Improving Patient Flow: Analysis of an Initiative to Improve Early Discharge
BACKGROUND: Discharge delays adversely affect hospital bed availability and thus patient flow.
OBJECTIVE: We aimed to increase the percentage of early discharges (EDCs; before 11 am). We hypothesized that obtaining at least 25% EDCs would decrease emergency department (ED) and postanesthesia care unit (PACU) hospital bed wait times.
DESIGN: This study used a pre/postintervention retrospective analysis.
SETTING: All acute care units in a quaternary care academic children’s hospital were included in this study.
PATIENTS: The patient sample included all discharges from the acute care units and all hospital admissions from the ED and PACU from January 1, 2014, to December 31, 2016.
INTERVENTION: A multidisciplinary team identified EDC barriers, including poor identification of EDC candidates, accountability issues, and lack of team incentives. A total of three successive interventions were implemented using Plan–Do-Check-Act (PDCA) cycles over 10 months between 2015 and 2016 addressing these barriers. Interventions included EDC identification and communication, early rounding on EDCs, and modest incentives.
MEASUREMENTS: Calendar month EDC percentage, ED (from time bed requested to the time patient left ED) and PACU (from time patient ready to leave to time patient left PACU) wait times were measured.
RESULTS: EDCs increased from an average 8.8% before the start of interventions (May 2015) to 15.8% after interventions (February 2016). Using an interrupted time series, both the jump and the slope increase were significant (3.9%, P = .02 and 0.48%, P < .01, respectively). Wait times decreased from a median of 221 to 133 minutes (P < .001) for ED and from 56 to 36 minutes per patient (P = .002) for PACU.
CONCLUSION: A multimodal intervention was associated with more EDCs and decreased PACU and ED bed wait times.
© 2019 Society of Hospital Medicine
It is difficult to compare our EDC improvements to those of previous studies, as we are unaware of published data on pediatric EDC efforts across an entire hospital. In addition, studies have reported discharges prior to different times in the day (noon, 1
As providers of all types were aware of the constant push for beds due to canceled surgeries, delayed admissions and intensive care transfers, and the inability to accept admission, it is difficult to compare the subgroups directly. Furthermore, although physician teams and units are distinct, individuals (nurses, case managers, trainees) may rotate through different units and teams and we cannot account for individual influences on EDCs depending on exposure to interventions over time. Although all groups improved, the improvement in slope in group 4 (exposed to interventions 1 and 3) was the only significant change. As group 4 contained a large number of surgical patients who often have more predictable hospital stays, perhaps this group was more responsive to the interventions.
Our EDC improvements were associated with a decrease in ED and PACU bed wait times. Importantly, we did not address potential confounding factors impacting these times such as total hospital admission volumes, ED and PACU patient complexity, and distribution of ED and PACU admission requests throughout the day. Modeling has suggested that EDCs could also improve ED flow,7 but studies implementing EDC have not necessarily assessed this outcome.10-15 One study retrospectively evaluated ED boarding times in the context of an EDC improvement effort and found a decrease in boarding times.21 This decrease is important as ED boarders may be at a higher risk for adverse events, a longer LOS, and more readmissions.3,7 Less is known about prolonged PACU wait times; however, studies have reported delays in receiving patients from the operating room (OR), which could presumably impact timeliness of other scheduled procedures and patient satisfaction.22-24 It is worth noting that OR holds as a result of PACU backups happened more frequently at our institution before our EDC work.
Our limitations include that individual providers in the various groups were not completely blind to the interventions and groups often comprised distinct patient populations. Second, LPCHS has a high CMI and LOS relative to most other children’s hospitals, complicating comparison with patient populations at other children’s hospitals. In addition, our work was done at this single institution. However, since a higher CMI was associated with a lower probability of EDC, hospitals with a lower CMI may have a greater opportunity for EDC improvements. Third, hospital systems are more impacted by low EDCs when operating at high occupancy (as we were at LPCHS); thus, improvements in ED and PACU wait times for inpatient beds might not be noted for hospitals operating with a >10% inventory of beds.25 Importantly, our hospital had multiple daily management structures in place, which we harnessed for our interventions, and better patient flow was a key hospital initiative garnering improvement of resources. Hospitals without these resources may have more difficulty implementing similar interventions. Finally, other work to improve patient flow was concurrently implemented, including matching numbers of scheduled OR admissions with anticipated capacity, which probably also contributed to the decrease in ED and PACU wait times.