Critical Success Factors for Addressing Discharge Inefficiency at a Large Academic Medical Center: A Lean Six Sigma Approach : Journal of Nursing Care Quality

Secondary Logo

Journal Logo


Critical Success Factors for Addressing Discharge Inefficiency at a Large Academic Medical Center

A Lean Six Sigma Approach

Feldman, Sue S. PhD, MEd, RN; Kennedy, Kierstin Cates MD, MSHA, FACP, SFHM; Nafziger, Sarah M. MD, MSHA; Orewa, Gregory N. MSc, MBA, LNHA; Kpomblekou-Ademawou, Enyonam LSSGB; Hearld, Kristine Ria PhD; Hall, Allyson G. PhD

Author Information
Journal of Nursing Care Quality 37(2):p 135-141, April/June 2022. | DOI: 10.1097/NCQ.0000000000000591



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


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.


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


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.


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.

The challenges with discharging patients on time have been well documented in the literature.1–4 On-time discharge can be specifically defined by considering the operational dependencies unique to an organization; however, much of the literature references discharge before noon (DBN) as the standard for on-time discharge.5–15

The discharge process is complex, the challenges are multifaceted, and contributing factors are rarely isolated. Ideally, patient discharge planning begins when a patient is admitted, when there is time to consider multiple critical processes throughout the patient stay.16,17 Advocates for DBN posit that early discharge planning contributes to improved patient outcomes,5,6 better quality of life,7 enhanced hospital throughput logistics,8,17 and organizational financial management.9,10

Researchers and performance improvement specialists at a large academic medical center in the south sought to understand the systemic factors contributing to discharge inefficiencies at the institution. They took a process improvement approach to identifying factors that might lead to improvements in discharge efficiency across the health system. The system offers a wide array of services to low-income, un- or underinsured, medically complex people with more than 130000 emergency department (ED) visits annually and more than 86000 inpatient visits annually.


Existing literature shows that ineffective discharge planning is a significant issue that exacerbates the problem of patient discharge.18 Discharge plans that lack a systematic approach, structure, management, effective communication, and advocacy create an environment where consistency, sustainability, and scalability around processes cannot be operationalized to allow for measurement around performance improvement. The complexity of the discharge processes involves not just a physician order but also other physicians, nurses, patients and their families, care and bed coordination, transport, pharmacy, physical therapy, laboratory, consultants, and various other parties. Communication across these lines is oftentimes fractured, leading to incomplete discharge plans and delays in discharge.19


Delayed discharges can be a systemic issue requiring a multidisciplinary team approach for consistent, sustainable, and scalable solutions to be effective and efficient. Delayed discharges could lead to patient dissatisfaction, higher employee turnover resulting from staff burnout, poor health outcomes, and increased labor costs. The cost associated with delayed discharge includes costs of patients occupying a bed after they are medically fit for discharge, the cost associated with increased use of supplies, labor costs, and administrative costs. The cost of delayed discharge also includes unit-level (eg, length of stay [LOS] or infection costs, increased ED boarding, or canceled operations), organizational, and local system-level impacts.20


Ensuring a multidisciplinary approach has been shown to improve the percentage of patients DBN, decrease discharge order time, decrease LOS, and lower average readmission rate.13,14,19,21–25 A multidisciplinary approach is best operationalized through multidisciplinary rounds,13 with structured daily communication among crucial members of the patient's care team (eg, nurses, physicians, case managers [CMs], social workers [SWs], pharmacists, rehabilitation services, and family) facilitating proactive discharge planning and preparation.22,25

Some organizations have reported DBN success by implementing a single-piece flow approach, borrowed from Lean processes in manufacturing and adapted to health care.26 Single-piece flow is appropriate when processes are predictable and repeatable. In other words, patients who are to be discharged move through the discharge flow individually instead of collectively (ie, waiting until several patients are ready for discharge before discharging any of them individually).27 Although organizations are implementing processes to address various DBN initiatives, organizations report inconsistent achievement in reaching their targets.13,23 These inconsistencies have led organizations to redesign discharge processes further and consider aggregating approaches across the organization. Single-piece flow was used to reduce discharge turnaround time from 2.2 to 1.7 hours, a time savings of 22.7%.26

Another study focused on a defined rounding standard whereby rounds on patients to be discharged are done at the start of the morning, and all necessary discharge work and patient instructions are done at the bedside.23 Team leadership meetings have been shown to be crucial to setting clear discharge expectations and identifying areas of process failure through discussions and documentation of previous day discharges.14 During such meetings, current day discharges are also reviewed to identify challenges with meeting the goal of DBN.23,26 Findings from this approach, when used in isolation of other approaches, suggest that there is more communication breakdown than perceived and that teams seem to function in their own silos.23,26

Because discharge delays are often thought to be a systemic issue, it is essential to consider a system-level approach when identifying root causes and enacting initiatives addressing discharge efficiency. Addressing it on a system level will involve multiple levels of intervention and a well-structured protocol by a multidisciplinary team on the discharge of patients. It is opined that implementing an efficient and realistic discharge planning process would bring about a decrease in the LOS of patients and reduce the readmission rate to the hospital.10 It is also believed that this would lower operating costs of the hospital and ensure the continuity of care in the community, improve patients' mental health, patient satisfaction with members of the care team, reduce diseases incident, and allow for a safer patient transition to home.10


Lean and Six Sigma (LSS) approaches have been well established for process improvement in manufacturing. Experts in process improvement have merged the two to create LSS, which aims to improve health care quality in terms of outcomes and processes. LSS as a method to improve outcomes28–30 and process30–34 of care has seen favorable results in health care. LSS is the combination of (1) tools and analytic techniques to identify problems (discovery) and solve (implementation) problems, (2) phased problem-solving to identify the root cause (discovery) and phased implementation (implementation), and (3) a culture of quality to identify optimal operations performance (discovery) and continuous process improvement (implementation). The 5-phase DMAIC method is often used within LSS approaches: this method includes (1) Define (what is the problem to be improved), (2) Measure (what is the magnitude of the problem), (3) Analyze (what is the root cause of the problem), (4) Improve (what are the viable solutions), and (5) Control (how do we maintain continuous process improvement).

This project reports on the first 3 phases of the LSS DMAIC process: define, measure, and analyze to understand contributing factors to discharge inefficiencies at the academic medical center (see Supplemental Digital Content Figure 1, available at: The article focuses on the output of the LSS DMAIC process, an often underanalyzed and not published critical contributor to the overall outcome. As such, the implementation elements are not addressed in this project.


Direct observation methods were used to identify factors contributing to discharge inefficiencies. Observational exploratory methods are appropriate as they are often used in social and medical research to facilitate inductive observation of symptoms or systems and to gain a deeper understanding of those symptoms or systems.35 Specifically, DMAIC was used as an LSS method. Process validation, considered essential in process redesign, was accomplished through focus groups, value stream map (VSM) feedback, and observations.36 Observers were not given any special training for this observation; however, those doing the observations were skilled in documenting workflows.

The setting for this project was an adult medical-surgical floor at the University of Alabama at Birmingham Health System (UABHS). This unit was chosen because the patient population is representative of the population across the system: socially complex with multiple comorbidities and their willingness to participate in observations. Ten observations were conducted by 5 observers (2 observations each) in 4-hour intervals (40 total observation hours) prior to and during postdischarge peak hours. There was no overlap of observations, meaning that each observation was conducted by a single observer. While it was known that observations were occurring, the observer would do so at a distance so as not to interrupt or otherwise slow down normal processes and workflows. After the observations, a debriefing session was held with those on the unit, some of which included those who participated in the observations, to discuss and verify workflows, barriers, and opportunities for improvement observed.

The Define phase included determining the current state of the unit including barriers, expectations of each role, and the overall non-value and non–value-added processes, and overall deliverables for the discharge efficiency project. We also established standardized communication practices. Project stakeholders were identified as leaders and staff on the unit. To create a shared understanding of the process and to inform analysis, discharge scenarios were discussed.

The Measure phase included establishing the magnitude of the discharge efficiency issue and what data were available for the team to access. More specifically, the discharge by 1 pm rate for the 12-month period prior to this project was 31.6%. Through discussion, the measure for discharge efficiency was agreed to be 50% discharged by 1 pm.

The Analyze phase included a team of 5 individuals from quality and process improvement, each of whom conducted 2 rounds of generalized observations (n = 10 observations). In addition, 6 key process stakeholder roles were identified: medical doctor (MD), SW, CM, registered nurse (RN), advanced practice providers, and occupational, speech, and physical therapy, respectively.


Results from the observations and the communications are reported collectively on the first 3 phases—define, measure, and analyze—of the process. Overall, we found that standardization and communication across each phase were critical.


We defined better capacity management as the operation to be improved with on-time discharges as the highest-impact component to capacity management (ie, alignment of bed supply with bed demand). We also identified that our performance on discharge turnaround time was 3 hours and that discharge orders are typically signed by 10 am. As noted, while the literature suggests DBN as the definition of early discharge, our institution elected to set discharge by 1 pm as the definition of early discharge. The observations suggest that most activity regarding patient discharge occurred before 1 pm and specifically during the time of transition of care rounds. This was important to inform some of the process measures.


As mentioned, our goal was to have 50% of the patients discharged by 1 pm. Therefore, discharge efficiency was our process measure (percentage of patients leaving by 1 pm/50%), LOS was our balancing measure (inpatient days/goal inpatient days), and ED boarding hours was our outcome measure (time interval from when the ED requests an inpatient bed until the patient occupies the inpatient bed). As a combined discharge efficiency metric to measure process and balance simultaneously, we took the arithmetic average of the process and balance measures.


One of the outputs of the observations was an accurate depiction of the discharge process workflow, barriers, and opportunities for improvement. It was especially noteworthy if the process, barrier, or opportunity for improvement involved multiple roles. For example, it was noted that transition of care rounds involved all roles and typically last 20 minutes. However, the timing of these rounds precluded some roles from attending as it presented a conflict with other responsibilities.

Value stream mapping

A modified VSM was constructed to outline the current state by identifying and confirming bottlenecks (see Supplemental Digital Content Figure 2, available at: This modified VSM was used with the goal of forming a blueprint to identify areas of improvement by exposing the source of waste and linking the flow of information together. The VSM session included walking participants through the workflow of each role (designated by a separate color), the work breakdown analysis, and process map. To reduce bias, the roles were not briefed on the findings of the observations prior to the VSM session. There was no overview of the barriers and disruptors noted during time of observation, but they were confirmed after the participants were given the opportunity to vocalize their concerns of patient safety, discharge, and common workplace barriers. On the VSM itself, the participants had the opportunity to correct the workflow and disruptors. This resulted in discharge process steps and disruptors being added, deleted, or rearranged to depict the workflow more accurately. Because the VSM session involved participants who were not involved in the observations, this provided a critical process validation point regarding the workflows, barriers, and opportunities for improvement.

Role-specific process variation, miscommunication of information that is pertinent to patient discharge among roles, and insufficient patient-provider accountability were current state factors in the success of discharge by 1 pm. It was also noted that actual discharge orders contain their own variability. For example, whereas the resident may input the order at 9:30 am, the order may not be signed off by the attending until 3 pm, causing an unnecessary delay in discharge.

Communication systems

The participants identified 8 communication systems were being used. The most common system was used for communicating the patient's disposition across disciplines in relation to their care plan and scheduling postdischarge arrangements. From the communication systems, 11 transactional systems for collecting and receiving data were found and were analyzed to how often they were utilized in specific process steps by each role. Since the communication and transaction systems are likely unique to UABHS, they are not delineated here. However, it is important to note that these systems were examined as to their contribution toward facilitating or impeding discharges.


Disruptors to the discharge process were identified and validated. Kaizen bursts are small, short-duration, rapid process improvement initiatives to solve a particular problem. In Supplemental Digital Content Figure 2 (available at:, these are represented by starburst icons. These bursts were the most frequent disruptors to the discharge process, particularly for the RN and the MD. Absent Kaizen Bursts, phone (primarily for the SW), and paging (primarily for the CM, Pharmacy, and SW) were most disruptive to the discharge process.

Unique role challenges

Results suggest that the SW and nursing have unique challenges that are specific to their roles. Charting, phone calls, redundant processes, and disparate communication systems were found to add to discharge delays. In addition to challenges shared by the SW, the RN faces additional challenges. This unit receives many overflow admissions meant for other units that are full, perhaps due to discharge inefficiencies on those units.

Prioritization matrix

A prioritization matrix is helpful in plotting process improvement elements on 1 page and providing visualization for all stakeholders. When a prioritization matrix is created as a group exercise, it fosters an environment of stakeholder weigh-in, mitigating opposition on which process improvement elements are more important. Since the Kaizen bursts were noted to be most disruptive to the discharge process flow, a prioritization matrix was used to map the Kaizen bursts and prioritize process improvement relative to those thought to be easiest to address and with the most impact. Supplemental Digital Content Figure 3 (available at: illustrates the mapped prioritization matrix. The x axis represents the ease of implementation, and the y axis represents the perceived impact. The prioritization matrix is presented in 4 quadrants, with high and low serving as indicators for the axes. The goal of the matrix was to illustrate feasible actions that would provide high impact and value and be easy to implement. A total of 14 Kaizen bursts were leveraged as opportunities for improvement for the unit.


Given that discharge delays can contribute to patient outcomes,5,6 quality of life,7 throughput logistics,8,17 and hospital financial management,9,10 many hospitals are turning to structured process improvement methods as a mechanism to increase the consistency by which patients are discharged early in the day.

Overall, our findings were consistent with the literature that establishing consistent multidisciplinary team communication processes was a contributing factor to reducing the inefficiencies around discharges.13,19,25 While much of this was accomplished during transition of care rounds first thing in the morning,23 the use of disparate communication systems across the health system resulted in siloed communications for the care team. As suggested in the literature,26 aggregating approaches by aligning process flows together were identified in the VSM as an opportunity for improvement. Because this article reports on the process, there are no results on the outcome of aggregating approaches.

Utilizing process validation methods described in the literature provided direction for specific process improvement activities.36 In addition, participants were able to modify the VSM for increased accuracy and ensure that all perspectives were represented. It is important to note that had we been reliant on the literature in suggesting that DBN as the standard for on-time discharge,1–4 we likely would have failed before we even began. Critical to our process was respecting our current workflows and making a simple 1-hour adjustment. These findings have implications to other organizations working on discharge efficiency. For example, a thorough understanding of organizational nuances that contribute to current workflows is an important foundational concept.

Key barriers include disparate communication systems, disruptors, specifically Kaizen bursts, and unique role challenges. Critical success factors include (in sequence) (1) identifying leaders, (2) charter creation, (3) application of DMAIC for a clear and shared understanding of the process, (4) documentation of processes through observation resulting in changing DBN to 1 pm, (5) all-inclusive VSM comment sessions, (6) prioritization matrix, and (7) clear separation of the discovery and implementation phases. In Supplemental Digital Content Figure 4 (available at:, we apply the findings to the conceptual framework originally presented in Supplemental Digital Content Figure 1 (available at:


Although this project provided valuable information to the organization, there are several limitations that may limit its generalizability. First, this project was conducted at an academic medical center. Other organizations may not have resources with which to initiate process improvement of this level. Second, ideally, there would be multiple observations of the same person by a different observer—then the 2 observers would compare notes. Finally, the unit used is known for its inherent culture of quality, one of the critical success factors in LSS. Other units may need to address culture change simultaneously to implementing process improvement. It is noteworthy that this article reports on the output of a process, an area of analyses in process improvement projects often overlooked. However, it creates a limitation in that the last 2 processes include implementation and control; therefore, we are uncertain what else might arise in the last part of the process.


In this article, we described and applied a framework for addressing discharge inefficiencies. In so doing, we presented findings from a current initiative related to having a process in place to understand systemic barriers that were impacting our ability to consistently discharge our patients by noon. Process findings suggest key barriers and critical success factors in the problem discovery phase of process improvement around discharge efficiency. 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. Future research on this project involves implementation and control on this unit. The goal would be that constant refinement of this framework and process leads to a blueprint that would then be generalizable to any health care organization.


1. Harrison JD, Greysen RS, Jacolbia R, Nguyen A, Auerbach AD. Not ready, not set discharge: patient-reported barriers to discharge readiness at an academic medical center. J Hosp Med. 2016;11(9):610–614. doi:10.1002/jhm.2591
2. Jacobs-Wingo JL, Cook HA, Lang WH. Rapid patient discharge contribution to bed surge capacity during a mass casualty incident: findings from an exercise with New York City hospitals. Qual Manag Health Care. 2018;27(1):24–29. doi:10.1097/0000000000000161
3. Meo N, Liao JM, Reddy A. Hospitalized after medical readiness for discharge: a multidisciplinary quality improvement initiative to identify discharge barriers in general medicine patients. Am J Med Qual. 2020;35(1):23–28. doi:10.1177/1062860619846559
4. Zeppieri KE, Butera KA, Iams D, Parvataneni HK, George SZ. The role of social support and psychological distress in predicting discharge: a pilot study for hip and knee arthroplasty patients. J Arthroplasty. 2019;34(11):2555–2560. doi:10.1016/j.arth.2019.06.033
5. Lim SC, Doshi V, Castasus B, Lim JK, Mamun K. Factors causing delay in discharge of elderly patients in an acute care hospital. Ann Acad Med Singap. 2006;35(1):27–32.
6. Hendy P, Patel JH, Kordbacheh T, Laskar N, Harbord M. In-depth analysis of delays to patient discharge: a metropolitan teaching hospital experience. Clin Med (Lond). 2012;12(4):320–323. doi:10.7861/clinmedicine.12-4-320
7. Salmani S, Imanipour M, Nasrabadi AN. The implementation of a discharge planning to improve quality of life in breast cancer patients: a quasi-experimental study. Arch Breast Cancer. 2018;5(4):163–167. doi:10.32768/abc.201854163-167
8. Majeed MU, Williams DT, Pollock R, et al. Delay in discharge and its impact on unnecessary hospital bed occupancy. BMC Health Serv Res. 2012;12(1):410. doi:10.1186/1472-6963-12-410
9. Pieper B, Sieggreen M, Freeland B, et al. Discharge information needs of patients after surgery. J Wound Ostomy Continence Nurs. 2006;33(3):281–289; quiz 290-291. doi:10.1097/00152192-200605000-00009
10. Shepperd S, Lannin NA, Clemson LM, McCluskey A, Cameron ID, Barras SL. Discharge planning from hospital to home. Cochrane Database Syst Rev. 2013;(1):CD000313. doi:10.1002/14651858.CD000313.pub4
11. Rachoin JS, Aplin KS, Kupersmith E, et al. Discharge before noon: is the sun half up or half down? Am J Manag Care. 2020;26(8):e246–e251. doi:10.37765/ajmc.2020.44074
12. Rajkomar A, Valencia V, Novelero M, Mourad M, Auerbach A. The association between discharge before noon and length of stay in medical and surgical patients. J Hosp Med. 2016;11(12):859–861. doi:10.1002/jhm.2529
13. Kane M, Weinacker A, Arthofer R, et al. A multidisciplinary initiative to increase inpatient discharges before noon. J Nurs Adm. 2016;46(12):630–635. doi:10.1097/NNA.0000000000000418
14. Wertheimer B, Jacobs RE, Bailey M, et al. Discharge before noon: an achievable hospital goal. J Hosp Med. 2014;9(4):210–214. doi:10.1002/jhm.2154
15. Wertheimer B, Jacobs RE, Iturrate E, Bailey M, Hochman K. Discharge before noon: effect on throughput and sustainability. J Hosp Med. 2015;10(10):664–669. doi:10.1002/jhm.2412
16. Pirani SSA. Prevention of delay in the patient discharge process: an emphasis on nurses' role. J Nurses Staff Dev. 2010;26(4):E1–E5. doi:10.1097/NND.0b013e3181b1ba74
17. Khanna S, Sier D, Boyle J, Zeitz K. Discharge timeliness and its impact on hospital crowding and emergency department flow performance. Emerg Med Australas. 2016;28(2):164–170. doi:10.1111/1742-6723.12543
18. Hesselink G, Zegers M, Vernooij-Dassen M, et al. Improving patient discharge and reducing hospital readmissions by using intervention mapping. BMC Health Serv Res. 2014;14(1):389. doi:10.1186/1472-6963-14-389
19. Patel H, Yirdaw E, Yu A, et al. Improving early discharge using a team-based structure for discharge multidisciplinary rounds. Prof Case Manag. 2019;24(2):83–89. doi:10.1097/NCM.0000000000000318
20. Rojas-García A, Turner S, Pizzo E, Hudson E, Thomas J, Raine R. Impact and experiences of delayed discharge: a mixed-studies systematic review. Health Expect. 2018;21(1):41–56. doi:10.1111/hex.12619
21. McGowan JE, Truwit JD, Cipriano P, et al. Operating room efficiency and hospital capacity: factors affecting operating room use during maximum hospital census. J Am Coll Surg. 2007;204(5):865–871; discussion 871-872. doi:10.1016/j.jamcollsurg.2007.01.052
22. Kane M, Rohatgi N, Heidenreich P, et al. Lean-based redesign of multidisciplinary rounds on general medicine service. J Hosp Med. 2018;13(7):482–485. doi:10.12788/jhm.2908
23. Beck MJ, Okerblom D, Kumar A, Bandyopadhyay S, Scalzi LV. Lean intervention improves patient discharge times, improves emergency department throughput and reduces congestion. Hosp Pract (1995). 2016;44(5):252–259. doi:10.1080/21548331.2016.1254559
24. Artenstein AW, Rathlev NK, Neal D, et al. Decreasing emergency department walkout rate and boarding hours by improving inpatient length of stay. West J Emerg Med. 2017;18(6):982–992. doi:10.5811/westjem.2017.7.34663
25. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428–436. doi:10.1136/bmjqs-2013-002556
26. El-Eid GR, Kaddoum R, Tamim H, Hitti EA. Improving hospital discharge time: a successful implementation of Six Sigma methodology. Medicine (Baltimore). 2015;94(12):e633. doi:10.1097/MD.0000000000000633
27. Jarvis PRE. Improving emergency department patient flow. Clin Exp Emerg Med. 2016;3(2):63. doi:10.15441/ceem.16.127
28. Griffin B, Cooper H, Horack C, Klyber M, Schimmelpfenning D. Best-practice protocols: reducing harm from pressure ulcers. Nurs Manage. 2007;38(9):29–32, 69. doi:10.1097/01.NUMA.0000289286.39557.b1
29. O'Donnell R, Kessler R. Quality improvement, performance management, and outcomes: Lean Six Sigma for integrated behavioral health. In: Machi CR, Kessler R, eds. Training to Deliver Integrated Care: Skills Aimed at the Future of Healthcare. Springer; 2018:79–101.
30. Murphy C, Mullen E, Hogan K, O'toole R, Teeling SP. Streamlining an existing hip fracture patient pathway in an acute tertiary adult Irish hospital to improve patient experience and outcomes. Int J Qual Health Care. 2019;31(suppl 1):45–51. doi:10.1093/intqhc/mzz093
31. Buck C. Application of Six Sigma to reduce medical errors. Paper presented at: 55th Annual Quality Congress proceedings—American Society for Quality Control; 2001; Charlotte, NC.
32. van den Heuvel J, Does RJ, Bogers AJ, Berg M. Implementing Six Sigma in the Netherlands. Jt Comm J Qual Patient Saf. 2006;32(7):393–399. doi:10.1016/s1553-7250(06)32051-x
33. Chassin R. The Six Sigma initiative at Mount Sinai Medical Center. Mt Sinai J Med. 2008;75(1):45–52. doi:10.1002/msj.20011
34. Agarwal S, Gallo JJ, Parashar A, et al. Impact of Lean Six Sigma process improvement methodology on cardiac catheterization laboratory efficiency. Cardiovasc Revasc Med. 2016;17(2):95–101. doi:10.1016/j.carrev.2015.12.011
35. Creswell JW, Poth CN. Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Sage Publications; 2016.
36. Mansar SL, Reijers HA. Best practices in business process redesign: validation of a redesign framework. Comput Ind. 2005;56(5):457–471.

discharge delay; discharge planning; Lean Six Sigma; patient discharge

Supplemental Digital Content

© 2021 Wolters Kluwer Health, Inc. All rights reserved.