Initially 2,057 potential papers were identified by the electronic search. After application of the inclusion/exclusion criteria - 2,010 papers were removed, leaving 47 papers for further abstracts, or full text screening. Finally, five papers were identified for possible inclusion in the review. Two co-authors independently assessed the five, final papers for inclusion, yet, none contained the nurse managers experience of allocation patients to outlier beds. At this stage it was decided to present the results of the review, as an Integrative Review. A summary of the five final papers is presented in Table 2, overall two major themes dominated the content of these papers: (1) patient flow; and, (2) patient safety.
Each of the included five papers addressed inefficiencies in patient flow as the primary purpose of their study. Harrison, et al.,  found that an over-census status invariably resulted in delayed hospital discharge, the largest patient cohort were those being treated by medicine and equally Reid, et al.,  identified that bed blocking as a result of delayed discharge increased with the age of the patient. Hospital occupancy and delayed patient discharges were identified as major causative factors in the availability of inpatient beds and the flow of admitted patients from ED to their inpatient ward placement [13, 14].
The number of patients discharged from hospital wards directly impacted the availability of inpatient beds despite patient load . Disposition of patients from hospital had been identified as a tool to facilitate patient flow. Conversely, excessive delays in patient discharges associated directly with disruptions to patient flow resulting in access block [13-15]. Reid et al.’s  ‘Day of Care’ survey across nine acute care hospitals used criterion-based indicators to identify ongoing acute care which measured illness severity (e.g. continued cardiopulmonary instability) and service intensity (e.g. receiving intravenous medication or continuous vital sign monitoring). Reviewing 3701 inpatient acuity status, they found that on average 23% (n=798) of the major causes in delayed patient discharge were related to in-hospital activities which were associated with waiting for a consultant or allied health review and/or awaiting the outcomes of a procedure/investigation/results (n= 262, 32%) and out-of-hospital delays, those associated with awaiting community hospital availability, home care, or social work assessment (n=228, 28%). Moreover, the authors found that those patients not meeting the criterion for ongoing acute care were more likely to become an outlier which often resulted in a prolonged length of stay, in some cases greater than 14 days .
Three papers took a solutions approach to improving patient flow and promoting access to inpatient beds, which focused on protocols implemented when a hospital is at capacity through the creation of inpatient bed spaces. Implementing a ‘pull’ rather than ‘push’ method to the patient journey, ward beds were created by firstly unblocking inpatient beds to allow for flow rather than ‘pushing’ for patient’s admission process to be hastened with no preparation for their ward disposition. This was achieved with careful discharge planning, morning rounds by physicians facilitating morning discharges, the implementation of a Quick and Sick ward to care for patients requiring higher level assessment and treatment, staffed with specialist physicians to quickly assess and treat patients taking some of the medical admissions load off emergency [15, 16].
Using an algorithmic decision-support system (DSS) that pre-emptively provided options for intra-hospital transfers and decreased reactive bed moves to create bed spaces, was introduced as a tool to support the bed manager. When compared with the previous reactive ‘bed manager decision’ model, the DSS allowed for a more refined approach by actively allowing decisions to relocate patients timelier and in most cases reduced the need for patients to be moved altogether. For example, using the DSS model saw a 59% reduction in in-patients actively being moved, more importantly there was an 89% reduction in last minute in-house transfers. While this study did not directly address the bed mangers experiences of the using the DSS - typically a nurse, who determines the destination ward for admitted patients, - the patient safety and patient flow implications were significant inasmuch that this approach reduced patient presentation time in the ED by one hour which when calculated over the year this was a saving of an additional 3360 patient bed hours .
The ultimate outcome when focussing on patient flow and hospital productivity remains patient safety and improvements in care. The ‘Quick and Sick’ intervention proposed by Gilligan and Walters  aimed at improving patient flow by implementing a weekly outlier physician rota where a designated consultant conducted ‘review’ rounds of medical outliers, to ensure the care of patients had not been compromised. Measuring weekly mortality rates for both current in-patients and recently discharged patients as well as the number of outliers and ED transfers, the authors saw a 34% decrease in the overall length of stay and a 22% decrease in in-patient mortality, all of which coincided with zero outliers. The mortality rate and the time patients waited in the ED for an inpatient bed decreased. Interestingly, this study saw the readmission rate of medical patients increasing by 36% and as a result so did the number of outlier patients.
Although, Thompson, et al., claimed patient care was not considered to have been compromised when the allocation of outlier bed spaces almost doubled. This was accomplished by improved capacity utilisation, increased bed availability and a decrease in ambulances being diverted to other hospitals. However, the authors do contend that as the number of available beds became smaller the waiting times increase exponentially. Thompson, et al.,  mentions there was no statistically significant change in patient “fall rates, medication errors, hospital-acquired infections rates, restraint usage, length of stay and patient satisfaction surveys” (Thompson, 2009. pp272). However, they did not measure patient mortality or morbidity in the outlying patients, nor the satisfaction of the staff caring for increasing numbers of patients not within their specialty.