internal consistency of the total model and the individual factors. The Norwegian translation of the SAQ-A adapted for nursing homes is an appropriate instrument for the study of patient safety climate in this setting.

The responses in our study tended to be skewed towards the favorable side of the scale, reflecting a positive attitude to patient safety. Still, as studies have shown that safety culture in nursing homes may be poorer than in other parts of the health services [16,17,18], and nursing home patients are particularly vulnerable to adverse events, it is important to address safety issues and medical errors also in this primary care setting. By measuring safety attitudes among the employees, it is possible to identify specific threats on the nursing home ward level.

We have previously studied the psychometric properties of the SAQ-A in Norwegian out-of-hours clinics and GP practices [40]. In that study, the following five factor model was shown to have acceptable goodness-of-fit values in the confirmatory factor analysis: Teamwork climate, Safety climate, Job satisfaction, Working conditions and Perceptions of management. These five factors were also confirmed in the nursing home setting. In addition, Stress recognition had acceptable goodness-of-fit values in nursing homes, but this factor was not confirmed in the GP practice or out-of-hours settings in Norway.

Despite a large degree of similarities across different health services within and between countries, important site-specific differences exist. For that reason, it is important to investigate the psychometric properties of the SAQ instrument, both in different countries and in different clinical settings in hospital and primary care.

Although authors state a correlation between patient safety culture and risk of adverse events [10,11,12], there are studies in which an association was not found [11, 52]. This underlines the need of further studies to investigate whether such an association applies to the nursing home setting. This was, however, beyond the scope of the present study.

The SAQ may be used to compare results before and after interventions. It also gives the possibility of comparing the relative prevalence of wards with good patient safety climate scores across institutions. This may help leaders to support health professionals in reducing the risk of medical errors. Nursing home leaders have the responsibility to encourage employees to be open about possible risks and adverse events by cultivating a “no-blame no-shame” culture. It is also important to compare safety climate across the varying services in primary and hospital care, in order to identify safety improvement strategies that can be used in different clinical settings.

Conclusions

Our study indicates that the Norwegian translated version of the SAQ-A might be an appropriate instrument for measuring patient safety climate in the nursing home setting. Discussing the findings at ward level may facilitate interventions reducing the risk of medical errors. In future studies, possible differences in patient safety climate across nursing home wards should be investigated. Variation could imply opportunities for leaders to direct support to where improvement is most needed. Likewise, it needs to be clarified whether varying professional background, experience and age may influence attitudes to patient safety in the nursing home setting. Further research should also validate the questionnaire externally by correlating the scores on the SAQ-A domains to patient-associated outcomes in nursing homes, as this was beyond the scope of the present study.