Re-Engineering the Operating Room Using VariabilityMethodology to Improve Health Care Value

C Daniel Smith, MD, FACS, Thomas Spackman, MD, Karen Brommer, RN, Michael W Stewart, MD,Michael Vizzini, MBA, James Frye, MBA, William C Rupp, MD

BACKGROUND: Variability in flow of patients through operating rooms has a dramatic impact on a hospital’sperformance and finances. Natural variation (uncontrollable) and artificial variation (control-lable) differ and require different resources and management. The aim of this study was to usevariability methodology for a hospital’s surgical services to improve operational performance.

STUDY DESIGN: Over a 3-month period, all operations at a referral center were classified as either scheduled(artificial variation) or unscheduled (natural variation). Data regarding patient flow werecollected for all cases. From these data, mathematical models determined explicit resources tobe allocated for scheduled and unscheduled cases, with isolation of the 2 flow streams.Services were allocated block time based on 80% prime time use, and scheduled cases werecapped at 5:00 PM. Guidelines for operating room access were implemented to smooth thedaily schedule and minimize artificial variation on the day of surgery. After implementationof this redesign, 12 months of data were compared with the previous 12-month period.Metrics analyzed included prime time use, overtime minutes, access for urgent or emergentcases, the number of room changes to the elective schedule on the day of surgery, andvariation of daily schedules.

RESULTS: Surgical volume and surgical minutes increased by 4% and 5%, respectively. Prime time useincreased by 5%. Overtime staffing decreased by 27%. Day-to-day variability decreased by20%. The number of elective schedule same day changes decreased by 70%. Staff turnover ratedecreased by 41%. Net operating income andmargin improved by 38% and 28%, respectively.

CONCLUSIONS: Variability management results in improvement in operating room operational and financialperformance. This optimization may have a significant impact on a hospital’s ability to adaptto health care reform. (J Am Coll Surg 2013;216:559e570. � 2013 by the AmericanCollege of Surgeons)

Our current health care system is heavily leveraged todeliver complex care through a hospital system. Thismodel of care is inefficient, expensive, and unsustainablein its current form. Preventative and predictive medicinepromise to improve an individual’s overall health whilemoving much of this care out of hospitals and into

Disclosure Information: Dr Smith served as a consultant for the Institutefor Healthcare Optimization, a not-for-profit entity, and received hono-raria for helping teach others the methodology used as part of the studydetailed in this article. All other authors have nothing to declare.

Presented at the Southern Surgical Association 124th Annual Meeting,Palm Beach, FL, December 2012.

Received December 12, 2012; Accepted December 12, 2012.From the Departments of Surgery (Smith), Anesthesiology (Spackman),Ophthalmology (Stewart), and Medicine, Division of Oncology (Rupp);Nursing Administration (Brommer); and Administration and Finances(Vizzini, Frye); Mayo Clinic in Florida, Jacksonville, FL.Correspondence address: C Daniel Smith, MD, FACS, Department ofSurgery, Mayo Clinic Florida, 4200 San Pablo Rd, Jacksonville,FL 32224. email: smith.c.daniel@mayo.edu

559ª 2013 by the American College of Surgeons

Published by Elsevier Inc.

outpatient settings or even patients’ homes. Althoughexciting, it will take decades before this promise can befully realized, and until then we will remain dependenton our hospitals as substantial care delivery platforms.The heavy dependence on hospitals is especially true

for the delivery of surgical care. Surgical care generatessubstantial revenue for hospitals, but it is also one ofthe largest drivers of cost within the hospital, and healthcare reform’s mandate to cut costs while simultaneouslyproviding care to millions of currently uninsured Ameri-cans will significantly affect our hospitals’ operatingrooms and surgical services.Over the years, numerous studies have looked at

improving the efficiency of an operating room’s perfor-mance.1-5 Most have tried to identify and eliminate wasteto improve throughput without increasing resources; putsimply, if cases start on time and room turnover timeis decreased, more cases will be completed in a day.

ISSN 1072-7515/13/$36.00

http://dx.doi.org/10.1016/j.jamcollsurg.2012.12.046

560 Smith et al Operating Room Optimization J Am Coll Surg

Although these efforts remain important, and somewould argue that improving patient flow through an indi-vidual operating room remains the holy grail of operatingroom efficiency, managing the flow of surgical patientsinto hospitals and operating rooms is a relatively unex-plored area that could yield significant gains in operatingroom performance. Tools used outside of health care helpindustries such as manufacturing and telecommunica-tions predict demand on resources and optimally manageflow into a system to allow consistent product delivery.6-8

These efforts focus largely on understanding andmanaging variability in demands on a system. Using theseconcepts and tools is a promising way to redesign ourhospital management strategies and deliver high valuecare consistent with health care reform mandates.7,9-11

To meet an increased demand for surgical services atthe Mayo Clinic Florida practice, construction of addi-tional operating rooms was being seriously considered.However, baseline data suggested that operating roomswere being underused during regular working hours(prime time), despite the incurrence of considerable over-time. We hypothesized that by using operations manage-ment principles and variability theory, we could expandthe capacity of our hospital’s operating rooms andincrease surgical throughput without adding infrastruc-ture or expense. The aim of this project was to test thishypothesis by designing and implementing a new oper-ating room management strategy. Herein we presenta case study of this work with 1-year results.

METHODSThis project was undertaken in collaboration with theInstitute for Healthcare Optimization (Boston, MA,www.ihoptimize.org), an independent not-for-profitresearch, education, and service organization that usesoperations management principles and variability meth-odology to help design strategies to manage patientflow through hospitals. With the direction and fullsupport of the hospital’s CEO, goals with measurableendpoints were established (Table 1). The focus of the

Table 1. Study Goals (Endpoints)

Primary goals (endpoints)Increased surgical volume (no. of cases and minutes of surgery)Decreased overtime (nonprime time minutes of surgery)Maintain appropriate access for emergency surgery (classificationcompliance)Secondary endpointsPredictable elective operating room schedule (no. of same daychanges to elective case schedule)Assure surgeons work with their primary team (block utilization)Staff satisfaction (staff turnover rate)Financial impact (net operating income)

project was to manage the flow of surgical patients intothe hospital and operating rooms to optimize the use ofexisting resources. This initiative was designated as the“Managing Variability Program (MVP),” with the“Program” designation to indicate its enduring presenceas opposed to a “project,” which is of finite duration.The executive group that managed the day-to-day

operations of the operating rooms formed the programteam (Table 2). This is a subcommittee of the SurgicalCommittee, which is composed of the chairs of all thesurgical departments and divisions and provides gover-nance and approval for all activities related to the hospital’ssurgical services. Beginning in November 2009 andextending through the implementation phase and firstyear of management, this executive team met twice weeklyto design and implement the operating room redesign.The program development was broken into 3 separate

but inter-related components: design, implementation,and management. Each was pursued concurrently toimplement the redesign on November 1, 2010 and assessits impact after 1 full year.

Design

Overall concepts of model

Design features are detailed in Table 3. The redesign ofthe management of the operating rooms relied on under-standing and defining variability in surgical patient flow.Variability theory defines 2 types of variation: naturalvariation (over which we have no control) and artificialvariation (which can be controlled). An example ofnatural variation (an emergency or unscheduled case)would be a patient presenting with an acute abdomenrequiring urgent surgery. Appropriate resources must beavailable at all times to care for these unscheduled cases.In contrast, artificial variation results from uneven sched-uling of elective operations. This creates artificially lightand busy surgical schedules, which may vary considerablyfrom day to day. The scheduling of an elective case can bemanaged according to pre-set clinical criteria, allowingflexibility in creating an operating room schedule to

Table 2. Operating Room Redesign Team

Chair, Surgical Committee e Chair, Department of SurgeryVice Chair, Surgical Committee e Chair, Department ofAnesthesiologyMember Surgical Committee e Chair, Department ofOphthalmologyAssociate Administrator, Surgery and Procedure OperationsDirector, Surgical ServicesDirector, Systems and ProceduresFinancial AnalystsInstitute for Healthcare Optimization Team Members

Table 3. DesignFeatures forOperatingRoomRe-Engineering

1. Understand and define variability in patient flow.2. Isolate natural variation from artificial variation.3. Define prime time and establish a “hard stop” to an operative

day.4. Establish urgency classifications.5. Collect prospective data based on preliminary definitions and

assumptions.6. Use mathematical modeling and test probability scenarios to

decide on room allocations for elective and emergent cases.7. Allocate service blocks based on actual service-specific needs.8. Assign block time to effect smoothing of volumes throughout

week.9. Re-evaluate staffing levels and tie to block time allocations.10. Set expectations around block utilization thresholds to gain or

lose block.

Table 4. Urgency Classifications for Urgent and EmergentCases

A e must start within 45 minB e must start within 2 hC e must start within 4 hD e must start within 8 hE e must start within 24 h

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best match fixed resources with the needs of the patientand surgeon.Unscheduled and scheduled surgical patients compete

for the same resources, but each represents a uniquelydifferent demand on hospital resources and patientflow. Despite the distinctly different needs for each ofthese cases, their scheduling into operating rooms is oftendetermined by patient and surgeon preference, and on theday of surgery, managed on the fly by a “board runner.”This leads to mixing of the scheduled and unscheduledflow streams and resources, resulting in significant unpre-dictability and unnecessary variability. To compensate forthis, operating rooms become chronically under- or over-staffed and under- or overused, creating an expensive andpoorly used resource that leads to significant staff andsurgeon dissatisfaction.At a very high level, once this definition of patient flow

variability is established and understood, a carefulaccounting and analysis of a hospital’s specific case types(scheduled vs unscheduled) and volume can be collectedand used for mathematical modeling of resource alloca-tion (eg, rooms, staff, equipment). This allows separationof the unscheduled cases and their resources from thoseneeded for elective cases.This isolation of unscheduled from scheduled surgical

cases is an essential component of variability method-ology. At its core, variability methodology involves iden-tification, quantification, and elimination of artificialvariability so that the flow of elective patients can bemanaged to optimize the operating rooms’ performanceand produce a smooth day-to-day schedule that ispredictable and reliable. If unscheduled cases are allowedto blend into the elective schedule, the predictability andreliability are lost, and if scheduled cases blend into theresource allocated for unscheduled cases, access for thoseunscheduled cases becomes blocked, inducing unaccept-able delays for emergent care.

To fully model and redesign a surgical practice,a comprehensive characterization of the surgical volumeis needed to do the mathematical modeling required fordecisions about resource allocation. In its most basicform, this includes classifying all cases as either scheduledor unscheduled, establishing urgency classifications forunscheduled cases (Table 4), measuring the start andend times of each case, and defining prime time (whenthe regular work day starts and stops). With these data,mathematical modeling creates numerous probability sce-nariosdeach uniquely dependent on how resources areallocateddwith risks calculated for each allocationstrategy. Risk is defined as not being able to accommo-date all emergency surgery within urgency classificationsor bumping of elective cases. Examples of several riskscenarios are shown in Table 5. Selection of an allocationmodel must only be done once the various probabilityand risk scenarios are considered. Once an allocationmodel has been selected, case scheduling tools, dailymanagement strategies, and metrics with reporting toolscan be developed to facilitate implementation andmanagement of the program.

Mayo Hospital Specific Design

We defined an urgent/emergent case as one that must beperformed within 24 hours for clinical reasons. We sub-divided the urgent/emergent case classification into 5distinct urgency classifications (Table 4). When postingan urgent/emergent case, the surgeon was asked to declarethe urgency classification. Cases that could wait morethan 24 hours, but needed to be completed within 5days, were classified as work-in cases. Work-in caseswere further classified according to either clinical need(eg, gallstone pancreatitis needing cholecystectomy beforedischarge) or administrative reasons (eg, surgeon orpatient required surgery within 5 days but not for clinicalreasons). All other cases were classified as elective. Wedefined prime time as 7:30 AM to 5:00 PM Mondaythrough Friday.Data were then collected for 3 months (Table 6). No

changes to how the operating rooms were assigned ormanaged were made during this 3-month data collectionphase. These data allowed characterization of the practice

Table 5. Examples of Probability Scenarios Used for RiskModeling and Choice of Redesign Plans

Cases included Variables

Scenario 3 - weekday prime time*

All urgent/emergent, rooms needed, n 1

Average room use, % 51.4

Case urgency classification Average waitingtime, min

A - within 45 min 92

B - within 2 h 107

C - within 4 h 132

D - within 8 h 171

E - within 24 h 268

Frequency of classification A bumps 1 every 2.7 wk(30% of all A cases)

Scenario 1 - weekday prime timey

All urgent/emergent, rooms needed, n 3

Average room use, % 17.1

Case urgency classification Average waitingtime, min

A - within 45 min 1

B - within 2 h 1

C - within 4 h 1

D - within 8 h 1

E - within 24 h 1

Frequency of classification A bumps 1 every 167 wk

Scenario 15 - weekday prime timez

All urgent/emergent þ kidneytransplant, rooms needed, n 2

Average room utilization, % 33.5

Case urgency classification Average waitingtime, min

A - within 45 min 16

B - within 2 h 17

C - within 4 h 19

D - within 8 h 22

E - within 24 h 28

Frequency of classification A bumps 1 every 8 wk

*Isolating 1 room for all urgent/emergent cases.yIsolating 3 rooms for all urgent/emergent cases.zIsolating 2 rooms for all urgent/emergent cases.

562 Smith et al Operating Room Optimization J Am Coll Surg

according to the categories and definitions used for theredesign and future management.After data collection was complete, modeling was per-

formed and probability scenarios, as outlined above and

Table 6. Preliminary Data Collection (3 Months)

Type of case e elective or urgent/emergentUrgency classification if urgent/emergent: A, B, C, D, EUrgent/emergent case request timeWheels in time: time patient entered operating roomWheels out time: time patient left operating room

depicted in Table 5, were considered. Rooms (includingstaff, equipment, instruments, and supplies) were allo-cated for urgent/emergent, work-in, or elective cases(Fig. 1). These data were also used to allocate electiverooms to the various surgical services as elective blocktime. Sufficient operating room block time was assignedto meet 125% of each service’s current demand. Putdifferently, a service that continued its current volumeof work would use 80% of its elective block room alloca-tion. After determining each service’s operating roomrequirements, elective block was assigned to assure thatcases were evenly distributed throughout the week toavoid disparate peaks and valleys in daily surgical volume(ie, the weekly volume was “smoothed” to allow a morepredictable end to each elective day). This resulted inan overall redesign of the operating room resource alloca-tions based on understanding and managing variability,to increase prime time capacity and use, and smooththe weekly volume of elective surgery performed.

Implementation

Concurrent with the redesign efforts, tactics for effectiveimplementation of the redesign were developed. Althoughbeyond the scope of this manuscript, implementationfollowed principles of quality improvement and changemanagement. All existing policies related to the day-to-day function of the operating rooms were reviewed andrevised to be consistent with anticipated redesign. Consid-eration was given to staged implementation by selectedservices vs simultaneous implementation by all services.To maximize the flexibility and impact of the redesign, itwas decided to implement the program for the entiresurgical practice at the same time. All policy changes andresource allocations were vetted and approved by theSurgical Committee (composed of the chairs of all surgicaldepartments and divisions) and the Executive OperationsTeam of Mayo Clinic in Florida. The new program wasimplemented on November 1, 2010.

Management

The design team served as the management team(Table 2). Dashboards for day-to-day, weekly, monthly,and rolling quarterly data were used (Fig. 2). Decisionstrees were developed to help manage conflicts and facili-tate real-time decision-making regarding access to theoperating rooms. Anesthesia and Certified RegisteredNurse Anesthetist board runners were educated regardingthe principles of the program. Consistent with qualityimprovement and change management principles,changes in the program (based on feedback and dataanalysis) were considered after 3 months.

Figure 1. Breakdown of room allocations for final redesign. CTS, cardiothoracic surgery; GS,general surgery; H/L, heart/lung; NS, neurosurgery; Ortho, orthopedic surgery; Tx, transplant.

Vol. 216, No. 4, April 2013 Smith et al Operating Room Optimization 563

RESULTSResults are summarized in Table 7. One year after imple-mentation of the redesign, both surgical volume (þ4%)and surgical minutes (þ5%) had increased. Prime timeuse increased by 5%, while overtime staffing decreasedby 27%. Day-to-day variability in case volumes andminutes of surgery decreased by 20% and 22%, respec-tively (Fig. 3), indicating a smoothing of the surgicalschedule. The number of same day changes to the electivesurgical schedule decreased by 70% (Fig. 4). A 41%decrease in staff turnover suggested improved job satisfac-tion (Fig. 5). These results were accompanied byimprovements in net operating income and net operatingmargin (38% and 28%, respectively).

DISCUSSIONOptimizing the function of a hospital’s operating rooms iscritical to delivering safe, cost-effective surgical care. Formany, the focus of optimizing the performance of oper-ating rooms has centered on increasing efficiency.5,12,13

Most attempts have tried to shorten the duration of oper-ating room processes (eg, room turnover time) to createcapacity for additional surgical cases. LEAN and Six Sigmaare commonly used managerial techniques to eliminatewaste and improve efficiency.1,2 Although these improve-ments are important, emerging concepts from nonhealthcare sectors centered around variability methodologypromise to expand capacity beyond what can be gainedby efficiently running the operating room. Variabilitymethodology aims to manage the flow of patients intoa hospital’s operating rooms and surgical services, asopposed to flow through the operating rooms themselves.

To effect improvements, the required methodology,processes, and metrics are vastly different from those thatimprove efficiency within a single operating room. Forexample, efficiency efforts geared to improving in-roomoperating room performance include strategies such asparallel processing, use of induction rooms, on-time starts,and shortened room turn-over times.3–5 In contrast, vari-ability methodology aims to isolate scheduled cases (artifi-cial variation) from unscheduled cases (natural variation),distribute scheduled cases throughout the week to smooththe weekly volumes, and allocate appropriate resources forunscheduled cases to avoid access restrictions.6,7,12,14,15 Thepredictability and subsequent operational gains achievedwith this methodology create capacity otherwise consumedby unmanaged artificial variation. This allows greater over-all throughput (more surgical cases) without the addition ofincremental resources. Ideally, the 2 efforts, operatingroom efficiency and variability management, are bothpursued and optimized.This project and case study explored the use of variability

methodology to achieve the stated goals. The work encom-passed not only application of this methodology, but alsothe design, re-engineering, implementation, and subse-quent impact of these concepts. To date, this is the mostcomprehensive application of these concepts to a hospital’ssurgical services, and through this effort and experience,significantly positive results were achieved.The results regarding performance outcomes are self-

evident. Throughput was increased without incrementalexpense, overtime was reduced, staff satisfaction wasimproved, and the same day changes to scheduled caseswere significantly decreased, all while maintaining appro-priate operating room access for urgent and emergent

Figure 2. Example of dashboard used for reporting metrics to leaders of surgical practice. MVP, managing vari-ability program.

564 Smith et al Operating Room Optimization J Am Coll Surg

cases. When taken together, these results led to improvedfinancial performance. Though not directly measured,one could argue that this redesign should also lead to safersurgery. Increasing prime time, service-specific block utili-zation means surgeons are consistently working with theirusual teams, thereby enhancing team work. Furthermore,by limiting the number of same-day changes to the electiveschedule, fewer cases are rerouted to rooms and teams notpreviously expecting these cases, limiting the errors thancan accompany multiple “handoffs.”

Other significant consequences of this work not readilyevident from these data, and beyond the scope of thismanuscript, deserve mention. Many of these concernthe cultural change required to implement sucha program. Although the management concepts devel-oped and used may appear obvious and simple tosomeone knowledgeable and versed in these principles,and the data are certainly compelling, the actual day-to-day application of variability methodology is counterintu-itive to how surgical practices and hospital systems have

Figure 2. Continued

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been structured. At its core, the cultural change asksproviders to transition from managing their practices,and especially their surgical schedules, from what is bestfor the surgeon and patient, to what is best for thehospital. That’s not to say that the patient ceases to bea focus of this redesign concept because the entire model

is built around defining the patient’s clinical needs andassuring appropriate resources are available to meet thoseneeds. One could argue that this concept is very patientcentric in assuring the availability of the right team atthe right time to meet the patient’s surgical needs.However, hospitals generally cater to the surgeon’s

Table 7. Results: Changes in Operational Performance of Operating Room

Variable Pre-redesign Postredesign Change, %

Surgical cases, n 11,874 12,367 4

Surgical min 1,757,008 1,844,479 5

Prime time OR use, % 61 64 5

Number of overtime full time employees, average, n 7.4 5.4 �27

Staff turnover rate, % 20.3 11.5 �43

Daily case volume variation (upper-lower control limit) 55.24 44.06 �20

Daily case minutes variation (upper-lower control limit) 6,531 5,124 �22

Daily elective room changes, average/mo 80 25 �69

Daily elective room changes, % 8 2 �70

Cost/case (added 15 OR staff full time employees), $ 1,062 1,070 0

Cost/min of surgery (added 15 OR staff full time employees), $ 7.18 7.26 1

Staff turnover cost (millions), $ 2.47 1.40 �43

Overtime cost savings, $ 111,488

Total OR net revenue (fee increase adjusted), $ 93,929,569 98,686,693 5

Net operating income, $ 15,877,986 21,957,708 38

Net operating margin, % 17 22 28

OR, operating room.

Figure 3. Control charts showing change in variability after implementation of oper-ating room redesign. LCL, lower confidence limit; UCL, upper confidence limit.

566 Smith et al Operating Room Optimization J Am Coll Surg

Figure 4. Number of changes to elective surgical schedule on theday of surgery before and after implementation of operating roomredesign. MVP, managing variability program.

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schedule to facilitate that surgeon delivering surgical carein that hospital. This business model has worked for allparties because it generally meets the patient’s needs,enhances the surgeon’s ability to deliver care even whenfaced with several competing demands, and keeps high-revenue surgical care at the given hospital. The hospital’srevenue has been sufficiently favorable to allow a “what-ever, whenever” culture for the surgeon and still maintaingood operating margins.Today, those favorable margins enjoyed by hospitals

are evaporating, forcing hospitals to cut costs while main-taining high-quality outcomes. At the same time, thesequality-focused outcomes are becoming increasingly scru-tinized and will soon factor into reimbursement formulas.Hospitals across the country are aggressively pursuingcost-cutting strategies, and the high-value, high-cost envi-ronment of the operating room is a prime target for cost

Figure 5. Staff turnover rate and cost over first 12 mont

reduction. Applying variability methodology swings thependulum for access to the hospital’s operating roomsfrom “whatever and whenever” the surgeon wants, towhat is best for the hospital. Put more directly, in thismodel, the surgeon is asked to compromise to meet thehospital’s financial needs. The resultant tension betweena surgeon and hospital administration can become intenseand was certainly present during the redesign and imple-mentation detailed in this case study. Before embarkingon such a program and applying variability methodology,it is critical that a detailed assessment of the hospital’sculture, its providers, and their willingness to acceptchange be performed. Process improvement and changemanagement strategies and tools should be assessed andliberally applied because gains like those demonstratedhere may take considerable time to realize. Softwareand information technology tools to help schedulesurgical cases within the redesign goals, and reportingtools within a quantitative dashboard are essential to facil-itate adoption of this program. Transparency regardingleadership decisions and frequent feedback to allproviders about performance improvements should beemphasized. Change management and analytics supportshould be identified either internally or pursued exter-nally before starting such a program.Finally, the more commonly pursued efficiency efforts

remain an essential component to realizing the gainspossible with variability methodology. Perfect manage-ment of the flow of patients into the surgical practicewithout an efficient and well-run operating room willproduce suboptimal results. The perfect schedule that istheoretically predictable and reliable will disintegrate ifpatients cannot enter and exit operating rooms in anexpeditious and efficient manner. The methods described

hs after implementation of operating room redesign.

568 Smith et al Discussion J Am Coll Surg

here do not replace these important elements of a well-managed suite of operating rooms.

CONCLUSIONSIn summary, we have shown that redesigning operatingroom management around variability theory and meth-odology allows increased throughput while increasingprime time use, decreasing overtime, and improving staffsatisfaction. At the same time, day-to-day variability incase volume and within-day changes to the electiveschedule are decreased, resulting in a more predictableand reliable flow of cases through the operating rooms.Overall, these improvements result in better financialperformance and support the hypothesis that moresurgical cases can be performed without incrementallyincreasing the cost of delivering that care. This strategyholds great promise for helping hospitals and surgeonsadapt to the challenges created by impending healthcare reform.

Author Contributions

Study conception anddesign: Smith, Spackman, Brommer,Stewart, Rupp

Acquisition of data: Brommer, Vizzini, FryeAnalysis and interpretation of data: Smith, Stewart,Vizzini,Frye

Drafting of manuscript: SmithCritical revision: Smith, Stewart, Vizzini

REFERENCES

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Discussion

DR JULIE A FREISCHLAG (Baltimore, MD): I actually hadspoken to Dr Smith quite a bit when we, too, became involved in

this process and used the Institute for Healthcare Optimization toimprove our operating room variability at Johns Hopkins. Wealso knew we were going to be moving into a new hospital and we

wanted to do things better before we moved. The 3 key things wefound in our process were preparation and buy-in of all the staff,nursing, anesthesia, and surgery, and that months of collecting

data and meetings were very important. We have to have championsin each area. And you have to stay focused on what’s best for thepatient, because, frankly, the way we run the OR is what’s best forthe surgeon. When are you available? When do you have clinic?

When do you have research? When are you out of town? We doa lot of negotiation about whether or not the patient needs surgeryright away or not, and we have to be really transparent about the

real urgency of the case. Is the surgeon really available? You know,most of us put in a slip and go do something else for 8 hours becauseit’s never going to get on. And what were the reasons that the case

didn’t go as planned? A third of the time, it is the surgeon; a thirdof the time, the patient; a third of the time, anesthesia and others.

And this is not for the faint of heart. Dr Smith and I have bothtaken major body blows for doing this kind of process in an oper-

ating room. And when you redesign the culture and take awayblock time, you can imagine how painful that will be. We, too,now do 6 to 8 more cases a day. We did that even before we got

into the new operating room with the new capacity. And wehave seen similar decreases in costs and more efficiency and lesspain in getting that elective case not interrupted, that urgent case

on, and even work-ins, of which we have a lot.Our elective rooms started off with more than 80% use, and

now it’s close to 95%. We have more block time to offer to others,

and we do take it away. The minute you’re under 80%, your blocktime goes, because we have to have 95% use of block time. We have5 emergent rooms that run about 60%.