To our knowledge, this is the first study to measure implicit rationing of nursing care and to explore associations between this factor and the selected patient outcomes. The related analyses provided estimates of the effect of implicit rationing of nursing care after controlling for patient, nurse, and hospital-related covariates, as well as for the clustering of observations within hospital units. Variations in nurse reports of rationing at the unit level were the only factor significantly related with all six patient outcomes studied. While the frequency of rationing appeared relatively low overall, increases in the unit-level scores were associated with large decreases in patients' likelihood of being satisfied with care, and substantial increases in the odds of nurses reporting that selected adverse patient outcomes had occurred with regularity over the preceding year.
While prior research suggests that lower nurse staffing ratios are related to worse patient outcomes [11
], in this study patient-to-nurse staffing ratios failed to predict nurse reports of any of the outcomes studied. As our conceptual model and the empirical evidence show, workload is influenced by a range of factors, including the amount and type of nursing resources needed to care for each patient, as well as patient case mix and complexity [26
]. As such, the patient-to-nurse staffing ratio reflects only one aspect of nurses' workloads and may not have been sufficiently refined to show a relationship with the patient outcomes studied here. Placing this study's mean unit-level ratio of eight patients per nurse into context, it is similar to those of 7–14 patients per nurse described in acute care hospitals in the United Kingdom [14
], but higher than the average ratio of five patients per registered nurse described in US hospitals [27
]. However, it should be borne in mind that patients in Swiss hospitals, particularly in the regional and cantonal hospitals, generally tend to be less acutely ill than those in some other countries (notably the US).
Higher nurse ratings of nursing resources and autonomy (as measured using the Resources subscale) were a consistent predictor of five of the six outcomes in unadjusted models, but did not remain statistically significant in models controlling for rationing and the other organizational variables. It was somewhat logical that the measure of interdisciplinary collaboration and competence (Collaboration subscale) would be associated with reports of avoidable critical patient incidents, but a significant relationship was only detected before controlling for other organizational variables. Such results are in line with prior research, which suggests that higher-quality practice environments in hospitals are associated with superior outcomes [15
]. However, the majority of studies in this area identify significant associations use nurse job outcomes or nurses' appraisals of care quality in general. Data has been much less clear in terms of showing work environments' effects on specific patient outcomes. For instance, McCusker et al.
] also failed to find an association between practice environment features and the nurse-reported frequencies of various types of adverse patient events.
In summary, the results of this study suggest that rationing of nursing care, a process that occurs at the nurse–patient interface, is a strong independent predictor of patient outcomes, and may partially explain the effects of patient–to-nurse staffing ratios and nurse work environment factors on patients. Even low rationing levels were linked with deteriorating patient outcomes. Since rationing can never entirely be avoided, it is important to define the threshold above which rationing affects outcomes negatively. Such data would enable nursing administrators to use implicit rationing of nursing care (e.g., through surveys employing the BERNCA instrument) as an indicator of the impact of cost-cutting strategies and changes in the nurse practice environment on processes of care in their facilities (particularly changes in staffing levels, skill mix and other resources). Regular surveys of this (and perhaps other measures of rationing on the front lines of care) could provide data for health policy discussions about nurse staffing levels and decisions regarding mandated minimum patient-to-nurse ratios.