Background

‘Adverse events’ (AE) harm and impact the lives of the involved patients, families and healthcare professionals, and AEs are one of the leading causes of disability and death in the world [1]. Patient AEs can be defined as unintended actions or omission that lead to or can lead to harm or injuries related to healthcare and not to the underlying disease [2]. AEs occur in at least 10% of in-hospital patients [1, 3, 4], and half of the AEs are estimated to be preventable [4,5,6,7]. AEs in low- and middle-income countries are estimated to affect 25% of hospitalised patients, constituting 134 million AEs and 2.6 million deaths annually [1, 5, 8]. The World Health Organization estimates the global costs of AEs to be US$ 1–2 trillion a year [5]. In Organization for Economic Co-operation and Development countries, 15% of all hospital costs are due to patient harm from AEs [1, 5].

Estimates of the occurrence of AEs as patient outcomes are often based on measurements from medical record reviews [4]. The ‘Harvard Medical Practice Study’ (HMPS) and the’Global Trigger Tool’ (GTT) are the most frequently used structured chart review methods for measuring AE rates in electronic medical records. The occurrence of in-hospital AE rates varies across studies, ranging from 2.9–21.9%, indicating methodological and contextual variation in retrospective chart reviews, as well as varying levels of patient safety [4]. A comprehensive approach to monitoringand learn from AEs is important to improve patient safety in healthcare systems [1, 4, 8, 9].

‘Safety culture’ is a multidisciplinary concept, however the interest of the concept safety culture in healthcare organisations, as ‘Patient safety culture’ (PSC) increased after the Chernobyl disaster in 1986, and PSC is perceived as a proxy outcome for quality of care [10,11,12]. PSC can be described as the overall attitudes and patterns of behaviours related to the patient safety work at multiple levels in an organisation. This includes individuals and groups` shared values, beliefs and norms influencing their actions both in preventing AEs in care delivery, and when an AE occurs [13,14,15]. In addition, the organisation`s efforts to protect patients from AEs through communication openness, organisational learning and error management culture are important dimensions influencing the PSC [12]. Another important dimension of PSC is the ‘Patient safety climate’. ‘Patient safety climate’ is also used interchangeable to PSC, and ‘Patient safety climate` can be considered as the more visible perceptions and deliberate behaviours. This can be measured, and indicates the priority given to safety at different healthcare levels, hence the PSC can also represent the invisible and intangible underlying dimensions. In this review, ‘Safety culture’ and ‘Safety climate’ in healthcare services will be covered by the concept PSC.

Measuring PSC has the last two decades become a strategy for understanding the processes of care and improving the overall quality of healthcare [16]. A questionnaire is often the tool used for such measurements, and a previous review of PSC measurement totally identified 127 tools. The review identified 11 main dimensions of PSC across the studied tools, however no single tool captured all the dimensions [17]. The most reported dimensions from such measurements are ‘Leadership’, ‘Perception of safety’, ‘Teamwork and collaboration’, ‘Safety systems’, ‘Prioritisation of safety’ and ‘Resources and constraints’ [17]. Healthcare should be aware of choosing an appropriate and validated tool [16]. The Safety Attitudes Questionnaire (SAQ) and the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture (HSOPS) are validated, and the tools used most frequently to measure PSC [16,17,18]. A recent review investigating PSC instruments for measurements in hospital settings, suggests that valid measurements of PSC can identify variability in healthcare professionals shared perceptions and guide the management to focus on the challenging PSC dimensions in their organisation [16].

Groves [19] reviewed the evidence on the association between safety culture and patient safety outcomes in acute medical care Despite a variety of concepts of safety culture and outcomes, work level of measurement and instruments utilised, ten out of fourteen studies were included in a meta-analysis. No significant association was reported in this review from 2013 [19]. DiCurrio [20] investigated the association between PSC scores and nurse-sensitive outcomes in hospitals. This review reported that a limited number of the included studies found a statistically significant association.However, this review limited the measurement to only selected nurse-sensitive outcomes in hospitals and excluded reports from healthcare professionals` perceptions [20]. Braithwaite [21] reviewed the association between the wide-range concepts of ‘Organisational- and workplace cultures’, and a broad range of included patient outcomes. This review from 2017 demonstrated a statistically significant inverse association in the included evidence and pointed to the need for higher quality studies to verify the findings [21].

We need to gain a better understanding of the association between PSC scores and AE rates [19,20,21,22], and an updated review is needed due to the rapid development of evidence in this research field. The main objective of this scoping review is to summarise the evidence on the association between PSC scores and AE rates in healthcare services. Moreover, in addition, map the characteristics and applied research methodology in the included studies and study the strengths and limitations of the evidence.

Methods

Scoping review

We conducted a scoping review to answer the main objectives. Scoping reviews often map and describe the available evidence and key concepts on a topic [23, 24]. The research questions in scoping reviews address broader topics than research questions in traditional systematic reviews. A scoping review may be the appropriate approach when a research question is complex, and a comprehensive review of the topic has yet to be undertaken [23, 24]. A scoping review is an appropriate methodological approach due to the broad objective to investigate the evidence on the association, and to scope a body of the literature [24]. We used the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and explanation for complete and transparent reporting of the scoping review [25]. We developed a study protocol prior to the literature searches. The protocol was not registered, however there were no deviations from the protocol. The filled PRISMA-ScR checklist and the study protocol are available in supplemental materials.

Search strategy

A comprehensive search strategy covering relevant databases was developed in collaboration with an experienced research librarian. The search terms and the three-step search strategy in Medline (Ovid) is outlined in Table 1, and the inclusion and exclusion criteria in Table 2. When conducting step 2 and 3, saved hits from previous steps were excluded. Despite using “patient safety culture” and “adverse patient events” in this study, we searched for a wide range of concepts to capture relevant evidence. We had no exclusion criteria on publication year due to the purpose of the broad objectives. We conducted the search in the databases Embase, PsycINFO, Cinahl, Cochrane Library and Epistemonikos in accordance with the different database thesauruses. The interprofessional databases Web of Science and Business Source Elite were also searched to identify relevant studies conducted in organisational and management research. In these databases, we subsequently narrowed the search by not using proximity operators. For a search across a greater variety of resources to possibly find pertinent evidence to supplement to supplement the primary search, we replicated the search in Google scholar, however we found no new hits after the first sixty results.

Table 1 The search strategy in Medline (Ovid)
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Table 2 Inclusion and exclusion criteria
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Selection of sources

The records retrieved were first screened by MV and SOD independently based on titles and abstracts. To ensure the process and conduct a blind screening, we used the Rayyan software as a screening tool [26]. We tested screening agreement after the first, second and third hundred records to ensure and align a common understanding of the studies that illuminated the scope of the review. The inter-rater agreement was 95%. In the event of conflict on inclusion, consensus was achieved by discourse. After screening, we included records for full text reading. This part of the screening was also blinded by Rayyan [26]. We conducted backward citation checking in the reference lists of included studies and in relevant reviews [27, 28].

Data charting, critical appraisal and synthesis of results

The data charting was performed using a pre-formatted Excel worksheet (Microsoft, Redmond, WA, USA, version: 2018). We charted first author, year, origin, purpose, single or multicentre study, medical specialty, intervention, quality improvement project or not, tools used to measure PSC and AEs, participants, response rate, AEs measured, the work unit level of measurement, analysis methods, time frame, confounding variables, key findings and reported knowledge gaps. Moreover, the measurement of PSC, AEs and statistical associations were specified in detail in the respective worksheets.

We explored the methodological quality of the included studies due to the heterogeneity of the individual sources of evidence, and conducted a critical appraisal of the included studies utilising the appropriate checklist ‘Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies’ [29]. The tool consists of 14 questions designed to evaluate the internal validity of studies and consider the potential risk of bias. MV and SOD conducted a consensus process to assess the risk of bias in the included studies, and translated the overall risk as ‘Good’, ‘Fair’ or ‘Poor’ [29]. The complete data charting form and critical appraisal is available in supplemental materials.

We summarised, made table schema maps and descriptive representations of the charted data relating to the research questions and study objectives.

Results

Selection and characteristics of sources of evidence

The selection of sources of evidence is presented by PRISMA flow chart [30] in Fig. 1. Fifteen per cent of the included studies were published within the last two years, 74% of the studies within the last decade and 12% of the studies were published in 2006–2009. Sixty-two per cent of the studies originated from the US and Canada, 21% from Europe, 15% from Asia and 3% from Australia. Most of the studies, 97%, were conducted as multicentre studies, and 91% of the studies were conducted in-hospital, otherwise in out-patient or primary care [31,32,33]. Surgery was the most frequently assessed medical context in hospitals, assessed in 32% of the studies. See Table 3 for more details about characteristics.

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PRISMA flow chart on inclusion of studies

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Table 3 The measurements of patient safety culture and adverse patient events, and their associations
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The studies used a variety of concepts to illuminate PSC. ‘Safety culture’ was used in 56% and ‘Safety climate’ in 44% of the studies. Different concepts were also used to illuminate AEs, and the most used concepts were ‘Events’ in 32% of the studies and ‘Outcomes’ in 26%. Some of the concept`s definitions were interchangeable at both side of the association. More details on the variety of concepts and their prefixes used are presented in Table 3.

Association between PSC scores and AE rates

A vast majority (n = 32) of the included studies were designed as cross-sectional cohort studies and only two studies measured the association in quasi-experimental intervention studies [35, 44]. Most of the included studies, 76%, demonstrated that increased PSC scores were associated with reduced AE rates [31, 33, 36,37,38, 41, 43,44,45,46,47,48,49,50,51,52,53,54,55,56, 59,60,61,62,63,64]. Around one-quarter of the included studies, 24%, found no association, i.e. reduced AE rates by increasing PSC scores [32, 34, 35, 39, 40, 42, 57, 58]. Studies indicating that increased PSC scores predicted reduced AE rates, were based on the association between overall PSC score or the scores of some of the PSC dimensions, and the composite AE rates or the rates of some of the AEs. Some studies suggested that the PSC scores of frontline personnel, nurses and physicians, were more strongly associated with reduced AE rates than the perceptions of managers and administrators [36, 57, 59].

To examine the statistical association between PSC scores and AE rates, 74% of the studies used a various number of measured PSC dimensions [31, 33, 34, 36,37,38,39,40,41, 43, 45, 46, 48, 49, 51, 53, 54, 56,57,58,59,60,61,62, 64], however two studies measured more dimensions than they included in the analysis [56, 61]. Many of these studies also used the ‘overall safety grade’ to measure the association [39, 43, 45, 48, 51, 53, 54, 57,58,59,60, 64], and some studies only utilised the ‘overall safety grade’ [35, 42, 52, 63], composite measure of selected items [44, 50, 55], single items and dimensions to analyse the association [36], or dominant dimension of PSC from one tool and the overall score from another tool to assess the association [32]. In 47% of the studies, the rates of predefined AEs were used to examine the statistical association with PSC scores [31,32,33,34, 37, 41,42,43, 45, 47, 48, 50, 54, 62,63,64], and 21% used the overall AE rates [36, 51, 52, 56, 57, 59, 61]. Adjusted estimated mortality or morbidity was used in 21% [35, 38, 40, 44, 46, 55, 58] and AE categories and scales in 9% of the studies [39, 49, 60].

The statistical analyses conducted to examine the associations were bivariate and/or multivariate, mostly regression analyses (logistics, linear or hierarchical) and correlation analyses, detailed in Table 3. The statistical association between PSC scores and AE rates was explored at different levels of the healthcare system. Analyses were conducted at unit level in 44% and at hospital level in 38% of the studies, others used group- or individual levels or combinations of levels as presented in Table 3. The measurement of PSC scores and AE rates was conducted within the same time frame in 48% of the included studies [31,32,33,34,35, 38, 42, 43, 47,48,49,50,51, 61, 63, 64]. Fifteen per cent of the studies measured AE rates after the measurement of PSC scores [37, 45, 52, 59, 60], and 6% of the studies measured AE rates after and during the PSC measurement [40, 41]. Other studies, 9%, measured AE rates before PSC measurement [39, 53, 55], and 15% of the studies measured AE rates before, during and after the PSC score measurement period [46, 54, 56, 58, 62]. Some of the studies did not report the time frame for both PSC and AE measurements [36, 44, 57]. The length of the study period represented additional variation in the included studies. The study periods ranged from PSC measurements combined with prospective observed AE rates over 48 h [61, 63] or two weeks at each unit [42], PSC measurements combined with retrospective nurse-estimates over 3–4 months [33, 34, 43, 47, 48, 50, 64], to AE rates from chart reviews collected over four years and AE rates from registers collected over three years [38].

Research methodology

All studies used a cross-sectional survey to measure PSC. The majority of the studies used the tools HSOPS (38%) and SAQ (29%) to measure PSC, and most of these studies used the complete tool, however some used translated og modified versions. Other studies measured selected items from HSOPS and/ or SAQ. Nurses’ and physicians’ perceptions of the PSC were, respectively, assessed in 79% and 59% of the included studies. Others were assessed in 44% of the studies and managers in 15% of the studies. Others included other clinical or administrative professionals in the healthcare. One study reported nurses’ PSC scores to be lower than those of surgeons [36], and another study suggested that hospital administrators have more positive perceptions of PSC than frontline personnel such as nurses and physicians [54]. Details of the PSC measurement are presented in Table 3.

The selected scientific papers demonstrated a variety of approaches to examining AE rates. Most of the studies employed a retrospective approach to measure AE rates (82%), and only a few, 18%, employed a prospective approach. Most of the included studies, 35%, used registers to obtain AE rates, 26% did chart reviews, 21% were based on nurse-reported estimates and 18% utilised the prospective staff`s reporting. Registers for obtaining AE rates were nationally based [31, 37, 38, 46, 51, 54], regional/state [49, 56, 62] or from institutional registers [52, 58, 59]. The details of the AE measurement are presented in Table 3.

Strengths and limitations of the included studies

The key questions in the critical appraisal of the included studies were measurement of PSC scores and AE rates, response rate and adjustment for confounding variables. The critical appraisal resulted in 71% of the included studies being rated as ‘Fair’, 21% being rated as ‘Good’, and 9% being rated as ‘Poor’. The rating of the studies is visually presented in Table 3.

Sixty-five per cent of the studies reported complete and validated use of the PSC tool [31, 34, 37,38,39,40,41,42,43, 46, 48, 51, 53, 54, 56,57,58,59,60,61, 63, 64]. Other studies reported on reliability by measuring the internal consistency using Cronbach`s alpha [32, 33, 35, 45, 47, 49, 50, 52, 55]. The study using focus groups to select items from HSOPS and SAQ was the only study that did not report the validity or the internal consistency of the tool used [36].

For AE measurement, almost half of the utilised registers in the included studies were reported as reliable and validated systems [51, 54, 56, 58, 59, 62]. The AE measurement procedures from other registers were well described and clearly defined, but not reported as validated for the intended use [31, 38, 46, 49]. Another register had well-described definitions and was based on voluntary reporting [37]. One study that obtained AE rates from their mandatory safety reporting system did not define the AEs in detail [52].

Half of the studies obtaining AE rates from chart reviews used standardised procedures, AE definitions and trained staff to identify AEs in records [36, 39, 40, 45, 55]. However, two studies used a standardised procedure but did not report who conducted the chart reviews [35, 44]. One of these combined chart reviews and constructed internal validation through dialogue with clinicians [44]. Additionally, internal validation by consulting clinicians was used in one observational study using a chart review as a supplementary methodology, however, the method was not externally validated [42]. Another study documented the inter-rater reliability of their procedure [40]. Automated tools such as ‘Agency for Healthcare Research and Quality Patient Safety Indicator software’ and the GTT were reported as validated [53, 57]. The systematic prospective tools and the retrospective nurse-estimates for measuring AE rates were not considered valid by the studies themselves, although the data collection was described as standardised.

The response rate of PSC surveys ranged from 26.4%—97.7%. A few of the studies had a response rate < 50% (18%). Some of the included studies did not report the response rate, either the sample size. The sample size ranged from 184 participants to 214,338 participants, and 21% of the studies had a sample size < 500. The distribution of the sample in 15% of the studies resulted in an average sample size of < 10 participants per unit/hospital (n = 5), and 35% had a distribution of the sample resulting in an average sample size of < 20 participants per unit/hospital.

Most of the studies 82%, described how they measured and adjusted for key potential confounding variables. Some studies did not measure and adjust for confounding variables, or we could not determine whether this was done [33, 35, 37, 44, 53, 63].

Discussion

We aimed to summarise the evidence on the association between PSC scores and AE rates in healthcare services, to map the characteristics and applied research methodology, and to study the strengths and limitations of the included studies. Recent evidence on the statistical association between PSC scores and AE rates reflects the increasing priority assigned to this topic over the last twenty years in response to the Institute of Medicine`s call for global and comprehensive efforts to improve the quality of healthcare [6, 10]. However, the included studies mainly originate from the US, Canada and Europe, and the evidence on the association is primarily conducted in-hospital. Hence there is a lack of studies from low- and middle-income countries, and a lack of studies conducted in primary care.

Most of the included studies demonstrated that increased PSC scores were statistically significantly associated with reduced AE rates. This is in line with previous reviews reporting mostly significant associations between PSC scores and patient safety outcomes [21, 65, 66]. The review assessing the association between ‘Organisational and workplace culture’ and patient outcomes, found that 74.2% of the evidence reported positive or mixed positive associations between culture and patient outcomes [21]. This finding is closely related to the evidence in this review and underlines the importance of promoting a culture for patient safety. As demonstrated in the Table 3, ‘Teamwork climate’ and ‘Safety climate’ tended to be the most frequent dimensions associated with reduced AE rates. This finding supports a review demonstrating that teamwork and communication training improves PSC scores and suggests that improving these dimensions may reduce AE rates [67]. Additionally, these finding rise the question about the concepts of ‘Patient safety culture’ and ‘Patient safety climate’. Previous reviews suggest that PSC questionnaires capture ‘Patient safety climate’ and the tangible themes, and not the PSC and intangible themes under the surface [17, 68]. Increased scores in the dimensions ‘Leadership’s perception and Action promoting patient safety’, ‘Management support’, ‘Communications openness and learning’, and ‘Non-punitive response to errors’, were also associated with reduced AE rates in the included studies. This resonates with a comprehensive review emphasising senior leadership as key to accountability for safety culture [69].

Fewer studies found that increased PSC scores did not reduce AE rates, and this is supported by previous research on the association between PSC and quality outcomes [19, 70]. However, one of the included studies that demonstrates no or an inverted result on AEs, reported that increased PSC scores were associated with a reduction in ‘Intercepted near-misses’ [39], which previous research indicates may be related to an actual reduction in “Near misses” [71]. These findings support increased PSC as a proxy for improved patient outcomes and better quality of care. Another of the studies demonstrating mixed results reported increased scores of specific PSC dimensions being associated with reduced rates of specific AEs [40, 57]. A previous review of the PSC literature identifies semantic inconsistencies, infrequent use of theory, limited discussion of the use of instruments, methodological variation in research on the relationship between safety culture and patient safety and quality of care outcomes [70]. Previous reviews and the discrepancy in the evidence on the association between PSC scores and AE rates in this review, make it reasonable to study the utilised methodology to further understand the discrepancy and improve research on the topic.

Despite the fact that all the included studies measuring PSC utilised a cross-sectional approach, there is great variation in conceptualisation, and whether the use of the tools was statistically validated for their specific use. There were some discrepancies between how authors utilised the PSC tools beyond the original complete tool and the composite scores described in the tools` guidelines. Only 41% the studies used the complete, validated and recommended tools HSOPS and SAQ [16, 72] to capture more dimensions of the PSC measurement. We suggest that these variations may affect the measurement of association with the AE rates in both directions, and thus reduce the validity of the measured association. Additionally, according to the results of included studies assessing the PSC measurement at group level, variations due to included groups of healthcare professionals and specialties can also affect the results. AEs related to surgery make up one of the three most common types of in-hospital AEs [4, 73], which may thus influence the association with PSC. Despite this, some of the included studies conducted in surgical contexts also reported finding no association [34, 35, 40]. Efforts to assess and understand PSC scores’ association with AE rates in a surgical context are relevant for further research. Whether the PSC measurements are utilised at hospital, unit or group level will likely affect the association with AE rates. It is known that PSC varies most between units within the same hospital due to organisational processes and structures [72, 74, 75]. Unit characteristics and work environment factors such as improvements, patient-centred care and quality are predictors of safety climate [76].

Representativeness is important for reliable interpretations. Studies with small samples sizes distributed in a high number of units or hospitals may not be powered to detect an effect of PSC on AEs. In addition, Pronovost and Sexton [72] recommend a response rate above 60% to capture the culture in an organisation rather than opinions. In this review, 62% of the studies report a response rate below 60%, thus this may affect the reliability of the PSC measurement and the association with AE rates. From the studies not demonstrating an inverse association between PSC scores and AE rates, 62.5% reported a response rate below 60% or did not report the response rate. The percentage for studies demonstrating an inverse association between PSC scores and AE rates was 61.5%. The evidence on PSC measurements in this review adds weight to the call for a more uniform, complete and validated approach to measuring and reporting PSC [17], measurements at unit or group level [72, 74], and a response rate above 60% as recommended [72].

Measurements of patient AE rates in the included studies display a great diversity of methodology, including conceptualisations, tools, validation criteria used, types of AEs assessed, and how the rates are used to measure association with the PSC scores. A previous review demonstrates that measured AE rates in the operating room depend on the method used. This review find that direct observations detect higher AEs rates than surveys, incident reports and reviews of patient charts [2]. De Vries et. al [3] demonstrates that a limitation of retrospective chart reviews was that the quality of data collection depends on documentation and interobserver variability [3]. Moreover, GTT and HMPS as manual methods for chart reviews are reported as reliable, however the inter-rater agreement increased when studies used a small group of reviewers [77]. The manual method of using the GTT tool is further developed and an automatic method for detecting triggers that indicate AEs is validated [78]. Reporting bias due to the prospective self-reporting may affect the results and may be affected by the Hawthorne effect [32, 41, 42, 60, 61, 63]. Hence, reporting bias and the Hawthorne effect may influence the retrospective nurse-estimated AE rates. The culture and supportive leadership for reporting and continuously learning from AEs may increase AE rates [79], and thus, if not adjusted for, this method of measuring AE rates may bias the results. Moreover, in 38% of the studies, AE rates were found by utilising administrative registers. Registers might be a useful method due to the opportunity for larger samples and the possibility to extract data at unit level [80]. However, less than half of the registers used in the included studies reported on their validity for the intended use. The available evidence on comprehensive, prospective national-level data on in-hospital AE rates is limited, and there is a lack of reporting on the validation of using the registers for AE data, thus, more transparent reporting is called for regarding studies using registers for AE data collection [4]. More standardised procedures are needed for validated identification, measured and reported AE rates [2, 4, 9].

We found studies that included other process variables in their assessment of the association between PSC and AE. Higher scores of ‘Patient safety competencies’ and ‘Safety training’ were reported to contribute to lower AE rates [42, 43]. Another included study found that reduced AE rates were associated with increased ‘Nurse work environment’ scores, described as enough staff to get the work done and provide quality of care, and the opportunities to discuss patient care and support colleagues [55]. A recent review reports a significant correlation between ‘Staff engagement’ and both PSC scores and AE rates, increased engagement as a cost-effective means of enhancing patient safety, and the health services’ need for a competent and engaged workforce of sufficient number [22]. Sexton et al. [81] have developed SAQ into ‘Safety, Communication, Operational Reliability, and Engagement’ (SCORE), where the main additions are ‘Staff burnout’ and ‘Resilience’. These dimensions are related to patient outcomes and are found to be critical to sustainable quality improvement [81]. Thus, SCORE captures more information related to processual factors and may contribute to providing more insights into the association between PSC and AEs.

We found indications that structural variables may have contributed to the finding that 24% of the studies did not yield reduced AE rates in association with higher PSC scores. One study found that the structural variable ‘Resource intensity’, i.e. resource allocation and patient case weighting, was related to the severity of AEs [49]. Increased ‘Hospital-level nurse-to-patient-ratio’ scores were reported to be significantly correlated with shortened length-of-stay, reduced readmission within 7 days and mortality [82]. Further, single studies reported that increased scores on the HSOPS dimension ‘Staffing’ were statistically significantly correlated with reduced AE rates [37, 48, 51, 60], increased ‘Workload’ was statistically significantly correlated with increased error composite rate and mortality [38, 42, 61], and increased ‘Rationing of nursing level scores’, described as nurses lack of possibility to act as needed, was statistically significantly correlated with reduced rates of specific AEs [34]. The latter study reported that ‘Nurse-to-patient-ratios’ were not significantly correlated with AE rates, and called on hospital units to monitor and balance the ‘Rationing of nursing level’ and education levels according to patients` characteristics [34]. Another included study reported a robust association between PSC scores and the ‘Structure of care delivery’ as ‘Skill mix’, ‘Contract workers’, ‘Patient ratio per licensed staff member’, ‘Turnover’ and ‘Workload intensity’, and between PSC scores and ‘Fall protocol’ as a measure of process [37].

Precautions must be taken regarding appropriate time frames for data collection on PSC and AEs due to other processual and structural variables. PSC measurement before AE measurement may influence the results because of the Hawthorne effect. Organisational processes may change PSC over time, however structural changes in an organisation and disruption due to leadership changes may negatively impact PSC more quickly [83]. Additionally, a time frame over years may be influenced by changes in other processual and structural factors affecting psychological and physical work environment in an organisation, and thus may, be liable to bias the results [76]. Determining the appropriate time frame can be difficult. Hence, precautions must be taken when designing studies on the association between PSC scores and AE rates.There is a need for a broader insight into the context, processual and structural variables, and how these can mediate and strengthen the inverse relationship between PSC scores and AE rates.

Strengths and limitations of this review

Our study has several limitations. Firstly, there is a risk of both selection and publication bias due to the large variety of methodological approaches and operationalisation of the concepts that our search strategy might not fully scope. This also includes that we have not searched grey literature [25]. Secondly, as we searched for the measurements of PSC and AE and the association between these variables, we excluded studies with a qualitative approach. Thirdly, the study protocol was not prospectively published, which implies reduced transparency. Fourth, we searched for single peer-reviewed articles and excluded conference abstracts and dissertations. This may result in the exclusion of relevant evidence. However, studies of dissertations within the inclusion criteria should be captured by the search strategy.

This study has several strengths. Firstly, a comprehensive search strategy was conducted and guided by a senior librarian with expertise in medical literature searches and reviews. The search used broad concepts, proximity operators and several relevant databases. The selected databases were multidisciplinary to identify such studies. Secondly, a blinded screening process ensured eligibility, and a detailed charting form ensured the included studies were mapped and summarised. Thirdly, the PRISMA-ScR checklist was utilised throughout the research process, and, as a result of the findings, we conducted a critical appraisal to answer the aim of this scoping review.

Conclusions

Most of the studies demonstrated that an increased PSC score is statistically associated with reduced AE rates. However, a quarter of the studies contradicted the main findings. The main characteristics of the evidence are that most of the studies are conducted as multicentre studies, in-hospital, in high-income countries, and are measuring the perceptions of nurses and physicians. The evidence on the association indicates a need for more uniform PSC and AE measurements utilising well-defined concepts, complete and validated tools, transparent reporting and data collection within appropriate time frames and study level to provide studies eligible for meta-analysis and synthesis, hence a better understanding of the relationship between PSC and AEs in healthcare. Longitudinal prospective research at group and unit level, especially in the surgical context, combined with qualitative approaches for a broader understanding of the context and the central concepts, may be valuable. Consequently, high-quality quantitative research can provide increased insights into the association and confounding variables and may identify interventions to reduce AEs and inform quality healthcare improvement projects.