This study showed an increase in the risk of hospital mortality for patients admitted during off hours compared with patients admitted during office hours (RR 1.059), and an increase of hospital mortality risk for patients admitted during the weekend compared with patients admitted during the week (RR 1.103).
Several analyses that describe the difference in mortality between patients admitted during office hours and those admitted to the ICU during off hours have been published [5
]. Unfortunately, all of these studies defined office hours differently. We defined working hours as those hours when a qualified intensivist was available for direct patient care. For most ICUs in The Netherlands this is from 08:00 to 22:00 hours. This definition is in accordance with another recent Dutch publication [10
]. However, our results contradict some of these more recent publications on this subject. For example, Meynaar et al. [10
] analysed the difference in mortality of 6,725 patients admitted during office hours and outside office hours. They could not detect a difference in mortality after correction for case mix and illness severity. As their sample size of only 6,725 patients was much smaller than our research sample, we used 300 random sub-samples from our research dataset to replicate their sample size. We found a statistically significant difference in only 49 of 300 samples (15%). Although the sub-samples are overlapping, this suggests that their sample size might have been too small to detect these differences in mortality. However, they analysed only three ICUs located in teaching hospitals, which are possibly much more homogenous in performance over time compared with our mixed set of 70 participating ICUs.
On the other hand, our results also contradict the largest analysis thus far [6
]. In a UK database of 56,250 ICU patients, Wunsch et al. found increased mortality for the weekends (Friday–Sunday) and during the evening and night. However, after correction for case mix, this difference disappeared. They concluded that there was no difference in outcome between office hours and off hours. However, they defined office hours differently, choosing three shifts (08:00–18:00, 18:00–24:00 and 24:00–08:00 hours) that best reflect ICU care in the UK. An analysis on 300 random sub-samples from our dataset sample with their sample size (n
= 56,250) showed a significant difference in mortality between office hours and off hours in 256 of the 300 samples. Although the sub-samples are overlapping, this suggests that the difference in conclusion is not likely based upon limited power in the study by Wunsch et al. We corrected in a similar way for potential confounders, and therefore our analyses are comparable. This suggests that the increased mortality in our study might be based on differences in staffing or logistics between the UK and The Netherlands.
Of course, ICU performance is influenced by an intricate interplay of various factors. Besides the ICU organisation during off hours there is intensive interaction with other medical disciplines, and changes in their quality of care during off hours might influence ICU outcome as well, which is not reflected by illness severity at admission. Such unknown confounders might be stronger in smaller hospitals, which often have less staff to fill the roster and/or have less sophisticated diagnostics than larger hospitals. Furthermore, the performance of health care workers (physicians and nurses) varies during the day. Although speculative, the detrimental effect of the circadian biorhythm on human performance during the night shift and especially at the end of the night shift is a known factor [24
]. We also found the highest (predicted and observed) mortality at the end of the night shift (05:00–06:00 hours), when both health care workers and patients perform at their worst.
This study has several limitations. Although the data were collected in prospective fashion during the first 24 h of admission to the ICU and the outcome (discharged alive or dead) was not influenced by subjective assessment, this remains a retrospective analysis. Therefore, true cause-and-effect relationships cannot be ascertained, and unmeasured confounders still might play a role. For example, differences of care beyond the ICU might be confounders in the association between admission timing and mortality. However, all surviving patients are discharged to the same wards, and it is reasonable to assume that they all experience the same quality of care on the wards.
Although APACHE II was used to correct for illness severity and patients were matched based upon a propensity score (age, gender, APACHE score, admission type, reason for admission), this still does not fully exclude the influence of case-mix differences. Surgical patients admitted in the middle of the night are different from patients admitted during office hours. For example, does waiting for emergency surgery during off hours result in higher acute physiology score and subsequently to higher APACHE II score (so-called lead-time bias)? Other, possibly very important, confounders might be differences in organisational aspects. Unfortunately, the data in this study could not be corrected for these organisational aspects, and we assumed office hours to be 08:00–22:00. Figure shows that there is an increase in the difference between observed and predicted mortality from 16:00 hours onwards. The effect of off hours on mortality would have been stronger if off hours had been defined as, say, 20:00–08:00 hours. As of 2008, all ICUs have collected data on quality parameters, such as nurse-to-patient ratio, physician-to-patient ratio, availability of ICU beds, etc. Such information might explain the differences between ICUs and explain why some ICUs apparently have equal performance during the entire day while others perform worse during off hours.
However, a strong feature of this analysis is its size and its power to detect these differences. This is one of the largest analyses of admission timing and survival. Additionally, this analysis is performed in a large sample of the Dutch ICUs (up to 80% of the Dutch ICUs in 2008), and therefore these results can be extrapolated to represent the level of critical care in The Netherlands. Previous studies were often performed in a smaller subset of ICUs and might represent the better-performing ICUs. Such decreased external validity might explain a lack of difference between office hours and off hours in these studies.
We conclude that admission timing is associated with differences in outcome, even when mortality is corrected for illness severity by means of recalibrated APACHE II score. Patients admitted during the night (22:00–08:00 hours) or weekend days have a decreased chance of survival in comparison with patients admitted during office hours. However, the cause of this association needs further analysis that corrects for more potential confounders. This investigation has been started in The Netherlands with the registration of various quality-of-care variables.