Healthcare Artificial Intelligence: Elevating Outpatient Medical Coding Automation
Artificialintelligence(AI)andmachinelearning(ML)algorithmsare transformingalmosteveryindustry,andhealthcareisnoexception.Many healthcareorganizationsareleveragingAItobetterallocateresources,predict patientoutcomes,andschedulepersonnel.AIandMLcanhelptoaugment medicalcoders-codingoutpatientservicesefficientlyandaccurately–allowingcoderstodevotemoretimetocomplextasks.
How does Artificial Intelligence help outpatient medical coding?
Manualoutpatientcodinghasseveraldrawbacks,includinglower productivity,lowercasereviewrates,andalongerphysicianresponsetime, allofwhichslowreimbursement.TheDiagnosticRelatedGrouping(DRG) assignmentisnotoptimizedthroughmanualcoding,andthestaffwillbe unabletotrackquerieseffectively.AIisapowerfulautomationtoolthat addressestheflawsinmanualoutpatientcodingprocesses.ThiscanaidHIMs optimizethecodingquality,ensuringpromptreimbursement,better
managinghospitalfinances,andimprovingpatientcare.Experiencedcoders don'tneedtowastetimecodingsimplechartswhentheycanfocusonmore complextasksthatmachinescan'thandle.
Benefits of AI in Outpatient
Medical Coding
• Tailored Patient Care
HealthcareAIanalyzestheoutpatientdatacollectedfromphysician’srecords, diagnosticresults,andlabtestsandcomparesthemwithmedicalprotocols, recommendations,andclinicalprocedures.Medicalstaffcanusetheresultsto determinewhetheranyadditionaltestingisrequiredandthebestcourseof treatmentforthepatient.AIallowsmedicaltreatmenttobetailoredto outpatientcare.
• Computer Assisted Coding (CAC)
Computer-AssistedCoding,orCAC,amalgamatesvariousfeaturesofAIand NaturalLanguageProcessing(NLP).AI-poweredCACsoftwarecanevaluate andinterpretphysiciannotes,assignmodifiers,detecterrors,andrecognize codingedits,freeingmedicalcoderstofocusonothertasks.Itsdedicated algorithmscanextractclinicalfactsandassigntheappropriateE/Mcode. Identifying,extracting,andfeedingitintothesystemarenolongerconcerns forphysicians.Additionally,AI-poweredCACprovidesreal-timefeedbackto thehealthcaresystemandphysiciansabouttheprecisionofE/Mcodesused duringoutpatientvisits.Cloud-basedsystemsarenotonlysecure,butthey alsooffereasyaccesstodata,enhancedatascalability,andreduceprocess downtime.
• Computer-Assisted Clinical Documentation Improvement (CDI)
NLP-enabledCDIsynchedwithEHRs(ElectronicHealthRecords)help medicalstafffillgapsinclinicaldata.Thistoolcanexaminedocumentationin real-time,enablingCDIs,coders,andphysicianstoworkconcurrentlyin improvingdocumentquality.Chartscanbeprioritizedbasedonsuggested queriesandheldinaworkqueuepriortocodingtoensurequeriesarenot missed.Eachchartcanbepredictivelycodedbasedoncurrentdocumentation andqueriessuggestedbasedonpotentialcodingopportunitiesormissing support.
• Real-time feedback
Real-timefeedbackhelpscodersimprovefaster.Assumeanewcodermakesa mistakeincodinganoutpatientchart.TheAIassistantwillimmediatelyflag theerror,suggestasolution,andnotifythecoderofthechange's repercussions.Thisway,theaccuracyissueiscaughtthesamedaywhilethe caseisnewandbeforeitissenttobilling.
• Improved Billing Procedures
HealthcareAItechnologyallowsmedicalbillingstafftoimprovetheefficacy andefficiencyoftheoutpatientcodingandbillingprocess.Manycompanies areadoptingAIapplicationstosimplifymanualcodinglabor.AIinhealthcare cansignificantlyreduceworkinghoursandhumanerror,inadditionto processingcodesandlargedatavolumes.
• Interaction analysis
Interactionanalysissystemsforoutpatientcarearetypicallydonemanually. Theseprovetobetime-consuming,costly,andcomplex.Thecomputerized algorithmsofAIcanmakethisprocessmorecost-effectiveand straightforward.Wecanalsogobeyondtheestablishedboundariesofpatientphysiciancommunicationwiththehelpoftechnology.
Onalargescale,AI/MLsolutionscanpinpointcommonmistakesinoutpatient medicalcoding,tightenthefloodgatesagainstcodingerrors,andimprove documentation.Throughreal-timefeedback,coderscanenhancetheirskills. Top-tiercoderscandevotemoretimetocomplexcasesratherthanmundane tasks.AGSrecommendsthishybridapproachascodersarealsoableto validatethecomputer’sproposedcodes–ensuringaccuracyandmaximizing reimbursements.
Source of content: Healthcare Artificial Intelligence - Elevating Outpatient Medical Coding Automation
