BIG DATA AND AN­A­LYT­ICS

Health Data Management - - IOT -

What is driv­ing the growth of big data in health­care?

There are many trends driv­ing big data in health­care - evolv­ing pay­ment models, emerg­ing health­care tech­nolo­gies, and care de­liv­ery im­prove­ments to name a few. But health­care re­form and the re­sult­ing land­scape of con­sumerism is a pow­er­ful force.

Health­care providers now need to com­pete for con­sumers – and these con­sumers are smart, mo­bile and savvy. Brand eq­uity, con­sumer pref­er­ence and choice en­ables propen­sity to seek out the best care at the best price. Or­ga­ni­za­tions must ef­fi­ciently uti­lize big data to be a player in health­care, and they must use it to un­der­stand us, the consuming pub­lic, as in­di­vid­u­als with pref­er­ence and choice as it re­lates to our over­all health.

How can health­care or­ga­ni­za­tions best lever­age an­a­lyt­ics to make the most of data?

These or­ga­ni­za­tions des­per­ately need ac­cess to data for pa­tient ac­qui­si­tion strate­gies and to gain in­sights on their ex­ist­ing pa­tient pop­u­la­tion and their to­tal con­sumer mar­ket. Con­sumer mar­ket seg­men­ta­tion is im­per­a­tive. By align­ing their ser­vices to the needs of the pop­u­la­tion – both as a whole and on the in­di­vid­ual level, they are in lock­step with a pa­tient’s life­style, stage and pref­er­ences and can truly max­i­mize the value of the con­sumer-pa­tient, and even con­stituent, con­tin­uum.

What are the big­gest chal­lenges as­so­ci­ated with deal­ing with large amounts of data?

Ac­qui­si­tion, Ac­cu­racy and Ef­fi­ciency. The onus is now on health­care or­ga­ni­za­tions to jus­tify value, cre­ate con­sumer con­fi­dence in their ser­vices and con­stantly at­tract new non-pa­tients and non-re­fer­ring physi­cians. And data is the cornerstone of these ef­forts, but stor­ing and main­tain­ing data­bases can be te­dious and costly. Or­ga­ni­za­tions can eas­ily find them­selves drown­ing in an ocean of data with no ac­tion­able in­for­ma­tion. Most providers don’t have the ca­pac­ity to an­a­lyze, in­ter­pret or ap­ply pre­dic­tive mod­el­ing to the data sets to drive tan­gi­ble an­swers. First, you have to source the ap­pro­pri­ate data and then it must be turned into ac­tion­able data sets or it will be in­ef­fec­tive for con­sumer tar­get­ing or pa­tient en­gage­ment strate­gies. As the Pres­i­dent and GM of Black­baud Health­care, Russ Cobb over­sees the over­all busi­ness strat­egy and com­pany sales, health­care mar­ket­ing and part­ner ecosystem devel­op­ment. His team in­cludes the sales and mar­ket­ing of cloud-based and on premise so­lu­tions specif­i­cally ben­e­fi­cial for the health­care mar­ket. Fo­cus­ing on health­care ex­ec­u­tives and fa­cil­ity’s phil­an­thropic foun­da­tions, Black­baud of­fers so­lu­tions that al­lows these en­ti­ties to in­crease rev­enue, re­duce costs and en­hance and in­crease con­stituent re­la­tion­ships.

Russ Cobb, Pres­i­dent & GM, Black­baud Health­care How can big data be used to im­prove pop­u­la­tion health ef­forts?

Big data helps providers drive so­phis­ti­cated in­tel­li­gence strate­gies in and around the so­cial de­ter­mi­nants of health or risk pro­files as­so­ci­ated with ge­og­ra­phy, wealth and so­cial con­sumer be­hav­iors. The key to suc­cess here is pro­vid­ing the right in­for­ma­tion to lever­age un­fore­seen pop­u­la­tion trends sup­port­ing both con­sumerism and pa­tient en­gage­ment. Modern data and an­a­lyt­ics can pro­vide un­ri­valed in­sights into the vast ar­ray of so­cial de­ter­mi­nants to as­sist in pop­u­la­tion health along­side con­cur­rent con­sumer and pa­tient ac­qui­si­tion strate­gies.

Pre­dic­tive con­sumer an­a­lyt­ics models span­ning data el­e­ments such as wealth, ge­og­ra­phy, so­cial be­hav­ior, pref­er­ence, phil­an­thropic ten­dency and so­cial me­dia eq­uity can have a tremen­dous im­pact on pop­u­la­tion health. Cou­pled with in­sights out­lin­ing health risk be­hav­iors, payer de­mand models, and pre­dic­tive prob­a­bil­ity models for read­mis­sion, or­ga­ni­za­tions can be uniquely po­si­tioned to drive bet­ter out­comes and in­creased value-based care.

What are some of the staffing chal­lenges as­so­ci­ated with big data man­age­ment and an­a­lyt­ics?

Health­care con­sumerism and its ac­com­pa­ny­ing changes rep­re­sent an un­prece­dented op­por­tu­nity to im­prove care de­liv­ery and in­crease op­er­a­tional rev­enue. For­ward-think­ing health sys­tems are work­ing to be­come more con­sumer-savvy, but many still lack the in-house tools and ex­per­tise needed to un­der­stand, nav­i­gate and op­ti­mize this new dy­namic.

The staffing im­pact will con­tinue to be seen on the data science side, but new par­a­digms will arise in health­care mar­ket­ing. Health­care mar­keters are be­ing asked to think dif­fer­ently, mov­ing from a blan­keted brand eq­uity strat­egy to a di­rect tar­get­ing ap­proach. Con­nect­ing with an ex­pe­ri­enced data and mar­ket­ing part­ner is key to fill­ing in the gaps and dra­mat­i­cally in­flu­enc­ing con­sumer be­hav­ior. Health­care providers will need to ro­bustly im­prove their data con­sump­tion ca­pac­ity with req­ui­site staffing in short order.

ThotWave’s pri­mary fo­cus is to help health or­ga­ni­za­tions ma­ture their use of data and an­a­lyt­ics. Through the strate­gic devel­op­ment of an­a­lyt­i­cal as­pi­ra­tions, best prac­tices for or­ga­ni­za­tional de­sign, pur­pose­ful tal­ent devel­op­ment strate­gies and im­prove­ments to an­a­lytic life­cy­cle pro­cesses, our prod­ucts and ser­vices are de­signed to help lead­ers achieve break­through per­for­mance in their use of data and tech­nol­ogy for de­ci­sion mak­ing.

Greg Nel­son, Chief Data Cham­pion, ThotWave

What is driv­ing the growth of big data in health­care?

I think there are sev­eral as­pects of modern health­care that an­swer the ques­tion, “why now?”. Growth in the use of big data is driven by a de­sire to move from gut-based de­ci­sion-mak­ing to a process that uses facts and in­sights to shape ac­tion. Driv­ers in­clude the dig­i­ti­za­tion of the health record; novel uses of data sourced from out­side the health sys­tem; and, of course, evolv­ing in­cen­tive models which de­mand greater in­sights for or­ga­ni­za­tional sus­tain­abil­ity. Be­cause data and tech­nol­ogy have be­come so ubiq­ui­tous in our ev­ery­day lives, peo­ple are in­creas­ingly de­vel­op­ing a data mind­set and want to ap­proach prob­lem-solv­ing in this man­ner.

How can health­care or­ga­ni­za­tions best lever­age an­a­lyt­ics to make the most of data?

For decades, we have been us­ing data to help make sense of the world around us. Our per­spec­tive is that an­a­lyt­ics is about driv­ing change and not sim­ply about re­port­ing on data, re­flect­ing on the past, or even pre­dict­ing the fu­ture. An­a­lyt­ics has the power to change what we know and what we do – whether that be where we in­vest or how we op­ti­mize care. To make the most of our data, we need to un­der­stand the po­ten­tial for change and what we can im­pact be­cause of these new in­sights.

What are the big­gest chal­lenges as­so­ci­ated with deal­ing with large amounts of data?

Sim­ply put, these are peo­ple and process. Tech­nol­ogy is rarely the real is­sue.

The mas­sive quan­ti­ties of datasets make it chal­leng­ing to quickly as­cer­tain what ex­act data is avail­able. Of­ten there is an un­war­ranted ob­ses­sion with gath­er­ing big data with­out first re­lat­ing that to the data strat­egy and whether it is used for pur­pose (ex­ist­ing busi­ness) or po­ten­tial (fu­ture in­no­va­tion).

Other chal­lenges in­clude weak pro­cesses for how data is man­aged, gov­erned, and made to be us­able. In­cre­men­tal im­prove­ments in how we man­age the an­a­lyt­ics life­cy­cle and how well we serve an­a­lytic cus­tomers will pay div­i­dends in ef­fec­tively im­pact­ing busi­ness de­ci­sions.

How can big data be used to im­prove pop­u­la­tion health ef­forts?

Our abil­ity to turn data into ac­tion­able in­ter­ven­tions is the cornerstone of pop­u­la­tion health.

Re­mem­ber, the pri­mary goals of pop­u­la­tion health are to (a) im­prove the over­all health of a pop­u­la­tion and (b) re­duce the health-re­lated dis­par­i­ties within that com­mu­nity. To do that, we need to be able to ac­cu­rately cap­ture the fac­tors which in­flu­ence health out­comes such as self-care, life­style, ed­u­ca­tion, and so­cial con­text (psy­choso­cial fac­tors). We also must fold in data re­lat­ing in­di­vid­ual well­ness to en­vi­ron­ment and ge­og­ra­phy. Us­ing this myr­iad of en­riched data, we can pre­dict, op­ti­mize, and per­son­al­ize care well be­yond the exam room.

What are some of the staffing chal­lenges as­so­ci­ated with big data man­age­ment and an­a­lyt­ics?

One of the big­gest chal­lenges for an or­ga­ni­za­tion is the devel­op­ment and nur­tur­ing of an­a­lytic tal­ent. An­a­lyt­ics com­pe­tency re­lates to the knowl­edge, skills, abil­i­ties and dis­po­si­tion re­quired to suc­cess­fully turn data into ac­tion­able in­ter­ven­tions. De­spite the vol­ume of read­ily avail­able data, health­care is still learn­ing how to sys­tem­atize data-guided con­ver­sa­tions.

Mak­ing this leap re­quires a fun­da­men­tal trans­for­ma­tion in the mind­set of how health­care staff ap­proach data through­out the busi­ness ecosystem. This re­quires that or­ga­ni­za­tions take swift ac­tion to im­prove health­care staff’s data lit­er­acy. Suc­cess­ful change will en­able staff to de­velop, evan­ge­lize, and be coun­seled by data in­sights in the ser­vice of pa­tients. Data lit­er­acy will grow to be­come as im­por­tant as read­ing and writ­ing com­pe­ten­cies for busi­ness pro­fes­sion­als in the com­ing years.

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