BACKGROUND AND OBJECTIVES:

Hospital discharge requires multidisciplinary coordination. Insufficient coordination impacts patient flow, resource use, and postdischarge outcomes. Our objectives were to (1) implement a prospective, multidisciplinary discharge timing designation in the electronic health record (EHR) and (2) evaluate its association with discharge timing.

METHODS:

This quality-improvement study evaluated the implementation of confirmed discharge time (CDT), an EHR designation representing specific discharge timing developed jointly by a patient’s family and the health care team. CDT was intended to support task management and coordination of multidisciplinary discharge processes and could be entered and viewed by all team members. Four plan-do-study-act improvement phases were studied: (1) baseline, (2) provider education, (3) provider feedback, and (4) EHR modification. Statistical process control charts tracked CDT use and the proportion of discharges before noon. Length of stay was used as a balancing measure.

RESULTS:

During the study period from April 2013 through March 2017, 20 133 pediatric discharges occurred, with similar demographics observed throughout all phases. Mean CDT use increased from 0% to 62%, with special cause variations being detected after the provider education and EHR modification phases. Over the course of the study, the proportion of discharges before noon increased by 6.2 percentage points, from 19.9% to 26.1%, whereas length of stay decreased from 47 (interquartile range: 25–95) to 43 (interquartile range: 24–88) hours (both P < .001).

CONCLUSIONS:

The implementation of a prospective, multidisciplinary EHR discharge time designation was associated with more before-noon discharges. Next steps include replicating results in other settings and determining populations that are most responsive to discharge coordination efforts.

The hospital discharge process is known to be complex and frequently requires task management by many care providers, including families, nurses, physicians, social workers, case managers, pharmacists, and others, all of whom have competing demands.1  The timing of discharge is influenced by the degree of coordination achieved around this process and has implications for efficient patient flow across the hospital,24  patient satisfaction,5  and health care costs.6  Although researchers and administrators have long sought to understand and improve discharge timing,7  interventions have typically required complex systems changes and substantial additional resources2,3,812  that may not be practical in many settings.

Whether efforts to coordinate discharge timing could lead to earlier discharge is unknown but plausible. Later discharge times have been observed to be due to organizational delays7,13  and influenced by other drivers, such as social work needs, home health care availability, and transportation,7,14,15  suggesting that improved care coordination might promote earlier discharges. A systematic review on the impact of discharge planning7  evaluated length of stay (LOS) and readmission rates but did not consider the possible impact of discharge planning on earlier time of discharge. Previously identified perceptions about barriers to discharge have included team communication around task completion and optimal timing of discharge.13,1618 

In this quality-improvement study, we implemented and evaluated an intuitive, low-cost intervention to improve coordination around discharge timing. Our aim was to implement a family-centered, system-wide electronic health record (EHR) discharge time designation for pediatric inpatients in our children’s hospital and to determine if implementation was associated with discharge earlier in the day.

The American Family Children’s Hospital is a 111-bed, urban, quaternary, nonbirth children’s hospital at the University of Wisconsin–Madison. The children’s hospital discharges >4000 patients per year and performs >6000 surgical procedures per year. The average LOS is 5 days. All pediatric patients are admitted to general hospital medicine, subspecialty, and surgical teaching services, in which an attending physician oversees care, supervises pediatric and surgical residents, and collaborates with multidisciplinary colleagues. Approximately 40% of patients are discharged from pediatric hospital medicine services, with the remainder being discharged from surgical and subspecialty services. Advanced practice providers assist with discharge coordination on surgical services and selected subspecialty medical services. Services are typically composed of 1 attending and 2 to 3 residents caring for an average of 5 to 15 patients. Multidisciplinary family-centered rounding occurs for all patients, as described elsewhere.19,20 

Increased institutional focus on the discharge process came from the desire to improve throughput and patient satisfaction by improving discharge coordination. Our institutional leadership identified increasing difficulty with high census and limited bed availability leading to elective procedure cancellations and comments on patient and provider surveys noting an opportunity to improve discharge coordination. The concept of making a family-centered “discharge appointment” was inspired by a previous study that invited patients to collaborate on discharge time planning with the medical team.21  A multidisciplinary stakeholder steering committee of nurse managers, unit medical directors, resident physicians, the medical director of patient experience, patient and family advisors, and the chief medical and nursing officers of inpatient care developed the plans for the intervention. This group created the confirmed discharge time (CDT) designation as a means of communicating discharge planning among all providers and the patient and/or family, hypothesizing that clear, inclusive, prospective communication would facilitate earlier discharges.

Discharge timing, via the CDT, would be prospectively determined, typically during family-centered rounds discussion with families about anticipated medical readiness for discharge, transportation, and related logistics. The CDT was envisioned to be nonbinding and adjustable to accommodate changes in health status or new information and was not equivalent to a discharge order. All members of the health care team would be empowered to enter a CDT into the EHR, and throughout the intervention period, providers were encouraged to enter the CDT at any point of the hospitalization to help promote discharge planning. Broadly visible displays at nursing stations, provider workrooms, and pharmacy stations would be developed to encourage providers to organize and prioritize their relevant patient care tasks to plan discharge-related activities efficiently throughout their day. CDT would also be added to unit discharge status boards and incorporated into patient lists for ancillary service teams. By encouraging all relevant services (eg, consultants, pharmacy, physical therapy, home health, etc) to organize discharge work for multiple patients on the basis of a goal discharge time, the CDT could prevent perceived bottlenecks in the discharge process. Families were included in CDT designation most commonly on rounds and were updated directly by providers or nurses in case of CDT change. A key driver diagram22,23  (Supplemental Fig 2) illustrated the relationship between the desired outcome and the activities within this initiative.

Iterative plan-do-study-act (PDSA) cycles were used after baseline assessment and throughout ongoing monitoring of CDT use in real time. Improvement activities were designed by the multidisciplinary quality-improvement team on the basis of the perceived primary drivers of CDT use from a convenience sample of stakeholder feedback presented at steering committee meetings and quarterly hospital leadership meetings.

Phased improvements included the following:

  1. Provider education: CDT designation was made available in the EHR and implemented with recurrent messaging to inpatient providers via e-mail bulletins, presentations to inpatient divisions by stakeholder members, presentations to nurse unit councils and residency meetings, and reminders at departmental meetings.

  2. Provider feedback: Public dissemination of individual physician performance against the measures (percentage of patients discharged with CDT and percentage of discharges by noon) was sent by e-mail to all physicians every 2 weeks.

  3. EHR modification: A default CDT column in resident-provider patient lists was added, and the EHR discharge workflow was modified to include a prompt for CDT.

All inpatient or observation status discharges from any unit in the children’s hospital were included in analyses. Using the Model for Improvement framework, process, outcome, and balancing measures were identified.22 

The process measure of interest was CDT use (defined dichotomously as entry of a confirmed discharge date and time by using the CDT designation), at least 30 minutes before the patient leaves his or her hospital room. The 30-minute threshold was a consensus-based decision based on an amount of time the quality-improvement team believed was the minimum duration that the designation could practicably facilitate coordination among providers or arrange for transportation. For patients with multiple CDTs entered during their stay, the final CDT was used.

The outcome measures were (1) the proportion of discharges before noon, defined as the total number of discharges between 6 am and 12 pm on a calendar date (numerator) divided by the total number of discharges (denominator), and (2) the discharge time. Discharge time was normally distributed and therefore summarized with the mean (SD). Our balancing measure was LOS, defined as the number of hours from admission to discharge. LOS was chosen to test for a potential unintended consequence of delaying discharge to the following day to count as a discharge before noon.24  Because LOS was not normally distributed, it was summarized with the median and interquartile range (IQR). Measures were aggregated throughout the intervention in twice-monthly increments and reflected all discharges during the period.

Statistical process control p-charts were used to monitor changes in the proportion of discharges with CDT use and of discharges before noon. Established rules for identifying special cause variation25,26  were applied. We considered 8 consecutive points above or below the centerline as well as any points outside the control limits to represent special cause variation and prompt a change in the centerline, as suggesting statistically significant changes.26,27 

Descriptive statistics evaluated differences in demographics (age, sex, race and/or ethnicity, primary language, and payer category) and outcome and balancing measures throughout PDSA cycles. χ2 analysis was used to detect differences in proportions, and t tests or Wilcoxon rank tests were used for differences in means or medians for continuous variables, respectively. Logistic regression models explored univariate relationships between CDT use and demographic characteristics and discharge before noon. P < .05 was considered significant. Statistical analyses were conducted in SAS version 9.4 (SAS Institute, Inc, Cary, NC).

This quality-improvement study was considered exempt by the University of Wisconsin–Madison School of Medicine and Public Health’s institutional review board.

During the quality-improvement period (April 1, 2013–March 31, 2017), 20 133 children were discharged from our institution, with 20.5% of discharges occurring during the baseline period, 25.4% after the provider education, 30.8% after provider feedback, and 23.3% after EHR modification. Patient characteristics were similar throughout all PDSA phases, as summarized in Table 1. Most patients were non-Hispanic white (77.4%) and English speaking (96.0%). Nearly two-thirds had a primary private payer.

TABLE 1

Selected Characteristics of Pediatric Discharges Over the Study Period

CharacteristicPDSA Phase
Baseline (April 1, 2013–March 31, 2014)Provider Education (April 1, 2014–March 15, 2015)Provider Feedback (March 16, 2015–May 10, 2016)EHR Modification (May 11, 2016–March 31, 2017)
Discharges, No. (%) 4132 (20.5) 5120 (25.4) 6197 (30.8) 4684 (23.3) 
Age, median (IQR) 5.62 (1.45–2.82) 5.99 (1.67–2.61) 6.00 (1.56–12.86) 6.24 (1.67–13.37) 
Female sex, No. (%) 1850 (44.8) 2326 (45.4) 2714 (43.8) 2012 (43.0) 
Race and/or ethnicity, No. (%)     
 White, non-Hispanic 3050 (73.8) 3859 (75.4) 4696 (75.8) 3565 (76.1) 
 African American, non-Hispanic 409 (9.9) 478 (9.3) 539 (8.7) 399 (8.5) 
 Hispanic 410 (9.9) 451 (8.8) 584 (9.4) 442 (9.4) 
 Other 263 (6.4) 332 (6.5) 378 (6.1) 278 (5.9) 
Payer category, No. (%)     
 Public 1388 (33.6) 1749 (34.2) 2172 (35.1) 1695 (36.2) 
 Private 2700 (65.3) 3338 (65.2) 3970 (64.1) 2917 (62.3) 
 Other 44 (1.1) 33 (0.6) 55 (0.9) 72 (1.5) 
Primary language is English, No. (%) 3990 (96.6) 4910 (95.9) 5958 (96.1) 4467 (95.4) 
CharacteristicPDSA Phase
Baseline (April 1, 2013–March 31, 2014)Provider Education (April 1, 2014–March 15, 2015)Provider Feedback (March 16, 2015–May 10, 2016)EHR Modification (May 11, 2016–March 31, 2017)
Discharges, No. (%) 4132 (20.5) 5120 (25.4) 6197 (30.8) 4684 (23.3) 
Age, median (IQR) 5.62 (1.45–2.82) 5.99 (1.67–2.61) 6.00 (1.56–12.86) 6.24 (1.67–13.37) 
Female sex, No. (%) 1850 (44.8) 2326 (45.4) 2714 (43.8) 2012 (43.0) 
Race and/or ethnicity, No. (%)     
 White, non-Hispanic 3050 (73.8) 3859 (75.4) 4696 (75.8) 3565 (76.1) 
 African American, non-Hispanic 409 (9.9) 478 (9.3) 539 (8.7) 399 (8.5) 
 Hispanic 410 (9.9) 451 (8.8) 584 (9.4) 442 (9.4) 
 Other 263 (6.4) 332 (6.5) 378 (6.1) 278 (5.9) 
Payer category, No. (%)     
 Public 1388 (33.6) 1749 (34.2) 2172 (35.1) 1695 (36.2) 
 Private 2700 (65.3) 3338 (65.2) 3970 (64.1) 2917 (62.3) 
 Other 44 (1.1) 33 (0.6) 55 (0.9) 72 (1.5) 
Primary language is English, No. (%) 3990 (96.6) 4910 (95.9) 5958 (96.1) 4467 (95.4) 

Mean CDT use increased from no use during the baseline period to use in 42% of discharges after initial implementation in the provider education phase. Little sustained change in CDT use was observed during the provider feedback phase. EHR modification was associated with an increase in mean CDT use, from 38% to 62%, with special cause variation observed immediately after the intervention (Fig 1).

FIGURE 1

A, Percent of discharges with CDT. B, Percent of those discharged from the hospital before noon.

FIGURE 1

A, Percent of discharges with CDT. B, Percent of those discharged from the hospital before noon.

Close modal

The proportion of discharges before noon also increased, with special cause variation observed after initial implementation. The absolute increase in discharges before noon between baseline and post–EHR modification was 6.2%, corresponding to a relative increase of 31% (P < .001; Table 2). LOS decreased from 47 to 43 hours (P < .001), with a decrease of 3 hours seen after initial implementation.

TABLE 2

Outcome Measures During Each Phase of the Study Period With Statistically Significant Differences Between the Baseline and Final Phase for Each Measure

MeasurePDSA Phase
BaselineProvider EducationProvider FeedbackEHR ModificationP
CDT, No. (%) 17 (0) 2141 (41.8) 2329 (37.6) 2881 (61.5) <.001 
Discharge time, mean (SD) 14:39:53 (2:59:37) 14:15:25 (3:04:27) 14:15:58 (2:57:41) 14:15:36 (2:59:14) <.001 
Discharge before noon, No. (%) 823 (19.9) 1284 (25.1) 1531 (24.7) 1220 (26.1) <.001 
LOS, median (IQR) 47 (25–95) 44 (24–89) 42 (24–86) 43 (24–88) <.001 
MeasurePDSA Phase
BaselineProvider EducationProvider FeedbackEHR ModificationP
CDT, No. (%) 17 (0) 2141 (41.8) 2329 (37.6) 2881 (61.5) <.001 
Discharge time, mean (SD) 14:39:53 (2:59:37) 14:15:25 (3:04:27) 14:15:58 (2:57:41) 14:15:36 (2:59:14) <.001 
Discharge before noon, No. (%) 823 (19.9) 1284 (25.1) 1531 (24.7) 1220 (26.1) <.001 
LOS, median (IQR) 47 (25–95) 44 (24–89) 42 (24–86) 43 (24–88) <.001 

Receiving a CDT was associated with being discharged before noon (odds ratio: 1.11; 95% confidence interval: 1.04–1.20). Discharges for younger, female, non-Hispanic African American, or publicly insured patients were associated with small but statistically significantly higher odds of having a CDT designation (Table 3).

TABLE 3

Univariate Associations Between Patient Characteristics and CDT Designation Throughout the Study Period

Patient CharacteristicOdds Ratio95% Confidence IntervalP
Age, y 0.98 0.98–0.99 <.0001 
Female sex 1.07 1.00–1.15 .05 
Race (reference: white)    
 African American 1.17 1.04–1.32 .01 
 Hispanic 0.99 0.88–1.11 .86 
 Other 1.10 0.95–1.26 .19 
Payer (reference: public or other)    
 Private 0.87 0.81–0.94 <.001 
Discharged before noon 1.11 1.04–1.20 <.01 
Patient CharacteristicOdds Ratio95% Confidence IntervalP
Age, y 0.98 0.98–0.99 <.0001 
Female sex 1.07 1.00–1.15 .05 
Race (reference: white)    
 African American 1.17 1.04–1.32 .01 
 Hispanic 0.99 0.88–1.11 .86 
 Other 1.10 0.95–1.26 .19 
Payer (reference: public or other)    
 Private 0.87 0.81–0.94 <.001 
Discharged before noon 1.11 1.04–1.20 <.01 

Implementation of a prospective, family-centered discharge time designation in the EHR was associated with improvement in the proportion of discharges before noon without prolonging LOS. This feasible set of interventions required modest alterations in EHR discharge workflows and relatively few resources.

Our results are consistent with previous studies describing quality-improvement interventions to improve discharge timing.3,8,9,12  However, our work is distinct because previously published interventions required complex system change and substantial resource commitment (eg, additional attending physician weeks on service, extensive changes to discharge workflows, new huddles and rounding routines, and changes in patient geography).3,8,9,12  In contrast, our CDT designation leveraged preexisting EHR functionality, and implementation resources were limited to time for quality-improvement meetings and educational sessions (estimated 20 hours), the generation of reports (estimated 2 hours weekly), and a 1-time modification to an EHR discharge workflow (estimated 5 hours). One challenge we acknowledge was that although the interventions required relatively few resources, the pace for each PDSA cycle was slower than we desired. Reasons for the slower pace included the institutional scale (ie, whole-system change) and the stakeholder approval processes needed to implement each PDSA intervention.

Our findings contribute to the evidence base about types of system-level interventions that may enhance discharge coordination. For example, provider education, which may be necessary,28,29  was insufficient to sustainably influence process uptake. After education in our initiative, CDT entry increased and peaked at ∼60%; however, declines were observed within 6 months. In particular, although past research suggests that public reporting of individual performance might be an effective method to motivate provider behavior change,30,31  this was not observed in our study. Instead, we observed that public auditing and reporting of attending-provider performance was associated with essentially static levels of CDT use. It is possible that many academic attending providers did not feel a strong sense of ownership for discharge processes largely performed and coordinated by trainees and advanced practice practitioners. Compared with more directly applicable safety and quality measures, attending providers may not have felt as competitive about this measure. In addition, awareness may have been limited if they did not open performance reports attached to e-mail notifications.

Modifications to the discharge provider EHR workflow were associated with the largest sustained process gains. The introduction of a default CDT column in EHR-generated patient lists and a CDT prompt in the discharge process within the EHR were associated with the highest sustained levels of CDT use. This observation complements a recent pediatric quality-improvement study in which the combination of provider education and EHR-linked reminders improved medication reconciliation on admission.32  To further improve CDT use, next steps should focus on understanding and targeting root causes for not using the designation. We speculate that a focus on empowering multidisciplinary team members, including nurses, families, and other providers, to enter CDT may be a promising next PDSA cycle. Anecdotally, we suspect inpatient nurses have a firm understanding of discharge readiness and thus may be an ideal group to target for increased participation in CDT entry and to prompt discussion about CDT on rounds.

Although our primary outcome was discharge timing, we believe CDT use may have other potential benefits that were not studied. The concept of collaboratively developing a transparent discharge time goal that all care team members and families can see has inherent face validity. This designation was also chosen because we anticipated it would help all team members set daily priorities. For example, we expected pharmacists to prioritize and plan tasks, including medication reconciliation and filling discharge prescriptions, on the basis of who was nearing discharge time.

Moreover, hospital capacity backlogs can inflate staffing needs and influence overall hospital spending. A formal cost-effectiveness analysis was beyond the scope of this study. We estimated that the improvements in discharge timing observed from this work would translate to reductions of ∼$64 000 per year in nurse staffing costs; however, several potential mechanisms could link earlier discharge to improved efficiencies extending beyond shorter LOS and lower staffing. Higher-value care might plausibly be achieved by improving throughput, and therefore access, to accommodate patients waiting for beds. For example, discharging patients earlier in the day opens beds for patients awaiting admission, transfer, and elective surgeries and procedures.4,33,34  Developing methods to reliably and validly quantify the financial impact of more efficient discharges across health systems is an important next step.

Future research on CDT designation should focus on these and other coordination outcomes (eg, readiness for discharge).3537  We expect that both discussing discharge timing with families and discharging families more efficiently could positively influence the patient experience. We would like to explore patient and family perspectives more generally on use of the CDT. As an initial step, these results are being brought back to our patient and family advisory councils to suggest additional PDSA interventions that bring the most value from the family perspective. A more proactive, coordinated, and transparently planned discharge might facilitate safer and more precise transitional care, such as ensuring follow-up appointments, medications, pending tests, and other psychosocial needs are met as well as educating and performing teach-back with families. Each of these concepts would benefit from inclusion in subsequent work.

Our study has several important limitations. As a quality-improvement study at a single center, firm conclusions cannot be drawn about causal relationships between our intervention and outcomes. Our findings may not generalize to other settings, and implementation may be limited by different EHR capabilities at other institutions. Qualitative data to explore why CDT was used for some children and not for others would be valuable to inform our next PDSA cycles. The evaluation design was intentionally at the system level, and therefore, we did not explore all possible relationships between both having a CDT and being discharged earlier. For example, we were not able to attribute the role of the provider who entered the CDT. Follow-up research should attempt to tease apart the relationship between when it is most useful to place CDT and when it translates to more efficient discharge. Our data do suggest that patient characteristics may have influenced CDT use. Subsequent work will focus on the patient38  and provider levels and more fully evaluate predictors of CDT use and discharge timing.

Lastly, there were limitations of the contextual data we have to interpret these results. Future analyses should evaluate whether these improvements facilitate a larger proportion of patients being discharged when they are medically ready as opposed to (or in addition to) being discharged earlier. Broader balancing measures might have identified unanticipated consequences from CDT use. For example, if the CDT was used but changed frequently, families and multidisciplinary providers could have become confused or frustrated. We do not know the extent to which CDT use actually influenced ancillary staff workflow and behavior. We did not investigate the influence of resident and nurse turnover occurring throughout the intervention periods. Although we are not aware of any simultaneous activities, competing interventions or trends could have influenced discharge timing separate from the intervention activities we evaluated.

Despite these limitations, our study describes a feasible intervention to improve visible sharing of a family-centered and prospective discharge time in the EHR. The goal to proactively establish for families and the entire health care team the time at which a patient is likely to leave the hospital is an important element of coordinated discharge care. This transparent, family-centered process may lead to earlier discharge and more efficient hospital throughput.

Drs Sklansky, Butteris, and Coller conceptualized and designed the study, conducted primary data analysis and interpretation, and drafted the initial manuscript; Drs Shadman, Kelly, Edmonson, Webber, Ehlenbach, Barreda, Nackers, Allen, Hoffman, and Tiedt and Ms Smith critically interpreted data analyses and critically revised the manuscript; Ms Thurber and Ms Zhao assisted with data collection, conducted primary data analysis, and critically reviewed the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

CDT

confirmed discharge time

EHR

electronic health record

IQR

interquartile range

LOS

length of stay

PDSA

plan-do-study-act

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

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