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; [email protected]
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.
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18 Journal of Healthcare Engineering
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