BERG An­a­lyt­ics

Health Data Management - - GROUP PRACTICES -

BERG An­a­lyt­ics pro­vides real time pre­dic­tive and pre­scrip­tive so­lu­tions that op­ti­mize pa­tient treat­ments and im­prove pop­u­la­tion health. BERG’s Ar­ti­fi­cial In­tel­li­gence plat­form, bAI­cis® uses pow­er­ful tech­nol­ogy to de­liver new in­sight, val­i­date clin­i­cal tri­als and drive bet­ter per­for­mance for health­care or­ga­ni­za­tions. BERG An­a­lyt­ics pro­vides health­care stake­hold­ers with ac­tion­able In­tel­li­gence pro­mot­ing best prac­tices while sup­port­ing value based care ini­tia­tives. Slava Ak­maev, Ph.D., Head of BERG An­a­lyt­ics

Value-based care is on its way to­ward be­com­ing the dom­i­nant care de­liv­ery model in health care. What tech­nolo­gies do health-care or­ga­ni­za­tions need to im­ple­ment to suc­ceed un­der this emerg­ing model?

The pay-for-per­for­mance model is a crit­i­cal next stage in health-care dy­nam­ics – not only in the U.S., but around the world. Health-care ser­vices, pro­ce­dures and med­i­cal in­ter­ven­tions are be­com­ing more so­phis­ti­cated and, at the same time, more ex­pen­sive. Be­cause of the high cost of new gene-edit­ing tech­nolo­gies – some have price tags of up to $1 mil­lion – pa­tients and pay­ers want the re­as­sur­ance of treat­ment ef­fi­cacy at the in­di­vid­ual level. As more so­phis­ti­cated, ex­pen­sive and com­pli­cated treat­ments come to mar­ket, the con­cept of as­sess­ing in­ter­ven­tion suc­cess on “av­er­age” will fade away. The in­dus­try can not jus­tify 20% ef­fi­cacy statis­tics, as on the other side, 80% of the pop­u­la­tion have no ben­e­fit from the in­ter­ven­tion. Cur­rently, pay­ers re­im­burse failed treat­ments en masse, and this has only been pos­si­ble in health care. But this ap­proach is rapidly chang­ing as health­care costs rise. Pre­ci­sion medicine tools – specif­i­cally ad­vanced an­a­lyt­ics and ar­ti­fi­cial in­tel­li­gence – will gain sig­nif­i­cant mar­ket share in health in­for­ma­tion tech­nol­ogy within the next five years. Deep anal­y­sis and in­ter­pre­ta­tion of the avail­able molec­u­lar data (such as ge­nomics and metabolomics) is nec­es­sary to drive the speci­ficity of care. Also, new waves of mo­bile data, thanks to wear­ables, are flood­ing the health-care mar­ket.

Im­proved pa­tient en­gage­ment is an im­per­a­tive for health­care or­ga­ni­za­tions. How do you en­vi­sion health-care or­ga­ni­za­tions us­ing smart de­vices and other con­sumer-fac­ing tools to more fully en­gage pa­tients in their care?

Many or­ga­ni­za­tions are al­ready col­lect­ing and/or mon­i­tor­ing pa­tients’ vi­tal data via mo­bile tech, so I see sub­stan­tial growth in the telemedicine mar­ket over the next decade. Smart mo­bile de­vices and wear­ables are mak­ing tremen­dous strides, start­ing with heart-rate mon­i­tor­ing and the re­cent ad­vance­ment of EKG record­ing on smart watches. Most likely, we’ll see wide­spread adop­tion of telemedicine in Asia and the de­vel­op­ing world be­fore it im­pacts the U.S. and Western Europe.

Staffing has emerged as a ma­jor chal­lenge for health care. What staffing strate­gies can health­care or­ga­ni­za­tions adopt that will en­able them to fully lever­age tech­nol­ogy in­no­va­tions?

Train­ing in IT, data sci­ence and ma­chine learn­ing are re­quire­ments for the suc­cess­ful im­ple­men­ta­tion of data-driven strate­gies in any health-care or­ga­ni­za­tion. Where telemedicine, ad­vanced an­a­lyt­ics and ar­ti­fi­cial in­tel­li­gence are typ­i­cally not well de­vel­oped within health-care en­vi­ron­ments, health-care or­ga­ni­za­tions must de­cide whether to buy or hire. While some of the largest phar­ma­ceu­ti­cal com­pa­nies are widely adopt­ing data-driven ap­proaches within their or­ga­ni­za­tions, and mak­ing the tran­si­tion to the data-and-medicine phi­los­o­phy, grow­ing such ca­pa­bil­i­ties in­ter­nally is a for­mi­da­ble task for most health-care or­ga­ni­za­tions.

Ar­ti­fi­cial in­tel­li­gence is hav­ing a sig­nif­i­cant im­pact on how busi­nesses and con­sumers use tech­nol­ogy. How can health-care or­ga­ni­za­tions best lever­age AI tech­nolo­gies?

Ar­ti­fi­cial in­tel­li­gence is a big term that is of­ten overused. Data re­search has played a vi­tal role in health care for decades, with statis­ti­cians and med­i­cal in­for­mati­cians suc­cess­fully us­ing data-anal­y­sis tools to pre­dict out­comes. It’s im­por­tant to un­der­stand that AI al­lows re­searchers and clin­i­cians to iden­tify key in­sight in myr­i­ads of data points in a hy­poth­e­sis-free man­ner. Ad­vanced pre­dic­tive meth­ods can help health-care or­ga­ni­za­tions to bet­ter man­age com­plex treat­ment path­ways, iden­tify pa­tients at risk of com­pli­ca­tions and ad­verse drug re­ac­tions, and ul­ti­mately pro­vide per­son­al­ized care lead­ing to bet­ter out­comes.

Newspapers in English

Newspapers from USA

© PressReader. All rights reserved.