Table 4.
Relationship of Patient Safety Indicators (PSIs) to Safety Climate by Type of Personnel
|
Senior Managers |
Frontline Workers |
|||||||
|---|---|---|---|---|---|---|---|---|
| 12-PSI Composite | 12-PSI Composite | |||||||
| Safety climate overall | 1.010 | 1.029** | ||||||
| (0.018) | (0.014) | |||||||
| Senior manager engagement | 0.995 | 0.985 | ||||||
| (0.014) | (0.013) | |||||||
| Organizational resources | 1.005 | 1.005 | ||||||
| (0.005) | (0.008) | |||||||
| Overall safety emphasis | 1.005 | 1.029* | ||||||
| (0.014) | (0.015) | |||||||
| Unit norms | 1.024 | 1.002 | ||||||
| (0.018) | (0.018) | |||||||
| Unit recognition and support | 0.988* | 1.000 | ||||||
| (0.006) | (0.009) | |||||||
| Fear of shame | 1.017 | 1.048** | ||||||
| (0.013) | (0.021) | |||||||
| Fear of blame | 1.003 | 1.007 | ||||||
| (0.006) | (0.005) | |||||||
| Hospital size (number beds) | 1.001** | 1.001** | 1.001** | 1.001** | 1.001** | 1.001** | ||
| (0.001) | (0.001) | (0.001) | (0.001) | (0.001) | (0.001) | |||
| Number of beds squared | 1.000*** | 1.000** | 1.000*** | 1.000*** | 1.000*** | 1.000*** | ||
| (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |||
| Constant | 0.00409*** | 0.00320*** | 0.00471*** | 0.00384*** | 0.00349*** | 0.00388*** | 0.00469*** | 0.00299*** |
| (0.001) | (0.000) | (0.001) | (0.001) | (0.001) | (0.001) | (0.001) | (0.001) | |
| Observations | 91 | 91 | 91 | 91 | 91 | 91 | 91 | 91 |
| Log pseudolikelihood | −378.7 | −377.7 | −376.8 | −378.1 | −379.1 | −376.5 | −379 | −374.6 |
| Wald's χ2 (df) | 44.2 | 44.66 | 64.88 | 37.98 | 34.79 | 49.78 | 35.71 | 59.37 |
| Prob >χ2 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| Pseudo-R2 | 0.0284 | 0.031 | 0.0331 | 0.0299 | 0.0273 | 0.0341 | 0.0275 | 0.0388 |
Robust standard errors in parentheses.
Dependent variable: risk-adjusted number of PSIs per year.
Independent variables: % responses indicating weak safety climate.
Results derived from negative binomial regressions, which adjust for the PSI population denominator. Models also apply backward stepwise regression, including the following control variables where significant: number of hospital beds and its square, a variable indicating whether the hospital belonged to the Council of Teaching Hospitals, was affiliated with a medical school, or neither; a variable indicating whether the tax status of the hospital was for-profit, nonprofit, or government-owned; a variable indicating the census region in which the hospital is located; a binary variable indicating whether the hospital was located in an urban center or not; and the hospital's ratio of average registered nursing hours per average number of patients per day.
p<0.01.
p<0.05.
p<0.1.