This study is the first to compare hospital safety climate between two fundamentally different sets of hospitals: one a nationally integrated hospital network, the other predominantly independent general acute-care hospitals. The study summarizes safety climate in the VA and other U.S. hospitals and factors influencing safety climate in each setting. Results also show how sample characteristics contribute to differences in safety climate between settings.
Overall, we found no difference in safety climate between U.S. and VA hospitals on average, based on descriptive statistics. Differences with respect to specific dimensions were significant, generally favoring U.S. hospitals. However, the range in safety-climate results among U.S. hospitals substantially overlapped, suggesting that neither population has achieved superior safety climate. In addition, relative to high reliability organizations, such as naval aviation, which serve as the “gold standard” for safety achievement despite hazardous and demanding conditions, safety climate in both U.S. and VA settings was considerably worse (Gaba et al. 2003
). This finding does not support our first hypothesis, that participating in a nationally integrated hospital network would be associated with stronger safety climate. It appears that potential advantages associated with the system's intense focus on safety improvement and its ability to implement uniformly its improvement program may have been outweighed by local considerations. While institutional programs may facilitate the ability of local managers to improve safety, they may not be targeted closely enough to the actual challenges of the workplace to make a difference alone.
We also found that characteristics of individuals influenced safety climate consistently across settings when controlling for other factors. Older age and more seniority corresponded to more positive perceptions of safety climate, while working as a nurse or in an HHU were associated with more negative perceptions. These findings are consistent with studies showing perceptions of safety climate differ by workgroup and management level (Pronovost et al. 2003
; Sexton et al. 2006c
; Singer et al. 2008a
). In contrast, facility characteristics influenced safety climate differently in U.S. and VA samples. Working in southern and urban facilities corresponded with higher PPR among VA employees and lower PPR in the U.S. sample. Other studies have found similarly mixed results regarding effects of geographical and structural characteristics within non-VA hospitals (Baldwin et al. 2004
; Coburn et al. 2004
; Loux, Payne, and Knott 2005
; Longo et al. 2007
;). Also consistent with prior studies (Aiken et al. 2002
; Stone et al. 2007
; Weissman et al. 2007
;), we found that higher nurse staffing ratios were associated with lower PPR in U.S. hospitals.
Decomposition analysis examined the influence of (1) variation in the distribution of observed sample characteristics among personnel in an integrated network compared with other U.S. hospitals and (2) differential effects of sample characteristics in each group. The overall difference between the samples, that is, the influence of (1) and (2) together, was a 1.4 percentage point higher PPR for the VA. We hypothesized that variations in sample characteristics between settings would explain more of this difference in safety climate than would differences in effects of those sample characteristics. Our results do not support this hypothesis. Instead, it was the differential effects of sample characteristics that explained more of the difference in safety climate between U.S. and VA hospitals. The difference based on the distribution of all the VA sample characteristics compared with U.S. characteristics was negative, indicating that the VA would be expected to have a 0.77 percentage point lower PPR based on observed sample characteristics alone. The unexplained difference, indicating the differential effect of sample characteristics, was 2.2 percentage points higher PPR in VA than in U.S. hospitals. This second difference was driven primarily by two factors: region and location, both of which act in opposite directions on PPR in the U.S. and VA models, and by unobserved characteristics. Decomposition of the residual suggests that our model explained just 5.9 percent of the variation in the outcome measure. Future research should explore additional characteristics of hospitals and factors driving the effects of region and location in order to determine whether some modifiable factors may be involved that could provide leverage for change.
Our results suggest that characteristics of respondents and their work facilities influence safety-climate scores. Thus, in comparing safety climate among hospitals or over time in hospitals whose respondent characteristics may have changed, it is important to include known characteristics in analyses. Such longitudinal studies would also provide opportunity for research on how the effects of respondent characteristics on PPR change over time.
Results should be interpreted within the context of several limitations. This was a cross-sectional study; thus, we cannot make assertions about causality. We cannot explain the mechanisms underlying effects of various factors on safety climate. Nor can we differentiate the effect on safety climate of observed from unobserved characteristics in the unexplained component of the difference between samples. We cannot rule out nonresponse bias as a factor in our results. The methodology in both settings aimed to maximize response rates while maintaining the voluntary and anonymous nature of the surveys. While the VA sample achieved a response rate that is similar to that of other studies of this type (Asch, Jedrziewski, and Christakis 1997
; Jepson et al. 2005
;), the overall response rate in the U.S. sample was lower. We adjusted for nonresponse and sampling bias through the use of weights in our analysis; however, it is possible that results do not accurately represent the facilities or populations intended. A related issue is the representativeness of the hospitals in each sample. We conducted a stratified random sampling strategy in both settings, but since participation was voluntary, sampled facilities may differ from facilities in their respective populations in unanticipated ways. As noted, administration dates and recruitment and sampling strategies also differed slightly between U.S. and VA samples. Although recruited on the basis of size and region rather than PSI rates, those rates among the U.S. hospital sample did not differ from those of U.S. hospitals overall. In addition, within the U.S. hospital sample we found no difference when we compared overall mean PPR between over-sampled hospitals and the other hospitals in that sample. Finally, while our models included variables associated with safety climate in the literature, we were limited by variables available in our datasets.
Nevertheless, the methodology employed in our study represents an advance over prior research. In particular, the decomposition analysis provides information about systematic differences in sample characteristics and the effects of specific characteristics on safety climate in different settings. By achieving a more thorough understanding of what is driving apparent differences in safety-climate survey results among hospitals we can proceed more clearly toward developing effective improvement interventions.
The results presented suggest that continued efforts are needed to improve safety climate in hospitals. While participation in systems can provide some advantages in this regard, the large unexplained component of safety climate from the regression estimates suggests that other factors, such as hospitals' emphasis on creativity and innovation and their leaders' abilities to motivate, implement, and sustain improvement, may matter more.