A Quality Improvement Project to Increase Discharges before Noon at a Pediatric Hospital

Abstract

Introduction:

Delays in patient discharges lead to inefficient hospital throughput and reduced access to care. The aim of this quality improvement (QI) project was to increase the percentage of discharge orders placed before noon (DOBN) by the pediatric hospital medicine (PHM) service from 27% to 32% between January 1, 2021, and December 31, 2022.

Methods:

We convened a multidisciplinary team of hospitalists, residents, nurses, and bed management staff and surveyed key stakeholders to identify the most important barriers. Key interventions included the implementation of a multidisciplinary huddle, earlier preparation of the electronic health record for discharges, and prioritizing rounding on discharge-ready patients. The outcome measure was the monthly percentage of DOBN. Balancing measures were 7-day readmission rates and average length of stay (LOS). The primary measure was analyzed using a statistical process control chart (p-chart), and the balancing measures were analyzed using run charts.

Results:

The baseline rate of DOBN on the PHM service was 27%. After interventions, this increased to 32%. The LOS was 2.5 days, and the average 7-day readmission rate was 2.4%. Run chart analysis showed no special cause variation in the balancing measures. These results were sustained for 16 months without increasing LOS or 7-day readmission rates.

Conclusions:

The QI team successfully increased the DOBN rate for a PHM service by applying QI methods and adopting a multidisciplinary approach to discharge planning and preparation.

INTRODUCTION

Delays in hospital discharges disrupt patient flow, leading to delayed care, increased adverse events, and lower patient satisfaction.^1–3 Impaired patient flow through the hospital also reduces access to care and negatively impacts hospital revenue.^4,5 Conversely, efficient hospital discharges reduce boarding times for emergency department (ED) patients awaiting admission.^6,7 Timely transfer of patients from EDs to acute care units is critical to ensuring patients receive appropriate care.^1–3 Mangum et al found that one-third of adverse patient events in their children’s hospital occurred during peak discharge hours, which also overlapped with the peak time for new admissions to arrive from the ED.⁸

The importance of efficient patient throughput is increasing in pediatric hospitals. The number of children seeking care in EDs is rising in the United States,^9,10 whereas the number of pediatric inpatient beds is decreasing.¹¹ This fact has resulted in pediatric inpatient care becoming increasingly concentrated in urban teaching and free-standing children’s hospitals.¹¹ As inpatient pediatric capacity becomes concentrated within fewer hospitals, efficient patient throughput is increasingly important to maintaining timely access to medical care for children. A study examining the impact of hospital occupancy on ED length of stay (LOS) at a pediatric hospital found that for every 5% increase in hospital occupancy above 80%, ED LOS increased by 34.3 minutes.¹² Because hospital occupancy and ED boarding are closely linked, interventions that support earlier inpatient discharges may help decrease crowding and improve patient flow.^6,13 Consistent with this concept, Stansbury et al demonstrated that increasing their discharges before noon by 6% increased bed availability by 16%.¹⁴

At our institution, a tertiary care, free-standing children’s hospital, there were recurrent difficulties with limited bed availability on the acute care units, particularly during the winter. Capacity constraints were most pronounced in the late morning and early afternoon when ED admissions and transfers from other units coincided with delays in morning discharges from the acute care units. By increasing morning discharges from the acute care units, we hoped to increase bed availability for the influx of admissions and transfers that occurred in the afternoons and evenings. This quality improvement project aimed to increase the rate of discharge orders placed before noon (DOBN) on the pediatric hospital medicine (PHM) service from 27% to 32% between January 1, 2021, and December 31, 2022.

METHODS

Context

We conducted this project at the primary campus of a free-standing academic children’s hospital with 287 licensed beds. The PHM service is the largest admitting service with approximately 5,000 admissions per year. When this project began, each PHM team cared for patients across 4 acute care units. Four teams were resident teams, and one was an advanced practice provider (APP) team. The resident teams consisted of 2 attendings, 2 senior residents, and 2–4 interns. The APP team included 2–3 APPs and an attending physician. The care teams also included a clinical coordinator who functioned as a charge nurse, bedside nurses, a case manager, and a social worker. Morning rounds began at 8:30 am and were completed by 11:00 am for patients on the APP team and on 3 of the 4 resident teams. Rounds started at 10:15 am and ended by 12:00 pm on the fourth resident team.

Residents or APPs typically placed orders. Our hospital uses computerized order entry through the electronic health record (EHR) system, Epic (Epic Systems, Verona, Wis.). We chose the time of discharge order entry as the outcome measure because it was the outcome within the team’s control. Impact on the timing of patients physically leaving their hospital rooms would have required a larger hospital-wide initiative that was outside the scope of this project.

We convened a QI (quality improvement) team of pediatric residents, hospitalists, bed management nurses, case managers, and clinical coordinators in January 2021. We selected the Model for Improvement as the project methodology.¹⁵ A working subgroup of pediatric residents and hospitalists met monthly to review data and plan interventions.

Before starting the project, it was necessary to obtain buy-in from key stakeholders and frontline staff. The QI team met with nursing leadership, hospitalists, and residents to introduce the project. To increase hospitalist buy-in, the primary outcome of this project was identified as a metric for the physician incentive plan (PIP). PIP is a value-withholding program at our institution that provides payments to attending physicians and advanced practice providers for meeting specific QI thresholds. The value-withholding threshold was aligned with the project’s aim of increasing DOBN by 5%. The PIP for this project started January 1, 2021.

To obtain buy-in from bedside nursing, the huddle and early discharge process were discussed with nurses at unit staff meetings and daily shift huddles. Nurses were invited to participate in intervention design actively and were updated on the project’s successes. A clinical nurse specialist also rounded on the acute care units to increase awareness and answer questions about the project.

The QI team created a 13-question voluntary survey and distributed it to acute care nurses, case managers, social workers, pediatric residents, and hospitalists. (See Supplemental Digital Content 1, which describes the survey of key stakeholders on perceived barriers to improving discharge efficiency, https://links.lww.com/PQ9/A796.) The QI team distributed the survey from January to February of 2021, achieving a response rate of 59% (98/166). Respondents completed the survey once online. They were asked to identify perceived barriers to discharge before noon and rank them by relative importance on a scale of 1 (most important) to 5 (least important). Respondents identified discharge orders not being prepared in advance as the top reason for delays, followed by care coordination with other subspecialties, case management issues, and social work issues (Fig. 1).

Fig. 1.

Pareto chart of key stakeholders’ perceived barriers to placing discharge orders before noon identified through a stakeholder survey (January–February 2021).

The QI team identified areas of focus based on the survey results and created a key driver diagram (Fig. 2). Throughout the project, the team held regular meetings with nursing staff, pediatric residents, and PHM providers to gather ongoing feedback and build buy-in for interventions.

Fig. 2.

Key driver diagram for the discharge before noon QI project.

Interventions

The QI team introduced interventions sequentially but maintained them cumulatively unless noted in the descriptions later. This approach allowed the project to function as a layered system redesign with multiple interventions operating concurrently rather than in isolation. Table 1 organizes interventions by starting date and provides additional details about the interventions labeled in Figure 3. We reviewed data for the primary outcome measure monthly. The QI team discussed the impact and feasibility of each intervention to decide whether to continue, modify, or abandon it. Each intervention underwent multiple small adjustments to optimize uptake. These minor adjustments were considered part of the intervention and were not evaluated individually for impact.

Table 1.

Interventions by Date for the Discharge Before Noon QI Project

Interventions (Start Date)	Intervention Descriptions	Outcome
Intervention 1 (April 2021)	Creating a multidisciplinary huddle • Started afternoon multidisciplinary huddle on 1 acute care unit on April 2021 • Huddle spread to 2 additional acute care units on June 2021	Improvement in communication between nursing, case management, and providers around potential discharges and discharge barriers
Intervention 2 (September 2021)	Optimizing rounding workflow • Earlier rounding on patients ready for discharge	Associated with an increase in discharge orders placed in the morning
Intervention 3 (September 2021)	Earlier preparation of the EHR and placement of orders for discharge • Preparation of medication reconciliation, discharge orders, instructions, and prescriptions in advance • Prioritizing signing discharge orders on rounds when possible	Associated with an increase in discharge orders placed in the morning
Intervention 4 (October 2021)	Resident assistants rounding with families • RAs round on patients in advance of discharge regarding need for school/work notes and transportation assistance	Streamlined discharge process
Intervention 5 (January 2022)	Changes to Resident Team Structure • yellow team rounding time changed from mid-morning to 8:30 am	Earlier rounding start time supported earlier discharge times
Intervention 6 (March 2022)	Meal vouchers • Meal vouchers provided for families to receive lunch in the cafeteria	No significant impact

EHR, electronic health record; RA, resident assistants; PHM, pediatric hospital medicine.

Fig. 3.

Percentage of discharge orders placed before noon for patients on the PHM service.

Intervention 1: Creating a Multidisciplinary Huddle

Survey respondents identified poor communication between providers and nursing as a primary barrier to increasing morning discharges. The QI team implemented multidisciplinary huddles to discuss goals of care, case management needs, anticipated discharge dates, and barriers to discharge. PHM providers, case managers, clinical coordinators, and social workers attended the huddles. They occurred after morning rounds so the medical team could provide updates based on discharge planning needs identified during rounds. Midday huddles also allowed for maximum team member attendance and provided case managers with adequate time to address case management needs for patients who would be ready for discharge the following day.

The QI team created work instructions to standardize huddle discussions. We piloted huddles on 1 acute care unit in April 2021 and expanded the huddles to two additional units in June 2021. The fourth acute care unit, which primarily functions as an inpatient rehabilitation unit, has only a few PHM patients each day and has not adopted the huddle.

Intervention 2: Optimizing Rounding Workflow

Before this project, PHM teams typically rounded in the morning by room numbers rather than prioritizing patients ready for discharge. For the second intervention, the PHM teams prioritized rounding earlier on patients who were ready for discharge. This increased the number of discharge-ready patients discharged in the morning.

Interventions 3: Earlier Preparation of the EHR and Placement of Orders for Discharge

Another barrier identified by the survey was that discharge documents were not prepared in the EHR before rounds. This barrier resulted in patients not being discharged during morning rounds. Intervention 3 consisted of 2 complementary workflow modifications implemented simultaneously. The first was the preparation of medication reconciliation, discharge orders, discharge instructions, and prescriptions before the anticipated day of discharge. The second was the prioritization of signing discharge orders during rounds. Because these changes were introduced concurrently and were intended to function together, they were analyzed as a single intervention. The QI team selected these interventions because they could be implemented quickly by the clinical teams without requiring modifications to the EHR. They also addressed a knowledge deficit among pediatric residents regarding how to prepare the EHR for discharge in advance.

To implement these interventions, the senior residents involved in the project provided education to all residents on how to start discharge preparation in the EHR early in the hospitalization. They hung checklists in the residents’ and APPs’ workrooms, listing items that could be prepared in advance in the EHR. (See Supplemental Digital Content 2, which describes EHR discharge preparation checklist, https://links.lww.com/PQ9/A797). Pediatric residents also received emails at the beginning of each inpatient rotation with instructions on how to prepare the EHR in advance. The QI team and PHM attendings also established the expectation that discharge orders be placed during morning rounds whenever patients were ready for discharge, and the residents adjusted their workflow to accomplish this.

The residents also piloted the practice of communicating anticipated next-day discharges to the night team during sign-out. Their sign-out included EHR items to be prepared overnight for these patients. This intervention was difficult to sustain, however, due to the high volume of admissions at night, and was therefore abandoned.

Intervention 4: Resident Assistants Rounding with Families

Resident assistants (RAs) joined resident teams in August 2021. Resident assistants are nonclinical staff who assist residents with administrative tasks. Although their integration was not a planned project intervention, the teams leveraged their support to complete tasks that helped streamline the discharge process. The RAs rounded every weekday afternoon, meeting with families to identify discharge needs such as notes for work and school and assistance with transportation home. They also scheduled follow-up appointments and confirmed preferred pharmacies.

Intervention 5: Changes to Resident Team Structure

After implementing changes to the rounding workflow, the percentage of DOBN improved in four out of five teams. The resident team that started their rounds at 10:15 am had persistently lower DOBN rates. To address this, the QI team adjusted the start time of rounds for this team to 8:30 am.

Intervention 6: Meal Vouchers

Another potential barrier identified by nursing staff was families wanting their child to eat the meal they had ordered from food services before being discharged. To mitigate this barrier, the team introduced meal vouchers for families, allowing them to receive a meal in the cafeteria rather than in their rooms.

Measures

Our primary outcome was the proportion of DOBN receiving PHM services. We defined this measure as the number of discharge orders placed in the EHR before 12:00 pm. The numerator was the number of PHM patients with discharge orders placed before 12:00 pm each month, and the denominator was the total number of discharges from the PHM service each month. The QI team collected baseline data from July 2020 to March 2021, intervention data from April 2021 to July 2022, and maintenance data from August 2022 to December 2022.

Balancing measures were LOS and 7-day readmission rates. We monitored LOS throughout the project to ensure efforts to improve discharge efficiency were not associated with unintended changes in overall hospitalization duration. We calculated LOS as total patient days divided by total discharges each month for the PHM service. We defined the 7-day readmission rate as the proportion of patients discharged from the PHM service who experienced an unplanned readmission within 7 days of discharge. The QI team extracted data from the EHR.

Data Analysis

We analyzed the primary outcome measure, the percentage of patients with DOBN, using a statistical process control chart (p-chart) and applied standard control chart rules to determine special cause variation (SCV). A run of ≥8 points in a row above or below the centerline was considered a shift.¹⁶ We analyzed the balancing measures—7-day readmission rates and LOS—using run charts. The QI team assessed SCV using standard run chart rules for 6 or more consecutive points above or below the median line.¹⁶ Statistical process control charts were created using Microsoft Excel (Microsoft Corporation, Redmond, Wash.) and a p-chart template maintained by the Akron Children’s Hospital Quality Services department and adapted from statistical process control chart templates developed by the James M. Anderson Center for Health Systems Excellence at Cincinnati Children’s Hospital Medical Center.

Ethical Considerations

The hospital’s institutional review board reviewed the project and determined it was not classified as human subject research.

RESULTS

During the project, the DOBN rate increased from 27% to 32% across all patients on the PHM service. Two data points exceeded the upper control limit in May and June, indicating SCV; however, this change was not sustained. The statistical process control chart did demonstrate SCV in August 2021 (Fig. 3). It was sustained across all PHM teams through the end of December 2022. The centerline shift occurred after our first 3 interventions were implemented. We did not see any improvement in the DOBN rate with the last intervention, which offered meal vouchers. Our balancing measures, LOS and 7-day readmission rates, were 2.5 days and 2.4%, respectively, and showed no significant changes throughout the project (Figs. 4 and 5).

Fig. 4.

Run chart for average length of stay for patients admitted to the phm service.

Fig. 5.

Run chart for the 7-day readmission rate for patients admitted to the PHM service.

DISCUSSION

The team successfully increased DOBN from a baseline of 27% to 32% in 4 months. Although the absolute increase was modest, we sustained it for 16 months without increasing LOS or 7-day readmission rates. Baseline discharge before noon rates in pediatric hospitals typically range from 7% to 25%, with many institutions targeting goals of 25%–30% as rates above this range are difficult to achieve and sustain without hospital-wide operational interventions.^14,17–20 Achieving a 32% rate of DOBN aligned with our goal to make a sustainable redesign of our discharge process.

We achieved and sustained a significant improvement in our DOBN rate after we introduced multidisciplinary huddles, optimized our rounding workflow, increased the earlier completion of discharge orders and the earlier preparation of the EHR for discharge, and changed the start time of rounds to 8:30 am for all resident teams. We chose these interventions based on feedback we received from our structured survey of frontline staff (Supplemental Digital Content 1, https://links.lww.com/PQ9/A796). The survey asked participants to identify perceived barriers to timely discharge and rank their relative importance. It enabled us to receive input from a broad group of stakeholders involved in the discharge process, including nurses, case managers, social workers, residents, APPs, and attending physicians. This approach allowed input from multiple disciplines and helped prioritize interventions based on the perspectives of those directly involved in the discharge process.

The centerline shift occurred after the introduction of the first 3 interventions: implementation of multidisciplinary afternoon huddles, optimization of rounding workflow, and earlier preparation of the EHR for discharge along with earlier completion of discharge orders. Because these interventions were implemented in close succession and were designed to function together, it is not possible to determine the independent effect of any single intervention. We believe the improvement was attributable to the synergistic effect of these workflow changes, which together improved the identification of discharge-ready patients, prioritized their evaluation during rounds, and facilitated earlier completion of their discharge orders.

We observed a SCV in May and June of 2021 that was not sustained (Fig. 3). The percentage of DOBN exceeded the upper control limit in both months but did not persist after June 2021. Given that this occurred within 2 months of starting the first intervention, it likely resulted from increased attention to a new QI project and participants’ awareness that their actions were being observed. The Hawthorne effect, described as “changes in behavior due to a subject’s awareness of being observed,” has been previously described in the healthcare literature.²¹ There are also studies in the healthcare literature that demonstrate the Hawthorne effect may wane “with continued observation past peak performance”²² which may explain why the improvements seen in May and June of 2021 were not sustained.

The use of RAs to complete nonclinical discharge tasks suggests they can also support interventions to increase discharge efficiency by reducing residents’ workloads. Although the data did not demonstrate a direct association between the introduction of RAs’ afternoon rounds and an increase in DOBN, the utilization of RAs to complete administrative discharge tasks may have supported discharge workflows and reduced resident workload. We did not observe an increase in the percentage of DOBN with the provision of meal vouchers, suggesting that the primary constraint in our system was order timing rather than family preferences.

We acknowledge that education is typically considered a lower-reliability QI intervention, particularly in academic hospital settings with frequent trainee turnover. However, we believe the sustained improvement in DOBN occurred due to a combination of interventions rather than the educational intervention alone. Specifically, the introduction of multidisciplinary huddles (Intervention 1) and optimizing rounding workflow (Intervention 2) created the expectation that discharge preparation was a routine part of the daily workflow. The educational intervention (Intervention 3) was reinforced with multiple sustainability mechanisms: (1) recurring educational emails sent to residents at the start of each inpatient rotation, (2) physical checklists posted in resident and APP workrooms, and (3) explicit attending expectations communicated during morning rounds. These reinforcement strategies may have mitigated the typical limitations of education-based interventions in high trainee turnover settings. Additionally, engaging senior residents from the QI team to teach their peers created a peer-to-peer educational model that supported widespread adoption and normalization of the new workflow.

Other discharge efficiency projects have focused on assessing medical readiness for discharge to improve timeliness. This has often been accomplished by creating standardized discharge criteria for common diagnoses.^23–25 These standardized discharge criteria are then integrated into teams’ workflows using EHR tools such as admission order sets and note templates.^23–25 These tools have been shown to improve discharge efficiency by supporting earlier recognition of patients’ medical readiness for discharge. The drawback of these tools is that they must be built into an EHR, which takes time and support from a clinical informatics team. This study adds to the QI literature by demonstrating that training providers to improve their EHR workflows, combined with workflow redesign and reinforcement strategies, may improve discharge efficiency. This allows it to complement interventions that support earlier recognition of medical readiness for discharge but require clinical informatics support to implement.

LIMITATIONS

This project has several limitations. First, this project was conducted at a single-site academic tertiary care children’s hospital with case managers and RAs. This may limit the generalizability of the findings to other institutions with different resources and processes. Second, the discharge time was based on when a discharge order was entered into the EHR, which may not reflect when the patient was physically discharged. Additionally, we did not directly measure improvements in patient throughput, such as increased midday bed availability or reduced acute care unit capacity constraints, which limited our ability to assess the project’s impact on operational flow. Third, although this project aimed to increase DOBN, the ideal discharge time would be when the patient is medically ready for discharge rather than adhering to a fixed time of day. Fourth, we used 7-day readmission rates and LOS as our balancing measures; however, LOS is influenced by multiple factors beyond discharge processes and may not fully capture all unintended consequences of increasing DOBN. We did not collect data on staff or patient satisfaction. Future studies should assess whether improving discharge efficiency is associated with improved patient and/or staff satisfaction. We also did not assess patient complexity over the study period. Changes in patient complexity during the study period may have influenced LOS and 7-day readmission rates, limiting the interpretation of these balancing measures.

CONCLUSIONS

Incorporating a multidisciplinary approach to discharge preparation and emphasizing early discharge documentation in the EHR increased the DOBN rate on our PHM service. Engaging frontline stakeholders and focusing on interventions they identified as barriers to early discharge has contributed to the long-term sustainability of these changes. Multidisciplinary midday huddles, prioritizing discharge-ready patients during morning rounds, and early EHR preparation remain in place on our service more than 3 years after the project’s completion. These are low-resource interventions that can be integrated into patient care teams across other services and hospitals. Future work will include incorporating standardized discharge criteria for common PHM diagnoses into the EHR, which will further help medical teams anticipate discharges earlier.

ACKNOWLEDGMENTS

The authors are grateful for the support of Akron Children Hospital’s P2P (Project To Publication) course and P2P coaches: Drs. Prabi Rajbhandari, Kerwyn Jones, Michael Bigham, and T.J. Wolski for their invaluable guidance throughout the manuscript writing process. The authors used ChatGPT (OpenAI) to assist with language editing, formatting, and figure refinement. The authors also used SciSpace (SciSpace, Inc., Bethesda, Md.) to assist with language editing and formatting. Neither ChatGPT nor SciSpace was used to generate scientific content, analyze data, or interpret study findings. The authors used Grammarly (Grammarly, Inc., San Francisco, Ca.) to assist with grammar, spelling, and language editing during manuscript preparation. All content was reviewed and verified by the authors, who take full responsibility for the manuscript.