Computer Assisted Coding Fact or Fiction, A Case Study

1. Computer Assisted Coding Fact or Fiction, A Case Study Amy L. Wood, CPC Yale-New Haven Health System

2. Computer Assisted Coding • Magic Bullet or Marketing Hype? • Selling the CAC concept to Administration • Do the results change as coders become use to the technology?

3. Administrative “Buy In” • Highlight organization benefits • Increased compliance • Increased productivity • Potential for increase in revenues • Increased employee satisfaction • Decrease of the coding productivity gap during ICD-10 transition

4. Selection Process for Product • Determine which service lines will be coded • Select visit types to be part of the process • Inpatient accounts • Determine what documents to be included

5. Selection Process Continued • Outpatient Accounts to include: • Ambulatory Surgery • Interventional Radiology • Heart and Vascular Center

6. Selection Process Continued • Facility Infrastructure • Additional Equipment Needs • Cost of Implementation

7. Coder Staff Buy-In • Non-Threatening Introduction to Process • Calming Fears of Job Loss • Product only a Tool, NOT a Replacement • Stress “Assisted” in CAC Discussion

8. Coder Staff Buy-In • Outline ICD-10 Benefits • What is Involved in the Learning Process • Coder Reaction to Suggested Codes

9. Steps to Implementation • HIM must inventory sources of current medical record documentation • Information Technology Department (IT) heavily involved • Detailed mapping of document types to be part of the process

10. Additional Steps to Implementation • Work with IT to determine infrastructure of Facility • Involved testing and re-testing • Realistic expectations regarding implementation timeline

11. Post Implementation-Go Live • Monitor coder productivity • Measure and compare pre and post productivity values • After assessment, adjust productivity standards as necessary

12. Post Implementation Go Live con’t • Monitor impact on Accuracy • Are there additional benefits of CAC? • Can you compare ICD-9 to ICD-10 at this point?

13. CAC Phase 1 Go-Live Results • Outpatient Surgery implementation process January, 2012 • Review conducted April, 2012 • 10% increase in coder productivity realized

14. CAC Phase 1 Go-Live Results • Inpatient implementation process December, 2011 • Productivity measured over a three month period • Demonstrated 15% increase in coder productivity

15. Phase 2 Auto-suggested Codes • Identify all possible document types • Build into test environment • Identify potential obstacles • Define what results wanted • Diagnosis codes only • Diagnosis and CPT codes • Service areas or visit types

16. Phase 2 Auto-suggested Codes • Keep a document type library • NLP engine needs to “learn” as product is used • Sample multiple scenarios to cover all visit types • Test and re-test results

17. Phase 2 Auto-suggested Codes • Define a reasonable timeline • Staff will need additional training • Select go-live date • Prepare for initial reduction in productivity during learning phase

18. Phase 2 results • Very little reduction in productivity with go-live • Staff has the option to use the product or to continue to code historical way • New productivity standards implemented 3months post go-live • Additional increase in productivity most notably in the surgical areas • GI procedures • Ambulatory Surgery

19. ICD-10 Impact • Increased coding challenges • New coding guidelines/regulatory rules • Need for increased specificity of documentation

20. CAC Fact or Fiction? • Fact based upon our use of the product • Fiction • Not a magic bullet

21. Lessons Learned from Implementation • Testing and Re-testing a must • Monitor coder use of CAC process • Does one visit type work better than the other • Inpatient vs Outpatient

22. Additional Lessons Learned • All document types not always easily available for use. • Coder training time and resources needed • Expectations of implementation timeline and deadlines • Interface monitoring and EMR changes and the effect on current system

23. Questions? Thank You!!!!!