October 14, 2013

Dual Coding: Tracking Your Output

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Roseanne Barr once said that she likes facts and data because they help her think clearly. With dual coding, it is easy to rationalize the reasons and justify the means. But what really matters is the output. Dual-coding efforts must produce useful information to prepare your organizations for ICD-10.

 

Measuring, monitoring, and tracking dual-coding data ensures that investments in time, money, and staff produce a solid return. Business intelligence gleaned from dual-coding data helps accurately measure ICD-10’s productivity, quality, and financial impacts. With dual coding already underway, now is the time to build your arsenal of ICD-10 data.

Measuring Productivity

To measure coder productivity in ICD-10 accurately, the coding of cases must be spread out over time (as discussed in my September ICD-10monitor article on cost-justifying your dual-coding program). This step compensates for chart “read time” and minimizes the impact of a coder remembering a case only during your final data output.

Dual-coding productivity data supports more accurate staffing and/or outsourcing decisions for ICD-10. With it, organizations are able to determine whether additional resources will be necessary to maintain productivity standards once ICD-10 goes live.

Your arsenal of dual-coding data should include criteria including: 

  • MRUN
  • Discharge date
  • Attending physician
  • Coding date
  • Coder name
  • Time started, stopped, minutes used, and MS-DRG assignment for both ICD-9 and ICD-10
  • Minutes difference between ICD-9 and ICD-10
  • Total minutes spent per case for dual coding
  • MS-DRG change

Armed with the above data, productivity information can be assessed and analyzed easily. Here is a sample productivity report from one of our clients:

ICD-9 Coding Time and Productivity

 

-          Total Minutes to Code

360.00

-          Average Minutes/Case

18.00

-          Longest Case Review (minutes)

45.00

-          Shortest Case Review (minutes)

5.00

ICD-10 Coding Time and Productivity

 

-          Total Minutes to Code

672.00

-          Average Minutes/Case

33.60

-          Longest Case Review (minutes)

75.00

-          Shortest Case Review (minutes)

6.00

DRG Analysis

 

Total Changes from ICD-9 to ICD-10 MS-DRGs

5

Based on these findings, the HIM director can clearly see how many more minutes will be required per case, day, week, month, and year, allowing him or her to make more informed staffing and outsourcing decisions.

Measuring Quality

To assess coding accuracy, quality reviews should be conducted by a coding manager or outside firm. It is a best practice to conduct quality audits for both ICD-9 and ICD-10 coding results, reviewing all cases included in the dual-coding study and recording accuracy percentages as part of the overall data tracking.

Address any ICD-10 coding errors as quickly as possible. Share findings with each individual coder during coder roundtables. ICD-10 presents a steep learning curve for everyone. It is important for coders to learn from each other as they go. Fix quality errors through focused retraining, and include any issues or areas of concern in your ICD-10 data arsenal.

We expect that all facilities will experience increases in claim denials during the first six months of ICD-10. An organization’s ability to correct codes, resubmit claims, and mitigate future risk of denials for each diagnosis, procedure, MS-DRG, or type of case is a key determining factor of your success. Knowing areas of coding quality concern and potential coding errors ahead of time offers key intelligence for a smoother ICD-10 journey.

Data entered and insights gleaned through your coding audits also must be captured, reported and tracked. Elements should include:

  • Coder and codes assigned
  • Reviewer explanations and source documentation
  • DRG changes and reviewer rationale
  • Accuracy rate/percentage by coder
  • Trends in missing codes and patterns of overcoding or undercoding

Measuring Documentation

Clinical documentation analysis is another area for inclusion within your dual-coding data reports and tracking. Combine clinical documentation reviews for ICD-10 with dual-coding quality reviews to identify documentation gaps and areas of opportunity in terms of focused physician education in coming months. Integrate coding and CDI for maximum effectiveness, and then train together on known DRGs, diagnoses, procedures, and service lines presenting ICD-10 concern.

Tracking Tools

Finally, tools used for tracking dual-coding output also should double as reporting tools for executive teams and ICD-10 committees. Tools that feature some type of automation such as formulas and sorting are recommended. For most hospitals, Microsoft’s Excel application or some other user-friendly database application suffices. However, if you are tracking dual-coding output across multiple facilities and hundreds of coders, a more advanced database may be required.

The Right Data Means Everything

Gathering the right data during dual coding of medical records yields customized productivity, quality, and documentation intelligence. Organizations that choose to closely track and analyze dual-coding outcomes mitigate financial and operational ICD-10 risk.

Disclaimer: Every reasonable effort was made to ensure the accuracy of this information at the time it was published. However, due to the nature of industry changes over time we cannot guarantee its validity after the year it was published.
Kim Carr, RHIT, CCS, CDIP, CCDS, AHIMA-Approved ICD-10-CM/PCS Trainer

Kim Carr brings more than 30 years of health information and clinical documentation improvement management experience and expertise to her role as Director of Clinical Documentation, where she provides oversight for auditing and documentation improvement for HRS clients. Prior to joining HRS, Kim worked as a consultant implementing CDI programs in varied environments such as level-one trauma centers, small community hospitals and all levels in between.

Before joining the consultant arena, Kim served as Manager of CDI in an academic level-one trauma center. She was responsible for education and training for physicians and clinical documentation specialists. Over the past 30 years, Kim has held several HIM positions; including HIM Coding Educator, Quality Assurance/Utilization Management Coordinator, DRG Coding Coordinator and Coding Manager. Kim holds a degree in Health Information Management and is a member of AHIMA, THIMA, ACDIS and AAPC.