everything you need to know to prepare for computer assisted coding nyhima june 2, 2014 darice...

Everything You Need To Know To Prepare For Computer

Assisted Coding

NYHIMA June 2, 2014Darice Grzybowski, MA, RHIA, FAHIMA

President, H.I.Mentors, LLC

Agenda

– Understanding Computer Assisted Coding

– Before You Begin

– Going Live

– Measuring Your Success

– What’s In The Future (Including I10)

– Q & A

2014 Confidential/Copyright HIMentors,LLC

Industry Pain Reasons Driving CAC

• Staffing shortages! (on top of already 20% shortage)– Belief (?) that CAC improves productivity

• Increased documentation (esp electronic)• Onset of ICD-10 and ICD-10-PCS • Multiple software concerns – not using

EDMS optimally so don’t have a good workflow

• BUT …..are you ready?


Computer Assisted Coding

• Typical definition: A computer assisted coding (CAC) system is a computer application that analyzes health care documents and produces appropriate medical codes for specific phrases and terms.

• NLP = Natural Language Processinghttp://searchhealthit.techtarget.com/definition/computer-assisted-coding-system-CACSthe document


HPI: Atrial fibrillation. This patient is a 32-year-old white female who has had a history of atrial fib on and off since she had her bypass surgery. Patient was originally diagnosed with coronary artery disease as well as mitral valve problems approximately 3 years ago. Dr. Tirona used to take care of her at that time. She had a bypass surgery as well as mitral valve repair done at that time. Postop she had an episode of A-fib which then resolved spontaneously. She remembers somebody talking to her about cardioversion, but then the A-fib resolved spontaneously. So she was started on Coumadin. She would get some occasional episodes, but usually they are very brief, so she never bothered about them. Of late, over the last few months, she has been getting more frequent episodes and duration of these episodes is also prolonged for a few hours. So she saw Dr. Hagan who has referred her here for further evaluation and treatment. The patient states when she does get the A-fib, she feels very weak, tired, and short of breath. She denies any chest pain. Otherwise she is usually very active physically, She works fulltime and has not had any problems as far as doing her day-to-day work.MEDICAL HISTORY: 1. Coronary artery disease as mentioned above. 2. Hypertension. 3. Hypercholesterolemia..IMPRESSION: Paroxysmal atrial fibrillation in a patient with prior mitral valve disease, currently having more frequent breakthroughs symptoms.

An Example of How NLP Annotation Works


Patient Care

Research

Contract Negotiation

Quality/Utilization

Education

PhysicianCredentialling

Reimbursement

Certificate of Need (Planning)

Marketing

Budgeting/Resources

Historical Documentation

Remember…..Uses of Coded DataRemember…..Uses of Coded Data

2014 Confidential/Copyright

HIMentors,LLC

Some of the Challenges of CAC

• Accuracy – Capturing MORE than what is needed, Capturing LESS than what is needed, Capturing the WRONG codes

• Negation and confusing terms (abbreviations) • Classifying historical conditions vs. current• Integrating lab results and medicines• Episodic vs. Single document specific• Treated conditions vs. untreated


Before You Begin• Is your environment ready? • Experienced coders, Remote Coders• Minimum 80% electronic documentation • Data integrity controls in place• Budget for interfaces and computer equipment• Back-up coding staff for training time • Dedicated project management staff• Calendar and training plan


Technical Considerations• Integration and Interfaces• Double Monitors (large)• Reconciliation

– document numbers/dates/types

• Server size /speed• Back-ups and versioning• Audit trails• Access control, feedback, support issues• Dedicated IT support and test environment


Focus onCoding Workflow:

It’s all about Efficiency


Coding Issues to Consider• Productivity Individual, group, by type of record, by facility,

DNFB (discharge not final build – but why)• Audits

– Can you review original codes, what changed, what was accepted, what was deleted

• Abstracting Process– Items on deficiency hold, missing documents added

• Accuracy/Compliance – sequencing, rules, special exceptions

• Coding Management– Work routing, exception assignments, inability to reject

cases, exception routing, direct to bill


System/Workflow Issues• Data Integrity (real life)

– how to fix errors, duplicate accounts/MRNs, patient status changes, discharge status updates

– “offline” catch up• System interface updates:

– HIS/EHR, other documentation systems, Abstracting, CDI, electronic document management systems,

– Who else may have access to code review or retrieval of data?

• Keeping current with ICD 9 CM, ICD10 CM, ICD 10 PCS, and CPT/HCPCS within CAC


Going Live: Challenges and Opportunities

• Integration Issues (other vendors) – keeping up with releases

• Reconciliation of documents – counts/type• Forms output control is key!• Staged or Big Bang – OP or IP or both? • Documentation inconsistency• Magnifying Glass to Exceptions,

Workarounds, Delays, and non-standard processes


Measuring Your SuccessNLP: Precision vs. Recall and F Scorehttp://www.youtube.com/watch?v=2akd6uwtowc-Precision – number of accepted machine generated codes/total number of machine generated codes - specificity ok = a score of 1 is desired – smaller numbers are worse i.e. 5/20 (machine is overcoding), 20/20 (machine gets it right – but we don’t know what was missed!)-Recall – number of accepted machine generated code /total number of final codes assigned (human and computer) = a score of 1 is desired – smaller numbers indicates less efficiency i.e. 5/10 (half the codes automated 10/10 – computer got it 100% correct)


http://www.youtube.com/watch?v=2akd6uwtowc

Graphic of F Score

F score is the harmonic mean of precision and recall

Condition(as determined by "Gold standard")

Condition positive Condition negative

Testoutcome

Testoutcomepositive

True positive False positive(Type I error)

Precision =Σ True positive

Σ Test outcome positive

Testoutcomenegative

False negative(Type II error) True negative

Negative predictive value =

Σ True negative Σ Test outcome ne

gative

Sensitivity =Σ True positive

Σ Condition positive

Specificity =Σ True negative

Σ Condition negative

^ POWERS, D.M.W. (February 27, 2011). "EVALUATION: FROM PRECISION, RECALL AND F-MEASURE TO ROC, INFORMEDNESS, MARKEDNESS & CORRELATION". Journal of Machine Learning Technologies 2 (1): 37–63.


http://en.wikipedia.org/wiki/Gold_standard_(test)

http://en.wikipedia.org/wiki/Type_I_and_type_II_errors

http://en.wikipedia.org/wiki/Positive_predictive_value

http://en.wikipedia.org/wiki/Type_I_and_type_II_errors

Measuring Your Success (cont.)• Taking a careful baseline measurement

– Include all tasks, like cases as single • Careful on numerators and denominators when

calculating accuracy and productivity improvement – What cases?– Number of cases or number of codes?– Diagnosis or Procedures?

• DNFB improving?• Accountability Factor for other departments

(i.e. Radiology, or late reports, or doc authentication delay)


NLP Processing-Philosophical Debates - What is Best Practice??

• Review all codes, then accept or eliminate? • Look for additional final codes, then add? • Turn on or off for specific types of

documents? • Turn on or off for specific types of cases? • What about documents that are not

machine readable? OCR or manual read (or both)?

• How are disagreements resolved or reported?


Implications for ICD-10 w CAC

• More complex documentation required – possible re-design in EHRs

• Productivity 30-70% increase in coding time• Education around new guidelines – Practice

with ICD 10 CAC?• Internal guidelines – potentially mandate more

specificity for PCS than required – terms not matching

• Make CHOICES in how to use effectively


ICD-9 to ICD-10Diagnosis Code Format Differences

1 2 1

A 1 2 1 2 2 A

1 1

Etiology, Anatomic Site, SeverityCategory

Etiology, Anatomic Site, Manifestation

Category

Alpha

Alpha or numeric

Qualifier -Additional code for obstetrics,

injuries, and external causes of injury

ICD-10 CM


ICD-10-CMMany possible codes

Diagnostic Specificity looks like this…

S72301A Unspecified fracture of shaft of right femur, initial encounter for closed fracture

S72322A Displaced transverse fracture of shaft of left femur, initial encounter for closed fracture

S72326A Nondisplaced transverse fracture of shaft of unspecified femur, initial encounter for closed fracture

S72301G Unspecified fracture of shaft of right femur, subsequent encounter for closed fracture with delayed healing

S72322G Displaced transverse fracture of shaft of left femur, subsequent encounter for closed fracture with delayed healing

S72326G Nondisplaced transverse fracture of shaft of unspecified femur, subsequent encounter for closed fracture with delayed healing

S72302A Unspecified fracture of shaft of left femur, initial encounter for closed fracture

S72323A Displaced transverse fracture of shaft of unspecified femur, initial encounter for closed fracture

S72331A Displaced oblique fracture of shaft of right femur, initial encounter for closed fracture

S72302G Unspecified fracture of shaft of left femur, subsequent encounter for closed fracture with delayed healing

S72323G Displaced transverse fracture of shaft of unspecified femur, subsequent encounter for closed fracture with delayed healing

S72331G Displaced oblique fracture of shaft of right femur, subsequent encounter for closed fracture with delayed healing

S72309A Unspecified fracture of shaft of unspecified femur, initial encounter for closed fracture

S72324A Nondisplaced transverse fracture of shaft of right femur, initial encounter for closed fracture

S72332A Displaced oblique fracture of shaft of left femur, initial encounter for closed fracture

S72309G Unspecified fracture of shaft of unspecified femur, subsequent encounter for closed fracture with delayed healing

S72324G Nondisplaced transverse fracture of shaft of right femur, subsequent encounter for closed fracture with delayed healing

S72332G Displaced oblique fracture of shaft of left femur, subsequent encounter for closed fracture with delayed healing

S72321A Displaced transverse fracture of shaft of right femur, initial encounter for closed fracture

S72325A Nondisplaced transverse fracture of shaft of left femur, initial encounter for closed fracture

S72333A Displaced oblique fracture of shaft of unspecified femur, initial encounter for closed fracture

S72321G Displaced transverse fracture of shaft of right femur, subsequent encounter for closed fracture with delayed healing

S72325G Nondisplaced transverse fracture of shaft of left femur, subsequent encounter for closed fracture with delayed healing

S72333G Displaced oblique fracture of shaft of unspecified femur, subsequent encounter for closed fracture with delayed healing

© 3M 2010. All rights reserved.

ICD-9-CM

821.01 Fracture of

femur, shaft, closed


ICD-10 CM

ICD-9 to ICD-10PCSProcedure Code Format Differences

2 1

A 1 2 1 2 2 A

1 1

Section

Etiology, Anatomic Site, Manifestation

Category

Alpha or numeric

Body System

Root Operation

Body Part

Approach Device Qualifier

ICD-9 CM


INTERPRETATION IS THE CONCERN!

Future CAC Planning?– Forms Inventory &/Or Electronic Document

Management System– Flowchart each type of medical record from start to

discharge– Clinical Documentation Improvement – minimum

physician education on principles – Site visits and setting baseline measurements– Vendor evaluation & project plan– Use of Subject Matter Expert– Future applications: Late documentation tracking, EHR

completeness


Questions? We’ve got answers…….

Contact:

Darice Grzybowski, MA, RHIA, FAHIMA, AHIMA Approved ICD10CM/PCS Trainer

[email protected]

Special thanks to 3MHIS-CodeRyte for their Contributions
