The association between discharge before noon and length of stay in medical and surgical patients

Assessing the impact of workload and clinician experience on patient throughput: A multicenter study

BACKGROUND

Various strategies have attempted to address increased patient lengths of stay (LOS), but effectiveness varies. Factors related to work design and workforce experience may also play significant roles.

OBJECTIVE

Utilizing data from the Discharge in the A.M. trial, we aimed to validate an electronic measure of workload (i.e., note count) and assess the relationship of workload, patient complexity, and physician years of experience to LOS.

METHODS

Retrospective observational study at three large academic hospitals with hospital medicine physicians and patients they care for during the study.

MEASURES

Workload as measured by electronic note count and physician years of experience; patient LOS.

RESULTS

From February 9, 2021 to July 31, 2021, 59 physicians completed daily surveys for 93% of 2318 scheduled shifts. We observed a moderate correlation (r: .56) between starting morning census and note counts but no association with LOS. We observed an effect modification between note count and the Charlson Comorbidity Index (CCI), with LOS increasing by 2.3% (95% CI: 0.3%, 4.3%; p = .02) and 3.9% (95% CI: 2.0%, 5.9%; p < .0001) per patient for every 1 unit increase in note count for patients with a moderate CCI or severe CCI, respectively. Years since training was associated with a 0.7% decrease in LOS (95% CI: -1.3%, -0.1%, p = .03).

CONCLUSION

Physician workload, as measured by note count, was associated with longer LOS with higher CCI, while more years of experience was associated with shorter LOS. Original Clinical Trial Registration: ClinicalTrials.gov number, NCT05370638.

Driving in the Wrong Direction: Exploring the Unintended Consequences of an Early Discharge Program on Length of Stay in Hospital Setting

BACKGROUND AND OBJECTIVES

Early discharge of patients has become standard work in acute care settings to reduce inpatient length of stay (LOS), improve patient flow, and reduce boarding in the emergency department (ED).

Retrospective analysis of outcomes from a "discharge by 11 am " program at an academic medical center from January 1, 2020, to June 30, 2022. The analysis addresses the effects of a discharge by 11 am goal on time from discharge order release to patient discharge, ED boarding, LOS, and observed-to-expected LOS.

METHODS

Patient-level electronic health record data included discharge order entry time, discharge time, LOS, and diagnosis-related group geometric LOS (GMLOS). Additional unit-level data for ED boarding volumes and hours were included. Analyses were conducted at the hospital and unit levels where indicated.

RESULTS

Patients with a discharge order by 9 am have longer mean hours from order to discharge than patients without a discharge order by 9 am (9.04 vs 2.48 hours, P < .001) ED boarding total ( R2  = 46.2%, P ≤ .001), percentage ( R2  = 50.4%, P ≤ .001), median minutes ( R2  = 24.6%, P = .005), and total minutes ( R2  = 40.8%, P ≤ .001) all increased as discharge by 11 am performance improved. The mean LOS is longer for the discharge by 11 am group than the non-discharge by 11 am group -1.67; 95% CI, -2.03 to -1.28, P < .001). Discharge by 11 am patients had a LOS/GMLOS ratio 21.9% higher than the non-discharge by 11 am cohort (difference -0.31; 95% CI, -0.36 to -0.26, P < .001).

CONCLUSIONS

Discharge order entry and release by 9 am and patient physically discharged by 11 am initiatives demonstrate a statistical increase in time from discharge order to discharge time, ED boarding, LOS, and observed-to-expected LOS.

PROPEL Discharge: An Interdisciplinary Throughput Initiative

BACKGROUND

Increased care demands at a health care institution led to strained resources, emergency department (ED) congestion, safety events, and patient and employee dissatisfaction. Moreover, high volumes of afternoon discharges contributed to limited early morning bed availability and admission bottlenecks.

METHODS

A 29-month pre-post design quality improvement project on 19 acute care, adult medicine units across two campuses at a large academic medical center was implemented to improve discharge timeliness, length of stay (LOS), and ED throughput by increasing pre-11:00 a.m. discharges. Based on Lean Six Sigma methodology, interventions included standardized interdisciplinary discharge processes and roles, processes to ensure performance data transparency and access, a recognition program, and a barrier tracking and mitigation process for continued improvements.

RESULTS

During the intervention period, pre-11:00 a.m. discharges increased from 5.1% to 21.8% (p < 0.001), discharge orders were entered 42 minutes earlier (p < 0.001), patients were discharged 56 minutes earlier (p < 0.001), the percentage of discharges completed within 90 minutes from discharge order improved from 26.2% to 38.1% (p < 0.001), the percentage of discharges by 3:00 p.m. improved from 44.7% to 55.9% (p < 0.001), ED admissions arrived to units 44 minutes earlier (p < 0.001), median LOS decreased by 0.46 days (p < 0.001), median observed-to-expected (O:E) LOS decreased by 0.05 (p < 0.001), and opportunity day reductions contributed to increased bed capacity of 18.84 beds per day.

CONCLUSION

Early morning discharges are associated with improved patient throughput and are safe, achievable, and sustainable via interventions focused on frontline engagement, interdisciplinary collaboration, standardization, barrier mitigation, data accessibility, and accountability.

Investing in a New Role to Increase Timely Morning Discharges in the Inpatient Setting

OBJECTIVE

Delays in discharges have a downstream effect on emergency department admissions, wait times, intensive care unit transfers, and elective admissions. This quality improvement project's aim was to increase the percentage of discharges before noon from a hospital medicine service from 19% to 30% over a 6-month period and sustain the increase for 6 months.

METHODS

Interventions included introduction of a dedicated patient flow provider (PFP), optimization of workflow, technology assistance with discharge tasks, and multidisciplinary education on patient flow. The primary outcome was percentage of discharges before noon, and secondary outcome was length of stay (LOS). The process measure compared discharges before noon with and without the PFP. Additional equity and regression analyses were completed. The balancing measure was 7-day readmissions.

RESULTS

Discharges before noon rose from baseline 19% to 34%. On days the PFP was present, discharges before noon were 43% vs 22% when not present. Rational subgrouping showed an initial and persistent disparity in discharges before noon for racial and ethnic minority patients and patients who use a language other than English (LOE). LOS remained stable from baseline 2.74 to 2.54 days. There was no change in 7-day readmission rate.

CONCLUSION

Discharges before noon significantly increased after the addition of a staff member dedicated to discharge tasks. Additional staffing represents a large investment, and additional studies are needed to quantify the financial impact of this intervention. Future targeted work to address persistent disparities in discharges before noon for racial and ethnic minority patients and those who use an LOE is also needed.

Implementing and Evaluating a Discharge Before Noon Initiative in a Large Tertiary Care Urban Hospital

BACKGROUND

Discharging clinically ready patients before noon on their discharge day may influence overall discharge process quality, emergency department (ED) boarding times, and length of stay (LOS). This study evaluated the effectiveness of a discharge before noon (DBN) initiative.

METHODS

Many DBN components were refined or added during a pilot, including incorporating the DBN process into daily rounds, an electronic tracking system, and other elements for possible DBN patients such as a car service when appropriate and expedited lab results and physical therapy consults. DBN was evaluated through a retrospective pre-post study (12-month periods). Study patients were from Maimonides Medical Center's medicine units. Kaplan-Meier estimates and a log-rank test characterized and compared the discharge time probabilities in pre-DBN and post-DBN groups. Log-logistic accelerated failure time (AFT) analysis assessed the influence of DBN on discharge time. Secondary analyses examined the relationship between LOS and readmission within 30 days for any cause and DBN.

RESULTS

The percentage of patients discharged before noon increased from 5.0% to 11.4% pre/post-DBN (p < 0.001). The AFT analysis estimated that post-DBN patients had discharge times 41.5% earlier (p < 0.001). DBN as an independent factor was not associated with LOS or subsequent readmissions within 30 days for any cause. Despite an increase in the percentage of patients admitted during the daytime (8:00 a.m. to 5:00 p.m.), the median ED boarding time increased by 41 minutes in post-DBN patients (p < 0.001).

CONCLUSION

The DBN initiative was associated with an increased percentage of patients discharged before noon. Further research is needed to identify strategies that reliably improve discharge timeliness while reducing ED boarding.

Discharge in the a.m.: A randomized controlled trial of physician rounding styles to improve hospital throughput and length of stay

BACKGROUND

To relieve hospital capacity strain, hospitals often encourage clinicians to prioritize early morning discharges which may have unintended consequences.

OBJECTIVE

We aimed to test the effects of hospitalist physicians prioritizing discharging patients first compared to usual rounding style.

DESIGN, SETTING AND PARTICIPANTS

Prospective, multi-center randomized controlled trial. Three large academic hospitals. Participants were Hospital Medicine attending-level physicians and patients the physicians cared for during the study who were at least 18 years of age, admitted to a Medicine service, and assigned by standard practice to a hospitalist team.

INTERVENTION

Physicians were randomized to: (1) prioritizing discharging patients first as care allowed or (2) usual practice.

MAIN OUTCOME AND MEASURES

Main outcome measure was discharge order time. Secondary outcomes were actual discharge time, length of stay (LOS), and order times for procedures, consults, and imaging.

RESULTS

From February 9, 2021, to July 31, 2021, 4437 patients were discharged by 59 physicians randomized to prioritize discharging patients first or round per usual practice. In primary adjusted analyses (intention-to-treat), findings showed no significant difference for discharge order time (13:03 ± 2 h:31 min vs. 13:11 ± 2 h:33 min, p = .11) or discharge time (15:22 ± 2 h:50 min vs. 15:21 ± 2 h:50 min, p = .45), for physicians randomized to prioritize discharging patients first compared to physicians using usual rounding style, respectively, and there was no significant change in LOS or on order times of other physician orders.

CONCLUSIONS

Prioritizing discharging patients first did not result in significantly earlier discharges or reduced LOS.

The Gap Between Daily Hospital Bed Supply and Demand: Design, Implementation, and Impact of Data-Driven Pre-Noon Discharge Targets

BACKGROUND

Hospitals have sought to increase pre-noon discharges to improve capacity, although evidence is mixed on the impact of these initiatives. Past interventions have not quantified the daily gap between morning bed supply and demand. The authors quantified this gap and applied the pre-noon data to target a pre-noon discharge initiative.

METHODS

The study was conducted at a large hospital and included adult and pediatric medical/surgical wards. The researchers calculated the difference between the average cumulative bed requests and transfers in for each hour of the day in 2018, the year prior to the intervention. In 2019 an intervention on six adult general medical and two surgical wards was implemented. Eight intervention and 14 nonintervention wards were compared to determine the change in average cumulative pre-noon discharges. The change in average hospital length of stay (LOS) and 30-day readmissions was also calculated.

RESULTS

The average daily cumulative gap by noon between bed supply and demand across all general care wards was 32.1 beds (per ward average, 1.3 beds). On intervention wards, mean pre-noon discharges increased from 4.7 to 6.7 (p < 0.0000) compared with the nonintervention wards 14.0 vs. 14.6 (p = 0.19877). On intervention wards, average LOS decreased from 6.9 to 6.4 days (p < 0.001) and readmission rates were 14.3% vs 13.9% (p = 0.3490).

CONCLUSION

The gap between daily hospital bed supply and demand can be quantified and applied to create pre-noon discharge targets. In an intervention using these targets, researchers observed an increase in morning discharges, a decrease in LOS, and no significant change in readmissions.

Time of Discharge and 30-Day Re-Presentation to an Acute Care Setting After Elective Lumbar Decompression Surgery

BACKGROUND

Evidence regarding the consequence of efforts to increase patient throughput and decrease length of stay in the context of elective spine surgery is limited.

OBJECTIVE

To evaluate whether early time of discharge results in increased rates of hospital readmission or return to emergency department for patients admitted after elective, posterior, lumbar decompression surgery.

METHODS

We conducted a retrospective cohort study of 779 patients admitted to hospital after undergoing elective, posterior, lumbar decompression surgery. Multiple logistic regression evaluated the relationship between time of discharge and the primary outcome of return to acute care within 30 days, while controlling for sociodemographic, procedural, and discharge characteristics.

RESULTS

In multiple logistic regression, time of discharge earlier in the day was not associated with increased odds of return to acute care within 30 days (odds ratio [OR] 1.18, 95% CI 0.92-1.52, P = .19). Weekend discharge (OR 1.99, 95% CI 1.04-3.79, P = .04) increased the likelihood of return to acute care. Surgeon experience (<1 year of attending practice, OR 0.43, 95% CI 0.19-1.00, P = .05 and 2-5 years of attending practice, OR 0.50, 95% CI 0.25-1.01, P = .054), weekend discharge (OR 0.49, 95% CI 0.27-0.89, P = .02), and physical therapy evaluation (OR 0.20, 95% CI 0.12-0.33, P < .001) decreased the likelihood of discharge before noon.

CONCLUSION

Time of discharge is not associated with risk of readmission or presentation to the emergency department after elective lumbar decompression. Weekend discharge is independently associated with increased risk of readmission and decreased likelihood of prenoon discharge.

Effect of an Attending Nurse on Timeliness of Discharge, Patient Satisfaction, and Readmission

AIMS

To improve the timeliness and quality of discharge for patients by creating the role of the Attending Nurse.

BACKGROUND

Discharge time affects hospital throughput and patient satisfaction. Bedside nurses and hospitalists have competing priorities that can hinder performing timely, high quality discharges.

METHODS

This retrospective analysis evaluated the effect of an Attending Nurse paired with a hospital medicine physician on discharge time and quality. A total of 8329 patient discharges were eligible for the study and propensity score matching yielded 2715 matched pairs.

RESULTS

In the post- intervention matched cohort, the percentage of patients discharged before 2pm increased from 34.4% to 45.9% (p <0.01) and the median discharge time moved 48 minutes earlier. In the unmatched cohort, patient satisfaction with the discharge process improved on several questions. While length of stay was not affected, the 30-day readmission rate did increase from 8.9% to 10.7% (p=0.02).

CONCLUSION

With the new Attending Nurse role, we positively impacted throughput by shifting discharge times earlier in the day while improving patient satisfaction Length of stay stayed the same but the 30-day readmission rate increased.

IMPLICATIONS FOR NURSING MANAGEMENT

Our multidisciplinary approach to the problem of late discharge times led to the creation of a new role. This role made ownership of discharge tasks clear and reduced competing priorities, freeing up nurses and hospitalists to perform other care related responsibilities without holding up discharges.

Influence of Time of Discharge and Length of Stay on 30-Day Outcomes After Elective Anterior Cervical Spine Surgery

BACKGROUND

Encouraging early time of discharge (TOD) for medical inpatients is commonplace and may potentially improve patient throughput. It is unclear, however, whether early TOD after elective spine surgery achieves this goal without a consequent increase in re-presentations to the hospital.

OBJECTIVE

To evaluate whether early TOD results in increased rates of hospital readmission or return to the emergency department after elective anterior cervical spine surgery.

METHODS

We analyzed 686 patients who underwent elective uncomplicated anterior cervical spine surgery at a single institution. Logistic regression was used to evaluate the relationship between sociodemographic, procedural, and discharge characteristics, and the outcomes of readmission or return to the emergency department and TOD.

RESULTS

In multiple logistic regression, TOD was not associated with increased risk of readmission or return to the emergency department within 30 days of surgery. Weekend discharge (odds ratio [OR] 0.33, 95% CI 0.21-0.53), physical therapy evaluation (OR 0.44, 95% CI 0.28-0.71), and occupational therapy evaluation (OR 0.32, 95% CI 0.17-0.63) were all significantly associated with decreased odds of discharge before noon. Disadvantaged status, as measured by area of deprivation index, was associated with increased odds of readmission or re-presentation (OR 1.86, 95% CI 0.95-3.66), although this result did not achieve statistical significance.

CONCLUSION

There does not appear to be an association between readmission or return to the emergency department and early TOD after elective spine surgery. Overuse of inpatient physical and occupational therapy consultations may contribute to decreased patient throughput in surgical admissions.

Critical Success Factors for Addressing Discharge Inefficiency at a Large Academic Medical Center: A Lean Six Sigma Approach

BACKGROUND

Delayed discharges can be a systemic issue. Understanding the systemic factors that contribute to discharge inefficiencies is essential to addressing discharge inefficiencies.

PURPOSE

This article reports on a Lean Six Sigma approach and the process to identifying inefficiencies and systemic barriers to early discharge in a large US academic medical center.

METHODS

A qualitative methodology guided this project. In particular, direct observation methods were used to help the project team identify factors contributing to discharge inefficiencies.

RESULTS

Overall, findings suggest that establishing consistent multidisciplinary team communication processes was a contributing factor to reducing the inefficiencies around discharges. On a more granular level, key barriers included disparate communication systems, disruptors (specifically Kaizen bursts), and unique role challenges.

CONCLUSIONS

This article provides a framework for addressing discharge inefficiencies. Because the output of the process, a critical contributor to the overall outcome, is often not analyzed, this analysis provides value to others contemplating the same or similar process toward discharge efficiency.

Rhythmicity of patient flow in an acute medical unit: relationship to hospital occupancy, 7-day working and the effect of COVID-19

BACKGROUND

The Acute Medical Unit (AMU) provides care for unscheduled hospital admissions. Seven-day consultant presence and morning AMU discharges have been advocated to improve hospital bed management.

AIMS

To determine whether a later time of daily peak AMU occupancy correlates with measures of hospital stress; whether 7-day consultant presence, for COVID-19, abolished weekly periodicity of discharges.

DESIGN

Retrospective cohort analysis.

METHODS

: Anonymised AMU admission and discharge times were retrieved from the Profile Information Management System (PIMS), at a large, urban hospital from 14 April 2014 to 31 December 2018 and 20 March to 2 May 2020 (COVID-19 peak). Minute-by-minute admission and discharge times were combined to construct a running total of AMU bed occupancy. Fourier transforms were used to determine periodicity. We tested association between (i) average AMU occupancy and (ii) time of peak AMU occupancy, with measures of hospital stress (total medical bed occupancy and 'medical outliers' on non-medical wards).

RESULTS

: Daily, weekly and seasonal patterns of AMU bed occupancy were evident. Timing of AMU peak occupancy was unrelated to each measure of hospital stress: total medical inpatients (Spearman's rho, rs = 0.04, P = 0.24); number of medical outliers (rs = -0.06, P = 0.05). During COVID-19, daily bed occupancy was similar, with continuation of greater Friday and Monday discharges than the weekend.

CONCLUSIONS

: Timing of peak AMU occupancy did not alter with hospital stress. Efforts to increase morning AMU discharges are likely to have little effect on hospital performance. Seven-day consultant presence did not abolish weekly periodicity of discharges-other factors influence weekend discharges.

Morning Discharges and Patient Length of Stay in Inpatient General Internal Medicine

BACKGROUND

Many initiatives seek to increase the number of morning hospital discharges to improve patient flow, but little evidence supports this practice.

OBJECTIVE

To determine the association between the number of morning discharges and emergency department (ED) length of stay (LOS) and hospital LOS in general internal medicine (GIM).

DESIGN, SETTING, AND PARTICIPANTS

Multicenter retrospective cohort study involving all GIM patients discharged between April 1, 2010, and October 31, 2017, at seven hospitals in Ontario, Canada.

MAIN MEASURES

The primary outcomes were ED LOS and hospital LOS, and secondary outcomes were 30-day readmission and in-hospital mortality. The number of morning GIM discharges (defined as the number of patients discharged alive between 8:00 AM and 12:00 PM) on the day of each hospital admission was the primary exposure. Multivariable regression models were fit to control for patient characteristics and situational factors, including GIM census.

RESULTS

The sample included 189,781 patient admissions. In total, 36,043 (19.0%) discharges occurred between 8:00 AM and 12:00 PM. The average daily number of morning discharges and total discharges per hospital was 1.7 (SD, 1.4) and 8.4 (SD, 4.6), respectively. The median ED LOS was 14.5 hours (interquartile range [IQR], 10.0- 23.1), and the median hospital LOS was 4.6 days (IQR, 2.4-9.0). After multivariable adjustment, there was not a significant association between morning discharge and hospital LOS (adjusted rate ratio [aRR], 1.000; 95% CI, 0.996-1.000; P = .997), ED LOS (aRR, 0.999; 95% CI, 0.997-1.000; P = .307), 30-day readmission (aRR, 1.010; 95% CI, 0.991-1.020; P = .471), or in-hospital mortality (aRR, 0.967; 95% CI, 0.920-1.020; P = .183). The lack of association between morning discharge and LOS was generally consistent across all seven hospitals. At one hospital, morning discharge was associated with a 1.9% shorter ED LOS after multivariable adjustment (aRR, 0.981; 95% CI, 0.966-0.996; P = .013).

CONCLUSIONS

The number of morning discharges was not significantly associated with shorter ED LOS or hospital LOS in GIM. Our findings suggest that increasing the number of morning discharges alone is unlikely to substantially improve patient throughput in GIM, but further research is needed to determine the effectiveness of specific interventions.

Creating a culture of quality: our experience with providing feedback to frontline hospitalists

BACKGROUND

One way to provide performance feedback to hospitalists is through the use of dashboards, which deliver data based on agreed-upon standards. Despite the growing trend on feedback performance on quality metrics, there remain limited data on the means, frequency and content of feedback that should be provided to frontline hospitalists.

OBJECTIVE

The objective of our research is to report our experience with a comprehensive feedback system for frontline hospitalists, as well as report the change in our quality metrics after implementation.

DESIGN, SETTING AND PARTICIPANTS

This quality improvement project was conducted at a tertiary academic medical centre among our hospitalist group consisting of 46 full-time faculty members.

INTERVENTION OR EXPOSURE

A monthly performance feedback report was distributed to provide ongoing feedback to our hospitalist faculty, including an individual dashboard and a peer comparison report, complemented by coaching to incorporate process improvement tactics into providers' daily workflow.

MAIN OUTCOMES AND MEASURES

The main outcome of our study is the change in quality metrics after implementation of the monthly performance feedback report RESULTS: The dashboard and rank order list were sent to all faculty members every month. An improvement was seen in the following quality metrics: length of stay index, 30-day readmission rate, catheter-associated urinary tract infections, central line-associated bloodstream infections, provider component of Healthcare Consumer Assessment of Healthcare Providers and Systems scores, attendance at care coordination rounds and percentage of discharge orders placed by 10:00.

CONCLUSIONS

Implementation of a monthly performance feedback report for hospitalists, complemented by peer comparison and guidance on tactics to achieve these metrics, created a culture of quality and improvement in the quality of care delivered.

Bed downtime: the novel use of a quality metric allows inpatient providers to improve patient flow from the emergency department

BACKGROUND

Emergency department (ED) boarding time is associated with increased length of stay (LOS) and inpatient mortality. Despite the documented impact of ED boarding on inpatient outcomes, a disparity continues to exist between the attention paid to the issue by inpatient and ED providers. A perceived lack of high yield strategies to address ED boarding from the perspective of the inpatient provider may discourage involvement in improvement initiatives on the subject. As such, further work is needed to identify inpatient metrics and strategies to address patient flow problems, and which may improve ED boarding time.

METHODS

After initial system analysis, our multidisciplinary quality improvement (QI) group defined the process time metric 'bed downtime'-the time from which a bed is vacated by a discharged patient to the time an ED patient is assigned to that bed. Using the Lean Sigma QI approach, this metric was targeted for improvement on the internal medicine hospitalist service at a tertiary care academic medical centre.

INTERVENTIONS

Interventions included improving inpatient provider awareness of the problem, real-time provider notification of empty beds, a weekly retrospective emailed performance dashboard and the creation of a guideline document for admission procedures.

RESULTS

This package of interventions was associated with a 125 min reduction in mean bed downtime for incoming ED patients (254 min to 129 min) admitted to the intervention unit.

CONCLUSION

Use of the bed downtime metric as a QI target was associated with marked improvements in process time during our project. The use of this metric may enhance the ability of inpatient providers to participate in QI efforts to improve patient flow from the ED. Further study is needed to determine if use of the metric may be effective at reducing boarding time without requiring alterations to LOS or discharge patterns.

A scheduling-based methodology for improving patient perceptions of quality of care in intensive care units

Research has found that hospitals with better scores on patient experience of care surveys have better patient safety records and outcomes. Therefore, targeting ways of improving patient experience of care is becoming relevant for hospitals not only for the patient health outcomes but also for the financial implications. Therefore, the goal of this paper is to develop new operation management strategies for improving patient experience of care in intensive care units (ICUs). A new scheduling-based methodology is developed that considers two of the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey dimensions, doctor communication and discharge information. Two hypotheses are studied. The first hypothesis postulates that to improve doctor communication with the patient, a nurse must be present in the patient room when the doctor performs ward rounds. The second hypotheses states that to improve the patient-doctor communication of discharge information aspect, doctors must see the patient expected to be discharged early in the day. A computational study is performed to gather insights and to measure the performance of the scheduling-based methodology on a case study from an intensive care unit located in a hospital in central Texas. The results show hospital improvement in the studied dimensions of the HCAHPS survey after 1 year of the hospital adoption of the study recommendations.

Trends in Medical and Surgical Admission Length of Stay by Race/Ethnicity and Socioeconomic Status: A Time Series Analysis

BACKGROUND

Length of stay (LOS), a metric of hospital efficiency, differs by race/ethnicity and socioeconomic status (SES) and longer LOS is associated with adverse health outcomes. Historically, projects to improve LOS efficiency have yielded LOS reductions by 0.3 to 0.7 days per admission.

OBJECTIVE

To assess differences in average adjusted length of stay (aALOS) over time by race/ethnicity, and SES stratified by discharge destination (home or non-home).

METHOD

Data were obtained from 2009-2014 Healthcare Cost and Utilization Project State Inpatient Datasets for New York, New Jersey, and Florida. Multivariate generalized linear models were used to examine trends in aALOS differences by race/ethnicity, and by high vs low SES patients (defined first vs fourth quartile of median income by zip code) controlling for patient, disease and hospital characteristics.

RESULTS

For those discharged home, racial/ethnic and SES aALOS differences remained stable from 2009 to 2014. However, among those discharged to non-home destinations, Black vs White aALOS differences increased from 0.21 days in Q1 2009, (95% confidence interval (CI): 0.13 to 0.30) to 0.32 days in Q3 2013, (95% CI: 0.23 to 0.40), and for low vs high SES patients from 0.03 days in Q1 2009 (95% CI: -0.04 to 0.1) to 0.26 days, (95% CI: 0.19 to 0.34). Notably, for patients not discharged home, racial/ethnic and SES aALOS differences increased and persisted after Q3 2011, coinciding with the introduction of the Affordable Care Act (ACA).

CONCLUSION

Further research to understand the ACA's policy impact on hospital efficiencies, and relationship to racial/ethnic and SES differences in LOS is warranted.

Late-afternoon communication and patient planning (CAPP) rounds: an intervention to allow early patient discharges

OBJECTIVE

Measure effect of late-afternoon communication and patient planning (CAPP) rounds to increase early electronic discharge orders (EDO).

METHODS

We enrolled 4485 patients discharged from six subspecialty medical services. We implemented late-afternoon CAPP rounds to identify patients who could have morning discharge the subsequent day. After an initial successful implementation of the intervention, we identified lack of sustainability. We made changes with sustained implementation of the intervention. This is a before-after study of a quality improvement intervention.

PROGRAM EVALUATION

Primary measures of intervention effectiveness were percentage of patients who received EDO by 11 am and patients discharged by noon. Additional measure of effectiveness were percent of patients admitted to the correct ward, emergency department (ED)-to-ward transfer time compared between intervention and nonintervention periods. We compared the overall expected LOS and the average weekly discharges to assess for comparability across the control and intervention time periods. We used the readmission rate as balancing measure to ensure that the intervention was not have unintended negative patients consequences.

RESULTS

Expected length of stay based upon discharge diagnosis/comorbidities and readmission rates were similar across the intervention and control time periods. The average weekly discharges were not statistically significant. Percentage of EDO by 11 am was higher in the first intervention period, second intervention period and combined intervention periods (28.9% vs. 21.8%, P < 0.001) compared with the respective control periods. Percent discharged before noon increased in the first intervention period, second intervention period and for the combined intervention periods (17 vs. 11.8%, P < 0.001). There was no difference in the percent admitted to the correct ward and ED-to-ward transfer time.

CONCLUSION

Afternoon CAPP rounds to identify early patient discharges the following day led to increase in EDO entered by 11 am and discharges by noon without an adverse change in readmission rates and LOS.

Discharge by Noon: A Checklist Initiative by the Otolaryngology Service

OBJECTIVES/HYPOTHESIS

Hospital length of stay (LOS) and throughput are critical issues for hospitals. Late hospital discharges contribute to bottlenecks in the emergency department, overcrowd surgical and procedural areas, and limit patient tertiary-care center transfers. Our goal was to increase discharge by noon (DCBN) percentage from 8% to over 50% in a sustainable manner.

STUDY DESIGN

Retrospective Review.

METHODS

We used a multiple time series design and a quality improvement approach. An interdisciplinary improvement team (IIT) identified the main causes contributing to late discharge and then developed and implemented multiple interventions to increase the percentage of DCBN. Admissions and discharge information were obtained for all patients in the otolaryngology service (January 2014-September 2017). The intervention was implemented in July 2015. The primary outcome was the percentage of DCBN per month. Secondary outcomes were LOS, case-mix index (CMI), patient experience, and 30-day readmissions. We analyzed the impact of our intervention and outcomes at the preintervention, peri-intervention, and postintervention periods.

RESULTS

One thousand four hundred sixty-four admissions to the otolaryngology service were included. Throughout the intervention period, the percentage of patients DCBN increased. Analysis of the intervention showed significant DCBN change of 15% in the first versus 42% in the last 12-months (P < .001), and shorter LOS (-1.4 days, P < .001) and lower CMI (-0.6, P < .001) in the DCBN group. Patient satisfaction scores improved by 4% (P < .05), and no difference in 30-day readmission rates (P = .29) was shown.

CONCLUSIONS

This multifaceted intervention improved early discharge and patient experience. Our checklist of key behaviors could be applied throughout other services and hospitals with reproducible success.

LEVEL OF EVIDENCE

4 Laryngoscope, 131:E76-E82, 2021.

Discharge Criteria Decrease Variability and Improve Efficiency

BACKGROUND AND OBJECTIVES

To determine the effect of discharge criteria on discharge readiness and length of stay (LOS). Discharge inefficiency is a common barrier to hospital flow, affecting admissions, discharges, cost, patient satisfaction, and quality of care. Our center identified increasing discharge efficiency as a method to improve flow and better meet the needs of our patients.

METHODS

A multidisciplinary team was assembled to examine discharge efficiency and flow. Discharge criteria were created for the 3 most common diagnoses on the hospital medicine service then expanded to 10 diagnoses 4 months into the project. Discharge workflow was evaluated through swim lane mapping, and barriers were evaluated through fishbone diagrams and a key driver diagram. Progress was assessed every 2 weeks through statistical process control charts. Additional interventions included provider education, daily review of criteria, and autotext added to daily notes. Our primary aim was to increase the percentage of patients discharged within 3 hours of meeting discharge criteria from 44% to 75% within 12 months of project implementation.

RESULTS

Discharge within 3 hours as well as 2 hours of meeting criteria improved significantly, from 44% to 87% and from 33% to 78%, respectively. LOS for the 10 diagnoses decreased from 2.89 to 1.47 days, with greatest gains seen for patients with asthma, pneumonia, and bronchiolitis without a change in the 30-day readmission rate.

CONCLUSIONS

Discharge criteria for common diagnoses may be an effective way to decrease variability and improve LOS for hospitalized children.

Outcomes of a Resident-Led Early Hospital Discharge Intervention

BACKGROUND

Early morning patient discharge from the hospital is increasingly being recognized as a key dimension of quality of care. At our institution, there is a significantly lower early discharge rate on the teaching hospitalist teams in comparison with the non-teaching teams.

OBJECTIVE

To implement a resident-driven intervention in the teaching medical services to increase overall discharge order rate before 11 am (DOB-11) and assess the effect of this intervention on hospital length of stay (LOS), 30-day readmission rates (RR), and resident perception.

DESIGN

Interrupted time series as well as controlled before-after designs.

PARTICIPANTS

All inpatients discharged from general medicine units.

INTERVENTIONS

We implemented an educational didactic in conjunction with resident-attending daily walk rounds followed by resident-led multidisciplinary discharge huddles to identify next-day discharges.

MAIN MEASURES

The primary outcome was DOB-11 rates 18 months pre- and 12 months post-intervention.

SECONDARY OUTCOMES

LOS and RR. Additionally, we assessed residents' perception of the early discharge protocol.

KEY RESULTS

The DOB-11 rate increased from 12 to 29% (p < 0.001), LOS increased by 1.47 days (P < 0.001), and RR increased by 0.32% (P = 0.84), respectively, on the teaching teams. Compared with the non-teaching (control) teams, the teaching teams registered a greater increase in DOB-11 rate (by 17%, p < 0.001; ratio of adjusted ORs 2.16; 95% CI, 1.65, 2.85; p value < 0.001), small increase in LOS (by 0.74 day, p = 0.39; ratio of adjusted post-/pre-intervention ratio [teaching] and post-/pre- intervention ratio [non-teaching] = 1.05, 95% CI, 0.97, 1.14, p = 0.23), and relative increase in RR (by 3.98%, p = 0.07, and ratio of ORs = 1.35, 95% CI, 1.03, 1.8), p = 0.03). Approximately 55% (16/29) of the residents agreed that the early discharge initiative helped in understanding the importance of prioritizing patients for early discharge. Additionally, 55% (20/36) of the residents "agreed" that the early discharge initiative compromised their learning during teaching rounds.

CONCLUSION

Our study demonstrates that DOB-11 is an achievable goal, not only for non-teaching teams but also for resident-run teaching teams.

The Association of Discharge Before Noon and Length of Stay in Hospitalized Pediatric Patients

BACKGROUND AND OBJECTIVES

To optimize patient throughput, many hospitals set targets for discharging patients before noon (DCBN). However, it is not clear whether DCBN is an appropriate measure for an efficient discharge. This study aims to determine whether DCBN is associated with shorter length of stay (LOS) in pediatric patients and whether that relationship is different between surgical and medical discharges.

METHODS

From May 2014 to April 2017, we performed a retrospective data analysis of pediatric medical and surgical discharges belonging to a single academic medical center. Patients were included if they were 21 years or younger with at least one night in the hospital. Propensity score weighted multivariate ordinary least squares models were used to evaluate the association between DCBN and LOS.

RESULTS

Of the 8,226 pediatric hospitalizations, 1,531 (18.61%) patients were DCBN. In our multivariate model of all the discharges, DCBN was associated with an average of 0.27 day (P = .014) shorter LOS when compared to discharge in the afternoon. In our multivariate medical discharge model, DCBN was associated with an average of 0.30 (P = .017) day decrease in LOS while the association between DCBN and LOS was not significant among surgical discharges.

CONCLUSIONS

On average, at a single academic medical center, DCBN was associated with a decreased LOS for medical but not surgical pediatric discharges. DCBN may not be an appropriate measure of discharge efficiency for all services.

Barriers to Early Hospital Discharge: A Cross-Sectional Study at Five Academic Hospitals

BACKGROUND

Understanding the issues delaying hospital discharges may inform efforts to improve hospital throughput.

OBJECTIVE

This study was conducted to identify and determine the frequency of barriers contributing to delays in placing discharge orders.

DESIGN

This was a prospective, cross-sectional study. Physicians were surveyed at approximately 8:00 AM, 12:00 PM, and 3:00 PM and were asked to identify patients that were "definite" or "possible" discharges and to describe the specific barriers to writing discharge orders.

SETTING

This study was conducted at five hospitals in the United States.

PARTICIPANTS

The study participants were attending and housestaff physicians on general medicine services.

PRIMARY OUTCOMES AND MEASURES

Specific barriers to writing discharge orders were the primary outcomes; the secondary outcomes included discharge order time for high versus low team census, teaching versus nonteaching services, and rounding style.

RESULTS

Among 1,584 patient evaluations, the most common delays for patients identified as "definite" discharges (n = 949) were related to caring for other patients on the team or waiting to staff patients with attendings. The most common barriers for patients identified as "possible" discharges (n = 1,237) were awaiting patient improvement and for ancillary services to complete care. Discharge orders were written a median of 43-58 minutes earlier for patients on teams with a smaller versus larger census, on nonteaching versus teaching services, and when rounding on patients likely to be discharged first (all P < .003).

CONCLUSIONS

Discharge orders for patients ready for discharge are most commonly delayed because physicians are caring for other patients. Discharges of patients awaiting care completion are most commonly delayed because of imbalances between availability and demand for ancillary services. Team census, rounding style, and teaching teams affect discharge times.

A targeted initiative to discharge surgical patients earlier in the day is associated with decreased length of stay and improved hospital throughput

BACKGROUND

The timing of inpatient discharges can impact hospital throughput with later discharges leading to decreased patient satisfaction, increased length of stay (LOS), and longer boarding times.

METHODS

A 12-month targeted intervention that included both pre-operative and inpatient components was implemented across all surgical inpatient services to increase the proportion of patients discharged by noon.

RESULTS

Discharge by noon rates increased from 14.3% to 21.5% during the 12-month initiative (p < 0.01). The case mix index adjusted LOS (aLOS) decreased from 2.17 to 2.02 days (p < 0.01). ED, PACU, and ICU boarding times were all significantly lower during the initiative (p < 0.01, p < 0.01, p = 0.03 respectively).

CONCLUSIONS

A targeted initiative to discharge surgical patients earlier resulted in a 50% increase in the proportion of patients discharged by noon. Associated with this finding were improvements in hospital throughput as measured by aLOS and boarding times in the ED, ICUs, and PACU.

An Electronic Dashboard to Monitor Patient Flow at the Johns Hopkins Hospital: Communication of Key Performance Indicators Using the Donabedian Model

Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.

Systematic identification and management of barriers to vascular surgery patient discharge time of day

OBJECTIVE

Length of stay fails to completely capture the clinical and economic effects of patient progression through the phases of inpatient care, such as admission, room placement, procedures, and discharge. Delayed hospital throughput has been linked to increased time spent in the emergency department and postanesthesia care unit, delayed time to treatment, increased in-hospital mortality, decreased patient satisfaction, and lost hospital revenue. We identified barriers to vascular surgery inpatient care progression and instituted defined measures to positively impact standardized metrics.

METHODS

The study was divided into three periods: preintervention, "wash-in," and postintervention. During the preintervention phase, barriers to patient flow were quantified by an interdisciplinary team. Suboptimal provider communication emerged as the key barrier. An enhanced communication intervention consisting of face-to-face and mobile application-based education on key patient flow metrics, explicit discussion of individual patient barriers to progression at rounds and interdisciplinary huddles, and communication of projected discharge and potential barriers via e-mail was developed with input from all stakeholders. Following a 4-week wash-in implementation phase, data collection was repeated.

RESULTS

The pre- and postintervention patient cohorts accounted for 244.3 and 238.1 inpatient days, respectively. Both groups had similar baseline demographic, clinical characteristics, and procedures performed during hospitalization. The postintervention group was discharged 78 minutes earlier (14:00:32 vs 15:18:37; P = .03) with a trend toward increased discharge by noon (94% vs 88%; P = .09). Readmission rates did not differ (P = .44).

CONCLUSIONS

Implementation of a focused, interdisciplinary, frontline provider-driven, enhanced communication program can be feasibly incorporated into existing specialty surgical workflow. The program resulted in improved timeliness of discharge and projected cost savings, without increasing readmission rates.