Open access peer-reviewed chapter

Psychometric Properties of the Hospital Survey on Patient Safety Culture (HSOPSC): Findings from Greece

Written By

Vasiliki Kapaki and Kyriakos Souliotis

Submitted: November 15th, 2016 Reviewed: June 2nd, 2017 Published: December 20th, 2017

DOI: 10.5772/intechopen.69997

Chapter metrics overview

1,167 Chapter Downloads

View Full Metrics


Background: Safety culture has been considered to be as one of the most crucial premises for the further development of patient safety in healthcare.


  • hospital survey on patient safety culture
  • construct validity
  • reliability
  • internal consistency

1. Introduction

Safety culture has been deemed as one of the most significant premises for following improvement of patient safety in healthcare [1]. The term ‘culture’ is often substituted with ‘climate’ when questionnaire surveys are utilized to assess an organization’s culture. The definition of ‘safety culture’ derives from the nuclear power industry and has been transferred to the field of the healthcare: ‘the safety culture of an organization is 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’ [2]. Safety climate can be faced as the superficial features of the underlying safety culture [3]. It assesses workforce perceptions of procedures and behaviours in their work environment that point out the priority given to safety relative to other organizational goals [4, 5].

Therefore, individual and self-administered questionnaires allow measuring an organization’s safety climate [69] while for assessing safety culture, other types of assessment (i.e. ‘interviews, on-site observations, focus groups’) are more suitable [1012]. These questionnaires are distributed to a group of professionals that operate in the healthcare field having an aim to provide information on aspects of the organizational culture underlying active failures and latent conditions that have to be addressed by patient safety initiatives [13].

Most of the available tools were developed in the United States (US) but some researchers suggest that various US tools cannot be adapted to European context. For this exact reason, after translating a questionnaire into another language and applying it in a different setting, it is of crucial importance to validate it before extending its use to populations differentiating from the specific geographical and healthcare contexts for which it was initially developed. The psychometric techniques are commonly used in order to ensure potential users that tools will be a good predictor of safety events and provide actionable information [9].


2. Clinical vignette

M.G., a 75-year-old woman with stage four chronic kidney disease (CKD), hypertension and gout was admitted for a total knee replacement under the orthopedic team. According to the routine renal biochemistry results and following advice from nephrology group, she was on a low dose of an activated vitamin D analogue. She was also taking a diuretic, an angiotensin receptor blocker, aspirin, sodium bicarbonate and a statin drug. Serum calcium was not verified again during her admission. Even though discharge communication included the recently started medication with the advised dose, no advice was given to the general practitioner about the required rate of monitoring serum calcium and renal function post discharge and the patient was not duly informed of the necessity for this monitoring. At her home, the patient made a slow recovery from her operation and had limited ability to move around. Her son phoned for the surgery and requested a general practitioner to make a visit to his mother 3 weeks after discharge, as she looked very sick, was more and more confused and was not consuming food or water. The general practitioner arranges for the patient to be re-admitted into the hospital. The last diagnosis was stage 2, acute kidney injury (AKI), second in importance, iatrogenic hypercalcaemia and dehydration.

2.1. Key learning points

  1. Knowledgeable safety culture is when bidirectional communication is open and honest, trust exists for the total levels of the health care structure, and messengers are trained and prized for making better systems. The system is precisely in the handling of employees, reporting of errors is valued, and learning from errors is recognized and valued.

  2. Communication has an effect on health care transactions among health care staff. To be more precise, it is necessary that the list of a patient’s medications that is accumulated at admission be communicated successfully to following providers as the patient is transferred between settings and practitioners extending all the way to discharge.

  3. Keeping patients properly informed is essential to good medical practice and may bring in a level of protection to the test results management system. Patients and where right their families and caretakers, need to be informed at the point of discharge that follow-up tests are needed, what the system for follow-up tests is, and how to navigate it.


3. Methods

3.1. HSOPSC measurement tool

The self-administered HSOPSC tool was developed by the US Agency for Healthcare Research and Quality (AHRQ). The HSOPSC tool assesses safety climate from the staff perspective and covers 7 unit-level composites (24 items) of safety climate, 3 hospital-level composites (11 items) and 4 outcome variables. Table 1 depicts the characteristics of the specific measurement tool [14].

CharacteristicsHSOPSC measurement tool
Writers and date of developmentSorra and Nieva, 2004
 ObjectiveTo empower hospitals to evaluate their patient safety culture
Number of items44
 ScaleOn a 5-point Likert scale
 StaffHealth care staff
  1. Communication openness

  2. Supervisor/manager expectations and actions promoting patient safety

  3. No punitive response to error

  4. Staffing

  5. Hospital management support for patient safety

  6. Teamwork within units

  7. Teamwork across hospital units

  8. Organizational learning—continuous improvement

  9. Feedback and communication about error

  10. Hospital handoffs and transitions

  11. Overall perception of patient safety

  12. Frequency of event reporting

  13. Overall patient safety grade

  14. Number of events reported in the past 12 months

Psychometric evaluation
  1. Sufficient psychometric properties

  2. Cronbach’s alpha range from 0.63 to 0.84

  3. Tested on large specimen

Table 1.

Characteristics of the HSOPSC measurement tool.

Statistical analysis such as item analysis, exploratory factor analysis, confirmatory factor analysis and correlated composites scores across elements were performed to evaluate psychometric properties. It has a solid content validity and has been validated in all levels. FA resulted in 12 factors.

HSOPSC was selected as the tool for testing for several reasons: (a) Organizations can use the tool to assess their patient safety culture, track changes over time and evaluate the impact of patient safety interventions [15]. (b) It had been designed for surveying all hospital personnel (clinical/non-clinical) [14]. (c) It was considered one of the few healthcare safety climate instruments for which initial psychometric results had been reported [6, 7]. (d) Benchmark statistics of HSOPSC can be retrieved from the internet [16]. (e) The questionnaire has been translated into 27 different languages and it is currently used in 59 countries [17]. To use the specific tool will allow for future international comparisons.

3.2. Translation process: pre-test

Firstly, permission was obtained from the authors to use HSOPSC. It was translated into Greek language and then translated back into English by two independent researchers to ensure validity of the translation. In the translation process, it was stressed that the same meaning and ‘strength’ should be reproduced in the translation into the Greek language. In order to test if respondents understood the meaning of all items, HSOPSC was pilot tested in a group of 35 healthcare professionals which was not incorporated to the final sample. The overall Cronbach’s alpha of the pre-test was 0.87.

3.3. Sample

The study was carried out in 12 Greek hospitals over the period from May 2014 to November 2014. The participating hospitals included nine general hospitals, one of them is a teaching hospital, and three specialty hospitals (1 anticancer-oncology hospital, 1 psychiatric hospital and 1 cardiac surgery centre). The HSOPSC was originally designed for application to all hospital professionals [14]. However, the pre-test showed that items dealing with direct patient care could often not be answered by staff not involved directly in patient care (i.e. hospital managers, administrators). Consequently, the survey was returned by 820 participants (response rate = 59.6%), 10 questionnaires in which fewer than half the items were answered were also excluded. Finally, 810 questionnaires were retained for further analysis.

3.4. Statistical analysis

Factor analysis (FA) clarifies the items which are in depth connected and allude in collaboration to a below composite (or factor). Therefore, the items are able to be lessened to the smallest potential number of understandings that as before make the largest potential part of the variance clear [18]. A FA was carried out (principal component analysis with varimax rotation) for the purpose of proving that the current scales/dimensions may be fairly employed within the Greek context. When proving the number of elements, the Eigen value (Eigen value > 1: Kaiser’s criterion) was taken into consideration, in comparison with the range of explained variance, the shape of the screen plot and the future outcome of interpreting the elements. Kaiser’s criterion is trustworthy in a specimen of more than 250 respondents and when the average communality adds up to or is larger than, 0.6. The figure of the screen plot supplies dependable knowledge when the sample is larger than 200 respondents [18]. The data fulfil the requirements.

The Kaiser-Meyer-Olkin (KMO) calculation of sampling appropriateness was ascertained. This value is able to fluctuate from 0 to 1. A value near 1 points out that there is just any diffusion in the correlation pattern, empowered trustworthy and unique elements by FA [18]. The KMO score was 0.9, not close to Kaiser’s standard of 0.5.

Additionally, the writers confirmed whether the inter-item correlations were adequate, by a test of the correlation matrix. Queries are a member of the common underlying composite, which will be related as they calculate the identical feature of patient safety culture. Objectives that are not related, or correlate with only a few other variables, are not compatible with FA [18]. Bartlett’s test of sphericity illustrated that the inter-item correlations were adequate: (x2 = 12,190, df = 861, p < 0.001).

Last but not least, the writers confirmed whether the contrary existed: too much connection between the items. According to an ideal, each feature of patient safety culture exclusively is responsible for the patient safety culture. An important connection between two items signifies that patient safety culture aspects cross each other to a comprehensive range. The amount overlapped in the answer patterns is about 50% when a connection is 0.7 [18]. No connections surpassed the specific boundary score. The pre-analyses depict that the data could be employed for FA.

The construct validity was accomplished by determining scale scores for each factor (after any essential opposite coding) and next measuring Pearson correlation coefficients (r) between the scale scores. The construct validity of each factor is revealed in scale scores that are reasonably connected. Despite this, strong correlations (r> 0.7) would point out that factors calculate the identical concept and the above factors may be joined and/or a few objectives could be taken out. Also, connections of the scale scores were measured with the outcome variable ‘Patient safety grade’. No connections were measured with the other outcome variable, ‘Number of events reported’, due to the shortage of variability and distorted type of the specific item (40.1% of the respondents pointed out not to have reported any events during the past 12 months and 35% had reported only one or two events).

Cronbach’s alpha was determined to examine the internal consistency of composites. It is expressed as a number between 0 and 1. In case that separate items are considered to calculate the identical concept, the internal consistency (reliability) should be greater than or equivalent to 0.6 [18]. To the reason that the form with questions composed of in a positive and negative way phrased items, the negative ones were made an entry in first reason, due to ensure that a higher score every time signifies a more affirmative reply. Statistical analysis was carried out using the IBM SPSS 21.0 (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.).


4. Results

4.1. Sample

Most respondents were nursing staff (45.7%), followed by physicians (25.4%), nurse/unit assistants (17.9%) and physical/occupational/speech therapists (3.8%). These percentages give a reasonable reflection of the real distribution of disciplines at the units (Table 2).

CharacteristicsCategoryN (%)
Hospital typeGeneral hospital501 (61.9)
Anticancer-oncology hospital110 (13.6)
Psychiatric hospital132 (16.3)
Cardiac surgery centre67 (8.3)
Hospital size (beds)100–250642 (79.3)
400 or more168 (20.7)
Location of hospitalCentral hospitals9 (75)
Peripheral hospitals3 (25)
Work area/unitMany different hospital units/no specific unit166 (20.5)
Medicine (non-surgical)166 (20.5)
Surgery204 (25.2)
Emergency department12 (1.5)
Intensive care unit (any type)49 (6)
Laboratory38 (4.7)
Psychiatry/mental health117 (14.4)
Rehabilitation11 (1.4)
Pharmacy1 (0.1)
Social services department19 (2.3)
Other27 (3.4)
Staff positionResident physicians110 (13.6)
Specialist physicians95 (11.8)
Nurses (university training)49 (6.1)
Nurses (technological education institute training)320 (39.6)
Nurse assistants136 (16.8)
Unit assistants9 (1.1)
Physical/occupational/speech therapists31 (3.8)
Psychologists5 (0.6)
Welfare workers26 (3.2)
Pharmacy staff1 (0.1)
Other26 (3.2)
GenderMale247 (30.5)
Female563 (69.5)
Age (years)Mean41.35
Std. deviation7.9
Education levelUniversity268 (33.1)
Technological education institute386 (47.7)
Secondary education156 (19.3)
Master degree130 (17)
PhD12 (1.6)
Professional experience (years)Mean14.97
Std. deviation8.71
Professional experience in the specific hospital (years)Mean12.12
Std. deviation8.8
Professional experience in the specific unit (years)Mean7.74
Std. deviation6.84
Working hours per weekMean44
Std. deviation12.88
Interaction with patientsDirect724 (89.6)
Indirect84 (10.4)

Table 2.

Respondents—hospital characteristics.

4.2. FA: internal consistency

Ten factors were drawn by FA with 37 items. All the items of ‘Hospital handoffs and transitions’ (F3r, F5r, F7r, F11r) blended into the factor ‘Teamwork across hospital units’. Two of the items of ‘Feedback and communication about errors’ (C3, C5) from the US version blended into the factor ‘Communication openness’. A new factor originated, which comprised four items from the original questionnaire (B3r, B4r, A7r, A10r). The factors of ‘Non-punitive response to error’, ‘Hospital management support for patient safety’ and ‘Frequency of event reporting’ from the American study remained stable to the G-HSOPSC. The overall Cronbach’s coefficient alpha for the G-HSOPSC was 0.91. Seven out of 10 factors in the G-HSOPSC had Cronbach’s coefficients alpha > 0.70 and three factors had values between 0.60 and 0.70, which indicate fairly good internal consistency of the Greek version of the questionnaire (Table 3).

HSOPSC factor analysisG-HSOPSC factor analysis
CompositeItemsaCronbach’s α American dataCronbach’s α Greek dataCompositeItemsaCronbach’s α
1. Supervisor/manager expectations and actions promoting safetyB1, B2, B3r, B4r0.750.701. Competent supervisor/manager expectations and actions promoting safetyB1, B20.84
2. Organizational learning—continuous improvementA6, A9, A130.760.492. Organizational learningA9, A130.60
3. Teamwork within unitsA1, A3, A4, A110.830.613. Teamwork within units—continuous improvementA1, A3, A4, A60.80
4. Communication opennessC2, C4, C6r0.720.624. Feedback and communication openness about errorsC2, C4
C6r, C3
5. Feedback and communication about errorsC1, C3, C50.780.74***
6. Non-punitive response to errorA8r, A12r, A16r0.790.715. Non-punitive response to errorA8r, A12r
7. StaffingA2, A5r, A7r, A14r0.630.516. Sufficient staffingA2, A5r
8. Hospital management support for patient safetyF1, F8, F9r0.830.797. Hospital management support for patient safetyF1, F8
9. Teamwork across hospital unitsF4, F10, F2r, F6r0.800.828. Teamwork across hospital units and handoffs and transitionsF4, F10
F2r, F6r
F3r, F5r
F7r, F11r
10. Hospital handoffs and transitionsF3r, F5r, F7r, F11r0.800.78***
Outcome variables
11. Overall perceptions for safetyA15, A18, A10r, A17r0.740.68***
12. Frequency of event reportingD1, D2, D30.840.829. Frequency of event reportingD1, D2
10. Adequate procedures and systems for safetyB3r, B4r
A7r, A10r

Table 3.

Cronbach’s alpha and characteristics of the factors after factor analysis.

The codes in items’ column refer to the sections in the questionnaire and the numbers of the questions.

Some of the items of the American factors ‘Feedback and communication about errors’, ‘Hospital handoffs and transitions’ and ‘Overall perceptions for safety’ assimilated to other factors and other items removed from the questionnaire.

Five items (A11, A15, A17r, A18, C1) did not have a sufficient factor loading on any of the factors (all loadings < 0.50) and were eliminated. Table 4 gives the mean scores with standard deviations and factor loadings per item. The factors jointly explained 62% of the variance in the responses (Table 4).

B1. My supervisor/manager says a good word when he/she sees a job done according to established patient safety procedures3.620.950.823
B2. My supervisor/manager seriously considers staff suggestions for improving patient safety3.670.910.805
A9. Mistakes have led to positive changes here3.120.940.772
A13. After we make changes to improve patient safety, we evaluate their effectiveness3.290.910.597
A1. People support one another in this unit3.520.910.802
A3. When a lot of work needs to be done quickly, we work together as a team to get the work done3.710.890.711
A4. In this unit, people treat each other with respect3.500.890.778
A6. We are actively doing things to improve patient safety3.980.750.618
C2. Staff will freely speak up if they see something that may negatively affect patient care3.780.920.695
C3. We are informed about errors that happen in this unit3.750.950.645
C4. Staff feel free to question the decisions or actions of those with more authority2.770.960.687
C5. In this unit, we discuss ways to prevent errors from happening again3.660.890.626
C6r. Staff are afraid to ask questions when something does not seem right (reverse worded)3.620.990.604
A8r. Staff feel as if their mistakes are held against them (reverse worded)2.350.940.753
A12r. When an event is reported, it feels like the person is being written up, not the problem (reverse worded)2.681.000.699
A16r. Staff worry that mistakes they make are kept in their personnel file (reverse worded)2.660.970.781
A2. We have enough staff to handle the workload2.161.030.663
A5r. Staff in this unit work longer hours than is best for patient care (reverse worded)
A14r. We work in ‘crisis mode,’ trying to do too much, too quickly (reverse worded)2.270.970.578
F1. Hospital management provides a work climate that promotes patient safety2.820.980.745
F8. The actions of hospital management show that the patient safety is a top priority3.101.090.753
F9r. Hospital management seems interested in patient safety only after an adverse event happens (reverse worded)2.761.040.752
F2r. Hospital units do not coordinate well with each other (reverse worded)2.730.930.638
F3r. Things ‘fall between the cracks’ when transferring patients from one unit to another (reverse worded)2.940.970.736
F4. There is good cooperation among hospital units that need to work together3.330.850.674
F5r. Important patient care information is often lost during shift changes (reverse worded)3.441.010.598
F6r. It is often unpleasant to work with staff from other hospital units (reverse worded)3.130.890.795
F7r. Problems often occur in the exchange of information across hospital units (reverse worded)2.960.910.804
F10. Hospital units work well together to provide the best care for patients3.200.880.718
F11r. Shift changes are problematic for patients in this hospital. (reverse worded)3.480.970.569
D1. When a mistake is made, but is caught and corrected before affecting the patient, how often is this reported?3.411.110.788
D2. When a mistake is made, but has no potential to harm the patient, how often is this reported?
D3. When a mistake is made that could harm the patient, but does not, how often is this reported?
A7r. We use more agency/temporary staff than is best for patient care.3.441.020.571
A10r. It is just by chance that more serious mistakes do not happen around here.
B3r. Whenever pressure builds up, my supervisor/manager wants us to work faster, even if it means taking shortcuts. (reverse worded)3.411.010.596
B4r. My supervisor/manager overlooks patient safety problems that happen over and over. (reverse worded)3.910.940.656
A11. When one area in this unit gets really busy, others help out.2.301.110.29
A15. Patient safety is never sacrificed to get more work done.4.120.810.41
A17r. We have patient safety problems in this unit. (reverse worded)
A18. Our procedures and systems are good at preventing errors from happening.3.070.970.46
C1. We are given feedback about changes put into place based on event reports.3.060.980.44

Table 4.

Mean scores and factor loadings of the items regarding patient safety culture.

Rotation converged in seven iterations.

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a

4.3. Construct validity: inter-correlations

For each of the 10 factors, scale scores were calculated by obtaining the mean of the item scores within one factor for every respondent. Immediately after, the mono-item outcome variable ‘Patient safety grade’ has been determined with the connections of the scales. The factors were anticipated to be related in a positive way with the specific outcome measure. Every one of connections with ‘Patient safety grade’ was important. With the ‘Teamwork across hospital units and handoffs & transitions’, the most significant correlation of this outcome was measured (r= 0.49). Moreover, correlations between the scale scores were calculated. The highest correlation was between ‘Hospital management support for patient safety’ and ‘Teamwork across hospital units and handoffs & transitions’ (r= 0.52) but no correlation was exceptionally high (Table 5).

FactorPatient safety grade12345678910
1. Competent supervisor/manager expectations & actions promoting safetyMean (SD)3.62 (0.86)
Pearson r0.3610.36**0.34**0.45**0.11**0.11**0.29**0.27**0.16**0.31**
Sig. (two-tailed)<0.001<0.001<0.001<0.0010.0020.003<0.001<0.001<0.001<0.001
2. Organizational learningMean (SD)3.20 (0.76)
Pearson r0.400.36**10.30**0.38**0.15**0.18**0.37**0.37**0.17**0.26**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
3. Teamwork within units—continuous improvementMean (SD)3.66 (0.67)
Pearson r0.340.34**0.30**10.38**0.16**0.09**0.29**0.39**0.14**0.39**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.0010.009<0.001<0.001<0.001<0.001
4. Feedback and communication openness about errorsMean (SD)3.51 (0.68)
Pearson r0.410.45**0.38**0.38**10.25**0.15**0.25**0.39**0.36**0.33**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
5. Non-punitive response to errorMean (SD)2.54 (0.77)
Pearson r0.220.11**0.15**0.16**0.25**10.38**0.22**0.29**0.13**0.29**
Sig. (two-tailed)<0.0010.002<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
6. Sufficient staffingMean (SD)2.23 (0.74)
Pearson r0.290.11**0.18**0.09**0.15**0.38**10.30**0.30**0.08*0.21**
Sig. (two-tailed)<0.0010.003<0.0010.009<0.001<0.001<0.001<0.0010.019<0.001
7. Hospital management support for patient safetyMean (SD)2.86 (0.87)
Pearson r0.440.29**0.37**0.29**0.25**0.22**0.30**10.52**0.11**0.31**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.0010.002<0.001
8. Teamwork across hospital units and handoffs & transitionsMean (SD)3.13 (0.69)
Pearson r0.490.27**0.37**0.39**0.39**0.29**0.30**0.52**10.15**0.42**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001
9. Frequency of event reportingMean (SD)3.20 (0.97)
Pearson r0.300.16**0.17**0.14**0.36**0.13**0.08*0.11**0.15**10.26**
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.0010.0190.002<0.001<0.001
10. Adequate procedures and systems for safetyMean (SD)3.49 (0.70)
Pearson r0.380.31**0.26**0.39**0.33**0.29**0.21**0.31**0.42**0.26**1
Sig. (two-tailed)<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001

Table 5.

Mean factor scores, correlations with patient safety grade and inter-correlations of the 10 composites.

Correlation is significant at the 0.05 level (two-tailed).

Correlation is significant at the 0.01 level (two-tailed).

NA: non applicable.


5. Discussion

Cultural and healthcare differences in terms of context between US and Greece set obvious that reproduction of HSOPSC would be meaningful in Greek hospital settings. The available evidence from studies which were conducted in European and non-European countries—such as Norway [19]; Sweden [20]; Slovenia [21]; the West Bank [22]; Iran [23]; Scotland [24]; the United Kingdom [25]; the Netherlands [26]; Norway [15]; Switzerland [26] and Belgium [27]—suggests that the HSOPSC developed based on the original US version should be cautiously adjusted to other healthcare contexts. In Switzerland, for instance [26], the use of agency staff in nursing is currently relatively uncommon. Moreover, the role of hospital management and the way it is organized presents differences between hospital types and national or regional regulations. Consequently, taking into account the relative published studies, the number of composites varied between 8 and 15 and included 27 to 50 items.

This is the first study which was conducted in Greece which reports the structure as well as the psychometric properties of G-HSOPSC in accordance with the guidelines of the AHRQ. Despite the fact that our results are aligned with the original version, some adaptations were demanded so that the Greek context is fitted correctly. A 10-factor model with 37 items performed better than the original one in the sample of the 12 Greek hospitals. The main difference was that the composite ‘Teamwork across hospital units’ merged with ‘Hospital handoffs and transitions’ and ‘Communication openness’ merged with ‘Feedback and communication about error’ except an item (C1). The studies [21, 28, 29] showed the same conflations. The items B3r and B4r, A7, A10r loaded slightly more on a new composite which was named ‘Adequate procedures and systems for safety’ instead of ‘Supervisor/Manager expectations & actions promoting safety’, ‘Staffing’, ‘Overall perceptions for safety’, respectively. Last but not least, the item A6 loaded slightly more on ‘Teamwork within units’ instead of ‘Organizational learning—continuous improvement’ which renamed the first one as ‘Teamwork within units—continuous improvement’.

Finally five items (A11, A15, A17r, A18, C1) of the original questionnaire were removed. Three of them (A11, A15, C1) have been eliminated from the Arabic, Dutch and French version, respectively too [22, 26, 28]. Ten underlying factors offered 62% of the variance of the items. The originally proposed 12 safety culture composites had explained 64.5% of the variance in the US version [14] and 57.1% and 59.8% in the Dutch adaptation and German version, respectively [26, 29].

If the factor structures of the various applications of the HSOPSC in Europe are compared to the original pilot tested US version, most of the composites presented similar patterns in the Cronbach’s alpha. The internal consistency of G-HSOPSC ranged between 0.60 and 0.88 with lowest Cronbach´s alpha values for ‘Organizational learning’ and ‘Sufficient staffing’ (both α = 0.60). These findings have also been presented in other studies [25, 26, 29, 30]. As far as the present study is concerned, our belief is that these composites and items should be kept since they signify important aspects of patient safety and as such shape a useful foundation for improvement work.

Correlations among the 10 safety culture composites varied from 0.08 to 0.52 (p < 0.01). These correlations are deemed satisfactory and do not indicate problematic associations among dimensions. ‘Patient Safety Grade’ showed its highest correlations with ‘Teamwork across hospital units and handoffs & transitions’ (r= 0.49). ‘Frequency of events reported’ has actually only a small interrelationship with the other safety culture sub-dimensions (the highest with ‘Feedback and communication openness about error’, r= 0.36). The above results underline the crucial role of the hospital procedures in developing a cooperative and communication openness environment that cultivates free process of evaluation about the adverse events, sharing data about the errors that take place, discussing the way to prevent adverse events and reporting the identified errors. As data indicate an aftermath of that environment will lead to a frequency of event report and improved patient safety grade [31]. Finally, the highest inter-correlation was between ‘Hospital management support for patient safety’ and ‘Teamwork across hospital units and handoffs & transitions’ (r= 0.52). Considering that both composites share some attention towards transference of important patient care information, this outcome was not considered as surprising; although these composites share a common meaning, they were not integrated into one concept.

5.1. Strengths and limitations of the study

The main strength of the study is the heterogeneity of the selected healthcare facilities. The sample was opted from different types of hospitals in order to capture a more comprehensive view of perceptions towards patient safety culture because the studies which have been published show that the patient safety culture composites may vary among different types of healthcare settings [32].On the other hand, the study has some limitations. Firstly, selection bias might have occurred as hospitals were selected on a voluntary basis and as head nurses were responsible for distributing the questionnaires. It is possible that head nurses chose not to include some healthcare professionals. Secondly, the relatively lower internal consistency of some scales (i.e. organizational learning, sufficient staffing) than that of the original AHRQ data consist another cause. Further studies are needed to investigate the possible association between certain composites and their items. Thirdly, the difficulty of achieving high response rates among hospital professionals, which was thought to be the most practical challenge after conducting this study.


6. Conclusion

The G-HSOPSC is suitable for clinical and research purposes and allows clinicians and researchers to make cross-national comparisons. Healthcare managers could benefit from using the G-HSOPSC for benchmarking when improving hospital patient safety culture in general and at the same time to obtain knowledge about specific areas of improvement (i.e. shift-working, staffing and over-occupancy). Examination of patient safety culture differences between staff groups and factors affecting patient safety culture is also a term of need in order to obtain knowledge of areas in order to take action to improve safety.



The authors would like to extend their gratitude and appreciation to the administration of the 12 hospitals and to their staff who devoted time to complete the survey. Furthermore, the authors did not receive any kind of funding for the research and they have no competing interests.


Ethical approval

The research complied with every one of the dilemmas concerned with ethics. The privacy and secrecy or anonymity of employees were made certain.



AHRQAgency for Healthcare Research and Quality
FAFactor Analysis
HSOPSCHospital Survey on Patient Safety Culture
G-HSOPSCHospital Survey on Patient Safety Culture in Greek version
USUnited States


  1. 1. Institute of Medicine Committee on Quality of Health Care in America. In: Kohn LT, Corrigan JM, Donaldson MS, editors. To Err is Human: Building a Safer Health System. Washington (DC): National Academies Press (US); 2000. Executive Summary. Available from:
  2. 2. International Atomic Energy Agency Safety Culture and I.S.A. Group. Safety Series 75‐INSAG‐4. Vienna: International Atomic Energy Agency; 1991
  3. 3. Flin R, et al. Measuring safety climate: Identifying the common features. Safety Science. 2000:34(1-3):177-192
  4. 4. Zohar D. Safety climate in industrial organizations: Theoretical and applied implications. Journal of Applied Psychology. 1980;65(1):96-102
  5. 5. Zohar D, et al. Healthcare climate: A framework for measuring and improving patient safety. Critical Care Medicine. 2007;35(5):1312-1317
  6. 6. Colla JB, et al. Measuring patient safety climate: A review of surveys. Quality and Safety in Health Care. 2005;14(5):364-366
  7. 7. Flin R, et al. Measuring safety climate in health care. Quality & Safety in Health Care. 2006;15(2):109-115
  8. 8. Nieva VF, Sorra J. Safety culture assessment: A tool for improving patient safety in healthcare organizations. Quality and Safety in Health Care. 2003;12(Suppl 2):ii17-23
  9. 9. Singla AK, et al. Assessing patient safety culture: A review and synthesis of the measurement tools. Journal of Patient Safety. 2006;2:105-115
  10. 10. Guldenmund FW. The nature of safety culture: A review of theory and research. Safety Science. 2000;34(1-3):215-257
  11. 11. Hale AR. Culture’s confusions. Safety Science. 2000;34(1-3):1-14
  12. 12. Hutchinson A, et al. Use of a safety climate questionnaire in UK health care: Factor structure, reliability and usability. Quality & Safety in Health Care. 2006;15(5):347-353
  13. 13. Reason J. Human Error. New York, NY: Cambridge University Press; 1990
  14. 14. Sorra JS, Nieva VF. Hospital survey on patient safety culture. Prepared by Westat, under Contract No. 290-96-0004. in AHRQ publication no. 04-0041. USA: AHRQ; 2004
  15. 15. Olsen E. Reliability and Validity of the Hospital Survey on Patient Safety Culture at a Norwegian Hospital, in Quality and Safety Improvement Research: Methods and Research Practice, National School of Public Health. Lisbon: International Quality Improvement Research Network (QIRN); 2008. pp. 173-186
  16. 16. AHRQ. Comparing your Results: Preliminary Benchmarks: Hospital Survey on Patient Safety Culture. USA: AHRQ; 2006
  17. 17. Agency for Healthcare Research and Quality (AHRQ). International Use of the Surveys on Patient Safety Culture. Agency for Healthcare Research and Quality, Rockville, MD; 2014. Available from:
  18. 18. Field AP. Discovering Statistics Using SPSS for Windows: Advanced Techniques for the Beginner. London: Sage Publications; 2000
  19. 19. Cappelen K, et al. Psychometric properties of the nursing home survey on patient safety culture in Norwegian nursing homes. BMC Health Services Research. 2016;16(1):446
  20. 20. Nordin A. Patient safety culture in hospital settings measurements, health care staff perceptions and suggestions for improvement [Dissertation]. Sweden: S.a.T.D.o.H.S. Karlstad University Faculty of Health; 2015
  21. 21. Robida A. Hospital survey on patient safety culture in slovenia: A psychometric evaluation. International Journal for Quality in Health Care. 2013;25(4):469-475
  22. 22. Najjar S, et al. The Arabic version of the hospital survey on patient safety culture: A psychometric evaluation in a Palestinian sample. BMC Health Services Research. 2013;13:193
  23. 23. Moghri J, et al. The psychometric properties of the farsi version of “Hospital Survey on Patient Safety Culture” in Iran’s hospitals. Iranian Journal of Public Health. 2012;41(4):80-86
  24. 24. Sarac C, et al. Hospital survey on patient safety culture: Psychometric analysis on a Scottish sample. BMJ Quality & Safety. 2011;20(10):842-848
  25. 25. Waterson P, et al. Psychometric properties of the Hospital Survey on Patient Safety Culture: Findings from the UK. Quality and Safety in Health Care. 2010;19(5):e2
  26. 26. Smits M, et al. The psychometric properties of the ‘Hospital Survey on Patient Safety Culture’ in Dutch hospitals. BMC Health Services Research. 2008;8:230
  27. 27. Hellings J, et al. Challenging patient safety culture: Survey results. International Journal of Health Care Quality Assurance. 2007;20(7):620-632
  28. 28. Occelli P, et al. Validation of the French version of the Hospital Survey on Patient Safety Culture questionnaire. International Journal for Quality in Health Care. 2013;25(4):459-468
  29. 29. Pfeiffer Y, Manser T. Development of the German version of the Hospital Survey on Patient Safety Culture: Dimensionality and psychometric properties. Safety Science. 2010;48(10):1452-1462
  30. 30. Hedskold M, et al. Psychometric properties of the Hospital Survey on Patient Safety Culture, HSOPSC, applied on a large swedish health care sample. BMC Health Services Research. 2013;13:332
  31. 31. Flin R. Measuring safety culture in healthcare: A case for accurate diagnosis. Safety Science. 2007;45(6):653-667
  32. 32. Bodur S, Filiz E. Validity and reliability of Turkish version of “Hospital Survey on Patient Safety Culture” and perception of patient safety in public hospitals in Turkey. BMC Health Services Research. 2010;10:28

Written By

Vasiliki Kapaki and Kyriakos Souliotis

Submitted: November 15th, 2016 Reviewed: June 2nd, 2017 Published: December 20th, 2017