Using six sigma to improve or throughput

7/27/2019 Using six sigma to improve or throughput

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Using SixSigma andLean Methodologies toImprove OR T h r o u g h p u tC A TH A R IN E B. FA IR BA N K S , R N , M S N / E D , C N O RI m plem enting im provem ents that willresult in tim ely patient flow thro ughthe p eriope rative experience is both achallenge and an opportunity for a hospi-tal, a department, managers, and staffmembers. Various stakeholders often havea variety of op inions and pe rceptions ofwhat is wrong and what is needed to fixa

problem . The challenge of deliveringquality, efficient, and cost-effective serv-ices affects all health care personnel, andim pr ov em ents affect not only th e financialbut the op erational perform ance of a de-partment and, ultimately, the organizationitself. With a focus on and adhe rence to asound methodology that identifies a prob-lem and implements lasting improve-m ents, change can occur and strategicgo als can be achiev ed. Six Sigm a is am ethodology that offers a way to define pro blem s sys-tem atically, p rov ides a m e a n s to measure andanalyze influential factors, identif ies im pr ov em ents that can bei mp l e me n t e d , ensure s that changes are sustainedt h ro u g h a control p hase, and m aintains the gains ove r tim e.

S I X S I GM A D E F I N E DSix Sigm a w as dev elo pe d in the 1986by Motorola, Inc, Schaumburg, Illinois,'and has been used successfully to reducedefects, redundancy, and waste in opera-tional p roce sses. As a re sult of imple-m enting a Six Sigm a pro cess, com paniesmay realize improvements in quality,customer satisfaction, and operationaland financial performance.- This busi-

faction, and overall quality.Sigma (o) is a letter of the Greek al-ph abet th at is used by statisticians todenote the s tandard deviat ion orvari-ability of a process. In a process withSix Sigma capability, process variationis reduce d to no m ore than 3.4 defectsper mil l ion opportuni t ies (DPMO).This can be thought of in two ways: aprocess is correct 99.9964% of the t ime ,or 99.9964% of processes fall within sixstandard deviations of the mean.^

Striving for excellence is an under ly-ing ph i losoph y of Six Sigma. In ahealth care setting, and specifically inan OR th roughpu t p ro jec t , a more rea l -is t ic goal may l ie somewhere betweenFour Sigma and Five Sigma. A patient 'son-t ime arrival to the OR at Four Sig-ma would t ranslate to24 cases o u t of100 m issing the on-tim e start each dayand at Five Sigma would translate toone case o ut of 100 (ie, five cases eachweek) missing the on-time start. A pa-t ient 's on-t im e arrival to the OR , fort h e p u r p o s e of this article, is defined asbeing on time exactly to the scheduledho ur and m inute (eg, 0900).A B S T R A C T

IMPR O VING PATIENT FLOW in the perioperat iveenvironm ent is challenging, but it has positive im pli-cations for both staff members and for the facility.ONE FACILITY IN VERMONT improved patientt h r o u g h p u t by incorporating Six Sigma and Leanme t h o d o l o g i e s for patients undergoing elect ivep rocedures .THE RESULTS O F THE PRO JECT we re significantly


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JULY 2007, VOL 86. NO 1 Fa i rba

A D D I N G A LEAN PROCESSThe project teini at ii soLithvvestern Vermontmedical center found that adding an additionalLean improvement process dramatically helpedto improve certain subprocesses within the largerthroughput process. Lean initiatives focus oneliminating waste or nonvalued activities in aprocess.' These initiati\'es are identified by mem-bers of a designated team, facilitated by a teamleader. This team walks through every step of ma-jt)r processes, measuring time, identifying activi-ties, and making rapid impro\ ements through theelimination of wasteful activi-ties. Using Lean initiatives, theteam was able to eliminate redundancy, resolve former patient trans-port issues, and replace telep hone con:imu-nication with person-to-person communication atthe site of patient care.The point-of-care site wasthe intake area for patients un-dergoing elective surgical pro-cedures. A combination of thestatistical rigor of Six Sigmawith the w\iste-reduction fo-cus of Lean contributed to thesuccess of the project.

T H E D EC I S I O N TO PROCEEDIn late 2004, leaders of thismedical center made a comm it-ment to incorporate Six Sigmainto their strategic philosophyand goals. The cliief executive officer champi-oned the initiative to incorporate a Six Sigma cul-ture into the organization's way of thinking andstrategic expectations. Individuals were nominat-ed and chosen for the Sigma team by executivemanagers. An intensive training schedule wasdeveloped for the Sigma team members.

Two types of team mem bers comprise everySigma team. Each team has one "Black Belt," a

Six Sigma team memberswere chosen for the skillsand knowledge that theybrought to the project.This included knowledge

of hospital finances, dataprogramming, scheduling,

and day-to-dayoperations in the O R,

team. Green Belts are trained to be problemsolvers and receive the samo training as BlacBelts, with the exception of the statisticalanalysis component. Green Belt team mem beoften are operational specialists from variousareas of the organization.

TH E S IX S I G M A TEA MTlu Sigma team for the Oii throughput initiative consisted of a Black Belt who w as a periopeative clinical nurse leader, and four Green Belts a financial specia list, an information systems

specialist, an OR schedu ling speciaist, and a perio pera tive RN frompreadmission teaching.Team members were chosenfor the skills and know ledgethat they brought to the proj-ect. This included knowledgeof hospital finances, data programm ing and retrieval,scheduling, and day-to-dayoperation s. The contact persofor elective surgical patientsalso was part of the team. Thmedical chief of staff waschosen to be the cham pion ofthe team. Subject matter ex-perts became involved in the

- . process as need ed. These in-cluded a perioperative clinicanurse specialist, two surgeonand an anesthesiologist.Training began in August 2005 and majorchanges had been completed by July 2006. At tpoint, the control phase was underway Tliisphase w as scheduled to last at least six months.METHODOLOGYThe life cycle of a Six Sigma project com-

prises five major p hase s. The ph ases are todefine,


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.lirbanks JULY 2007. VOL 86. NO 1

FIGURE 1Problems Identified by Survey Respondents120-

100-

8 0 -cI- 60

4 0 -

20 -

0

Case delay zvas the most requent actor This represents the"vital few" factor inuen cing the system.

-100

-80

-60 ^

-4 0

-20

Case delayNumber 81Percentage (%) 73.6Cumulative % 73.6

Excess paperwork109.182.7

Other65.588.2

Room unstocked54.592.7

IV start43.696.4

TAT* > 30 minutes43.6100.0* TAT turnaround tm\e between cases.

sually one that is systemic or chronic, affect-

roblem into a statistical problem, then into astical so lution, and finally into a practicalDEFINE. The OR throughput project beganon that surgical p rocedures

uled in tlie OR in a manneret surgeon or p atient needs. A frequentlyted cause of this was p rocedu ral de lays. Sig-

he completed surveys, the team grouped sur-to help identify problems, not to

A Pareto ch art (io, a bar chartor categorical data in which categories are pre-

categorical data (ie, the defects), indicating thatthe survey w as an accurate measuremen t tool.When a problem in the data exists, the resultingPareto diagram has equally dispersed defectcategories. In instances when this is noted, thedata are not useful in identifying or addressingthe causes of a problem .To provide focus for the Six Sigma initiative, itwas necessary to identify in-scope and out-of-

scope attributes of the problem . The Sigma teamchose to focus on orthopedic and general sur-gery procedures because these types of proce-dures have the highest x'olume. For measure-ments in this initiative, process time w as definedas beginning when the patient arrives in the fa-cility to register for surgery, and it includes in-room time (ie, time in the OR) to the time the pa-tient leaves the room, as well as the timerequired to turn tlie room over for the next pro-cedure. A fishbonediagram (ie, a pictorial dia-gram in the shape of a fishbone, which shows all


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JULY 2007, VOL 86, NO 1

T A B L E 1Suppl i er , Inputs , Process , Outputs , and

Customers (SIPOC) for Surgical ThroughputS u p p l i e r SiirgotMi I'erioperiitivf ind sterileprocessing dcpiirtment (Sl'D)staff mombor representatives Materials nidnagenit'ntrepresentatives

I n p u t s A ccurate schedule A ccurate preference cards E quipm ent/instruments available Check invento ry iiid pullinstruments for procedure

P r o c e s sl\itient readyfor surgery

SurgeonsA nesthesia staff mem bersPeriopertitive sttiff membersSPD stuff membersPer i ope r.i tive staff members andlicensed nurs ing assistants (I.NA ^

Case cart set up Correct equipment Sterility/asepsis A ccuracy

LNA s i A mbuL itorv care center (A CC) RN i OR RN "


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JULY 2007, VOL 86, NO 1

T A B L E 1SIPOC for SurgicalT h r o u g h p u t ( c o n t i n u e d )Outputs Patient and teammember prepared Family memberssupported Accuracy, correct items On-time start

OR ready forpatient andteam members

Surgery can begin

Correct surgery Safe surgery r Timely surgery No wastet)f materials Patient to PACU or ACC Begin communicationfor next patient

Room ready fornext procedureto be opened

Open for nextprocedure

Customers Patient Facility

Patient Surgeon Perioperativestaff members

I'atient Team members Familymembers

Patient Surgeon & ACP Staif members Familymembers Staff members Next patient

Next patient Staff members

Staff members

The process map is a valuable tool to helpteam members decide what to measure. The

for induction of anesthesia, for emergencefrom anesthesia, and

for room tea rdo wn and cleanup .Room turnaround time also was measured.

MEASURE. The measurement phase was theniost time-consuming and work-intensive por-tion of the process. It required computer pro-gramming to capture data from OR data enteredby the OR scheduling coorciinator and staffmembers. When this was accomplished, datatrends could be identified. During the 13-monthreview period, the average number of proce-dures per day was 18.57. Four or five ORs wereused each day. In December 2005, '[2% of thefirst procedures of the day started exactly ontime and 53 % start ed wit hin five mi nut es of (ie,before or after) the scheduled time.

Process capability gra ph s (ie, a repr esent a-tion of a proc ess that pr od uc es a defect-freeservi ce in a cont rolle d environmenf ^) we reused to deterinine how well certain work cycletimes fell within the specification limits, and adesign target time was chosen for eachprocess, without any extra time allowance."Data on the holding area time (Figure 2)showed an average of 11.6 minutes with a tar-get time allowance of 10 minutes. This trans-lated to a DPMO of 403,846 (eg, a Sigma valueof 1.74). Obviously, much improvement wasposs ibl e in this area. Thi s sort of inf orma tio nwas useful to nursing staff members to shovi'that improvements couici be made.

Boxplot gr ap hs (ie, a gra phic repre senta tiondepicting the centering, spread, and distributionof data') of on-time starts of the physicians indi-cated the best performers in terms of starting ontime with the least variability (Figure 3). Pre-senting this information to surgeons helpedkeep them interested and engaged in the im-provement process.

ANALYZE. Tlie analysis phase of the Six Sigmalife cycle "uses data and statistical tools to un-der sta nd the cause-and-effect rel ationsh ip in theprocess or system."^''^'^^' This step comprises themost important work of the Black Belt teammember, who determines the most sigiiificant


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JULY 2007, VOL 86, NO 1

FIGURE 2Patient in Holding Room Cycle Time0 ininutc>

XIE

1 \ J

1

\\

\\N

\

Dotted line represents Weibull cunvof normaldistribution of the holdingroom time (ie, process).

Opportunity40.38% of cases takeLonger than 10 minutefor holding time.Defects per millionopportunities =403,846

Average = 11.6minutesn - 5 2

2 18 24 30 36Minutes spent in holding area

48

FIGURE 3Procedure Start Times by Physician5 0 -

2 5 -

- 25 -

- 5 0 -

- 7 5 -

Boxplot keyWhiskers (indicate general J. extent of the data)MedianThe box represents the 25th to75th percentile of the data.

C D EPhysician

In the OR throu ghp ut analysis, a fitted lineplot {ie, a linear graph scoring the predicted .imount ot" time the patient spent in the holdi


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JULY 2007, VOL 86, NO 1

FIGURE 4Line PlotPatient Holding Room Time and On-Time Start100 1

Si 50-

-50

-100-1

Null hypothesis: No relationship exists between timepatient spends in holding area and on-time start.

-100 -50 0 50Molding area time in minutes to scheduled time

S*R-Sq"R-Sq(adj)'16.896377.5%77.1%

Conclusion: Statistically significant relationship he-tween amount of time patient presently spends inholding area and on-time start (P= .000).* S is a regression statistical output stiowing unex-

plained data variation.*' R-Sq and R-Sq(adj) indicate the strength of theconclusion.

T AB LE 2On-Time Starts and Key PlayersHypothesis: No reiationsliip exists between on-time start andwhen the key player arrives for the case (eg, difference betweenscheduled time and the time the individual shows up for the case)Regression analysis: The regression equation is on-time start = 7.089+0.533 MD-sched (ie, surgeon arrival to scheduled on-time start) +0.108 ACP*-sched (ie, ACP ready to scheduled on-time start) + 0.276team-sched (if, OR team preparedness to scheduled on-time start)

PredictorConstantMD-schcdACP-sched

Coefficientof variation7.0890

0.10780.275S

SE**coefficient2.04100.12820.10570.1.120

t3.474.161.02

P.001.000.313,042

5 = 11.6780R-Sq - m.7%R-SqCadj) = 89.0%

(regression statistical output showingunexplained data variation)(indicating the strength of the conclusion)(indicating adjusted strength of the conclusion)

Analysis of VarianceSourceRegressionResidual errorTotal

34851

SS'56911654663457

F test18970136 139.10 .000

Conclusions: Slatistii..illv significant relationship between physi-cian arrival for procedure and on-time start (P = .000), and statisti-cally significant relationship between team members' preparedness

plane ) (Table 2) showed a sig-nificant relationship betweensurgeon nrri\'al for a procedureand on-time start {P - .000)and a significant relationshipbetween team preparednessfor procedure and on-timestart (P = .042).

Based on further team dis-cussions, improvement effortswere directed toward reducingor eliminating the holdingarea time, measuring surgeonarrival times, anci demonstrat-ing to surgeons that patientsare transferred to the ORpending the timely arri\'al ofsurgeons. This information ledto a cascade of changes aimedat improving the process.

In the physical, structuraldesign of the health care facili-ty', the ambulatory care admis-sion and discharge areas werelocated on the first floor, andthe OR and postanesthesia careunit (PACU) were lcKated onthe secondfloor.This setup cre-


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JULY 2007. VOL 86, NO 1 Hai rb. i

would meet with pa tients in the holding area.This created a problem because the ambulatorycare center, which is the point of entry (ie, admis-sion and preoperative preparation for surgicalpatients), was not on the same floor as the ORs.

IMPROVE. The improvement phase requiredcontinual and open comm unication with all careprov iders, change facilitation, leadership, feed-back solicitation, sup port, and coaching. It re-quired all staff members to "step outside thebox," to think about doing things differentlyfrom the way things had been done for manyyears. Support from clinical nurse leaders wascritical to the success of the im provem ent phase .

Facused survey of patients indicatedthat patients perceived a greater level

af teamwork among perioperative' ' ' staff mem bers.

Beginning in May 2006, all first cases of theday were brought to the PACU as the stagingarea for nu rsing , anesthesia,, and surgical as-sessment before surgery. Because of thischange, the percentage of on-time starts im-proved dramatically from 12% in December2005 to 89"/ ,. This change w as attributed to point-of-care admission and com mun icationamong all team members, the elimination of teleph one calls to deter-mine if a patient was ready or to send for apatient; the elimination of patient transpo rt time, timely IV starts and adm inistration of anesthe-

sia blKks or morphine spinal anesthesia, and surgeon confidence that when they arrive

cal patients w ere brough t to the PACU staginarea for admission and assessment before sugery. Patients also returned to the PACU staging area for phase 1 and phase 2 recovery andischarge to home. This change w as p erhapsthe most difficult in terms of adjustment bystaff members and in patient-flow strategies. resulted in the PACU becoming the hub of patient and staff-member activity, and this in-creased noise, traffic, and privacy concerns.Focused surveys of patients conducted threeseparate times, however, indicated that pa-tients perceived a greater level of attentiveneand care from providers, experienced reducetransport and waiting times, perceived agreater level of teamwt)rk among physiciansand nurses, and generally were very satisfiedwith all aspects of care.

On a few of the sur\'eys, patients mentioned perceived decrease in privacy. This has becomethe next critical need to be addressed. Designchanges currently are underway to renovate theformer holding area into an intake area and tocreate partitions between phase 2 recovery baysto provide a greater sense of privacy and to faciltate family member presence during recovery.

Turnaround times also have decreased froma mean of 23.8 minu tes to 17.9 min utes. This in pa rt, a result of the availability of patientcare assistants who formerly were multitask-ing with transporting patients and assisting ithe room turnover. Additionally, because stafmembers have increased access to anesthesiacart' providers and surgeons for questions anIV antibiotics and anesthetic blocks are admiistered in a more timely fashion, delay s inturnaround have been reduced.

An additional benefit is that nurses now havthe opportunity for face-to-face hand-off com-munication preoperatively; hand-off communication previously occurred by telephone. Sur-geons also began show ing u p on time or a bitearly, and they voiced a greater confidence thatthere would be fewer p rocedural delays. Whenthe reasons for the change in patient flow were


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JULY 2007, VOL 86, NO 1

0)'1 = 0?* i.5^-20" -40

FIGURE 5On-Time Starts, Before, During and After InterventionJanuary to March 2006 Apri l to June 2006

1 1 V * 1 1 1

Juty to September 2006

[1 14 27 40 53 66 79 92 105 118 131Observation Days

UCL upper control limitIT arithmetic meanLC L lower control limit

Key

UCL = 22.97X = 4.74

LCL = -32.45

Late starts {+)On-time startsEarly starts (-)

in this setting (eg, attempting to trackstarts, assigning licensed nurse assistantstoover rooms, tracking on-time starts by specif-c service or staff members). Changes can be diffi-only by vigilant control ofces be keptfromslipping backatterns. The control phase also pro-ects against a loss of interest by stakeholders.for six months to ensure theof this project.On-time starts, timely physician arrivals,ck turnaround times, and reduced length ofof surgical outpatients currently are beingto ensure that results are maintained. A5)was created to show on-ime starts beginning in December 2005, a periodin control because onlyirst patients of the day came to the PACU ad-itting area; the improved in-room times in bet-er control began in July 2006.GAINS. Improved efficiency creates a greaterapacity for more surgical cases and greaterredictability in surgical start times. It also re-uces the amo unt of overtime required toomplete scheduled surgical procedu res, Twotaff members were assigned to work flexibletime sche dules each day to cover the last pro-

hanced because prospective employees valueefficiency in a job setting.Patient sur\ ey satisfaction scores improvedduring the quarter following the implementa-tion of these changes. Wait times before surgi-cal proced ures im proved 2.4 points (ie, a scorebased onpercentage) from 85.7 to88.1. Com-munication of information regarding delaysthat did occur improved 2.3 points from 85.9to 88.2. Patient perception of how well staffmembers worked together improved 1.4 pointsfrom 95.8 to 97.2 with statistically significantgains at a .05 confidence level. The overall facil-ity rating improved 1.2 points from 93.2 to 94.4,and ambulatory overall scores improved fromthe 84th percentile to the 97th percentile.CONCLUSIONIn a report of a similar Six Sigma initiative un-dertaken by another health care facility, Adams etal noted that before the initiative to decrease turn-around time between general surgery cases, "eachpart of the team was quick to blame someone[else] for long hjmaround times.""''''"^' A similarobservation was made before the commencementof this Six Sigma project. After the Six Sigma ini-tiatives were employed, staff members noted agreater sense of cohesiveness, collaboration, and


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JULY 2007, VOL 86, NO 1 Fairb

R E F E R E N C E S1. Motorola University'. Six Sigma dictionary, http://vvww.motorola.com/contL'nt.jsp?globa!ObjectId=3074-5804. Acces.sed March 20, 2007.2 . Carrigan MD, Kiijawa D. Six Sigma in healthcart' management .iiid strategy Health Ciuv Manag(Freilerick). 200b;25{2):\3?,-U]'3 . Juran Institute. Six Sigma introduction, http://www.jiiran.com. Accessed May 16,2007.4. Cygi C, DeCarlo N, Williams B. S/.v Sigmn forDummies. Hoboken, NJ: For Dummies; 2005.'5. Statistical Six Sigma definition. iSixSigma.com.ht tp : //wwvv.isixsigma,com/library/content/cOlOlOla.asp. Accessed March 19, 2007. "6. Pexton C. Measuring Six Sigma results in the

healthcare industry. iSixSigma.com. http://healthcam,isixsigma.com/library/contL'nt/c040623a.aspAccessed March 19, 2007.'7 . Adams R, Warner P, Hubbard B, Goulding T Dcreasing turnartiund time between general surgerycases: a Six Sigma initiati\'e. / Niif.s Aiim. 2004;34(3140-148.

Catharine B. Fairbanks, RN, MSN/ED,CNOR, is director of perioperative servicesat Southwestern Vermont Medical Center,Bennington, VT.

Moderate Dr ink ing May Reduce Women's Hear t At tack RiskW omen who regularly drink alcohol in modera-tion but do not get drunk may reduce their n'skof having a nonfatal heart attack, according to aJune 5, 2007, article in the New York Times. Womenwho had a daily alcoholic drink were 3 1 % less like-ly to have a nonfatal heart attack than women whohad less than one drink a day. Women who becamedrunk (eg, those who experienced slurred speech orunsteady gait) even once a month, however, werealmost six times more likely to have a heart attack.Researchers studied 320 women between theages of 35 and 69 years who had experienced heart

attacks and compared them with 1,565 healthywomen of similar age. Data were adjusted for agerace, education, smoking, and body mass index.The data were collected through self reporting,which may be subject to error; however, the impcations of the study are that there may be healthbenefits to the moderate consumption of alcohoBakatar M. Heart health: women who drink a little mayheart-attack risk. New York Times. June 5. 2007. http://www. nyt imes. com/2007/06/05/health/05hear. h tml. AcJune 5, 2007.

Fetal Mortalities Decline but Radal Disparities RemainT he rate of fetal deaths (ie, stil lbirths) occurringat 20 weeks of gestation or more decreased sub-stantially between 1990 and 2003, according to aFebruary 21, 2007, news release from the Centersfor Disease Control and Prevention. The fetal mor-tality rate (ie, number of fetal deaths per 1,000live births and fetal deaths) showed a steady de-cline of an average of l.t% per year from 1990 to2003, particularly among pregnancies at 28 weeksof gestation and longer.

Although the rates declined across all racial andethnic groups, the rate for non-Hispanic blackwomen (ie, 11.56 per 1,000) was more than doublethat of non-Hispanic white women (ie, 4.94 per1,000). Researchers also found that the fetal mortali-ty rate for American Indian women (ie, 6.09 per 1,000) was24% higher than that for non-Hispanic white

w o m e n ; and Asian or Pacific Islander women (ie, 4.98 per

1,000) was comparable to that for non-Hispaniwhite women.Relatively little is known about the causes offetal mortality. Researchers have identied risk factors for a fetal death, however, including placentaand cord problems and intrauterine growth retardation as well as the mother smoking during pregnancy, being obese, having severe or uncontrolled high blood pressure having diabetes, having infections, and having had a previous perinatal death.N ew Report Shows Decline in Stillbirths; Racial DisparPersist [news release}. Atlanta, G o: Centers for Diseas


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Using six sigma to improve or throughput