CAC, ICD-10 and the Changing Role of the Medical Coder
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CAC, ICD-10 and the Changing Role of the Medical Coder. AGENDA. Introduction to Computer-Assisted Coding The Coding Problems Definition of CAC “Accuracy” and “Efficiency” Changing the Role of the Coder How to use CAC for ICD-10 CDI & ICD-10 Training Implementation examples

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AGENDA

  • Introduction to Computer-Assisted Coding

  • The Coding Problems

  • Definition of CAC

  • “Accuracy” and “Efficiency”

  • Changing the Role of the Coder

  • How to use CAC for ICD-10 CDI & ICD-10 Training

  • Implementation examples

  • Demonstrating coders work space

  • Recommendations

  • Question - Answer



The Computer-Assisted Coding Concept

  • Capture physicians’ typed documents electronically

  • Automatically extract the clinical codes using a computerized mechanism.

  • Deliver Results to the billing department real time

  • Reduce the amount coding time and costs

  • Utilize CAC for Clinical Documentation Improvement

  • Capitalize on the Global experience of countries that already have electronic documentation, ICD-10 and CAC in the healthcare environment


Automated Coding Goals

  • Streamline the process of clinical coding

  • Reduce physician paperwork

  • Increase coder productivity

  • Offset qualified coder shortages

  • Reduce denials & increase consistency

  • Create opportunities for peer review and physician-led quality review.

  • Electronically advance CDI initiatives

  • Address ICD-10 transition issues


In 1996 AHIMA’s Vision for 2006

“Coding using ICD-10-CM and ICD-10-PCS codes.......would be generated automatically at the patient’s bedside from electronic documentation with automatic queries to the physician when inadequate or inconsistent information was entered.”

- Available 15 years after AHIMA’s prediction

- US is the last 1st world country to implement

ICD-10



The Coding Problem

“Mention the word "coding" to a physician, and a clinically significant reaction occurs: The eyes widen, the neck veins throb. Teeth gnash, fists clench. Cheeks flush, brows twist into knots. A clammy dew of cold sweat spreads across the forehead….”

Medical Economics


The Coding Problem

"Clinicians are reluctant to change their workflow on the clinical side. On the administrative side, they understand they are losing large amounts of revenue with the manual process. The known problem of correct charge capture…is creating increasing anxiety in the whole healthcare sector”

Health Management Technology


The Coding Problem

“The coding task itself is daunting. Some coders are extensively educated and have attained certification in the field, but these coders are in short supply …..

“These coders must rely on the clarity and completeness of the documentation and then apply countless rules and interpretive bulletins-to identify and code all the care a patient has received. Any activity missed in either the documenting or the coding - results in lost revenue.”

Healthcare Financial Management


Medical Coding Issues

  • Rules changing all the time

  • Coders: highly skilled, scarce resource

    - 40% of AHIMA respondents agree they have a shortage

  • Organizational success depends on timeliness and accuracy of coding

  • Increased scrutiny with significant risk and penalties

    • Incomplete/inaccurate results

    • Inconsistent results

  • Risk “leaving money on the table”

  • Increasing calls to abstract for quality, outcomes analysis

  • HIPAA regulations


OIG Report on Improper Payments

Improper Payments for Services With Documentation Errors in Five States

Improper Payments (in Millions)

State Documentation Errors All Errors*

A $3.19 $3.38

B $25.32 $28.56

C $71.78 $77.91

D $24.18 $26.98

E $13.42 $17.88

Total $137,880,000$154,720,000


OIG Report on Home Health Agencies

  • Office Inspector General (OIG) released a report that showed home health agencies submitted nearly 22% of claims in error because services were either not medically necessary (2.1%) or were coded improperly (20.2%). –March 2012

  • This is the first time OIG has significantly addressed home health’s coding on claims. They stated that one of the factors for this review was the fast rise in Medicare home health spending—84% from $8.5 billion in 2000 to $15.7 billion in 2007—which“leads to concerns about the potential for improper payments due to fraud and abuse.”


OIG Report on Home Health Agencies

  • More than 10 percent of claims (a value of $278 million) were considered up-coded, and 9.8% of claims (a value of $184 million) were found to be down-coded. Net loss of $94 million for the Medicare system.

    The bright side? Just 2% of claims did not show medical necessity.

    Agencies are doing a great job ensuring services are needed.


Payer-Provider Tension

  • Advanced automation on the Payer side

    • Full rule checking looking for objections

    • Vendors excelling in this niche

  • Software Vendors claiming ability to reduce claim payout by as much as 8% more using “cunning” strategies

  • RAC Audits accelerating


Provider Tools

  • “Scrubbers”

    • Identify code-sets that break rules

    • Highlight them for finance dept

    • Incorporate national, local and payer edits

    • EMR/EHR point n click - drop down menus

  • Coder tools

    • Encoder products

    • Incorporate CCI Edits

    • Some incorporate local/payer edits

    • Prompt the coder for action at code time


Automated coding tools can…

  • Reduce detail work for the coder

  • Increase throughput

  • Reduce inconsistency

  • Improve accuracy

  • Reduce risk

  • Increase billing opportunities

  • Ability to flag encounters for RAC, ICD-10, CDI

  • Leave less $ on the table



Computer-Assisted Coding:

“Computer-Assisted Coding (CAC) is generally defined as the use of computer software to “read” clinical documentation and automatically generate medical codes which are then reviewed and validated by a trained “human” coder.” – AHIMA


Computer-Assisted Coding:

Numerous dissimilar products out there

Confusion between EHR and CAC

EHR’s often have point/click menus with codes

Coding options that have little to do with CAC

(Options available whether you use CAC or not)

Such as viewing images and links to references

CAC Less useful as a term


“CBC is the new improved CAC”

CBC: Coded by Computer

Maintains the key elements of the original AHIMA definition:

  • Computer reads the charts and generates codes

  • Human Coder audits the results

    The major benefit for CAC is EFFICIENCY.

  • Efficient implementation, efficient training and

    efficient coding.


  • Computer-Assisted Coding:

    Natural Language Processing Rules

    • Mimics some clinical behaviour:

      • Quick overview of the document to get the “gist”

      • Examination of key segments to understand events

      • Analysis of whole document looking for extra detail that changes codes

    • Words and sentences examined for clinical term matches to generate codes

      2 common types; Rules-based and Statistical processing


    A 3rd type of Clinically-Oriented Mechanism;

    Binary Pattern Filtering

    • Binary pattern algorithms sent through one or more “filters” to derive codes.

      • ICD9, ICD10, CPT, HCPCS, specialist research sets...

    • No supervised learning process

    • No gradual improvement as hundreds of thousands of documents flow through

    • No need for vendor to retain documents as a statistical resource


    NLP Enhanced: a clinically oriented mechanism

    • The Binary Pattern Filtering Process converts your

      clinical documentation into a binary pattern that

      retains all of the rich clinical content and detail.

    • Charts are coded passing their binary pattern

      through one or more Code Set Filters – When a

      match is found, the correct code is displayed.

    • Any Code Set that has an index can have a

      Binary filter, such as; ICD-9, ICD-10, E & M

      and CPT codes.

    • An index is list of clinical concepts with their correct codes.



    “Our Patented Process

    makes it easy for

    clients to create

    and modify filters

    for their own

    unique terms and

    coding conventions while maintaining the highest CAC accuracy available

    today.” Dr. John Ryan


    Additional CAC Capabilities

    • CCI edits

    • LCD edits

    • POA alerts

    • RAC alerts

    • Payer rules - All applied at coding time

      • EFFICIENCY IS THE IMMEDIATE WIN

      • Many other benefits which are easier to achieve once you have gained the efficiency


    Changing the Role of the Coder

    • Speech Recognition Technology changed

      Transcription to make MT’s Editors

    • CAC transforms Coders into Auditors

    • Coders become Verification Specialists

    70450-RT


    Coders edit and validate the ICD-9 and/or ICD-10 codes found by the NLP engine -Saving time and money


    Coder Benefits beyond production by the NLP engine -Saving time and money

    • Speech Recognition Technology extended

      careers for some MT’s with carpal tunnel

      - Spell check reduced errors

    • CAC does the heavy lifting for Coders

    • CAC reads 200 lines of text per second

    • Reduced reading - reduced eye strain

      - reduces data entry by coder


    ICD-10 and CAC by the NLP engine -Saving time and money

    The value of this transition will be broad and far-reaching throughout the healthcare industry, and will result in:

    • Greater coding accuracy and specificity

    • Higher quality information for measuring healthcare service quality,

    safety, and efficiency

    • Improved efficiencies and lower costs

    • Greater achievement of the benefits of an electronic health record

    • Recognition of advances in medicine and technology

    • Alignment of the US with coding systems worldwide

    • Improved ability to track and respond to international public health

    threats

    • Enhanced ability to meet HIPAA electronic transaction/code set

    requirements

    • Increased value in the US investment in SNOMED-CT

    • Space to accommodate future expansion


    ICD-10 and CAC by the NLP engine -Saving time and money

    Although ICD-10 has been used around the world for many years and it is due to be implemented in the US by October 1, 2013, for now.

    It is a brand new issue for the US system that already faces numerous challenges. However, this challenge does present several opportunities there is no reason to delaypreparation.

    AHIMA August 2010 survey of 838 members preparing for 5010 or ICD-10

    • 52% had not yet started preparing for ICD-10.

    • Of that 52%, 49% said they did not know when they would

      begin preparation

    • 20% said they were still six months away from beginning


    ICD-10 and CAC by the NLP engine -Saving time and money

    Jump to August 2011

    85 percent of respondents to the August survey said that their organizations had begun work on ICD-10 planning and implementation, a significant jump from 62 percent one year earlier.

    The will to win is not nearly as important as the will to prepare to win. - Bob Knight 76’


    ICD-10 and CAC by the NLP engine -Saving time and money

    Basic Comparison of # Codes

    Because of the significant increase of specificity over ICD-9, there is a large increase in the number of codes:

    ICD-9-CM ICD-10-CM Change

    Diagnoses 14,315 69,101 54,786

    Procedures 3,838 71,957 68,119


    ICD-10 In Use for Over a Decade by the NLP engine -Saving time and money

    New Zealand

    • One of the first countries to go to Electronic Health Records

    • Transitioned to ICD-10 in 1998

    • Coded ICD-9 and ICD-10 both for 1 year

    • First 1st world country to use CAC in the 1990’s

    • US facilities can emulate the New Zealand ICD-10 experience

      by coding ICD-9 & ICD-10 simultaneously


    ICD-10 and CAC by the NLP engine -Saving time and money

    • Introducing an ICD-10 CAC tool today would allow a facility to

      make rational decisions about documentation process

      changes between now and 2013.

    • CAC allows facilities to assess the state of their electronic

      record. Coding to ICD-10 will reveal detail on “unspecified”

      codes, in which case documentation improvements starting now

      may be of great benefit to the facility in due course.

    • In addition, if coders are able to review ICD-10 codes alongside

      ICD-9 codes starting today, by 2013 ICD-10 will no longer

      represent the serious challenge that most professionals are

      expecting.


    Additional Benefits/Services by the NLP engine -Saving time and money

    • CAC as a training tool for ICD-10

    • Concurrently code ICD-9 and ICD-10

    • ICD-10 and CAC as a judge of documentation quality

    • Unspecified” codes will always end in 9 and “other specified” codes will end in 8 - we will flag for CDIS

    • CCI edits, LCD edits, payer rules…BUT

      • INCREASED PRODUCTIVITY IS THE IMMEDIATE WIN!

      • Other benefits are easier once you have efficiency


    Unique Characteristics of ICD-10 by the NLP engine -Saving time and money

    ICD-10 has moved entire codes into their own code groups.

    For example, in ICD-9, “left knee osteoarthrosis” would be coded as

    715.16 - Osteoarthrosis -Localized Primary Involving Lower Leg.

    Now, looking at the equivalent codes in ICD-10 we notice something

    is missing:

    M19.01 Primary arthrosis of other joints, shoulder region

    M19.02 Primary arthrosis of other joints, upper arm

    M19.03 Primary arthrosis of other joints, forearm

    M19.04 Primary arthrosis of other joints, hand

    M19.07 Primary arthrosis of other joints, ankle and foot

    M19.08 Primary arthrosis of other joints, other site

    M19.09 Primary arthrosis of other joints, site unspecified


    Do You Like Surprises? by the NLP engine -Saving time and money

    At first glance it would appear that there is no equivalent

    code for 715.16. A coder may be tempted to use M19.08

    instead. ‘M19.08 Primary arthrosis of other joints, other site’

    This would be incorrect indeed.

    The correct code to use would be M17.1 - Other primary

    gonarthrosis – which is in an entirely different section!

    This scenario is extremely common when changing

    from ICD-9 to ICD-10 – but if a coder has already been

    exposed to these sorts of changes prior to actually

    coding using ICD-10 then it won’t be such a surprise.


    “Facility On-Site Database” by the NLP engine -Saving time and money

    • Facility drops HL7 records in a designated folder

    • Cases submitted to Computer-Assisted Coding engine

    • Documents and CAC codes are retained in customer database

    • Codes and documents retrieved for display to coder/auditor

    • Assisted process for variance analysis

    • Productivity and other reporting tools.

    • Comply with new HITECH/HIPAA PHI policies


    Efficient Integration by the NLP engine -Saving time and money

    • Computer-Assisted Coding: prefers to interface with your existing (or preferred) tools

    • Example: Encoder: Computer-Assisted Coding solution pre-fills fields on the encoder screen

      • No new process for the coder who is now an auditor/verification expert, not a data entry clerk.

    • Resulting codes feed the billing system exactly as they do today

    • Minimal disruption to the organization


    Coder's process without CAC by the NLP engine -Saving time and money


    Coder's process with CAC by the NLP engine -Saving time and money

    CAC Engine

    Electronic Documents are coded

    by the CAC engine & displayed to coders for validation before being sent to Encoder for DRG and billing


    What will my work space look like
    What will my work space look like? by the NLP engine -Saving time and money


    CAC Demonstrating the coder workspace by the NLP engine -Saving time and money


    Accuracy and Efficiency by the NLP engine -Saving time and money


    Accuracy has a special meaning in CAC by the NLP engine -Saving time and money

    • AHIMA Paper 2009 – Measuring CAC Accuracy

      “reproducible method to measure complexity”

    • AHIMA Paper 2010 – Using CAC for ICD-10 CDI

      “method for documentation improvements”

    • Another due for AHIMA 2012

    • Whitepapers Available upon request


    Efficiency Expectations by the NLP engine -Saving time and money

    • Outpatient Diagnostic:

      • 100% efficiency improvement simply by dropping in CAC

        • No process improvement, minimal training

        • 100% after 1 month of experience

    • Same-day Surgery:

      • At least 100% efficiency improvement

    • “Head in the Game” can multiply improvements


    Efficiency Expectations by the NLP engine -Saving time and money

    • Inpatient Charts:

      - 200% efficiency improvement acheivable

      • Depending upon electronic documentation

      • POA, RAC, MNE all applied at coding time

    • Large volumes no problem for CAC

      • CAC reads & codes a 250 page chart before a coder can finish page 1

      • Concurrent Coding made easy

      • CAC recodes the entire encounter


    Better deployment of Coders/Auditors by the NLP engine -Saving time and money

    • Coder numbers will be reduced, not eliminated.

    • Coders’ jobs will move on from data entry.

    • Information management, accreditation, auditing, reporting, research.

    • Teaching the clinicians.

    • Capturing hand-written notes.

    • Prompting coders for physician queries


    Reporting, Audits, Hospital-acquired.. by the NLP engine -Saving time and money

    • Concurrent coding

    • Retention of source justification for Audit, RAC

    • Flags for POA - HAC

    • Alerts the Coders during review

    • Scheduled Reports that automatically email supervisors, auditors and CDI specialists

    • Complete Audit trail – every action monitored


    Preparing your Organization for CAC by the NLP engine -Saving time and money

    • Evaluate existing clinical documentation

      - CAC tools require electronic clinical documentation

    • Assess current coding workflow

      - Assess what is being done currently, step by step

      - identify how use of a CAC tool would alter the current workflow

    • Define expectations for balancing productivity

      and accuracy

      -Identify your “gold standard” for translating clinical data into medical

      codes. What level of productivity is acceptable?

    • Define organizational goals and objectives

      - CAC may be necessary for an organization that is often short staffed

      - Or a Radiology practice that employs no coding staff looking to improve

      compliance

    • Develop a testing and audit plan

      - perform random audits and consider complexity of coding


    Recommendation - Phased in Approach by the NLP engine -Saving time and money

    • Start with SDS or Diagnostics

      • Aim for 100% efficiency improvement

      • Benefits flow back to all other coding

      • Electronic documentation in most facilities

    • Inpatient:

      • Process charts from day 1 for ICD-10

      • Use ICD-10 results for advance training

      • Flag/Audit “unspecified” codes for documentation improvement in 2013


    Questions? by the NLP engine -Saving time and money


    Answers by the NLP engine -Saving time and money


    For questions and information contact by the NLP engine -Saving time and money

    Leo Schafer

    at

    [email protected]

    800-245-3195 Ext: 211


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