Research ArticleUsing Six Sigma DMAIC Methodology and Discrete EventSimulation to Reduce Patient Discharge Time in King HusseinCancer Center

Mazen Arafeh ,1 Mahmoud A. Barghash,1 Nirmin Haddad ,1 Nadeem Musharbash ,1

Dana Nashawati ,2 Adnan Al-Bashir,3 and Fatina Assaf 2

1 e Department of Industrial Engineering, e University of Jordan, Amman, Jordan2King Hussein Cancer Center, Amman, Jordan3 e Department of Industrial Engineering, e Hashemite University, Zarqa, Jordan

Correspondence should be addressed to Mazen Arafeh; hfmazin@gmail.com

Received 18 December 2017; Revised 16 April 2018; Accepted 6 May 2018; Published 24 June 2018

Academic Editor: Antonio Gloria

Copyright © 2018Mazen Arafeh et al.(is is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Short discharge time from hospitals increases both bed availability and patients’ and families’ satisfaction. In this study, the SixSigma process improvement methodology was applied to reduce patients’ discharge time in a cancer treatment hospital. Data onthe duration of all activities, from the physician signing the discharge form to the patient leaving the treatment room, werecollected through patient shadowing. (ese data were analyzed using detailed process maps and cause-and-effect diagrams.Fragmented and unstandardized processes and procedures and a lack of communication among the stakeholders were among theleading causes of long discharge times. Categorizing patients by their needs enabled better design of the discharge processes.Discrete event simulation was utilized as a decision support tool to test the effect of the improvements under different scenarios.Simplified and standardized processes, improved communications, and system-wide management are among the proposedimprovements, which reduced patient discharge time by 54% from 216 minutes. Cultivating the necessary ownership throughstakeholder analysis is an essential ingredient of sustainable improvement efforts.

1. Introduction

Overcrowding in emergency departments (ED) is a probleminmany countries around the world [1]. ED overcrowding hasbeen reported to cause delays in diagnosis, delays in treat-ment, decreased quality of care, and poor patient outcomes[2, 3]. (e main causes of ED overcrowding seem to originateoutside the ED [4]; patients are held in the emergency de-partment after they have been admitted to the hospital be-cause no inpatient beds are available [5]. (e lack of inpatientbeds is themost significant reason for ED overcrowding [5, 6].One strategy hospitals have used to combat overcrowding isinvesting in new construction and additional staffing. An-other strategy, which offers the potential for greater return oninvestment, is process improvement [7].

We chose to use the latter approach in tackling the patientdischarge process. A lengthy, inefficient process for discharging

patients is a common concern for hospitals. Good dischargemanagement is vital to ensure patient satisfaction, as well asbed availability for emergency and elective admissions [8].

6σ is both a quality management philosophy and amethodology that focuses on reducing variation, measuringdefects, and improving the quality of products, processes, andservices [9]. (e foundations of 6σ were established by BillSmith atMotorola Corporation in response to product qualitychallenges in the late 1980s [10]. It was further developed byGeneral Electric in the late 1990s [11]. 6σ projects are formalizedand highly structured, making use of scientific approaches in theselection and management of projects. 6σ projects use a Define-Measure-Analyze-Improve-Control (DMAIC) structure, con-sidered by many practitioners to be the primary reason for 6σ’ssuccess [12].

Although Six Sigma (6σ) originated in manufacturing inlate 1980s [13], it has been successfully applied in the

HindawiJournal of Healthcare EngineeringVolume 2018, Article ID 3832151, 18 pageshttps://doi.org/10.1155/2018/3832151

healthcare field in an effort to improve processes and remedyinefficiencies. (e literature has several examples that tacklenumerous problems, including reducing medical errors [14],improving pharmacist dispensing errors [15], lessening med-ication dispensing time [16], identifying variables affecting therisk of healthcare associated infections and decreasing thepercentage of patients with healthcare associated infections[17, 18], and decreasing the length of stay and treatmentimaging [19] just to mention few.

Because the discharge process is stochastic in nature,simulation provides a vibrant platform to capture the dy-namic and complex features and to predict the consequencesof potential improvement efforts. (is happens to be theentirety of the project through the steps designed to un-derstand the system, build a model, run the model, andanalyze the results using appropriate statistics. Discrete eventsimulation (DES), a computerized method of imitating theoperation of a real-world system over time, can providedecision makers with an evidence-based tool to develop andobjectively vet operational solutions prior to implementation[20]. DES was developed in the 1960s in industrial engi-neering and operations research to help analyze and improveindustrial and business processes [21]. A benefit of using DESis the ability to incorporate multiple performance measuresassociated with healthcare systems to help to understand therelationships between various inputs [22]. (e use of simu-lation is growing and is seen as a powerful tool for thehealthcare industry, able to model a wide range of topic areasand answer a variety of research questions [23–25]. DES inhealth care commonly focuses on (1) improving patient flow,(2) managing bed capacity, (3) scheduling staff, (4) managingpatient admission and scheduling procedures, and (5) usingancillary resources (e.g., labs and pharmacies) [20].

In this paper, we present a holistic approach thatcombines DES and stakeholder analysis under the umbrellaof the 6σ DMAIC framework to examine the dischargeprocess of patients in a hospital.

(e rest of the paper is organized as follows. (e nextsection provides a review of the literature on patient dis-charge processes and stakeholders analysis. Section threepresents a background on the project and a brief descriptionof the methodology used. Section four discusses the appli-cation of the 6σ DMAICmethodology in detail including (anoverview of the discharge process, the DES model, and theimprovement scenarios and results). (e final sectionprovides concluding remarks.

2. Literature Review

Because of the complex nature of the discharge process, onlya few authors have examined the application of 6σ to theimprovement of the discharge process in hospitals. Allenet al. [26] described the application of 6σ to streamliningpatient discharge at a community hospital in Alliance, Ohio,United States. (eir findings suggested that focusing onphysician preparation for writing discharge orders wouldhave the greatest impact. Using several tools, includingstatistical process control charting, process mapping, Paretocharting, and cause-and-effect matrices to analyze and solve

the problem, they reported a reduction in the average dis-charge time from 3.3 to 2.8 hours.

AlthoughNiemeijer et al. [27] titled their work “Quality intrauma care: improving the discharge procedure of patientsby means of Lean Six Sigma,” the work actually addressed thereduction of the average length of stay of patients at theUniversity Medical Center Groningen in the northern part ofthe Netherlands. Here we do not undermine their efforts andfindings, we only point out that their work was not specificallyaimed directly at improving the discharge process.

Udayai and Kumar [8] attempted to reduce the dischargetime of cash patients at an Indian hospital based on resultsfrom analysis of voice of the customers (patients).(e authorsconducted a time-motion study to measure each step in theprocess to determine factors impacting the overall process.Improvements included starting billing one hour earlier andassigning priority for patients “pending discharge” on thecomputer that listed patients who needed an X-ray, lab report,or medicines.

El-Banna [28] presented a case study in which he builta simulationmodel of the discharge process at a private hospitalin Amman, Jordan. He focused on insured patients in all threedepartments of the hospital (female, male, and pediatrics). Hethen optimized the model with a designed experiment andresponse surface model. He found that insurance and pharmacyoperations were critical in the process. (e author reportedthat the patient discharge time was decreased to be less than50 minutes, which increased customer satisfaction, increasedthe number of admissions and turnovers on the rooms, andincreased the hospital’s profitability.

Vijay [29] suggested various improvement strategies toreduce the cycle time of patients’ discharge process ina multidisciplinary hospital setting in India using the 6σDefine, Measure, Analyze, Improve, and Control (DMAIC)model.(e study identified five critical issues causing delays inthe timely handover of the discharge summary to the patients.(e issues were failure to utilize information technology togenerate and verify the patient information, job rotation, lackof decentralized discharge summary preparation process,failure to empower the assistant physician or surgeon to proofread the rough discharge note prepared by the editor forreview, and failure to link all the computers located in all thedepartments with ERP software so that accurate and up-to-date information about the patients can be gathered withoutdelay.(ese issues were further explored and subjected to rootcause analysis using brainstorming techniques. A 61% re-duction in the cycle time of the discharge process was thenachieved by removing non-value-added activities.

Rossi et al. [30] utilized the Lean 6σ methodology toimprove discharge room cleaning processes. Large delays inturnover of patient rooms and inconsistent cleaning prac-tices were occurring because of a lack of knowledge aboutcleaning roles and responsibilities and because of a lack ofcommunication between the services.

Table 1 summarizes the articles that have addressed thedischarge process, highlighting the different tools used.

Notably, in the case studies presented in these articles,only one used simulation as a tool and none included stake-holder analysis.(is work attempts to present a comprehensive

2 Journal of Healthcare Engineering

approach that includes tools that can detect problems andfailures, tools thatmeasure current and future performance andtools that help generate new solutions. (is work also usesstakeholder analysis.

Stakeholders are critical to the success of Lean Six Sigma(LSS) projects [31, 32]. Regardless of its technical justifi-cation, any change effort needs sufficient support and in-volvement from key stakeholders. (e ability to mobilizecommitment often makes the difference between a successand a good idea that failed [33].

Stakeholder analysis identifies the stakeholder groups,their roles, how they are impacted, and their concerns relatedto the process [9]. A stakeholder is anyone impacted by theproject; however, the project sponsor and project managerneed to identify the key stakeholders needed to support,promote, and sustain the project and its improvement.

Stakeholder analysis enhances the ownership of theproject’s success (including sustaining the improvement)among the stakeholders and improves communication [34].(e main aim in performing a stakeholder analysis is tounderstand the stakeholders’ attitudes toward change andpotential reasons for resistance. (e next step is to developactivities, plans, and actions that can help the team toovercome resistance and barriers to change. It is used to helpensure that the entire organization will accept and becomfortable with the improvement initiative and thechanges that it is proposing. All stakeholders are analyzed totry and identify any issues or concerns that they may havewith the new improvement strategies. You can then developa strategy to address these potential barriers so that thetargeted processes and areas can be changed effectively.

3. Project Background andMethodology Overview

(is 6σ project was implemented at King Hussein CancerCenter (KHCC), a 262-bed hospital specialized in cancertreatment in Amman, Jordan. (is public nongovernmentalhospital provides high-quality services to patients of more

than 48 nationalities from around the world. (e hospital isfamous for its provision of diagnostic, therapeutic, andhealthcare services to different types of cancer patients withdifferent needs. In 2016, approximately 8,722 patients weredischarged from the hospital. Delays in discharging patientsaffected the hospital operations and impacted the over-crowded ED throughput since many patients in the ED awaitto be admitted to the hospital.

6σ DMAIC is used in addition to DES to help to clarifythe problems in the patient discharge process. (e 6σDMAIC approach was applied for process improvement infive phases: (1) the “Define” phase, where the objectives weredefined and a project charter was made; (2) the “Measure”phase, where shadowing at the KHCC took place for real-time data observations through the eyes of patients and theirfamilies, resulting in enough information to draw a processflow map and a supplier-input-process-output-customer(SIPOC) diagram; (3) the “Analyze” phase, which utilizedthe fishbone diagram, the five whys, and the communicationplan, as well as the implementation of the simulation modeland validation using the ProModel software package todetect long-duration activities and to try to reduce them andto eliminate the non-value-added activities if they exist; (4)the “Improve” phase, the phase of change, where all possibleimprovements were made to minimize the total dischargeduration; and (5) the “Control” phase, where the benefits ofusing the improvement model were described so that KHCCcan take suitable actions regarding this issue.

4. Application of Six SigmaDMAIC Methodology

(e project was managed by a 6σ Black Belt (BB) following theDMAIC roadmap. (e BB ensured that each improvementtools were used appropriately during each phase. (e BB alsoverified that the project’s solutions were correct and complete.

4.1. “Define”Phase. (eproject BB and Champion describedand scoped the project. (ey also met with selected team

Table 1: Summary of tools used in existing work applying Six Sigma to hospitals’ discharge process.

Tools usedCase studies

Allen et al. [26] Udayai and Kumar [8] El-Banna [28] Vijay [29]Process maps 1 1 1Time study 1 1Brainstorming 1Checklist 1 1Control chartsIndividual moving range (IMR) 1 1Root cause analysisCause-and-effect (C & E) matrix 1C & E diagram 1 15 why? 1Brainstorming 1Pareto 1Simulation 1Sigma quality level (SQL) 1Design of experiment (DOE) 1

Journal of Healthcare Engineering 3

members, explaining the project objectives and importance,discussing their roles, and listening to their feedback. �eteam decided to focus on medical and surgical patients.Preliminary data analysis showed that medical patients hadlonger discharge times than did surgical patients, who haveplanned discharges, and for this reason, surgical patientswere excluded from this study.

Process mapping was essential for understanding theprocess. A clear overview of the discharge process scopewas provided with help of a SIPOC analysis, as shown inFigure 1. �e SIPOC analysis included the macro processsteps and identi�ed all of the suppliers and customers in-volved in the process.

Developing the SIPOC analysis provided the team withan understanding of the project’s major components andboundaries. �e patient discharge process was de�ned as theset of activities that started with a specialist’s signature on thedischarge order and ended with a patient leaving the room.�e team prepared a project charter, which was approved toproceed to the next step.

4.2. “Measure” Phase. �e “Measure” phase began withpreparing detailed process maps and data collection, fol-lowed by analyzing the initial state and conducting a processcapability analysis of the discharge process. �e key measurein this phase was the time of all the activities starting fromthe physician’s signature on the discharge form and endingwhen the patient left the room.

To create a detailed process �owchart, team membersshadowed patients and gathered real-time data observationsthrough the eyes of patients and their families. Since we aredealing with cancer patients, most patients were accom-panied by their family members during the discharge

process. Patients and/or their families are henceforth re-ferred to as “PF.” �e process map enabled the team tounderstand the process and to pinpoint potential bottlenecksand areas of variation in the discharge process.

Figures 2 and 3 present a process �ow map detailing thedischarge process work�ow. �e �gure presents one of themany scenarios that a discharged patient may experience.�e process begins after the doctors �nish their rounds anddecide which patients are to be discharged.�e nurse waits forthe doctor to write the prescription for medication and thenfaxes it to the pharmacy, where the medication is prepared.After some time, the doctor writes the discharge order, whichallows themedical records department to start working on thepatient’s �le. A porter then takes the �le to the accountingdepartment on the ground �oor, and the medical recordsdepartment instructs the PF to pay the patient’s bill andgenerates the clearance sheet indicating that the patient hasno outstanding bills. After the medication is ready at thepharmacy and the porter has arrived, the medication is de-livered to the nurses’ station. �e nurse contacts the clinicalpharmacist, who provides counseling to the patient regardingthe medication. If the doctor has forgotten a medication, anadd-on prescription is written, and the process repeats. Beforeclosing the inpatient �le, extra medications that were pre-scribed to the patient but not used during the hospital staymust be returned to the pharmacy.

�ere are cases where the patient may have extra needs,such as the following:

(i) For narcotics, the physician also writes an outpatientcontrolled drug prescription, which the nurse deliversto the PF, who then submit it to the pharmacy. �isstep may occur early or late in the discharge process,depending on the physician.

Supplier

Doctor

Nurse

Medical records

Patient's family

Pharmacy

Clinical pharmacist

Nurse

Process

Doctor writes the dischargeorder, discharge note, andmedication prescription

Nurse faxes the medicationprescription to the pharmacy

Medical records sends thepatient's file to the finance

Patient's family goes toaccounting to pay the

invoice Pharmacy sends the out

medication Clinical pharmacist arrives

and explains the medication

Discharge

Output

Filled discharge order

Filled discharge note

Filled dischargemedicationsprescription

Dischargemedicationsprescription

Patient's file

Clearance

Out medication

Informed patient

Discharged patient

Customer

Nurse

Pharmacy

Finance

Patient's family

Nurse

Patient

Patient

Input

Discharge order

Discharge note

Medical prescription

Discharge medicationsprescription

Patient's file

Medical number

Out medication

Patient's family

ClearanceOut medicationPatient's family

Figure 1: SIPOC diagram for the discharge process.

4 Journal of Healthcare Engineering

(ii) When supplies are issued after the inpatient �le hasbeen closed, the PF need to go to the outpatientclinic to create an outpatient �le to buy the supplies.

(iii) For the removal of a central IV line, the nursecontacts the venous access device team.

(iv) When patients require equipment such as an oxygengenerator, the nurse contacts a social worker, whosuggests places where the family can buy the neededequipment.

Other needs such as sickness reports and settlement ofbilling questions are addressed in the Patient A�airsO�ce/Admissions, where the reports are printed. Somepatients request sickness reports for medical leave purposes,these reports are then signed by the physician in charge.

�e data were collected using approved and pretesteddata collection methods. Data on the discharge process werecollected for a period of one month. �e data collectedincluded activities and durations. Observations regardingthe activities were also noted. Of the discharges that tookplace, a sample of 41 patient discharges were closely

shadowed. �e selection was random from di�erent �oors.Each day 2 or 3 patients were shadowed. �ree dischargeswere cancelled due to errors in measurements, leaving uswith 38 patient discharges.

We calculated the mean and standard deviation of thesample, 215 minutes and 67 minutes, respectively. �eminimum sample size needed was calculated using a con�-dence level of 95% and an error of 30 minutes (ap-proximately half the standard deviation) using followingequation [35]:

n �1.96 × 67

30( )

2� 20 patients. (1)

However, since we had 38 discharges, we decided to endthe data collection and move forward to data analysis.

Initial analysis of the data identi�ed two populations, asshown in Figure 4.

�e �rst population represents patients who go throughthe standard discharge process, which includes medicationpreparation, clinical pharmacist counseling, and accounting.�e second population represents patients with extra needs

Process flow map

Start

NurseDoctor Patient/patient’sfamily Pharmacy Medical records Accounting

department

Others(supplies, equipment,

CT scan, VADteam, pain team)

Phas

e

Informsdischarge to

nurse

Informsdischarge to

patient/patient’sfamily

Writes discharge order

+ discharge summary + medications prescription

Faxes the medications

prescription and return

medication to the pharmacy

Preparespatient’s outmedications

Calls theclinical

pharmacist

Listens to theclinical

pharmacist

Takes the clearance back

to the floor

Goes down to pharmacy and

accounting department to

pay actual invoice

Takes the medication and goes back to the

floor

Takes the clearance from patient’s family

Gives the narcotics

prescription to patient’s family

Does patienthave narcotics

or add on?

Doctor writes outpatient

controlled drug prescription +

add on Prepares themedication

Works onpatient’s file and

new appointmentif patient has one

Tells thepatient’s family

to go toaccountingdepartment Finishes the

patient’s file andgives clearanceto the patient’s

family

Takes the file toaccountingdepartment

Preparespatient’sadd on

Yes

Porter moves medication to floor

Patientinformed about

discharge

Figure 2: Discharge process �ow map (part 1).

Journal of Healthcare Engineering 5

(prescribed equipment, supplies, or add-on medications).We de�ne discharges belonging to the �rst population asstandard discharges and discharges belonging to the secondpopulation as complex discharges.

An individual control chart was drawn to identify thepresence of special-cause variations in the discharge process,

as shown in Figure 5. �e typical discharge process takesabout three hours. �e out-of-control points (marked in redin the �gure) are data points belonging to the secondpopulation.

Process flow map

Nurse Patient/patient’sfamily Pharmacy Medical records Accounting

department

Others(supplies, equipment,

CT scan, VADteam, pain team)

Phas

e

Goes to themain stores to

open anoutpatient file

Does patientneed

equipment(O2

generator)?

Listen to socialworker and

leave to bringthe equipment

Patient leavesthe floor to do

CT scan

Sends returnmedication tothe pharmacy

Calls thesocial worker

Calls theVAD team

Calls painteam

Calls the CTscan andprepares

patient to godown

Checks thereturn

medication andcloses the

inpatient’s file

Takes suppliesfrom outpatient

clinics

VAD teamcomes to the

floor to removethe central line

Adds neededmedication

CT scan

Does patienthave supplies?

Does patienthave central

line?

Does patienthave

intolerablepain?

Does patientneed a

CT scan?

Yes

Yes

Yes

Yes

Yes

No

No

No

No

End

Figure 3: Discharge process �ow map (part 2).

100 150 200 250 300 350

9876543210

Duration of discharge process (min)

Freq

uenc

y

Histogram of duration of discharge process

38

215.767.10

MeanStDevN

Figure 4: Histogram of the two populations.

37332925211713951

350

300

250

200

150

100

Observation

Indi

vidu

al v

alue UCL = 270.6

X = 177.9

LCL = 85.3

11

11

1

11

11

In controlOut of control

Figure 5: IMR control chart (collected data).

6 Journal of Healthcare Engineering

To analyze observations of the process through the eyesof the patients, patients were classified according to theirneeds, as shown in Figure 6.

(e average time spent on each activity was recorded,and a sample of these results is shown in Figure 7.

(e following are some of the observations noted:

(i) Approximately 40% of patients needed narcotics(Figure 6), which adds an average of 43 minutes(Figure 7).

(ii) Approximately 16% of patients needed specialequipment, adding an average of 134 minutes.

(iii) Approximately 5% of patients needed supplies from theoutpatient clinic, requiring an average of 195 minutes.

(iv) Additional medication was ordered for approxi-mately 16% of patients; on average, this occurs 83minutes after the first prescription is written.

(v) (e duration between writing the discharge orderand the medication order is about 38 minutes.

A process capability analysis was performed to assess theperformance of the discharge process. (e main purpose of

a capability study is to determine whether a process is ca-pable of meeting certain requirements [36]. Capabilityanalysis involves the calculation of the percentage of defectsin the process and their corresponding sigma quality level(SQL). Figure 8 shows the results of the process capabilityanalysis performed using Minitab®; the resultant Zbench of−0.78 is equivalent to an SQL of 0.72.

4.3. “Analyze” Phase. After observing the discharge processand collecting data, efforts in the “Analyze” phase werefocused on investigating the root causes of the problems inthe processes. Observations noted while shadowing patients(data collection) followed by brainstorming sessions wereused to examine potential reasons behind long dischargedurations. A summary of the findings is presented usinga cause-and-effect diagram (Figure 9). Some root causesidentified in the figure actually were observed and some wereidentified as potential trying to holistically encompass thecauses.

For example, in one rare case, the discharge process wasdelayed because of late arrival of the patient family.

16% 16%

5%

39%

13% 12%

5%3%

05

1015202530354045

Add

-on

med

icat

ion

Equi

pmen

t

Supp

lies

Nar

cotic

s

Sick

ness

repo

rt

Com

pani

on p

robl

ems

VA

D te

am

Pain

team

Perc

enta

ge o

f pat

ient

s (%

)

Patients possible added needs

Figure 6: Classification of patients’ needs (percentages).

42.60

47.89

74.29

80.00

83.00

87.68

134.83

195.00

0 50 100 150 200 250

Narcotics prescription given-narcotics taken

File sent to accounting-patient's family leaves floor

Medication order written-family goes to bring narcotics

Add-on medication faxed-add-on medication ready

Medication order-add-on medication

Medication faxed-medication ready

Bringing equipment

Bringing supplies from outpatient clinics

(Minutes)

Figure 7: Duration of discharge process activities (minutes).

Journal of Healthcare Engineering 7

Unnecessary variation in the discharge process anda lack of standardization led to two important undesirableoutcomes: increased discharge time and decreased quality,where mistakes were likely to occur and people were likely toforget. Discharge orders, medication orders, and suppliesand equipment orders were made in di�erent sequences andat di�erent times. Additionally, a prescription was sent to thepharmacy for preparation, but then later during the dis-charge process, another prescription order was sent to thepharmacy for the same patient for another medication,causing the discharge process to take longer than necessary.

Furthermore, a lack of preplanning for the dischargeprocess and issues with the hospital layout were also amongthe root causes of the problem. A major cause of the longdischarge process was poor communication between thedi�erent stakeholders (treating physicians, consultants,nurses, pharmacy sta�, and the accounting department).

Because the discharge process is a highly people-dependentprocess, it was imperative to observe the complexity of thecommunication in the discharge process. A communicationcomplexity diagram is shown in Figure 10. For example, themedical records communicate with the porter, who in turncommunicates with the accounting department. Communi-cation between the accounting department back and forthwith the PF and the PF with the nurse is also shown. �esepartial communications, highlighted in red and numbered 1–6,represent part of the communication cycle emphasizing thecomplex and multiplex details of the overall discharge process.

Observed delays caused by lapses in communicationwere noted in organizing the radiotherapy session, the

inpatient chemotherapy regimen, the necessary diagnosticlab tests, and the diagnostic radiology imaging.

Delays caused by hospital security-PF-accounting de-partment communications sometimes occurred because ofPF challenging the fees added for companions. PF oftendenied having companions stay with the patient overnight,claiming that they had visitors who were incorrectly countedas companions when they visited after the last securityrounds and refusing to pay the charges. In these cases, PFchallenged the charges and requested a revision.

4.4. “Improve” Phase. In the “Improve” phase, the teamexamined the current state of process maps in depth, usingbrainstorming and cause-and-e�ect analysis techniques toexplore possible solutions.

�e improvement e�orts included many facets. Figure 6shows that about 20% of patients discharged from the hospitalcould be classi�ed as complex discharges; they requiredspecial equipment or supplies at discharge. �e remaining80% of discharged patients were classi�ed as standard dis-charges; they were discharged without the need for specialequipment or supplies, and their discharge could be ac-complished without complex planning. Changing how dis-charge occurs for both groups of patients will have a majorimpact on patient �ow and the e�ective use of bed capacity.�is can mean the di�erence between a system where patientsexperience long delays and one where delays are minimal.

�e e�ective management of system-wide processes thatsupport patient �ow, such as admission, assessment and

0 75 150 225 300 375 450

Process dataLSL ∗

Target ∗

USL 150Sample mean 213.479Sample N 188Shape 2.99394Scale 239.283

Overall capabilityZ.bench –0.78Z.LSL ∗

Z.USL –0.78Sample mean –0.26

∗

Observed performancePPM < LSLPPM > USLPPM total

∗

Exp. overall performancePPM < LSLPPM > USLPPM total

USL

755,319.15755,319.15

781,110.23781,110.23

Calculations based on weibull distribution model

Figure 8: Process capability report before improvement.

8 Journal of Healthcare Engineering

treatment, patient transfer, and discharge, can minimizedelays in the delivery of care [37].

To support the improvement e�orts and address the lackof standardization, checklists were proposed as a way tostandardize the processes and ensure that all medications areprescribed together, thus eliminating the unnecessary delaycaused by adding new medications to a patient’s medicationlist. A thorough review of all medications should be anessential part of discharge planning. E�ective dischargeplanning can ensure that medications are prescribedcorrectly.

According to “Discharge, Referral and Follow up”Standard no. 4.3, under “Access to Care and Continuity ofCare,” planning for referral and/or discharge should beginearly in the care process [37]. Diligent discharge planninghas been associated with positive outcomes, including higherpatient satisfaction [38].

However, despite the fact that it clearly increases thewell-being of patients and caregivers, discharge planning isoften not given the attention it deserves. Indeed, ine�cientplanning often adds to patients’ and caregivers’ stress. Ef-fective discharge planning is crucial for ensuring timelydischarge and making sure that the hospital’s limited re-sources are used most e�ectively. Under the best of cir-cumstances, the discharge planner should begin his or herevaluation when the patient is admitted to the hospital.

Furthermore, it is recognized that all departments in-volved in the discharge of a patient, from the pharmacy tothe transport services, must collaborate to reduce overlap,waste, and frequent frustrations [39]. �e role of dischargeplanning coordinator may be assigned to administrativesta�, rotating-shift nurses, or full-time coordinator nurses.�ree main roles are assigned to the coordinator: com-munication, multidisciplinary teamwork, and assessment.�e inclusion of such a coordinator leads to successfulprocess improvement e�orts in non-physician-centeredprocesses without interrupting physician care [40].

4.4.1. Discrete Event Simulation. We tested several solutionsto the problems identi�ed in the “Analyze” phase using DES.�e discharge process was modeled using ProModel 6.0software. To build a complete simulation model, the sim-ulation starts with the patient’s arrival at the hospital fortreatment and progresses through the receipt of treatment.�en, the discharge process is initiated, as shown inFigure 11.

We focus here on the discharge process. Figure 12presents a detailed process �owchart describing the simu-lation model from patient arrival to discharge. In ProModel,a process is initially de�ned by an entity and a location atwhich the operation is performed as shown in Figure 13.

Longdischarge

People

Poorcommunication

Physicians

Physicians-nurse

Nurse-pharmacy

New residence

Lack of training

Patient family

Porter

Place

Late rounds

Outpatientsupplies

Policy

Procedures andmethods

Accounting-patient

Physicianrounds

Late

Processes

Changing shi�s

Nurse-nurse

Suppliesdispensing

Close inpatientfile to getsupplies

Unplannedscans and

radiotherapy

Late physicianand consultant

decision

Physician-consultant

In anotherbuilding Pharmacy and

accounting

Located far Delay

Infrequentrounds

Medication

No proteravilable

Longpreparation

Lateannouncementof medication

Supplies

Late arrival ofsocial worker

Lateannouncement

of need

Accounting

Companionaccountingproblems

Early securityrounds

Sickness reportLate

Sequentialprocedures

Narcotics,medication not

announcedconcurrently

Medicationorder a�er

discharge order

Lack ofpreplanning for

dischargeprocess

Manual deliveryof documents

Unstandardizedprocesses &procedures

Hospital silos

Lack of policies oneffective

communication

Figure 9: Cause-and-e�ect diagram.

Journal of Healthcare Engineering 9

�e operation de�nes the procedure performed in theprocess and the routing, which de�nes the outcome entity ofthe operation and where it is sent.

Detailed code was developed to simulate each step in thedischarge process. For illustration, a sample of the simu-lation code developed is shown in Figure 14. �e �gureexplains the tracking of the patient’s �le.

In the simulation, the patient’s �le is represented as anentity called “Patient_�le.” �e patient’s �le requires the at-tention of the medical records o�cer for W (1.7374, 22.091)time, where W (β, η) Weibull distribution with shapeparameter� β and scale parameter� η. �is is modeled using“USE 1 Med. Rec. 3rd �r. for W (1.7374, 22.091)” for theoperation in the location “medical_record_3rd_�oor.” �e�le is then moved to the accounting department. �e �ow inthe accounting is done by the patient’s family. �is is rep-resented by the load statement “load if patient family.” In thiscase, the patient �le does not receive any attention in theaccounting department until the patient’s family arrives.�en

the accounting process takesN (1.1087, 1.43610) in delay timeand L (2.39750, 2.24560) in attention from the accountant,where N (μ, σ) is normal distribution with mean� μ andstandard deviation� σ, and L (μ, σ) is the lognormal distri-bution with mean� μ and standard deviation� σ.

�e process results in the clearance entity in the ac-counting department, moving the patient’s �le to the third�oor in the routing. �e clearance is then sent to the speci�edpatient room, according the attribute “Patient_room_ID.”

4.4.2. Veri cation and Validation of the Model.Veri�cation was initially performed by visualizing the ani-mation of the simulation model �ow, entity by entity. Allstakeholders’ (PF, doctors, nurses, and porters) movement

Doctor

VAD team

Pain team

Social worker Supplies store (out clinics) Accounting department Clinical pharmacist

File porter

Medical record

PatientPatient’s familyNurse

Medication porter

Patient office affairs/admission

Pharmacy

1

23

45

6

Security

Figure 10: Communication complexity diagram.

Arrival Treatment Discharge

Figure 11: High-level process �owchart.

10 Journal of Healthcare Engineering

in the hospital was checked to verify the correctness of thesimulation model. Figure 15 shows a snapshot of the sim-ulation model while running in the di�erent �oors.

�e simulation model was then validated by comparingthe output of the model to the actual discharge process in thehospital. We looked at both the number of discharges andthe average duration of the discharge process.

�e model was run for a simulated period of time equalto one month. Because of the stochastic behavior of thesystem, a single run would be insu�cient to draw an actual

estimate from simulation model. Instead, 100 replicationswere performed, and the average of these runs was evaluated.�e simulated average time for the 100 replicates of thedischarge process was 213.38 minutes, with standard de-viation of 5.47 minutes as shown in Figure 16.�e results forone replication were an average time of 213.48 minutes andstandard deviation of 76 minutes. �e average dischargetime observed in the collected data was 215.7 minutes. �eerror between the real collected data and data from thesimulation model is calculated using the following formula:

Patient arrival

Patient goes to dummyroom

Medication prescription

Equipment appears at the patient’s family dummy room to decide whether patient needs equipment

or not

Patient family settles inanother dummy room

Patient file

Yes

NoNo

TreatmentDoes

patient havedischarge?

Yes

IF CONTENTS(room1_1) = 0 AND CONTENTS(room1_1d) = 0 AND record1_1 = 0 THEN {record1_1 = 1WAIT 60 MIN route 1 }

2

3

4

5

1Patient arrival

Is thereempty room?

Waits forroom

housekeeping Waits at the

ER

Figure 12: Patient discharge in the simulation model.

RoutingProcess 2Process 1

Address Operation 1

Process 1

Entit

y 1

Loca

tion

1

Address Operation 2

Process 2

Entit

y 2

Loca

tion

2

Routingnext

address

Entit

y 2

Loca

tion

2

Figure 13: ProModel process de�nition.

Journal of Healthcare Engineering 11

error �215.7− 213.38

215.7� 1.08%. (2) 4.4.3. Proposed Changes and Time Improvements. After the

simulation model was veri�ed and validated, we identi�edseveral activities that contributed substantially to increasing

Patient’s file

Medical recordprocedure

Transfer toaccounting by

porter

Accountingprocess delay and

procedure

Accountingprocedure

starts a�er patientfamily arrives

Clearanceprocedure by thenurse and send tothe right patient

room

Transfer to nursein floor

Select the rightroom to send the

clearanceaccording to ID

Clearancetransfer to the

right room

N (μ, σ) Normal distribution with mean = μ and standard deviation = σ

Figure 14: Patient’s �le tracking.

12 Journal of Healthcare Engineering

the duration of the discharge process. �ese activities in-cluded medication preparation in the pharmacy, waiting forthe porter, and the preparation of supplies and equipment.In addition, activities related to physicians, such as laterounds and the fact that physicians do not write pre-scriptions for medication at the same time as the dischargeorder, were also important factors adding to the duration ofthe discharge process.

Before approaching the hospital management withrecommendations for improvements, the simulation modelwas run to study how improving each activity would a�ectthe discharge process time.�e improvements are visualizedin a Pareto chart (Figure 17).

�e �rst improvement noted is creating a discharge “fasttrack” in the pharmacy.�ismeans that the pharmacy wouldtake 30 minutes for medication preparation instead of anaverage of 88 minutes. In the Pareto chart, it can be seen thatthis improvement would reduce the total discharge time byan average of about 36 minutes.

Because the pharmacy also waits for the porter’s arrivalto transport the medication to the patient, even when themedication is ready, we suggested making another porteravailable, which would save 8.53minutes. Another suggestedsolution was eliminating both waiting at the pharmacy andthe high variation in porter transportation by assigning therole of transporting the medication to the clinical pharmacist,

GROUND FLOOR

NURSE STATION

NURSE STATION

ACCOUNTINGDEPARTMENT

PHARMACY WAITING ROOMRECEPTION

FOURTH FLOOR

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

THIRD FLOOR

FIFTH FLOOR

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTROOM

NURSE STATION

PATIENTROOM

PATIENTROOM

PATIENTROOM

PATIENTSUITE

PATIENTSUITE

PATIENTSUITE

PATIENTSUITE

Figure 15: View of the simulation model used for veri�cation.

Figure 16: General report from ProModel showing the average time for 100 replications.

Journal of Healthcare Engineering 13

thus eliminating the nurse’s phone call and waiting duringdelays in the pharmacist’s arrival; this would result in a21-minute reduction, on average, in the total discharge duration.

Announcing the need for equipment one day earlierwould lead to an average reduction of 4.2 minutes. Addi-tionally, if supplies were brought to the �oor instead ofrequiring the patient to go to the outpatient clinic, this wouldsave 7.36 minutes.

When improvements were applied to all of the activities,the discharge process decreased by about 115 minutes,resulting in a discharge process of about 98 minutes as shownin Figure 18 and a total reduction of approximately 54%.

A process capability analysis was also performed afterimprovement, as shown in Figure 19. �e Zbench is equal to1.17, which is equivalent to an SQL of 2.67. �e SQL valueincreased from 0.72 to 2.67, meaning that there was a decreasein the number of patients waiting longer than 150 minutes.

4.5. “Control” Phase. �e last phase of the DMAIC is the“Control” phase. A control plan was put in place to ensurethat the improvements would continue in the future. �egoals here were to ensure that the processes continue to workwell, produce the desired output results, and maintainquality levels.

All organizations experience resistance to change. AsLSS are by de�nition about changing how people work,

many LSS e�orts are met with resistance. Furthermore, Yih[25] has argued that this resistance is often viewed as in-surmountable in healthcare organizations. �is gloomy viewarises because physicians—one of the most important andmost highly constrained resources in hospitals—are mostlyautonomous in the management structure and thus immuneto incentives typically available in other organizations.

Because of the autonomous nature of their profession, itis di�cult for physicians to accept standardization, especiallywhen it goes against their own interests [41]. Physicians donot feel comfortable adopting a standardization initiativeunless there is transparent evidence of its impact on patientoutcomes [42].

To alleviate physicians’ resistance, we performeda stakeholder analysis.

As shown in Table 2, physicians have high levels ofin�uence and impact on the control process steps, but theirinterest in these issues is low. We recommend involvingphysicians in the analysis and development of solutions,whether through participation in the improvement team orworkshops and meetings presenting and discussing qualityimprovement issues.

Other stakeholders such as pharmacy workers, the ac-counting department, and medical records sta� membersshould collaborate in the proposed methods to sustain andcontrol the improvements, for example, using an electronicdischarge system. �ese stakeholders have low-to-moderateinterest in leading or initiating any change process andmedium impact on the process control and improvement.Patients’ family members who usually participate in thedischarge process are contacted by the discharge planningcoordinator in a one on one meeting, their role in executingan e�ective discharge process is explained, and any specialarrangements are discussed and taken care of.

Change is always unsettling, even when all the parties in-volved are committed to the outcome. Taking the time to briefthe stakeholders ensures cooperation and reduces stress duringand immediately following the improvement event [43]. Aresponsible, accountable, consulted, and informed matrix wasutilized to improve communication, convey information aboutresponsibilities, and identify any gaps or redundancies associ-ated with stakeholders’ responsibilities, as shown in Table 3.

If all of the stakeholders understand this matrix and takethe proper actions accordingly, communication betweenthese people will improve, reducing the waste of time andthus bene�ting the patient.

Control charts were used to monitor the ongoing per-formance of the key variables. After implementing all of theimprovements in the process, a decrease in the mean du-ration of the discharge process was observed, as seen inFigure 20, which shows the control chart before and afterimprovement. �e mean discharge time decreased by ap-proximately 54%, from 216minutes to 98minutes.�e lowerand upper control limits of the individual values and themoving range also showed a reduction, indicating a morestable process.

A control plan was put in place to ensure that theseimprovements would continue in the future. Control chartsare used to verify compliance.

120

100

80

60

40

20

0

(Min

utes

)

115

36

2114 13 10 9 7 4 4 1

Com

bina

tion

Disc

harg

e pha

rmac

y

Phar

mac

ist b

rings

med

icat

ion

with

out u

sing

port

er

Nar

cotic

s and

acco

untin

g sa

me t

ime f

or p

atie

nts w

ith n

arco

tics

Nar

cotic

s ord

er w

ritte

n sa

me t

ime a

s ord

er

No

add-

on m

edic

atio

n

Mor

e tha

n on

e ava

ilabl

e por

ter

Read

y eq

uipm

ent

M.O

and

D.O

sam

e tim

e

Redu

ctio

n in

wai

ting

time o

f fam

ily to

go

to ac

coun

ting

Supp

lies f

rom

floo

r

Figure 17: Reduction in time per activity.

14 Journal of Healthcare Engineering

5. Conclusions

6σ, combinedwith the power ofDES, has been effectively appliedto the improvement of patient discharge processes, an intricatehealthcare operational process involving multiple stakeholders.

Application of the 6σ-DMAIC methodology provided a struc-tured framework to define the project goals, understand thecurrent state, analyze the data to identify the root causes, assessstatistically significant improvements, and implement a controlplan to maintain improvements in the discharge process.

250

200

150

100

50

0

Curr

ent s

ituat

ion

M.O

and

D.O

sam

e tim

e

NO

add-

on m

edic

atio

n

Mor

e tha

n on

e ava

ilabl

e por

ter

Phar

mac

ist b

rings

med

icat

ion

with

out u

sing

port

er

Read

y eq

uipm

ent

Nar

cotic

s pre

scrip

tion

writ

ten

sam

e tim

e as D

.O

Nar

cotic

s and

acco

untin

g sa

me t

ime f

or p

atie

nts w

ith n

arco

tics

Redu

ctio

n in

wai

ting

time o

f fam

ily to

go

to ac

coun

ting

Disc

harg

e pha

rmac

y

Supp

lies f

rom

floo

r

1.65% 5.23% 3.86% 6.50%4.23%

3.39%10.04% 2.21%

1.73% 31.36%

213.38 209.86 198.89 191.21178.78 171.21 165.41

148.81 145.52 143

98.15

Improvements

Figure 18: Percentage improvements with the addition of each improvement.

Overall capability1.17

Z.LSLZ.USLppk

∗

1.15

Z.bench

0.38

0 40 80 120 160 200 240 280

USLCalculations based on weibull distribution model

Exp. overall performancePPM < LSL ∗

PPM > USLPPM total

120,246.13120,246.13

Process dataLSL ∗

∗TargetUSL 150Sample mean 98.26Sample N 200Shape 2.48421Scale 110.885

Observed performancePPM < LSL ∗

PPM > USL 115,000.00115,000.00PPM total

Figure 19: Process capability report after improvement.

Journal of Healthcare Engineering 15

(e patient discharge process was complex and un-standardized and involvedmulti-department processing andsequential operations. Discharged patients were classifiedinto two groups (standard and complex patients) since theirdischarge times differed significantly.(is was due to the factthat complex patients required extra needs (medical suppliesand equipment) and thus extra processing steps and time,many of which can be preplanned and prepared before thedischarge process took place.

Leveraging 6σ methodology with DES enabled us to getthe most out of process improvement initiative. Buildinga simulation model with the smallest details of the dischargeprocess provided a realistic ideation tool for stimulating andeliciting more solution ideas for consideration. After veri-fication and validation, analysis of the simulation resultsprovided a means for doing scenario comparisons andidentifying key process factors affecting performance of thedischarge process. With DES, we were able to quantify the

Table 2: Barriers and proposed engagement methods for stakeholders in the discharge process.

Stakeholder

Knowledge ofstakeholderregarding theinitiative

Interest in theissue

(willingness toinitiate or lead)

Influence/power(low, medium,

high)

Level ofengagement

Impact of issueon actor (low,medium, high)

Proposed engagement method

Physician Medium Low High Involve High Increaseownership/workshops/meetings

Nurse Low Medium Medium Involve Medium Workshops/meetingsPatient/patient’sfamily Medium High Low Involve High One on one meetings

Pharmacy Low Low High Involve Medium Electronic systemAccountingdepartment Low Low Medium Collaborate Medium Electronic system

Medical records Medium Medium Medium Collaborate Medium Electronic system

Table 3: RACI matrix for stakeholders in the discharge process.

Task Physician Nurse Pharmacy Accounting department Suppliers Medical records Patient’s familyDischarge orders R/A I I I IMedication orders R/A I C/I I ISupplies and equipment orders A A C/I I I IPrescription preparation I R/A I I ISuppliers preparation I I R/A I IMedical records update I I R/A IBill preparation I R/A I I IBill settlement I I I I R/AR� responsible; A� accountable; C� consulted; I� informed.

480

300

200

100

0

360

240

150

0

UCL = 362.2

UCL = 182.7

MR = 55.9LCL = 0

X = 213.5

LCL = 64.8

UCL = 174.2

X = 98.3LCL = 22.3In

divi

dual

val

ue

UCL = 93.8MR = 28.6

LCL = 0

1 40 79 118 157 196 235 274 313 352Observation

1 40 79 118 157 196 235 274 313 352Observation

Mov

ing

rang

e

IMR chart of discharge time before and a�er improvement1

1 1

111 1 1

1 11

11 1

1 11

1 1 11 1 1 1 1

1 11 1

11

1 11

11

11 1 1

1 1 1 1 1 1 11 1

1 1111

2

2

Figure 20: Early indications of success: IMR chart of discharge time before and after improvement.

16 Journal of Healthcare Engineering

levels of improvement that can be anticipated from thedifferent proposed solutions, and thus, offering the KHCCmanagement a variety of solutions. (e total reduction indischarge time was approximately 54%.

(is project has been extremely challenging, duemainly tothe large scope and the complexity of the processes, and theinvolvement of stakeholders from a variety of levels and acrossdifferent functional areas. However, understanding processdynamics and improving communication and collaborationbetween stakeholders based on stakeholder analysis ensuresa significant and sustainable impact on operations.

Conflicts of Interest

(e authors declare that there are no conflicts of interestregarding the publication of this paper.

Acknowledgments

(e authors thank Jennifer Barrett, Ph.D., from EdanzGroup (www.edanzediting.com/ac) for editing the draft ofthis manuscript.

References

[1] R. Salway, R. Valenzuela, J. Shoenberger, W. Mallon, andA. Viccellio, “Emergency department (ed) overcrowding:evidence-based answers to frequently asked questions,”Revista Medica Clınica Las Condes, vol. 28, no. 2, pp. 213–219,2017.

[2] R. W. Derlet, J. R. Richards, and R. L. Kravitz, “Frequentovercrowding in US emergency departments,” AcademicEmergency Medicine, vol. 8, no. 2, pp. 151–155, 2001.

[3] S. G. Lynn and A. L. Kellermann, “Critical decision making:managing the emergency department in an overcrowdedhospital,” Annals of Emergency Medicine, vol. 20, no. 3,pp. 287–292, 1991.

[4] S. Trzeciak and E. Rivers, “Emergency department over-crowding in the United States: an emerging threat to patientsafety and public health,” EmergencyMedicine Journal, vol. 20,no. 5, pp. 402–405, 2003.

[5] B. Asplin, F. C. Blum, R. I. Broida et al., “Emergency de-partment crowding: high-impact solutions,” ACEP Task ForceReport on Boarding, American College of Emergency Phy-sicians, Washington, DC, USA, 2008.

[6] R. Steele and A. Kiss, “EMDOC (Emergency Departmentovercrowding) Internet-based safety net research,” Journal ofEmergency Medicine, vol. 35, no. 1, pp. 101–107, 2008.

[7] J. B. Montgomery and K. Davis, “(e hospital patient flowmodel: a simulation decision support tool,” in Proceedings ofthe 2013 Winter Simulation Conference, Huntington Beach,CA, USA, 2013.

[8] K. Udayai and P. Kumar, “Implementing six sigma to improvehospital discharge process,” International Journal of Phar-maceutical Sciences and Research, vol. 3, no. 11, p. 4528, 2012.

[9] S. L. Furterer, Lean Six Sigma Case Studies in the HealthcareEnterprise, Springer, Berlin, Germany, 2014.

[10] F. W. Breyfogle, Implementing Six Sigma: Smarter SolutionsUsing Statistical Methods, John Wiley & Sons, Inc., Hoboken,NJ, USA, 2nd edition, 2003.

[11] T. Pyzdek and P. A. Keller, e Six Sigma Handbook: AComplete Guide for Green Belts, Black Belts, and Managers atAll Levels, McGraw-Hill, New York, NY, USA, 2003.

[12] H. De Koning and J. De Mast, “A rational reconstruction ofSix-Sigma’s breakthrough cookbook,” International Journal ofQuality and Reliability Management, vol. 23, no. 7, pp. 766–787, 2006.

[13] D. Stamatis, Essentials for the Improvement of HealthcareUsing Lean & Six Sigma, CRC Press, Boca Raton, FL, USA,2010.

[14] G. Esimai, “Lean Six Sigma reduces medication errors,”Quality Progress, vol. 38, no. 4, p. 51, 2005.

[15] A. L. F. Chan, “Use of Six Sigma to improve pharmacistdispensing errors at an outpatient clinic,” American Journal ofMedical Quality, vol. 19, no. 3, pp. 128–131, 2004.

[16] M. Arafeh, M. A. Barghash, E. Sallam, and A. Alsamhouri,“Six Sigma applied to reduce patients’ waiting time in a cancerpharmacy,” International Journal of Six Sigma and Compet-itive Advantage, vol. 8, no. 2, pp. 105–124, 2014.

[17] G. Improta, M. Cesarelli, P. Montuori, L. C. Santillo, andM. Triassi, “Reducing the risk of healthcare-associated in-fections through Lean Six Sigma: the case of the medicineareas at the Federico II University Hospital in Naples (Italy),”Journal of Evaluation in Clinical Practice, vol. 24, no. 2,pp. 338–346, 2018.

[18] E. Montella, M. V. Di Cicco, A. Ferraro et al., “(e applicationof Lean Six Sigma methodology to reduce the risk ofhealthcare–associated infections in surgery departments,”Journal of Evaluation in Clinical Practice, vol. 23, no. 3,pp. 530–539, 2017.

[19] M. Taner, B. Sezen, and K. M. Atwat, “Application of SixSigma methodology to a diagnostic imaging process,” In-ternational Journal of Health Care Quality Assurance, vol. 25,no. 4, pp. 274–290, 2012.

[20] E. Hamrock, J. Parks, J. Scheulen, and F. J. Bradbury, “Discreteevent simulation for healthcare organizations: a tool for de-cision making,” Journal of Healthcare Management, vol. 58,no. 2, pp. 110–124, 2013.

[21] J. Karnon, J. Stahl, A. Brennan, J. J. Caro, J. Mar, and J. Moller,“Modeling using discrete event simulation: a report of theISPOR-SMDM modeling good research practices task force-4,” Value in Health, vol. 15, no. 6, pp. 821–827, 2012.

[22] S. H. Jacobson, S. N. Hall, and J. R. Swisher, Discrete-EventSimulation of Health Care Systems. Patient Flow: ReducingDelay in Healthcare Delivery, Springer, Berlin, Germany,2006.

[23] E. S. Kim, Using Computer Simulation to Study HospitalAdmission and Discharge Processes, Masters thesis, Universityof Massachusetts Amherst, Amherst, MA, USA, 2013.

[24] M. H. Rutberg, S. Wenczel, J. Devaney, E. J. Goldlust, andT. E. Day, “Incorporating discrete event simulation intoquality improvement efforts in health care systems,”AmericanJournal of Medical Quality, vol. 30, no. 1, pp. 31–35, 2015.

[25] Y. Yih, Handbook of Healthcare Delivery Systems, CRC Press,Boca Raton, FL, USA, 2016.

[26] T. T. Allen, S. H. Tseng, K. Swanson, and M. A. Mcclay,“Improving the hospital discharge process with Six Sigmamethods,” Quality Engineering, vol. 22, no. 1, pp. 13–20, 2009.

[27] G. C. Niemeijer, A. Trip, K. T. Ahaus, R. J. Does, andK. W. Wendt, “Quality in trauma care: improving the dis-charge procedure of patients by means of lean six sigma,”Journal of Trauma and Acute Care Surgery, vol. 69, no. 3,pp. 614–619, 2010.

[28] M. El-Banna, “Patient discharge time improvement by usingthe six sigma approach: a case study,” Quality Engineering,vol. 25, no. 4, pp. 401–417, 2013.

Journal of Healthcare Engineering 17

[29] S. A. Vijay, “Reducing and optimizing the cycle time of pa-tients discharge process in a hospital using six sigma DMAICapproach,” International Journal for Quality Research, vol. 8,no. 2, pp. 169–182, 2014.

[30] E. Rossi, D. Mann, B. Baldwin-Rodriguez, and H. Alvarez, “Alean six sigma approach to improving the discharge roomcleaning process,” American Journal of Infection Control,vol. 42, no. 6, pp. S143–S144, 2014.

[31] B. Cole, Lean-Six Sigma for the Public Sector: LeveragingContinuous Process Improvement to Build Better Governments,ASQ Quality Press, Cuernavaca, MOR, Mexico, 2011.

[32] A. Laureani, M. Brady, and J. Antony, “Applications of leansix sigma in an Irish hospital,” Leadership in Health Services,vol. 26, no. 4, pp. 322–337, 2013.

[33] B. Palmer, Making Change Work: Practical Tools for Over-coming Human Resistance to Change, ASQ Quality Press,Milwaukee, WI, USA, 2004.

[34] L. Hambleton, Treasure Chest of Six Sigma Growth Methods,Tools, and Best Practices, Pearson Education, New York, NY,USA, 2007.

[35] W. G. Cochran, Sampling Techniques, Wiley, Hoboken, NJ,USA, 3rd edition, 1977.

[36] C. M. Borror, e Certified Quality Engineer Handbook, ASQQuality Press, Milwaukee, WI, USA, 2009.

[37] JCI, Joint Commission International Accreditation Standardsfor Hospitals, Joint Commission Resources, Oakbrook Ter-race, IL, USA, 2014.

[38] F. C. Alliance, “Hospital discharge planning: a guide for 3families and caregivers,” 2016, https://www.caregiver.org/hospital-discharge-planning-guide-families-and-caregivers.

[39] D. Hindmarsh and L. Lees, “Improving the safety of patienttransfer from AMU using a written checklist,” Acute Medi-cine, vol. 11, no. 1, pp. 13–17, 2012.

[40] M. R. Day, G. Mccarthy, and A. Coffey, “Discharge planning:the role of the discharge co-ordinator,” Nursing Older People,vol. 21, no. 1, pp. 26–31, 2009.

[41] G. Ellingsen, “Tightrope walking: standardisation meets localwork-practice in a hospital,” International Journal of ITStandards and Standardization Research (IJITSR), vol. 2, no. 1,pp. 1–22, 2004.

[42] P. Kurtin and E. Stucky, “Standardize to excellence: improvingthe quality and safety of care with clinical pathways,” PediatricClinics of North America, vol. 56, no. 4, pp. 893–904, 2009.

[43] J. Aherne and J. Whelton, Applying Lean in Healthcare: ACollection of International Case Studies, CRC Press, BocaRaton, FL, USA, 2010.

18 Journal of Healthcare Engineering

International Journal of

AerospaceEngineeringHindawiwww.hindawi.com Volume 2018

RoboticsJournal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Active and Passive Electronic Components

VLSI Design

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Shock and Vibration

Hindawiwww.hindawi.com Volume 2018

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwww.hindawi.com

Volume 2018

Hindawi Publishing Corporation http://www.hindawi.com Volume 2013Hindawiwww.hindawi.com

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com

Journal ofEngineeringVolume 2018

SensorsJournal of

Hindawiwww.hindawi.com Volume 2018

International Journal of

RotatingMachinery

Hindawiwww.hindawi.com Volume 2018

Modelling &Simulationin EngineeringHindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Navigation and Observation

International Journal of

Hindawi

www.hindawi.com Volume 2018

Advances in

Multimedia

Submit your manuscripts atwww.hindawi.com