Coder ICD-10 Productivity:
A Time Study
UASI – United Audit Systems, Inc.
Funded Research University Hospital – Cincinnati, Ohio
Over a 5 month period, UASI in conjunction with the University of Cincinnati & University Hospital conducted a research study to measure ICD-10 productivity time loss.
Objectives
Determine the variance in coder productivity using ICD-9-CM vs. the ICD-10-CM/PCS coding classifications and to calculate the potential initial productivity loss due to the transition to ICD-10-CM/PCS.
Hypothesis
Null hypothesis indicates there will be no difference in coding productivity when coders utilize ICD-9-CM and ICD-10-CM/PCS classification systems. The alternative hypothesis indicates coding productivity using ICD-10-CM/PCS will be significantly lower than coding productivity using the ICD-9-CM classification system.
Impacts on Coding Productivity
The study took into consideration several factors that would impact productivity in today’s ICD-9-CM environment. Such factors included:
Complexity of cases
Health record format – paper, hybrid and EMR
Coder familiarity with record format
Individual reading speed
Coding methodology – book, logic based encoder and book based encoder
System access issues such as downtime
Study Methodology
The study was designed to simulate the current coding reality by using 2 record sets of equivalent types of cases. One record set coded in ICD-9-CM and the other record set coded in ICD-10-CM/PCS. The coders used the 3M encoder for all cases.
Sample Selection
Records selected from University Hospital Inpatient acute care cases reflected the most common inpatient cases. Records were analyzed to verify all documentation was complete with a representative sample of Medical and Surgical cases. The sample reflected the most common inpatient cases and all information was in the hospital EHR. The sample resulted in two groups of equivalent cases.
Coding Quality Scoring
Study participants compared to experts were given a quality score for each record coded with ICD-10-CM/PCS.
Description
Quality Score
Complete match for Principal Diagnosis 5 One digit behind the decimal point is different 4 Two digits behind the decimal point are different 3 The three digits before the decimal point match 2 The code begins with the same alpha character 1
No part of the code matches 0
Study Participants
All study participants were experts in ICD-9-CM coding, with varying levels of ICD-10-CM/PCS coding expertise including Basic, Advanced (AHIMA-Approved ICD-10 Trainers), and Expert (AHIMA ICD-10 Academy Faculty). Study participants also varied in terms of education level and professional credentials.
UASI – United Audit Systems, Inc.
The Results
Overall Productivity
Overall productivity with ICD-9-CM compared to productivity with ICD-10-CM/PCS:
•ICD-9-CM Avg. Coding Time – 25.51 minutes. •ICD-10-CM/PCS Avg. Coding Time – 43.23 minutes.
•Overall, on average it took, 17.72 minutes (or 69%) longer to code a record in ICD-10-CM/PCS.
Coder Differences
•The six coders included increased coding time anywhere from an additional 10.6 minutes (31.6%) to 27.78 minutes (89.8%) on average. •Three coders who had earned AHIMA ICD-10 trainer certification increased coding time by an additional 14.7 minutes (54.4%) per case on average.
•Two who received basic training needed an additional 17.0 minutes (81.8%) on average.
Quality
Overall quality score in comparison to Gold Standard – 3.37 across all coders.
As the time spent per record increases, the coding quality decreases.
Study Implications
It appears that previous estimates of initial coder productivity loss may have been understated. Prior to the implementation delay from October 1, 2013 to October 1, 2014, estimates projected around 50% loss in productivity.
Expect significant return on investment from training.
There is no “perfect” ICD-10-CM coder. Experience and/or education did not appear to have an impact. A coder’s current speed in ICD-9-CM is not necessarily a predictor of his/her speed with ICD-10-CM/PCS. More time spent on a record does not translate to higher quality.
UASI – United Audit Systems, Inc.
About the Company
UASI is a leading national provider of revenue cycle solutions designed to help
healthcare facilities achieve correct reimbursement in the quickest possible time.
Our services include: Remote Coding, Onsite Coding, Clinical Documentation
Support, Coding Compliance Audits, ICD-10 Support Services, Revenue Integrity
Audits, and Health Information Interim Management solutions. Based in
Cincinnati, Ohio with service nationally, UASI is unique in its ability to fuse
technology and professional services to deliver superior financial performance.
UASI – United Audit Systems, Inc.
UASI ICD-10 Support Services
Documentation Gap Analysis
Through an intensive medical record review, UASI provides an action plan to identify and correct documentation gaps and/or provide specific areas of focus for your Clinical Documentation Improvement (CDI) program.
Reimbursement Impact Analysis
To minimize financial impact, UASI coding professionals evaluate potential shifts and changes in the case mix index by comparing MS-DRG assignments based on 9-CM codes to those based on ICD-10-CM/PCS codes in a representative sampling of inpatient cases. Results are analyzed to identify variances and provide well-supported financial projections for transitioning to ICD-10-CM/PCS.
Targeted Training on Documentation Gaps
Customized Training to Address Identified Documentation Gaps for Clinicians, Clinical Documentation Specialists and Health Information Management Professionals.
Targeted Application-based ICD-10 Training Support
Complete CM/PCS coder training onsite or remote including practice coding in ICD-10-CM/PCS for Medical Coding Professionals.
UASI – United Audit Systems, Inc.
Experienced Coders available for supplemental coding. With proven experience in high volume, high quality coding, UASI is uniquely positioned to provide workforce solutions tailored to your organization – ranging on-site and remote coding staff augmentation to complete coding outsourcing.
ICD-10 Coding Accuracy Reviews
Action Plans for Improved Medical Coder Accuracy Rates.
