Here’s a Better Way to Schedule Surgeries
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Operations Healthcare Sep 5, 2018

Here’s a Bet­ter Way to Sched­ule Surgeries

A new tool could dri­ve sav­ings of 20 per­cent while still keep­ing sur­geons happy.

A man tries to improve OR scheduling.

Michael Meier

Based on the research of

Chaithanya Bandi

Diwakar Gupta

When patients arrive at the hos­pi­tal for a surgery, they prob­a­bly don’t think about what goes into sched­ul­ing the oper­at­ing room (OR) where the pro­ce­dure will happen. 

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But OR sched­ul­ing is some­thing that Chaithanya Ban­di, asso­ciate pro­fes­sor of oper­a­tions at the Kel­logg School, thinks about — a lot.

How best to sched­ule ORs is an impor­tant puz­zle hos­pi­tals need to solve,” Ban­di says. They need to allo­cate rooms while both hon­or­ing the requests of sur­geons and keep­ing costs in check.” 

ORs are indeed cost­ly to oper­ate — $1000 per hour is typ­i­cal — but they also make mon­ey. Sur­gi­cal oper­a­tions and asso­ci­at­ed hos­pi­tal­iza­tions typ­i­cal­ly gen­er­ate about 70% of total hos­pi­tal rev­enues. So opti­miz­ing OR sched­ul­ing is a top pri­or­i­ty for administrators.

Ban­di and col­lab­o­ra­tor Diwakar Gup­ta of the Uni­ver­si­ty of Texas, McCombs School of Busi­ness stud­ied sur­gi­cal-request data at a large com­mu­ni­ty hos­pi­tal. They found that hos­pi­tals gen­er­al­ly keep more ORs at the ready than might be need­ed at any giv­en time in order to accom­mo­date unpre­dictable sur­geon requests. 

In hopes of reduc­ing this cost, the researchers devel­oped an inno­v­a­tive algo­rithm to improve OR oper­a­tions, min­i­miz­ing the num­ber of ORs hos­pi­tals had to keep open, while still hon­or­ing sur­geon requests.

Our goal was to help hos­pi­tals improve on cur­rent OR oper­a­tions while still sat­is­fy­ing sur­geon needs.”

Appli­ca­tion of the algo­rithm can dri­ve sav­ings of about 20% in OR costs — a fig­ure with sig­nif­i­cant impact on hos­pi­tals’ bot­tom lines. And Ban­di sees appli­ca­tions for this algo­rithm-dri­ven approach in oth­er fields that have high costs and unpre­dictable sched­ul­ing requests.

We designed the algo­rithm for a spe­cif­ic med­ical con­text,” he says, but its appli­ca­tions stretch well beyond that.” 

The Chal­lenge of Hos­pi­tal Scheduling

Hos­pi­tal admin­is­tra­tors gen­er­al­ly use a sched­ul­ing sys­tem to deter­mine which OR will be assigned to meet a surgeon’s request for a par­tic­u­lar surgery. 

This process is decep­tive­ly com­plex because in order to opti­mize OR sched­ul­ing, hos­pi­tals must take three main con­sid­er­a­tions into account. 

First, the cost: a ful­ly staffed OR costs an esti­mat­ed $15 – 20 per minute to run, or about $1,000 or more per hour. That means the few­er ORs the hos­pi­tal can keep open at any giv­en time, the greater the savings. 

Sec­ond, hos­pi­tal admin­is­tra­tors try their best to hon­or sur­geons’ requests for spe­cif­ic OR slots. 

Sur­geons are very impor­tant from a hospital’s point of view,” Ban­di says, so the admin­is­tra­tors work hard to respect their preferences.”

The third fac­tor is the noisy” nature of OR requests, which arrive at irreg­u­lar, unpre­dictable times giv­en that patients’ health prob­lems do not occur on a reg­u­lar schedule. 

The chal­lenge is that the hos­pi­tal doesn’t know when the OR requests will arrive,” Ban­di says. It’s just a call that the sur­geon makes, and the hos­pi­tal needs to find the space — they can’t move the patient to a dif­fer­ent hos­pi­tal or surgeon.” 

Anoth­er unknown is the exact amount of time an upcom­ing surgery will take. Sur­geons have a gen­er­al sense of how long a giv­en pro­ce­dure takes,” Ban­di says, but there is a very wide range — it could be half the request­ed OR time or dou­ble, and hos­pi­tals need to find a way to accom­mo­date this.”

Because so many fac­tors in OR sched­ul­ing are unpre­dictable and unknown, hos­pi­tals tend to prep and staff an excess num­ber of ORs to accom­mo­date all requests. Ban­di says, It’s a prob­lem of excess capac­i­ty — and a cost­ly one.” 

Bet­ter OR Sched­ul­ing, Low­er Costs

The fac­tors above sug­gest an intrigu­ing research opportunity.

Our goal was to help hos­pi­tals improve on cur­rent OR oper­a­tions while still sat­is­fy­ing sur­geon needs,” Ban­di says. 

Using 18 months of sur­gi­cal sched­ul­ing data shared by a large hos­pi­tal, the researchers devel­oped an algo­rithm to do exact­ly that. Their mod­el used a nov­el approach to ana­lyze OR request data and deter­mine the min­i­mum num­ber of ORs to keep open at any giv­en time.

But bet­ter uti­liza­tion of OR capac­i­ty helps the hos­pi­tal see more patients in a short­er peri­od of time, with low­er rejec­tions or delays for surgery requests.

The results con­firmed that the hos­pi­tal was need­less­ly oper­at­ing with excess OR capacity.

A typ­i­cal hos­pi­tal, like the one in the study, keeps about 10 ORs open, Ban­di says. But in Phase 1 of our study, we show that keep­ing only eight open would allow the hos­pi­tal to han­dle the request­ed vol­ume of surg­eries while achiev­ing the same ser­vice levels.”

The researchers knew, how­ev­er, that this first analy­sis did not take into account more spe­cif­ic sur­geon requests, such as want­i­ng the same surgery times each week. So the sec­ond phase of the research took this into account, accom­mo­dat­ing spe­cif­ic requests by either shuf­fling surg­eries among avail­able ORs, adding anoth­er OR, or a com­bi­na­tion of both.

Impor­tant­ly, the mod­el enables hos­pi­tal admin­is­tra­tors to place greater weight on spe­cif­ic fac­tors as need­ed. For exam­ple, if a par­tic­u­lar­ly impor­tant sur­geon wants a spe­cif­ic OR at a spe­cif­ic time, the hos­pi­tal can give this request top pri­or­i­ty, mak­ing adjust­ments to the remain­ing sur­geons’ sched­ules as needed.

We enable the hos­pi­tal to con­trol trade-offs relat­ed to sched­ul­ing while still sav­ing a lot in over­all OR costs,” Ban­di says.

Indeed, the reduc­tion in the num­ber of ORs the hos­pi­tal must keep open means large sav­ings — rough­ly 20% of OR costs, on aver­age. We sim­u­lat­ed mul­ti­ple OR request sce­nar­ios that result­ed in any­where from 10% to 25% in total sav­ings,” Ban­di says.

This is great news for hos­pi­tals. But it does not change the finan­cial equa­tion much for insur­ers or the patients who occu­py those ORs.

In health­care set­tings, these kinds of sav­ings don’t trans­late imme­di­ate­ly to con­sumers,” Ban­di says. But bet­ter uti­liza­tion of OR capac­i­ty helps the hos­pi­tal see more patients in a short­er peri­od of time, with low­er rejec­tions or delays for surgery requests.” In the long run, how­ev­er, he expects that these sav­ings will lead to low­er health­care costs and thus low­er insur­ance premiums.

Oth­er Uses for a Sched­ul­ing Algorithm

This opti­miza­tion algo­rithm has poten­tial uses beyond the hos­pi­tal set­ting, Ban­di says.

For exam­ple, cloud-com­put­ing data cen­ters must opti­mize how they sched­ule big data” ana­lyt­ics projects, such as large sim­u­la­tions request­ed by researchers.

Projects like these can take hours to run and incur very large ener­gy costs,” Ban­di says. By some esti­mates, as much as 12% of the world’s total ener­gy goes toward these projects.”

As with ORs, data cen­ters receive ana­lyt­ics job requests at unpre­dictable times, and it’s not clear upfront exact­ly how long a giv­en project will take. As a result, the cen­ters tend to over­com­mit, retain­ing excess com­put­ing capac­i­ty to accom­mo­date all requests. The result: wast­ed ener­gy and extra costs.

Ban­di is explor­ing how to apply an algo­rithm sim­i­lar to the OR-opti­miza­tion mod­el to help data cen­ters improve project effi­cien­cy. There’s a lot of dis­cus­sion about how to green’ these data cen­ters to help them use less ener­gy,” he says. Our algo­rithm can play a big role in this effort.” 

About the Writer

Sachin Waikar is a freelance writer based in Evanston, Illinois.

About the Research

Bandi, Chaithanya, and Diwakar Gupta. “Operating-Room Staffing and Online Scheduling.” Under review.

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