2026生成式AI时代下的临床决策白皮书

theEraofGenerativeAIEmerging

behavioral

signals

from

EuropeanhealthcareprofessionalsWhitePaperClinicalDecision-Making

inIQVIADataStrategyand

Architecture(DS&A)TableofcontentsExecutivesummary:TheGenAIfrontierinclinicalcognition

1Introduction

2Surveyfindings:Adoptionpatternsandemergingbehavioralsignals

3HowhealthcareprofessionalsareusinggenerativeAI

5Trust,challenges,andinstitutionalreadiness

9ImplicationsforcommercialandmedicalstrategyinaGenAI-enabledenvironment13Closingperspective

14Surveydesign,scope,andconsiderationsforinterpretation

14AboutIQVIADataStrategyandArchitecture(DS&A)

16References

17StrategicimplicationsMedical

Affairs:Medical

Affairsmust

transition

froma“solesourceof

truth”

toastrategicpartnerinan

AI-mediatedenvironment.Scientificcommunicationmustbeoptimized

for

AIdiscovery

toensurepeer-reviewedevidenceisaccuratelyinterpretedby

themodelsHCPs

usedaily.Commercialandsalesoperations:GenAI

accelerates

theestablishmentof

the

“pull”dynamic

whereHCPsactively

look

forinformationand

veryifyclaimsinreal-time

viaGenAI.Commercial

teamsmustpivot

towardhigh-value,personalizedinteractions

thatcomplement,rather

than

replicate,

theinstantretrievalcapabilitiesof

AI

tools.Moving

from

observation

to

integrationTheshift

towarddistributedindividualusagerequiresare-engineeringof

engagementmodels.Organizationsmustnowcodifygovernancestructures

toreflectareality

where

AI-augmentedcognitionisapermanent,routineprerequisiteofmodernmedicalpractice.AbouttheresearchAsaleaderinhealthcaredataandanalytics,IQVIAprovides

the

foundationalinsightsand

frameworksnecessary

tonavigate

this

transition.

Thisstudyispartof

our

efforts

to

bridge

the

gap

between

emergingtechnologyandclinicalreality,enablingstakeholders

toadapt

theirstrategies

foraGenAI-enabledecosystem.Generative

AI(GenAI)isnolongeraperipheralexperiment.Itisfundamentallyreconfiguringclinicaldecision-making

by

decentralizing

how

evidence

issynthesizedandapplied.Ratherthanawaitingformal

institutionaldeployment,healthcareprofessionals(HCPs)have

already

started

to

integrate

these

toolsinto

their

individual

clinical

cognition

to

validateinformation

and

explore

complex

medical

data.Thisshift

is

evidenced

by

a

comprehensive

IQVIA

multi-country

study

conducted

in

December2025,surveying

HCPs(oncologists

and

general

physicians)acrossFrance,Germany

and

the

United

Kingdom,whichevaluatedreal-worldadoptionandevolvingbehavioralshifts

among

HCPs.KeyfindingsWidespreadadoption:85%of

surveyedHCPsutilizeGenAIforwork,peaking

at92%amongspecialists

like

oncologists.High-frequencyuse:Integration

is

deeply

habitual;41%of

HCPs

useGenAI

daily,and73%engage

atleast

weekly.Geographicvariation:Franceleads

adoption

at91%,followed

by

the

UK(88%)and

Germany(79%).Clinicalutility:Usage

isdriven

byimmediate

needs,including

clinical

reasoningsupport,informationretrieval,andliteraturesynthesis.Executivesummary:TheGenAIfrontierinclinicalcognition

|1onpreviousIQVIAresearchexamininghowhealthcare

professionals

use

artificial

intelligence

tools

to

accessandinterpretscientificinformation,highlightingthegrowingroleofgenerative

AIwithinclinicalinformation-seeking

behavior.3

The

research

examinedadoptionpatterns,accessmodels,subscriptionbehavior,satisfaction

levels,perceived

challenges,and,

critically,real-world

prompt

examples

shared

directlybyrespondents.ThefindingssuggestthatGenAIuseamonghealthcare

professionalsisneitherspeculativenorperipheral.Instead,it

represents

a

meaningful

evolution

in

clinical

information-seeking

behavior.Adoption

is

high,frequency

of

use

is

significant,and

usage

extendsbeyondadministrativeefficiencyintoareascloselylinked

to

clinical

reasoning

and

treatment

evaluation.Atthesametime,institutionalenablementhasnotkeptpacewithindividualbehavior.Most

usageremainsself-initiatedandfrequentlyaccessedthroughprivatedevices,withlimitedformalgovernancestructuresororganization-fundedaccess.Thisimbalancebetweenwidespreadindividualadoptionandstructuredinstitutionalsupport

introducesbothopportunityandrisk.Thiswhitepaperexplorestheimplicationsof

thesefindings.It

examines

how

GenAI

is

currently

beingused

in

clinical

contexts,where

trust

and

validationremain

limiting

factors,and

how

life

sciencesorganizationsshouldinterpretthesebehavioralsignals

inshapingfuturecommercialandmedicalstrategies.IntroductionHealthcaresystemsacrossEuropeareundergoingstructuraltransformationinhowclinicalinformationis

accessed,interpreted

and

applied.¹While

formalengagementmodelsbetweenindustryandhealthcare

professionalshaveevolvedincrementallyoverthepast

decade,aquieterandpotentiallymoreconsequential

shift

is

now

taking

place

within

daily

clinical

workflows.Generativeartificialintelligencetoolshavemoved

rapidlyfromnoveltytoroutineutility.2

Whatbeganas

exploratory

experimentation

has,in

many

cases,

becomeembeddedinthecognitiveprocessesthatunderpinclinicalreasoning,literaturereview,

treatmentevaluation,andpreparationforpatientdiscussions.Yet

this

evolution

has

largely

occurredoutsideformalinstitutionalstructures,governance

frameworksorestablishedengagementstrategies.Forpharmaceuticalandlifesciencesorganizations,

thisdevelopmentraisesimportantquestions.How

widespreadisGenAIadoptionamonghealthcareprofessionals?Whatspecifictasksarethesetoolsbeingusedforinpractice?Whatconcernspersistregardingreliability,transparencyandclinicaldepth?

Andwhatdoesthisbehavioralshiftsignalforfuture

engagementmodels?Tobetterunderstandthisemergingdynamic,IQVIA

conducted

a

multi-country

survey

of

oncologists

andgeneralphysiciansacrossGermany,FranceandtheUnited

Kingdom

in

December2025.This

work

builds2|ClinicalDecision-MakingintheEraofGenerativeAIGenAIadoptionhasreachedwidespread

professionaluseSurveyfindingsindicatethatgenerative

AItoolsare

alreadyintegratedintotheprofessionalworkflowsofa

large

majority

of

healthcare

professionals.Overall,approximately85%of

HCPs

surveyed(272out

of319respondents)report

using

GenAI

in

a

work-related

context.Frequency

of

use

further

reinforces

the

maturity

ofadoption.More

than

four

in

ten

respondents

report

dailyuse,

with

a

substantial

share

engagement

on

a

weeklybasis.Onlyasmallminorityreportsnousageatall.Adoptionpatternsarebroadlyconsistentacrossspecialties,includinggeneralpractitionersandoncologists.Whilethereare

variationsacrosscountries,the

overall

picture

is

clear:GenAI

use

isnotexperimentalorperipheralbutembeddedwithin

routine

clinical

practice.Usagefrequencyreflectsoperational,not

occasional,integrationThedistributionofusagefrequencysuggeststhat

GenAIisfunctioningasaregularsupporttoolratherthan

an

ad

hoc

reference

resource.Daily

and

weeklyusagetogetherrepresentthedominantpattern,indicating

that

HCPs

are

returning

to

these

toolsrepeatedlywithintheirclinicalroutines.This

pattern

holds

across

both

HCP

specialties

includedin

the

survey.While

intensity

may

vary

slightlybetweenmarkets,nocountryreflectslowstructural

engagement.Eveninmarketswithrelativelyhighernon-use

rates,most

clinicians

report

consistentinteractionwithGenAItools.Thisreinforcesthe

viewthatgenerative

AIhascrossed

thethresholdfromcuriosity-drivenexperimentationto

operationalintegration.General-purposeGenAItoolsdominate

clinicalusageSurveyresponsesshowthathealthcareprofessionals

overwhelminglyrelyongeneral-purposegenerative

AI

platforms

rather

than

healthcare-specific

solutions.

ChatGPTclearlydominatesusageacrosscountriesand

specialties,accounting

for

over

two

thirds(71%)of

all

reported

tool

usage

in

the

survey

and

significantly

outpacinganyotherplatform.Othergeneralistsystems

such

as

Gemini(with14%the

second-mostused

tool),Copilot,Perplexity,and

DeepSeek

appearSurveyfindings:Adoptionpatternsandemerging

behavioralsignalsAdoptionpatternsandaccessmodelsOncologists:92%85%GenAIusersGPs:80%

88%

80/88 79%95/212HCPadoptionofGenAIatwork:Overall

and

by

specialty(DE/FR/UK,

n

=319)Figure1:Adoptionpatterns(datacollected12/2025)97/110GenAIadoptionbyusagefrequency(DE/FR/UK,

n=319)GenAIadoption:HCP

users

bycountry(n=

319)32%41%Daily15%12%

|

3Monthly

orlessNon-

usersWeekly91%assecondarytools,whilededicatedhealthcare-focused

AI

solutions

are

used

only

by

a

small

minorityofrespondents.Thispatternindicatesthatadoptionis

currently

driven

by

accessibility,familiarityandimmediateavailabilityratherthanbyclinicalspecialization,with

clinicians

adapting

widely

availablegeneralisttoolstosupportmedicalinformation-seekingineverydaypractice.Accessispredominantlypersonaland

self-initiatedDespite

widespread

adoption,access

models

revealthat

GenAI

usage

remains

largely

self-driven.MostrespondentsreportaccessingGenAI

throughprivateweb

browsers

on

personal

computers

or

mobile

devices.Institutionallyprovidedaccessremainslimited.Only

asmallproportionofrespondentsreportthattheir

organizationdirectlyfundsorprovidesGenAItools.Instead,most

usage

occurs

through

free

plans

orpersonallyfinancedsubscriptions.ThisimbalancebetweenindividualusageandinstitutionalenablementsuggeststhatGenAIintegrationisoccurringorganically,outsideformal

governancestructures.Freeplansdominate,but

personal

investmentisemergingMost

users

rely

on

free

versions

of

GenAI

tools.However,ameaningfulminorityreportpayingfor

subscriptions,indicatingperceivedvaluebeyondcasual

use.Institutional

fundingremainscomparativelylow,eveninmarkets

withhigheroveralladoption.

Thissuggeststhat

whileorganizationsmay

tolerateorallowusage,structuredenablementstrategiesarestillinearlystages.Country-level

variationis

visiblebutdoesnotfundamentallyalter

thepattern:GenAIadoptionispredominantlyclinician-ledrather

thanorganization-led.Figure2:Accessmodels(datacollected12/2025)Comparativeanalysis:Medicalsubscriptionmodels(GenAIusers

n=272)25%74%16%79%71%Free

planPaidpersonally

Paidby

institution6%14%80%8%30%62%Subscriptionadoptionbyspecialty(GenAIusers

n=

272)

FreeplanPaidpersonallyPaidby

institution4|ClinicalDecision-MakingintheEraofGenerativeAISubscription

breakdown:

DE,

FR&UK(GenAI

users

n=

272)22%14%23%63%7%OncologistsGPsUKDEFRGenAIisprimarilyusedtosupportclinicalthinking,notworkflowautomationSurvey

findings

indicate

that

healthcare

professionalsareusinggenerative

AIpredominantly

tosupportclinical

reasoning

and

knowledge

work,rather

thanto

automate

administrative

or

operational

tasks.Across

countries

and

specialties,reported

use

casesconsistently

center

on

interpreting

medical

information,validating

understanding

and

exploring

clinical

options.

The

most

frequently

cited

applications

include

diseaseand

condition

information,literature

and

guidelinereview,

treatment

support,and

knowledge

refresh.Theseusecasessitclosetothecognitivecoreofclinicalpractice,

where

decisions

are

shaped

by

evidenceinterpretation,synthesis

of

complex

information

andprofessional

judgment.Bycontrast,operationalapplicationssuchasdocumentationcreationorpatientcommunicationappear

less

central,while

advanced

use

cases

suchasimageinterpretationremainniche.Thispatternsuggests

that

GenAI

is

being

adopted

not

as

aproductivityshortcut,butasanondemandcognitive

support

tool

within

existing

clinical

workflows.WhatthissignalsTakentogether,thesefindingsindicatethatgenerativeAIhasachievedmeaningfulpenetrationintoclinicalworkflowsacrossEuropeanmarkets.Adoptionis

broad,usageisfrequent,andengagementspansmultiple

specialties.Atthesametime,accesspatternsrevealthatintegrationisoccurringprimarilyattheindividuallevel.Mostcliniciansrelyon

privatedevices

and

self-fundedorfreetools,withlimitedinstitutional

sponsorshiporgovernance.Thisdynamiccreatesstructuralasymmetry:whileGenAIisalreadyinfluencingclinicalinformation-seekinganddecisionsupport,organizationalmodels

have

not

yet

fully

adapted

to

support,standardize

or

formalize

its

use.HowhealthcareprofessionalsareusinggenerativeAI

|

5EducationGuidelinecheckDruginfoDiagnosticsTreatmentcomparisonandpreferencesPatientcommunication

DosingRegulatoryAccessandreimbursementAdverseeffectsandsafety

OtherEducationandguidelinechecksdominate

GenAIengagementinreal

promptsAnalysis

of

both

structured

survey

responses

and

open

text

prompts

confirms

that

education

and

guideline-related

questions

are

the

dominant

drivers

of

GenAIuse

among

HCPs.When

asked

what

they

use

GenAI

for,large

shares

of

respondents

selected

disease

education,

literature

review,and

guideline

or

evidence

checks.Analysis

of

real

HCP

sample

prompts

reinforces

this,with

education

and

guideline

validation

emerging

as

themost

common

primary

intentions

across

more

than400

real

prompts.Figure4:Promptintentionanalysis(datacollected12/2025)Primarypromptintention:

byspecialty(HCP

GenAIusersn

=272:

GPsn

=

143,

Oncologistsn

=

129,promptsn

=421)Figure3:Self-reportedGenAIusageintentions(datacollected12/2025)FunctionalapplicationsofGenAIamongHCPGenAIusers(n=

272)(GenAI

users—multiselect

question)

69

62

18

12

8

16

13

514

549%—Literaturereview48%—Supportdecisionontreatment17%—Accreditedlearningactivities11%Interpretationofimages11%Summarizationofanotherdoctor'snote59%—Diseaseorconditioninformation46%—Refreshknowledge

>50%

49%-40%

39%-20%

19%-0%37%—Supporttodefinediagnosis33%—Createdocumentation6|ClinicalDecision-MakingintheEraofGenerativeAI30%—Productandprescribinginfo29%—Newsof

treatments7825%—Academicactivities22%—Communicationtopatients18%Getasecondopinion

Oncology

GeneralpracticeOther103ThisbehaviorisconsistentacrossGermany,Franceand

the

UK,and

across

general

practitioners

andoncologists.

Whilethespecifictopics

varybyspecialty,the

underlying

motivation

is

similar:clinicians

use

GenAItoquicklyorient

themselves,

validateunderstandingand

contextualize

information

within

current

standardsof

care.Importantly,

this

pattern

suggests

that

GenAIisalreadyinfluencinghowHCPsaccessandprocessmedical

knowledge,often

upstream

of

traditionalengagement

channels

such

as

peer

discussion,medical

meetings

or

industry-provided

materials.Diagnosticclarificationanddecision

validationareemergingusecasesBeyond

education,a

substantial

share

of

GenAI

userelates

to

diagnostic

clarification

and

decision

validation.HCPs

report

using

GenAI

to

support

differentialdiagnosis,clarifydiagnosticcriteriaandexplorealternative

interpretations,particularly

in

situations

ofuncertainty

or

complexity.

This

behavior

is

especiallypronouncedamonggeneralpractitioners,reflectingthe

breadth

of

conditions

encountered

in

primary

care.Oncologists,

while

less

focused

on

broad

diagnosticquestions,still

use

GenAI

to

validate

interpretationsandsensecheckdecisions

withinhighlyspecialized

therapeuticareas.Rather

thanreplacingclinical

judgment,GenAIappearstofunctionasaninformalsecondopinion:areadilyaccessible

source

of

synthesis

that

complements,butdoesnotsubstitute,professionalexpertise.

Thisroleisnotable

given

that

most

usage

occurs

outside

formalinstitutional

frameworks,highlighting

the

extent

towhich

GenAI

has

already

been

embedded

into

individual

clinicalpractice.DiagnosticcriteriaDifferentialdiagnosisBiomarkertestingSymptominterpretationTestinterpretationRiskevaluationScreeningprotocolsImagingguidanceFigure5:Promptanalysis:diagnosticinformationneeds(datacollected12/2025)Promptanalysis:Diagnosticinformationneeds—

byspecialty(HCP

GenAIusersn

=272:

GPsn

=

143,

Oncologistsn

=

129;Promptsn

=421)69%76%50%80%100%67%50%50%31%24%50%20%33%50%50%n

=45n

=37n

=

12n

=

5n

=

3n

=

3n

=2n

=2 General

practice

Oncology

Sum

=

109

|

7This

finding

is

strategically

significant.It

indicates

thatGenAIhasalreadybecomeaninformalinformationsourcefortherapyexploration,evenwhencontent

is

not

sourced

from

validated,industry-approvedmaterials.As

a

result,GenAI

is

shaping

perceptionsandunderstandingofproductsearlierintheclinical

informationseeking

journeythanmanytraditional

engagementmodelsassume.Realworldpromptanalysisrevealsdepth

driveninformationneedsThe

analysis

of

real

prompts

shared

by

HCPs

provides

additional

insight

into

how

GenAI

is

being

used

inpractice.The

prompts

are

typically

specific,context-rich

and

clinically

framed,focusing

on

questions

such

astreatmentoptions,guidelinealignment,diseasemechanismsandcomparativeefficacyorsafety.Across

specialties,promptsfrequentlyseeksynthesisrather

than

raw

facts,reinforcing

the

view

that

HCPs

useGenAItoaccelerateunderstanding,notsimplyretrieve

information.Differencesbetweenspecialtiesreflectdepthratherthandirection:generalpractitionersaskbroadereducationalanddiagnosticquestions,whileoncologistsfocusmoreonspecializedtreatment

considerationsandevidenceinterpretation.Productrelatedqueriesarealreadypart

ofGenAIuseDespite

the

lack

of

formal

pharmaceutical

integration,GenAI

is

already

being

used

for

product-relatedinquiries.Prompt

analysis

shows

that

a

meaningfulshare

of

GenAI

questions

reference

specific

therapies,

withanotableproportioninvolving

treatmentorproduct

comparisons.

These

queries

are

more

commonamong

oncologists,reflecting

the

complexity

andrapid

evolution

of

oncology

treatment

landscapes.However,product-related

questions

are

also

presentamong

general

practitioners,particularly

in

areas

wheremultipletherapeuticoptionsexist.Figure6:Promptanalysis:productqueries(datacollected12/2025)Promptanalysis:Productrelated

insights(HCP

GenAIusersn=272:

GPsn

=

143,

Oncologistsn

=

129;Promptsn

=421)Notably,only

a

small

share

of

prompts

includes

explicit

patientidentifiers,suggestingsomedegreeofcaution

arounddataprivacy,evenintheabsenceof

formalgovernancestructures.79questionsrelatedtoproducts110uniqueproductsmentioned

Oncologists

GP25(32%)questionswithproductcomparison8|ClinicalDecision-MakingintheEraofGenerativeAI33

30166%off-labelrelated

questionsSplitbyspecialtySplitbycountry本报告来源于三个皮匠报告站（）,由用户Id:863553下载,文档Id:1199937,下载日期:2026-04-2552

DE

FR

UK27Generalistvs.healthcare-specificgenerativeAItoolsSurveyresponsesandpromptanalysisindicatethat

mosthealthcareprofessionalscurrentlyrelyongeneralistgenerative

AItoolsratherthanhealthcarespecific

solutions.These

tools

are

widely

used

dueto

their

accessibility,speed

and

ease

of

use,makingthem

the

most

common

entry

point

for

GenAI

in

day-

to-day

clinical

information

seeking.At

the

same

time,

respondentsfrequentlynotethatthesetoolsarenotdesigned

specifically

for

medical

contexts,raisingquestionsaboutmedicaldepthandthetransparencyof

underlying

sources.As

a

result,the

current

GenAIlandscapeinhealthcareislargelyshapedbygeneral

purposetechnologiesthatcliniciansareadaptingto

professionaluse.HighsatisfactioncoexistswithpersistentreservationsSurveyresultsshowthathealthcareprofessionalsare

broadlysatisfiedwiththeGenerativeAItoolstheyuse.Averagesatisfactionscoresinthesurveycluster

attheupperendof

thescaleacrosscountriesandspecialties,indicatingthatGenAIgenerallymeetsexpectationsintermsofusability,responsivenessand

basicperformance.However,thispositivesentiment

shouldnotbeinterpretedasfullconfidence.SatisfactionreflectsthatGenAItoolsareperceivedas

usefulandconvenient,notthattheyareconsidered

clinicallyauthoritative.Thesurveyrevealsacleardistinctionbetweenpracticalutilityanddecision-leveltrust.WhileHCPsvalueGenAIasasupporttool,theyremaincautiousaboutrelyingonits

outputs

in

situationswhereclinicalaccountabilityishigh.This

tension,highsatisfactionpairedwithconstrainedtrust,emergesconsistentlyacrossmarketsandspecialtiesanddefinesthecurrentmaturitystageof

GenAIuseinclinical

practice.Reliabilityandsourcetransparencyare

theprimaryconstraintsReliabilityandsourcetransparencyarefrequentlycitedconcernswhenlargelanguagemodelsareused

in

professional

contexts.⁴The

most

frequentlycited

challenges

relate

to

reliability

and

sourcetransparency.Acrosscountriesandspecialties,unclear

or

undisclosed

sources

are

the

single

mostcommon

concern

raised

by

GenAI

users.This

is

closely

followedbyperceptionsofinaccurate,incompleteor

insufficientlycontextualizedanswers.Importantly,theseconcernsoutweightechnicalorusabilityissues.Challenges

such

as

slow

response

times,complexity

of

use

or

access

limitations

are

cited

far

less

often.Instead,thedominantbarriertodeeperintegrationis

confidence

in

the

medical

validity

of

outputs.ThispatternsuggeststhatHCPsarenotresistingGenAI

on

principle.Rather,they

are

actively

using

itwhile

simultaneously

self-limiting

its

role

in

decision-

criticalcontextsduetouncertaintyabouthowanswers

aregeneratedandwhethertheycanbetracedbackto

authoritativeevidence.WhatthissignalsOverall,

these

findingssuggest

thatgenerative

AIisalreadyinfluencinghowclinicalunderstandingisformed,not

just

how

information

is

accessed.HCPs

areusing

GenAI

as

a

cognitive

layer

that

sits

upstream

ofdecision

making,supporting

education,

validation,andexploration

within

everyday

clinical

practice.Forpharmaceuticalandlifesciencesorganizations,this

represents

a

meaningful

shift:influence

is

moving

earlierintheclinicalreasoningprocess,intospacesthatarecurrentlyinformal,self-directed,andlargelyunstructured.Trust,challenges,andinstitutionalreadiness

|

9Perceivedgapsin

medicalspecificitypersistInadditiontosourcetransparency,manyHCPsreportgapsinmedicalspecificity,particularlywhenengagingw