Early adopters of Big Data seek ad­vis­ers, part­ners

Modern Healthcare - - NEWS - Joseph Conn

Like part­ners choos­ing up for a dance— or, de­pend­ing on one’s out­look for the health­care in­dus­try, teams form­ing for a game of dodge­ball—provider or­ga­ni­za­tions want­ing to be early adopters of Big Data and large-scale data an­a­lyt­ics pro­grams are busy pick­ing out their ad­vis­ers and health in­for­ma­tion tech­nol­ogy providers.

The aim of those data an­a­lyt­ics early birds is to bet­ter lever­age their al­ready heavy in­vest­ments in health­care in­for­ma­tion tech­nol­ogy to im­prove care, con­trol costs and ready their or­ga­ni­za­tions for the advent of out­comes­based re­im­burse­ments.

All of this pair­ing up comes as 77% of hos­pi­tals and more than half of of­fice-based physi­cians have adopted elec­tronic health­care-record sys­tems, ac­cord­ing to HHS Sec­re­tary Kath­leen Se­be­lius and CMS data from the fed­eral EHR in­cen­tive pay­ment pro­gram. The feds, un­der the pro­gram funded by the Amer­i­can Re­cov­ery and Rein­vest­ment Act, have paid providers more than $14.6 bil­lion to adopt, im­ple­ment, up­grade and mean­ing­fully use EHR sys­tems.

Now, for some, Job 1 is blend­ing clin­i­cal data from those EHRs with in­for­ma­tion gleaned from fi­nan­cial sys­tems, pay­ers and other providers in su­per data­bases, of­ten called en­ter­prise data ware­houses, and then us­ing data an­a­lyt­ics soft­ware and tech­niques to rapidly query and make sense of it all.

“The health­care or­ga­ni­za­tions that make th­ese in­vest­ments in an­a­lyt­ics are go­ing to be the ones who end up the win­ners.”

—Dr. Kevin Fick­en­scher Amer­i­can Med­i­cal In­for­mat­ics As­so­ci­a­tion

“I think we’re see­ing the be­gin­ning stages of the next phase,” said Dr. Kevin Fick­en­scher, pres­i­dent and CEO of the Amer­i­can Med­i­cal In­for­mat­ics As­so­ci­a­tion. “With the de­ploy­ment of elec­tronic health records, we have all this in­for­ma­tion that was dead data, on hand­writ­ten notes that was on pa­per, and now we have this data (dig­i­tized) and we can do ana- lyt­ics on it. Par­tic­u­larly, the large sys­tems are rec­og­niz­ing the next phase is here.

“The health­care or­ga­ni­za­tions that make th­ese in­vest­ments in an­a­lyt­ics are go­ing to be the ones who end up the win­ners,” Fick­en­scher said.

Two weeks ago, Seat­tle Chil­dren’s Hos­pi­tal an­nounced it had picked IBM and Bright­light Con­sult­ing of Red­mond, Wash., “to fully un­der­stand the hos­pi­tal’s ‘ Big Data’—the thou­sands of data points as­so­ci­ated with each child—im­me­di­ately, as needed,” Wendy Soethe, the hos­pi­tal’s en­ter­prise data ware­house man­ager, said in a news re­lease.

Last week, Part­ners Health­care, Bos­ton, the cor­po­rate par­ent of Mas­sachusetts Gen­eral Hos­pi­tal, ar­guably the birth­place of health IT in the U.S., dis­closed it had plunked down $1 mil­lion and joined the ven­ture cap­i­tal arms of Kaiser Per­ma­nente and In­di­ana Univer­sity Hos­pi­tal that had al­ready con­trib­uted $7 mil­lion, to in­vest in Health Cat­a­lyst, a data ware­house and an­a­lyt­ics firm based in Salt Lake City. Part­ners will be a cus­tomer, too, de­ploy­ing Health Cat­a­lyst tech­nol­ogy at its multi-hos­pi­tal, multi-clinic sys­tem.

“We do a lot of an­a­lyt­ics to­day, but the data is siloed, and our an­a­lysts spend a good por­tion of their time ac­tu­ally pulling that data to­gether so they can do the an­a­lyt­ics,” said Part­ners CIO Jim Noga. “The cool ap­proach with Health Cat­a­lyst

is they’ll cut that time out so they can fo­cus on anal­y­sis and not on data gath­er­ing.”

Two days later, group pur­chaser Pre­mier, IBM and four ma­jor health­care sys­tems un­veiled their Data Al­liance Col­lab­o­ra­tive, which will fo­cus ini­tially on de­vel­op­ing data an­a­lyt­ics meth­ods tar­get­ing med­i­ca­tion non­com­pli­ance and pre­ventable hos­pi­tal read­mis­sions. The par­tic­i­pat­ing providers, which com­bined, op­er­ate or man­age more than 70 hos­pi­tals, are the Caroli­nas Health­Care Sys­tem, Char­lotte, N.C.; Catholic Health Part­ners, Cincinnati; Fairview Health Ser­vices, Min­neapo­lis; and Texas Health Re­sources, Ar­ling­ton.

“We’ve been work­ing on this for over a year, defin­ing the op­er­at­ing model, and get­ting their ware­house in­stances up and de­ployed,” said Sean Cassidy, gen­eral man­ager, en­ter­prise provider an­a­lyt­ics for the GPO. Ini­tially, Cassidy said, “Mem­bers are go­ing to de­ploy an­a­lyt­ics on their own data sets,” but then they will col­lab­o­rate with each other and Pre­mier ex­perts on bench­mark­ing us­ing larger, shared and nor­mal­ized data sets.

Vet­eran health IT mar­ket watcher Vi Shaf­fer is re­search vice pres­i­dent for Gart­ner Re­search, Stam­ford, Conn., which tracks in­for­ma­tion tech­nol­ogy across many in­dus­tries, in­clud­ing health­care.

Over the years, she’s watched the for­tunes of would-be tech­no­log­i­cal ad­vances rise and fall—and, if they’re good enough, rise again to wide­spread adop­tion, fol­low­ing what’s called the Gart­ner “hype cy­cle.”

“It is the per­fect method­ol­ogy for strate­gic plan­ning,” help­ing lead­ers avoid the risk of be­ing too early or too late in adopt­ing a tech- nol­ogy, Shaf­fer said.

The cy­cle starts with a “trig­ger­ing” event, the in­tro­duc­tion of a game-chang­ing new idea, which, if it gains cur­rency, rises up to “the peak of in­flated ex­pec­ta­tions.” That’s where “things are pro­moted more than can be de­liv­ered,” Shaf­fer said. Then, typ­i­cally, the in­no­va­tion falls through the “trough of dis­il­lu­sion­ment,” and ei­ther fades away or be­gins to rise again, up the slope of en­light­en­ment to­ward the plateau of pro­duc­tiv­ity.

“So, the hype around Big Data is an ex­am­ple,” Shaf­fer said. “It’s at its peak. It seems so per­va­sive.”

In com­par­i­son, com­put­er­ized physi­cian-or­der en­try, a high-level func­tion of an elec­tronic health-record sys­tem that in the early 2000s posed a threat to the ca­reer of a chief in­for­ma­tion of­fi­cer or chief med­i­cal in­for­ma­tion of­fi­cer try­ing to in­stall it, had edged onto the plateau of pro­duc­tiv­ity, ac­cord­ing to 2012 anal­y­sis by Gart­ner. Per­sonal health records, mean­while, re­mained in the trough of dis­il­lu­sion­ment.

The time be­tween peak and trough is when part­ner­ships are formed, ven­ture cap­i­tal money flows in and “the ven­dors are roil­ing at the same time the health sys­tems are try­ing to buy,” Shaf­fer said. “Ev­ery­thing has speeded up.”

The way Big Data is mov­ing, Shaf­fer said, it may be an­other two to five years be­fore that con­cept reaches the plateau of pro­duc­tiv­ity, where it be­comes com­mon­place with 30% to 50% of or­ga­ni­za­tions us­ing it.

For now, she said, us­ing data an­a­lyt­ics for pop­u­la­tion health man­age­ment is a bit ahead of Big Data in the hype cy­cle, but she hes­i­tated to give an es­ti­mate of when it might come into wide­spread ac­cep­tance, say­ing that’s the sub­ject of a re­search re­port due in July.

The good news—or maybe not—is that with the advent of EHRs, health­care, his­tor­i­cally a lag­gard in terms of IT use, is catch­ing up with other in­dus­tries, Shaf­fer said.

“The take­away for the health­care ex­ec­u­tive is, we’ve al­ways thought of the value in IT is in ap­pli­ca­tions—EHRs, sched­ul­ing, sup­ply­chain man­age­ment,” Shaf­fer said. “Ex­ec­u­tives need to el­e­vate in­for­ma­tion to equal im­por­tance with ap­pli­ca­tions. They need to align in­vest­ments in in­for­ma­tion as­sets with their busi­ness strate­gies,” she said.

That means look­ing for ways “to align in­for­ma­tion with high-im­pact ac­tiv­i­ties” that will change their health­care sys­tems, en­abling them to move into new ar­eas of ser­vice. “As part of your cul­ture and your core com­pe­ten­cies, you now need to own lever­ag­ing in­for­ma­tion,” Shaf­fer said.

Dr. Jon Nielsen of North Me­mo­rial Health Care in Min­nesota demon­strates Health Cat­a­lyst’s data an­a­lyt­ics.

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