Evaluation and Management (E&M) Coding: How AI Augments the Entire Workflow
Sincetheirintroductionin1995,E/Mcodesservedastheonlyreliablesource ofinformationfordoctor-patientinteractions.Thesecodesareessentialto simplifyingbillingbecausetheysuccinctlyencodetheinteraction's informationinnumericcodes.Therefore,accurateandcompliantE&Mcoding isessentialforphysiciansandclinicians. However,theE/Mcodingprocedurehasencounteredconflictingresponses fromthemedicalcommunityovertheyears.Thevalueoftheprocesscannot bedisputed,butneithercanthemountingburdenitplacesondoctors.
Agrowingnumberofmetricsarebeingappliedtophysicianstoimprove quality,satisfaction,andeffectiveness.Electronichealthrecords(EHRs)and theburdenofdocumentationcreateanexcessofE/Mdocumentation
requirements,leadingtoerrors,"notebloat,"andphysicianstakingtimeaway fromcaringforpatients.
TheprimarygoaloftherevisedCPTE/Mcodingguidelines,whichtookeffect onJanuary1,2021,wastoeasetheadministrativeburdenondoctors. ButevenbeforethenewAMArecommendationstookeffect,thehealthcare sectorfoundwaystoeasethoseburdens.TheuseofAI-poweredcomputerassistedcoding(CAC)isonesuchmethod.AMarketsandMarketsreport estimatesthevalueofAIinmedicalcodingautomationwillreach$14billion by2026,providingaclearillustrationofthevalueanddemandforthis technology.
The Need for AI-powered CAC in E/M Coding
Complexrevenuecyclemanagementisaproblemthatmanyhospitals nationwidemustdealwith.Therevenueforoutpatientvisitsdirectlyresults fromhowaccuratelyE/Mcodingisdone.Healthcareorganizationsmust adoptmoreefficientcodingtoolsbecauselegacyinfrastructurecan'tboost revenuethroughenhancedE/Mdocumentation.
Introducing Computer-Assisted Coding (CAC)
Thetermcomputer-assistedcodingorCACreferstoatechnologythat combinesvariousaspectsofNLPandAI.Unstructuredmedicalnotescanbe examinedandanalyzedusingCACsoftwarethatisNLP-powered.The softwarecanextractclinicalfactsandassignproperE/Mcodesusing specializedlinguisticalgorithms.Therefore,physiciansarenolongerrequired toperformthelaborioustaskoflocating,extracting,andrecordingdatainto thesystemfromthedocuments.
Voice-basedNLPenhancestheprocessevenmore.Dictationbeingoneofthe primarysourcesofunstructuredmedicaldata,CACsoftwarecanusespeech recognitionprovidedbyvoice-basedNLPtoextrapolatetheappropriateE/M codes.Thisdramaticallyminimizestheamountofcodingthatphysiciansmust dowhilealsoimprovingprocessaccuracy.Thismakesitpossibletoalign payerreportingsystemsandE/Mcodingstandardsmoreclosely,greatly enhancingthebillingprocessandloweringdenialsandauditdiscrepancies.
Additionally,CACgivesphysiciansandthehealthcaresystemreal-time feedbackabouttheaccuracyofE/Mcodesusedtoevaluatepatientsduring outpatientvisits.
The AGS Health Advantage
Theadvantagesofcomputer-assistedcodingareclear,asareitsrequirements. Butevenso,usingCACsoftwarealonedoesnotproducethedesiredresults.
ConsidertheRichmondUniversityMedicalCenter(RUMC)inStatenIsland, NewYork,whichencounteredawidespreadproblemamongitshospitals. RUMC’scurrentencodertechnologywasunabletooffersufficientworkflow capabilities.RUMCrequiredathoroughCACframeworktoensureregulatory andpayercompliance,inadditiontoincreasingproductivityandaccuracyof thecodingprocess.
WhenRUMCandAGScollaboratedtoachievethisgoal,notableoutcomes wereachieved.Complexdenialsdroppedby13%,whilecoderproductivity increasedby33%.
AGSHealth'sCACsolutionautomatestheassignmentofE/Mcodesand suggestscasehistorycodesbyfusingtheabilitiesofnaturallanguage processing(NLP)andmachinelearning(ML)withtheE/Mlogicalgorithm. Theoutpatientevaluation'sexaminationtypesandcomplexitylevelscanbe assignedusingmoreadvancedautomationtechniques.Additionally,the includedE/McalculatoraidscodersinselectingtheappropriateE/Mcode level.
AGSpartnershipentailsmorethanjusthavingtechnologyatyourdisposalto streamlinetheE/Mcodingprocess.Wearewithyoueverystepoftheway. Withinweeks,wecanimplementanend-to-endprocessyoufullyown.
TolearnmoreaboutAGS’sAI-basedmid-revenuecyclemanagement solutions,checkouttheAGSAIPlatform.
Source of content:
https://www.agshealth.com/blog/evaluation-and-management-em-coding-how-ai-augments-the-entire-workflow/