Everything You Need To Know To Prepare For Computer Assisted Coding NYHIMA June 2, 2014 Darice 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? 2014 Confidential/Copyright HIMentors,LLC

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 Processing document 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

Patient Care Research Contract Negotiation Quality/Utilization Education Physician Credentialling Reimbursement Certificate of Need (Planning) Marketing Budgeting/Resources Historical Documentation Remember…..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 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

Focus on Coding Workflow: It’s all about Efficiency 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

Measuring Your Success NLP: Precision vs. Recall and F Score -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) 2014 Confidential/Copyright HIMentors,LLC

Graphic of F Score F score is the harmonic mean of precision and recall Condition (as determined by "Gold standard")Gold standard Condition positive Condition negative Test outcome Test outcome positive True positive False positive (Type I error)Type I error PrecisionPrecision = Σ True positive Σ Test outcome po sitive Test outcome negative False negative (Type II error)Type II error True negative Negative predictive valueNegative predictive value = Σ True negative Σ Test outcome ne gative SensitivitySensitivity = Σ True positive Σ Condition positiv e SpecificitySpecificity = Σ True negative Σ Condition negati ve ^^ 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."EVALUATION: FROM PRECISION, RECALL AND F-MEASURE TO ROC, INFORMEDNESS, MARKEDNESS & CORRELATION" 2014 Confidential/Copyright HIMentors,LLC

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) 2014 Confidential/Copyright HIMentors,LLC

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? 2014 Confidential/Copyright HIMentors,LLC

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 2014 Confidential/Copyright HIMentors,LLC

ICD-9 to ICD-10 Diagnosis Code Format Differences 121 A12122A 11 Etiology, Anatomic Site, Severity Category Etiology, Anatomic Site, Manifestation Category Alpha Alpha or numeric Qualifier -Additional code for obstetrics, injuries, and external causes of injury ICD-10 CM 2014 Confidential/Copyright HIMentors,LLC

ICD-10-CM Many 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 All rights reserved. ICD-9-CM Fracture of femur, shaft, closed 2014 Confidential/Copyright HIMentors,LLC

ICD-10 CM ICD-9 to ICD-10PCS Procedure Code Format Differences 21 A12122A 11 Section Etiology, Anatomic Site, Manifestation Category Alpha or numeric Body System Root Operation Body Part ApproachDeviceQualifier ICD-9 CM 2014 Confidential/Copyright HIMentors,LLC 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 2014 Confidential/Copyright HIMentors,LLC

Questions? We’ve got answers……. Contact: Darice Grzybowski, MA, RHIA, FAHIMA, AHIMA Approved ICD10CM/PCS Trainer Special thanks to 3MHIS-CodeRyte for their Contributions 2014 Confidential/Copyright HIMentors,LLC