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Survey: Coding Productivity Dipped After ICD-10 Implementation

Survey: Coding Productivity Dipped After ICD-10 Implementation

Article by Mary Butler. This article was originally published on the Journal of AHIMA website on June 13, 2016 and is republished here with permission.

The implementation of ICD-10 did result in a perceived loss of coding productivity, with a minimal dip in coding accuracy, according to a recent coding productivity and accuracy survey. The survey was conducted by the AHIMA Foundation in the first three weeks of May, and was released today, June 13.

Investigators from the Foundation sought to determine whether the implementation of ICD-10 increased, decreased, or had no change on the productivity and accuracy of coding professionals. The survey contained 13 questions pertaining to respondent demographics (level of education, years of experience in the field), type of facility at which the respondent is currently employed, and the perceived impact of the ICD-10 implementation on coding productivity and accuracy. In total, investigators sampled 438 coding professionals and received responses from 156 individuals.

According to the survey results, overall, respondents noted they experienced a 14.15 percent decrease in productivity, yet only a 0.65 percent decrease in accuracy. Of those who responded, 67.9 percent noted a decrease in productivity, 5.8 percent noted an increase in productivity, and 26.3 percent noted no change in productivity. In terms of accuracy, only 26.9 percent saw a decrease in accuracy, 11.5 percent an increase in accuracy, and 61.5 percent no change in accuracy.

“Health information management (HIM) professionals are already coding with the same degree of accuracy as in ICD-9,” said AHIMA CEO Lynne Thomas Gordon, MBA, RHIA, CAE, FACHE, FAHIMA. “Of course with any change there will be an initial period of productivity decline, but we fully expect this decrease will be short-term in nature. In fact, respondents indicated in the survey that they have become more comfortable with the new code set with each day and productivity decreases continue to lessen.”

A Closer Look at Productivity Rates

Members of the Foundation who worked on the survey told the Journal that the decrease in coding productivity was in line with what they were expecting to see.

“We anticipated seeing a dip, but were glad to hear from folks that while they did have an initial large dip it is now settling back to pre-ICD-10 levels, though slowly,” said Kate Jackson, RHIA, the Foundation’s research manager.

One interesting finding in the survey is how the level of coding experience impacted productivity. According to the results, those with one to five years of experience encountered the lowest levels of decreased productivity, while those with between 6 and 10 years of experience had the highest levels of decrease (19.97 percent and 27.14 percent, respectively).

Somewhat surprisingly, the level of education of coding professionals appeared to have little impact on coding productivity. According to the results, those with bachelor degrees had the lowest level of reported decreased accuracy, while those holding graduate degrees had the highest level of decreased accuracy (7.62 percent and 25.6 percent respectively).

Accuracy Rate Breakdown

For the most part, the implementation of ICD-10 had a very limited impact on coding accuracy, starting with the fact that only 26 percent of respondents noted a decrease in accuracy and 11 percent saw accuracy increase.

But investigators were quick to note that findings concerning the use of computer-assisted coding (CAC) programs had surprising results for productivity and accuracy. According to the survey, those who coded with a CAC experienced a 17.1 percent decrease in productivity overall, while those who did not experienced on average an 11.92 percent decrease in productivity overall. What’s more, those who use a CAC to code experienced a 0.2 percent increase in accuracy and those who did not noted a 1.58 percent decrease in overall accuracy. The report authors point out that this seems counterintuitive.

“To better understand why this difference occurred, we examined the difference in productivity and accuracy for inpatient and outpatient coding. When we break down the analysis, we see that initial discrepancies seem to be based on the fact that a higher percentage of CAC use occurs in inpatient settings that have higher levels in decreased productivity with CACs. When controlling for setting (in-patient/outpatient), differences do not exist in rates in the use of CAC when coding records,” they note.

Investigators suggest a need for further research to:

  1. Find out whether or not levels of productivity will revert to pre-ICD-10 levels
  2. Investigate whether productivity and accuracy levels will increase as the use of CACs become more ingrained into the coder workflow
  3. Provide more clarity in defining accuracy

Click here to register to download a copy of the full report.

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