Crossroads Conference

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Crossroads Conference. ICD-10 Industry Update. Susan H. Fenton, PhD, RHIA Asst. Dean for Academic Affairs UT School of Biomedical Informatics @ Houston. Policy The delay ICD-11 SNOMED Practical impacts Clinical documentation Coding productivity Quality Measures. Agenda. - PowerPoint PPT Presentation

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Crossroads Conference

Susan H. Fenton, PhD, RHIAAsst. Dean for Academic Affairs

UT School of Biomedical Informatics @ Houston

ICD-10 Industry Update

Policy•The delay• ICD-11•SNOMED

Practical impacts•Clinical documentation•Coding productivity•Quality Measures

Agenda

• H.R. 4302• SEC. 212. DELAY IN TRANSITION FROM ICD–9 TO ICD–10

CODE SETS. The Secretary of Health and Human Services

may not, prior to October 1, 2015, adopt ICD–10 code sets as

the standard for code sets under section 1173(c) of the Social

Security Act (42 U.S.C. 1320d–2(c)) and section 162.1002 of

title 45, Code of Federal Regulations.

• $1 billion to $6.6 billion additional – CMS

The Delay

“On April 1, 2014, the Protecting Access to Medicare Act of 2014

(PAMA) (Pub. L. No. 113-93) was enacted, which said that the

Secretary may not adopt ICD-10 prior to October 1, 2015.

Accordingly, the U.S. Department of Health and Human Services

expects to release an interim final rule in the near future that will

include a new compliance date that would require the use of ICD-

10 beginning October 1, 2015. The rule will also require HIPAA

covered entities to continue to use ICD-9-CM through September

30, 2015.”

Latest Update

Part B News, 73% of providers plan to stick with their original ICD-

10 implementation plans, despite the delay, EHR Intelligence

reports (Bresnick, EHR Intelligence, 4/24).

How providers feel about the delay. Specifically:

• 34% of organizations ready but appreciate additional time;

• 31% of organizations disappointed with the delay;

• 20%+ of organizations frustrated because physicians now might want to

delay training; and

• 13.5% of organizations happy with the delay because they would not have

been ready otherwise (Marbury, Medical Economics, 4/23).

Provider Responses

Conducted in March 2014•2,600 participating organizations; 50% were clearinghouses

•127,000 claims submitted with ICD-10-CM/PCS codes

•89% of claims were accepted• Some claims included intentional errors to ensure the system would reject appropriately

Contact local MAC for acknowledgment testing detailsMore end-to-end testing in 2015

CMS ICD-10 Claims Submission Testing

Release delayed to 2017 – WHO

Derived from SNOMED

Compatible with EHRs

Participate @ http://www.who.int/classifications/icd/revision/icd11faq/en/

ICD-11

Focused on clinical information

Compatible with EHRs

311,000 active concepts

33% agreement on core concept choice•Andrews, J.E., Richesson, R.L., and Krischer, J. (2007) SNOMED CT Coding of Clinical Research Concepts, Journal of AMIA, 14(4), 497-506.

SNOMED

• Public health

• Quality patient care

• Research

• Reimbursement

So, why move at all?

• Laterality: No longer accept injuries to limbs or bilateral organ conditions without laterality.

• Paralytic syndromes require right/left and dominant/nondominant

• Infectious organisms. How can we help clinicians include these in their documented diagnoses?

Clinical Documentation Improvement

• A for Initial Encounter – active initial treatment

in ER, surgery or new clinician

• D for Subsequent – healing or recovery such

as cast change or aftercare

• S for Sequela – complications or conditions as

a direct result of the injury. Examples include

scars or frozen joint

Injuries

• Open, including Type vs. Closed

• Routine vs. Delayed healing

• Nonunion vs. Malunion

• Displaced vs. Nondisplaced

• Many types, transverse, comminuted, or spiral

to name just a few

Fractures

Track use of unspecified codes by clinician

•Appropriate or not?

Random coding of records in ICD-10-CM/PCS to

determine adequacy of documentation

•Feedback

•Evaluation criteria

Clinician-specific Efforts

• 54 records

• 6 coders

• ICD-9-CM Avg Coding Time – 25.51

• ICD-10-CM/PCS Avg Coding Time – 43.23

• Overall on average it took 17.72 minutes or

69% longer to code a record in

ICD-10-CM/PCS

Inpatient Coding Productivity

• ICD-9-CM Diagnostic = .68

• ICD-9-CM Procedural = .61

• ICD-10-CM = .49

• ICD-10-PCS = .42

Coding Quality or Inter-rater Reliability

• Spearman’s Correlation

•Correlation Coefficient = -.424

•P-value = .027

• As the time spent per record increases, the

coding quality decreases

Quality vs. Minutes/Record

• 382 inpatient records

• 65% decrease in productivity

• 12.5 minute decrease without procedures

• 20 minute decrease with procedures

• Non-OR procedures accounted for longest

Veterans Health Administration Inpatient Coding Productivity

• 1,024 ambulatory care records

• 6.7% decrease in productivity

• Longest time to code ER and Therapy

• Productivity recovered within 2 months

Veterans Health Administration Ambulatory Coding Productivity

• Comparability, aka bridge-coding, for longitudinal

data comparison

• Performed for ICD-9 to ICD-10 for Cause of Death

•http://www.cdc.gov/nchs/data/nvsr/nvsr49/nvsr49_02.pdf

• Must dual code same set of records

Comparability Factors or Ratios

• Frequencies run for ICD-9-CM and ICD-10-CM

diagnostic codes

• Used the 2013 General Equivalence Maps

• Used the July 2, 2013 National Hospital Inpatient

Quality Measures, Appendix A (ICD-9) and Appendix

P (ICD-10)

Calculating the Comparability Factors

Joint Commission Core Measure Comparison (ongoing analysis)

Missing ICD-9-CM Cases for AMI

I21.02 – STEMI involving diagonal coronary artery

I21.4 – Acute subendocardial MI

410.72 – Subendocardial infarction 6410.12 – AMI of other anterior wall 1

Extra ICD-9 Cases for Respiratory Failure

J96.01 – Acute hypoxemic respiratory failure

J96.02 – Acute hypercapnic respiratory failure

518.81 – Acute Respiratory

Failure 27 4

• Implementation now slated for 10/1/2015

• Review insurance and vendor contracts

• More time for system upgrades

• Continue documentation improvement

• Maybe consider Computer-assisted Coding

• Identify potential longitudinal data concerns

In the Final Analysis

Thank you to Texas Tech and the West Texas AHEC.

Questions

• Susan H. Fenton, PhD, RHIA, FAHIMA

• Assistant Dean, UT SBMI

• susan.h.fenton@uth.tmc.edu

Contact Information

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