Using LSS DMAIC In Improving Emergency Department Waiting Time

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Int. J. Pharm. Sci. Rev. Res., 35(2), November – December 2015; Article No. 28, Pages: 151-155ISSN 0976 – 044XReview ArticleUsing LSS DMAIC in Improving Emergency Department Waiting Time123Nurul Fadly Habidin *, Noor Zakiah Yahya , Mohd Fahmi Shukur Ramli1*Dept of Management and Leadership, Faculty of Management and Economics, University Pendidikan Sultan Idris, Tanjung Malim, Perak, Malaysia.2Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Tanjung Malim, Perak, Malaysia.3Hospital Sultanah Hajjah Kalsom, 3900 Tanah Rata, Cameron Highland, Pahang, Malaysia.*Corresponding author’s E-mail: on: 19-10-2015; Finalized on: 30-11-2015.ABSTRACTThe objective of the study is using Define, Measure, Analyze, Improve and Control (DMAIC) in improving emergency departmentwaiting time. Emergency department is the first line in hospitals to face emergency patients. The goal of this study is to use Lean SixSigma (LSS) methodologies, specifically DMAIC improvement format within the emergency department in order to address thedissatisfaction of patients who encounter long waiting time. The root causes of long waiting time in emergency department areequipment, registration and treatment process, patient and staff factors.Keywords: DMAIC, Lean Six Sigma, Emergency Department, Waiting Time, Improvement, Healthcare.INTRODUCTIONLiterature ReviewODavid and Yariv1 found that waiting time comprise 51-63percent of total patient turnaround time in ED. Its majorcomponents are: time away for an x-ray examination;waiting time for the first physician’s examination; andwaiting time for blood work.vercrowding in the Emergency Department (ED)has become a phenomenon all around Malaysia.Patients have to wait for hours and the ED staffhad to work overtime to solve patient’s illness. Mostpatients experience very lengthy waits before receivingcare, and some leave without being attended. Staffs incharge for daily operation are medical officers (doctors),paramedic (medical assistant and nurses) and hospitalattendant.The ED must deal with a 24-hour cycle and be expected tohandle all the abundant patient demands. The medicalstaff must be adequately equipped in order to meet therising demands of basic acute medical care. The challengein ED is the people expectation to always be opened inorder to serve community. In addition, not all patientsarriving in ER are equally sick. Shortage in humanresources, high patient care cost in private hospitals andthe increase in patient volume have placed more burdenfor ED to provide the best quality care in the mostefficient way.Quality of healthcare in Malaysia is based on theaccreditation by the Malaysian Society for Quality inHealth (MSQH). MSQH role is to stimulate �sperformance and the outcome of care. Thus, theorganization performance in ED is also to be emphasized.To enhance the quality of emergency department flow,the application of Lean Six Sigma is used.This study is conducted to identify the weakness ofpatient flow in emergency department in a districthospital of Pahang. Observation was executed within fivedays from 3rd April 2013 (Wednesday) to 7th April 2013(Sunday). It was found that, if the waiting time can bereduced, the overall patient satisfaction will increase.Medeiros2 developed and implements a new approach topatient flow in the ED where Provider Directed Queuing(PDQ) places an emergency care physician at triage. Theemergency care provider listens to the patient’scomplaint and the triage nursing assessment and worksas part of a team to provide the resources necessary forpatient care.Johnson3 uses Define, Measure, and Analyze stages in SixSigma methodology to improve the quality of care whilereducing patients’ length of stay (LOS) and process errorsin ED located in central of Texas. The simulation aspectsof the study utilize ProModel’s MedModel software and isthe “as-is” model building stage.In this paper, DMAIC has been chosen as a process tocreate breakthrough improvements in quality of EDwaiting time in Malaysia. Within the context of the fivephases, this study chooses SIPOC, Fishbone Diagram,FMEA table, and Gantt chart to make decision.DISCUSSIONLSS Define-Measure-Analyze-Improve-Control (DMAIC) isthe core methodology used in LSS project4-8. Thismethodology assists medical practitioners to utilize theconcept of DMAIC when a process is in existence at acompany but is not as per customer specifications.DMAIC methodology also refers to practical problem thatis converted into statistical data that is encouragedthrough lean six sigma method by improving certain areasof business processes9,10. Each phase of the DMAIC isInternational Journal of Pharmaceutical Sciences Review and ResearchAvailable online at Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited.151 Copyright pro

Int. J. Pharm. Sci. Rev. Res., 35(2), November – December 2015; Article No. 28, Pages: 151-155based on actual data, rather than opinion or perception.This section will discuss on the DMAIC stages.DefineISSN 0976 – 044Xneeded, will be admitted to ward while patient that donot need further investigation will be discharged afterreceive medicine from pharmacy.The Define stage is the most crucial amongst otherDMAIC process because how well it’s completed willdirect to the success of the project. Here, we have toscope down the problem into a manageable level. In thedefine stage, the problem to be solved is defined.SIPOC (Suppliers – Inputs – Process – Outputs –Customers) analyses are perform in this stage as shown inFigure 1. SIPOC analysis is a simple tool for identifying thesuppliers and their inputs into a process, the high-levelsteps of a process, the output of the process, and thecustomer segments interested in the outputs10.The process begins when patients arrive at the triagedesk and ends when the patient is admitted or discharge.Figure 1 shows a SIPOC that contains the process of apatient. When patients arrive at the ED, they will beclassified to three stages, red, yellow, and green. Triagered is for critical patients, yellow for semi-critical patientand triage green for non-critical patient.Figure 1: SIPOCMeasureThe measure phase is about understanding the currentprocess, how the process is measured, and performanceimprovement. A process flow chart are develop tounderstand the process and to gain consensus for theoverall scope of the project as shown in Figure 2.The triage red patients are immediately sent for secondtriage for vital signs examination such as blood pressureand heart rate checkup. While for the triage yellow andtriage green patients they have to complete a miniregistration whereby they have to provide their particularand chief complaint before attending the secondarytriage.Figure 2: Process Flow ChartFrom the flow chart above, the process which involveswaiting time in ED will be measured. However, the timecan be dragged longer during school holidays and publicholiday. The standard estimated time for the ED processare shown below:1.Registration after first triage (30 minutes)After secondary triage patients are once again classifiedto three stages as per first triage. Triage yellow and greenpatients go for examination and investigation by MA suchas x-ray and blood test follow by consultation withdoctor. Meanwhile, triage red patient go directly forconsultation with doctor.2. Waiting time to get vital signs and early treatment(secondary triage) by paramedics (1 hour)4.Waiting time to see doctor (3 hours)Lastly, the process in ED ends with doctor decideswhether patient needs further investigation or not. If5.Patients admitted to ward (1 hour)3. Treatment and investigation (x-ray/blood test/medication) (4 hour)International Journal of Pharmaceutical Sciences Review and ResearchAvailable online at Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited.152 Copyright pro

Int. J. Pharm. Sci. Rev. Res., 35(2), November – December 2015; Article No. 28, Pages: 151-155AnalyzeAnalyze phase is a step that looks into the possiblesources of the variation that cause the defect. To identifythe root causes in Analyze phase, a Fishbone diagram wasconstructed to identify the major causes and sub causesof this study.Fishbone diagrams are also known as cause-and-effectdiagrams, are about organizing possible causes behind agiven problems. The following Fishbone Diagram exampleas shown in Figure 3 looks at possible causes of longwaiting time in ED.The first major problem is the registration. Registrationprocess at the triage takes time when there is not enoughstaff to register. In addition, communication failure existsif the patient walk in to ED but they are not able toconvey their problem properly.ISSN 0976 – 044Xsuch as x-ray takes time when there are not enoughequipment and equipment failure. In addition, patientsfrom outpatient department also come to the imagingdepartment to do x-ray.For patient that can be discharged, waiting at thepharmacy also takes time because of the crowdednessand not enough staff to prescribe.The last factor for long waiting time is the humanresource. For the doctors, their scheduled is really tightespecially for districts hospital. They have to do wardrounds in the hospitals.There are no specialists in district hospital; therefore longtime is needed if the patient’s problem is complicated.ImprovementImprovement phase involves the improvement that hasto be developed to fix the problem. Designing andrunning pilot test can be done here. The ultimate goal isto see if the ideas will solve the problem.The Failure Modes and Effects Analysis (FMEA) are theprimary tools for risk assessment. FMEA assist to reducedefect, fast action and countermeasures based on JITapproach. The outputs would yield a list of defects to beimproved. Here we can detect which process that effectthe most for the waiting time in ED.The first component is the Process input, then the FailureMode – “what can go wrong with the input?” thePotential Failure Effects – “what is the effect on theoutput?” Then, assigning a Severity Level score (1-10,where 10 is the score representing a very likelyoccurrence) for each Potential Cause.The Occurrence score (1-10, with a score 10) representingthe case where the detection of the cause or failurewould never occur. Finally, a Risk Priority Number (RPN) iscalculated by multiplying Severity, Occurrence andDetection scores together for each Process Input row11.Figure 3: Fishbone DiagramSecond problem comes from the patient themselves.New patients arriving at the same time and unscheduledtime are the main problems that will drag to long waitingtime. Referrals from general practitioner (GP) aresometimes not necessary to go to ED. In addition, disasterwill drag very long time in the ED. Equipment failure willdrag really long time to be fixed. Not enough equipmentwill disturb the waiting flow.Waiting for treatment contribute the most waiting time inthe process. Investigation in lab will be disturbed if thereare not enough reagent and machine failure. Also,running some tests also takes time. Imaging modalityFrom Table 1, it is found that the biggest RPN is physicianconsultation with patient. This means, the longest waitingtime occur in this stage because complicated diseasetakes long time to be diagnosed. Furthermore, criticalcases requiring further extended investigation drag verylong waiting time.The FMEA helps to define which process should beimproved the most. For Improvement phase, someimprovement has been done in the ED such as:1.Sending staff for more courses related to emergency2. Train paramedical staff to do all processes except fordoctor’s task3. Incompetent doctor will be monitored by welltrained doctor until they became really efficient.4. Address the equipment problems by dealing with theinventory department.International Journal of Pharmaceutical Sciences Review and ResearchAvailable online at Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited.153 Copyright pro

Int. J. Pharm. Sci. Rev. Res., 35(2), November – December 2015; Article No. 28, Pages: 151-155ISSN 0976 – 044XTable 1: FMEAControlThe final phase is the control phase. The control phase iswhere control charts and other monitoring tools are usedto track the solution of the problem are designed in orderto ensure long term success of the solution. A qualitycoordinator was appointed to the ED department tocontrol the waiting time process in ED.Table 2: Gantt chartIn this study, Gantt chart is built to keep the improvementin control as shown in Table 2. Gantt chart assists to planthe allocation of resources needed to complete theproject. The processes with the maximum durations areshown. Waiting time for patients could not be more thanthe durations stated in the Gantt chart in order to ensurethe flow runs effectively.RecommendationFor further research, it is suggested to study therelationship between lean six sigma practice (LP) andSupply Chain Innovation (SCI) in ED department forMalaysian Healthcare Industries.CONCLUSIONIn order to successfully integrate the new process, themedical staff must believe in the solution and be capableof the continual monitoring of the process to ensure thatimprovement are maintained. Therefore, this studyassists hospital managers and policy maker to find thebest quality management to achieve their bestperformance in managing the waiting time in ED.International Journal of Pharmaceutical Sciences Review and ResearchAvailable online at Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited.154 Copyright pro

Int. J. Pharm. Sci. Rev. Res., 35(2), November – December 2015; Article No. 28, Pages: 151-155REFERENCES1.David S, Yariv M, Ways to reduce patient turnaround timeand improve service quality in emergency departments,Journal of Health Organization and Management, 19(2),2005, 88-105.2.Medeiros DJ, Swenson E, DeFlitch C, Improving patient flowin a Hospital Emergency Department, Proceeding of theWinter Simulation Conference, 2008.3.Johnson C, Shanmugam R, Roberts L, Linking leanhealthcare to Six Sigma : An Emergency Department casestudy (Unpublished Thesis), 2008.4.Habidin NF, Yusof SM, 2012, Relationship between lean sixsigma, environmental management system, andorganizational performance in Malaysian automotiveindustry, International Journal of Automotive Technology,13(7), 2012, 1119-1125.5.Habidin NF, Yusof SM, Omar CMZC, Mohamas SIS, JanudinSE, Omar B, Lean six sigma initiative: Business engineeringpractices and performance in Malaysian automotiveindustry, IOSR Journal of Engineering, 2(7), 2012, 13-18.ISSN 0976 – 044X6.Habidin NF, Yusof SM, Critical success factors of lean sixsigma for Malaysian automotive industry, InternationalJournal of Lean Six Sigma, 4(1), 2013, 60-82.7.Habidin NF, Yusof SM, Sallehdevelopment and validation ofperformance improvement toolautomotive industry, Journal ofAgriculture, 9(21), 2014, 41-45.8.Habidin NF, Yusof SM, Six sigma, translating strategy,strategic control systems and financial performance inMalaysian automotive industry, Journal of ContemporaryIssues and Thought, 1(1), 2011, 187-204.9.Habidin NF, Structural analysis and tool of lean six sigma,strategic control systems and organizational performance(Doctoral dissertation), Universiti Teknologi Malaysia, 2012.MI, Latip NAM, Thegreen lean six sigma(LSSPI) for MalaysianApplied Science and10. Gitlow HS, Levine DM, Six Sigma for green belts andchampions, Prentice Hall: USA, 2005.11. Terry, Improving process turnaround time in an outpatientclinic (Unpublished), 2011.Source of Support: Nil, Conflict of Interest: None.International Journal of Pharmaceutical Sciences Review and ResearchAvailable online at Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited.155 Copyright pro

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