Computer Assisted
Coding (CAC)
Background and Related
Information
January 2013
NCHIMA
Computer Assisted Coding (CAC) - Agenda
Topic
Page #
Background
3
Challenges and Opportunities
8
Market Vendor Summary
24
Coding Compliance and CAC
29
Clinical Documentation Review and SMART
35
Core Technology
*CAC natural-language processing (NLP) applications
•
Scrutinize and interpret unstructured clinicians’ notes using specialized linguistic algorithms,
extracting the clinical facts that support the assignment of codes. Electronic document is sent
to an NLP coding engine, the engine reads the document and selects potentially applicable
codes and then goes to coding/HIM for validation.
CAC Structured (Codified) Input
•
Structured input applications integrate the coding into the clinical documentation process,
producing clinical documents with embedded codes
How Deployed
Cloud-based (also known as SaaS or Software-as-a-service)
Local installation requirements are minimal. CAC products often include a number of different
modules to provide a complete coding work-flow solution, including coding review, production
monitoring, management reporting, coding automation and auditing.
Data interfaces are required to feed the clinical documentation into the CAC application and accept
the coded data into the organization’s billing system.
Conventional client-server software install
Web services are also an option for some environments, particularly if an existing programming
interface is available. The output of the CAC work flow is coded records, including the CPT and
ICD-9 coding and other information needed to file a complete claim, such as modifiers, units, code
linkage, patient demographics and payer demographics. For optimum work flow that does not
require data entry, the coded data transfers directly from the CAC system into the billing system.
CAC Implementation Progress
Service Area
Implementation Progress
Early
Adoption
Market
Interest
Product
Usage
Wide Spread
Adoption
Outpatient
Inpatient
Common Market Perceptions
Misperception of what CAC is
•
Does not replace staff
Replaces Coding Staff
•
CAC does not code the record, it SUGGESTS codes
Increases the CMI
•
Not enough data to verify
CAC vendor selection is not dependent on Grouper/Encoder/Abstracting Technology
•
Grouper/Encoder “was cool 10 years ago”
•
All related applications not required to be supplied by one vendor
Assumptions
•
Successful use of Computer Assisted Coding is based on the premise that the
technology is properly mapped to “read” the record and apply the necessary
code recommendations to the coding professional. “Tune the Engine”
•
Ability of the engine to learn and be tuned is critical to accuracy of output
•
CAC can be considered to “Google-ize” the record
•
Even in a totally electronic record environment, the more consistency in the
format of notes, the better the outcomes of an electronic review (an
application of rules) of that record. (Physician resistance to “standardized”
notes?)
•
Consistency in the record can affect the accuracy of NLP (for instance
physicians with different documentation styles)
Challenges
Coder Knowledge is Still Required
Inexperienced coders are more likely to “rubber stamp” CAC outcomes
Incorrect NLP context goes unrecognized (i.e. opiate substance abuse vs. prescribed pain
control)
Assumptions may be made that “nothing was missed” by CAC
Implementation Impact on Coder Productivity
Learning Curve
Coder lack of trust in the CAC technology
Hybrid records impact productivity/outcomes (NLP does not read hand written notes)
Independent Compliance Reviews Remains “Best Practice”
Astute supervisory personnel who understand both CAC and compliance
CAC does not replace the facility requirements related to accurate billing/compliance
policies and procedures – in fact some would argue it increases the need
Challenges – Scenarios of CAC inconsistency to think
about
Challenges - Scenario 1
Background
Patient admitted due to acute cholecystitis. Patient underwent laparoscopic
cholecystectomy. After the procedure, progress notes documented that the patient fell
and was found on floor with bleeding from back of head. Subsequent CT scan
documented subarachnoid hemorrhage. Progress notes and discharge summary
documented the patient had head trauma due to the fall.
Challenges - Scenario 1
CAC Coding & Financial Impact
Additional diagnosis coded was 431 Intracerebral hemorrhage,
Revised to diagnosis code 852.01 Subarachnoid hemorrhage following injury without
loss of consciousness, POA = No
Also added E884.4 and E849.7 to indicate fall from bed, residential institution,
POA = No.
Challenges - Scenario 2
Background
Patient admitted due to atherosclerosis of lower extremity and gangrene of foot. Surgery
consult and numerous progress notes as well as discharge summary documented
atherosclerosis, foot ulcer, gas gangrene. Patient had below knee amputation
Challenges - Scenario 2
CAC Coding & Financial Impact
PDx code revised from 440.24 Atherosclerosis native artery with ischemic gangrene, to
PDx diagnosis code 440.29 Atherosclerosis of native artery, other. Secondary diagnosis
code added: 040.0 Gas gangrene, consistent with physician documentation
Gas gangrene is excluded from 440.24 per the ICD-9-CM code book exclusion notes and
Coding Clinic 1Q 1995 pg 11.
Challenges - Scenario 3
Background
Patient admitted with inflamed mass of the abdomen. Physician’s dictated operative
report documented that necrotic skin was excised from the subcutaneous tissue on the
abdomen. Post-op note also documented excision of necrotic tissue. Surgeon progress
notes several days later documented pathology findings of infected epidermoid inclusion
cyst of the abdomen. There does not appear to be documentation of benign neoplasm of
soft tissue of the abdomen.
Challenges - Scenario 3
CAC Coding & Financial Impact
Correct Principal Diagnosis code revised from 215.5 Benign neoplasm soft tissue
abdomen, to new Principal Diagnosis code 706.2 Sebacceous cyst, consistent with
physician and pathology documentation of epidermoid inclusion cyst.
Challenges - Scenario 4
Background
A 25 year old patient was admitted due to uncontrolled diabetes mellitus, type II.
Patient history: automobile accident with spinal injury several years PTA. Physician
stated severe back pain controlled with methadone. All progress notes document
degenerative disc disease-DDD-chronic due to back injury, methadone for pain. There
was no documentation that the patient was receiving methadone due to heroin addiction,
nor that the patient was "drug seeking" or addicted to methadone.
Challenges - Scenario 4
CAC Coding & Financial Impact
Incorrect secondary diagnosis code 304.01 Opioid dependence-continuous was originally
assigned. Correct SDx diagnosis code should have been V58.69 Long term current use of
medication-other, consistent with medical record documentation and consistent with
ICD-9-CM code book inclusion note for V58.69:
“Includes: Long term current use of methadone for pain control”
Reimbursement effect: $0 for hospital, potential significant adverse patient
effect due to use of opoid dependence code on bill sent to insurance
Challenges - Scenario 5
Background
Patient admitted due to increased falling, slurring of speech. Workup documented
metastatic lesion to brain as the cause of presenting symptoms. Radiation oncologist
documented Stereotactic Radiosurgery procedure performed prior to discharge with
planned follow-up radiation as an outpatient.
Challenges - Scenario 5
CAC Coding & Financial Impact
Additional procedure codes 92.30 Stereotactic radiosurgery unspecified, and 93.59
Application of stereotactic heat frame, should have been added based on radiation
oncology documentation, and Coding Clinic 4Q 1998 pg 79.
Opportunities
Productivity
CAC pre-reads the chart and provides suggested codes for review and approval to potentially
increase the speed of the coding process in a receptive environment.
Consistency & Accuracy
Rules-based evaluation of the documentation and programmed application of codes has the
potential of creating more consistent outcomes once “tuned” to hospital coding practices
Facilitating the Transition to ICD-10
Properly programmed to match “rules” to procedure and diagnosis codes, a rules-based NLP
engine can have a significant positive impact on the transition to ICD-10
Can potentially reinforce ICD-10 training of coding staff
Depending on vendor, CAC may provide the opportunity to perform “modeling” of both
ICD-9 and ICD-10
Accuracy and Productivity Outcomes
(Vendor Reported)
Productivity Improvement
Inpatient > 30%
Outpatient 50% to 100%
Coding Quality Improvement > 10%
Reduce Coding Related Denials > 20%
A/R Days Improvement – 5 – 60 Days
Reduction of Total Cost to Collect > 40%
Partial List of Key Vendors-Self-reported Capabilities
Key Vendor
Description
3 M
3M offers integrated solutions for transcription, speech recognition, clinical
documentation improvement, documentation management, computer-assisted
coding, quality, and revenue cycle management, effectively meeting the industry's
changing needs
* Please note, 3M recently purchased CodeRyte
Dolbey
leader in providing dictation, transcription, speech recognition and coding solutions
for healthcare in the United States and Canada. Together, Dolbey and Company,
Inc. and Dolbey Systems, Inc. offer the award winning Fusion Suite™ of integrated
products
Innovative Health Solutions,
LLC
Innovative Health Solutions, LLC develops Web based coding, compliance,
reimbursement, and information management solutions to healthcare providers,
information technology vendors, and managed care organizations. Its products
include CDM FOCUS, an automated system that provides a set of tools to ensure
optimum coding, compliance, and reimbursement; Clinical Coding Expert, a
solution that support to code, abstract, and analyze inpatient and outpatient
medical records; APC FOCUS, an automated and Web-based chart selection
system for providers and consultants to ensure coding accuracy and compliance;
Partial List of Key Vendors-Self-reported Capabilities
Key Vendor
Description
Optum (A-Life Medical
/ Ingenix)
Optum™ is an information and technology-enabled health services platform serving the
broad health marketplace.
A-Life uses its proprietary and patented Natural Language Processing (NLP) technology,
LifeCode, to decipher electronic transcribed patient encounters via the Internet through its
data center. These documents are then appropriately coded for reimbursement purposes.
A-Life’s NLP technology utilizes proprietary knowledge bases which contain tens of
millions of facts to automate the coding process.
Precyse Solutions
PrecyseCode is the industry's first computer-assisted and NLC-driven intelligent workflow
solution, enabling productivity increases of up to 20-50%. PrecyseCode features
computer-assisted coding that uses NLC to create the patient's clinical story, allowing for
the assignment of appropriate, compliant ICD-9 and ICD-10 codes, and SNOMED clinical
terminology. NLC is achieved through the unique combination of M*Modal contextual
understanding technology with Precyse's collaborative technology platform and extensive
coding and clinical documentation expertise.
Nuance-Quantim
Quantim®, the Health Information Management (HIM) business of QuadraMed, is a
provider of leading information technology solutions for the healthcare industry. Working
closely with industry partners, including electronic healthcare record (EHR) providers,
Nuance and Quantim will ease healthcare providers’ transition to ICD-10, while preserving
clinician productivity and document workflows and, most importantly, ensuring the quality
of patient care.
Coding Outcomes Touch Every Part of Revenue Cycle
Start:
Patient
Access
Scheduling/
Registration
Cert
Financial
Counseling
Encounter
Charge
Capture
Coding
Utilization
Review
Medical
Third
Party
Follow-up
Rejection
Processing
Payment
Posting
Appeals
Contract
Management
Coding Compliance and CAC:
Automating the coding process increases the need for coding compliance
The need is greater with the implementation of new CAC systems, as hospitals
adjust NLP rules to match their desired outcomes.
(e.g. “HAC” and “POA” indicators)
ICD-10 code accuracy and compliance with coding guidelines as well as medical
necessity will be scrutinized closely by payers when implemented in 2014
Hospital and physician “quality” measures can be negatively affected under ICD-10
if codes assigned are not specific, accurately reflecting the documentation in the
record
Robust compliance process is necessary for both Inpatient and Outpatient services
to protect the hospital from inadvertent incorrect code assignments
•Enhance the
manageability of the coding process by
providing evidence of the workflow and thought processes that went into coding results.
•Links to assigned codes and associated record
•Audit trail of changes to coding
•Ensures that guidelines are applied similarly over time and across multiple coding resources.
•Instills confidence in the coding results,
supporting accurate clinical and financial analysis.
•Connectivity through
• Coding output matches both official guidelines and payer reporting requirements
•Decrease in denials, reduction in audit
discrepancies, and finding lost charges that were previously under-coded
•Assures that an
organization captures all the charges that it is entitled to collect
•Improved Coder efficiency
•Increases when average amount of time to code decreases
•Due to elimination of document sorting, storage and retrieval, duplicate identification, code lookup and selection, code
ordering, or data entry
Productivity
Accuracy
Transparency Consistency
