AHIMA Releases ICD-10 Coding Productivity White Paper

A new white paper from AHIMA examines ICD-10-CM/PCS coding productivity from three different perspectives:

  • Where it’s been
  • Where it stands now
  • How it’s expected to evolve in the near and distant future

As the whitepaper, titled “Measuring and Benchmarking Coding Productivity: A Decade of AHIMA Leadership,” notes, AHIMA launched a benchmarking process to assess coding professional productivity well before the transition’s go-live date in order to enable development of best practices, ensure a smooth transition, and establish a framework for assessing productivity at pre-determined points once the transition from ICD-9 to ICD-10 occurred.

The white paper outlines AHIMA’s review of how coding has evolved, beginning with ICD-9-CM, then moving to the transition to ICD-10 and looking ahead to what the healthcare industry can expect next in coding and documentation.

“By leading the transition from ICD-9 to ICD-10, AHIMA and our members saw the growing demand for high-quality data to support patient safety and reduce healthcare costs and continue to develop best practices to meet the demand,” said AHIMA CEO Wylecia Wiggs Harris, PhD, CAE. “Benchmarking where we’ve been against where we are now allows us to look at how coding affects the various sectors of the healthcare industry, and ultimately lets us pave the way for the future of coding productivity.”

Best Practices for Measuring Productivity

According to the white paper’s authors, a set of best practices can be used—regardless of the care setting or version of the ICD in use—to give the best chance of achieving optimal coding productivity. AHIMA established these attributes when evaluating productivity in ICD-9 to create a benchmark for ICD-10. They include:

  • High-quality, consistently available, high-speed, and secure network access to needed data sources and repositories
  • A quiet work environment with limited distractions and interruptions
  • Ease of access to data, as well as the availability of that data in a single source (i.e., the EHR) versus data that must be accessed from multiple sources
  • Data presented in a narrative structure versus documentation segregated by clinician or data type
  • Timely transcription of, completion of, and access to necessary documentation, written orders, results, and reports
  • Limited keystrokes
  • Online/mobile access to relevant and timely coding materials; edit guidance; and access to an encoder coupled with reference material
  • Access to at least quarterly coding-oriented professional development

These best practices provided a guidepost for setting coding productivity benchmarks in 2007, prior to the ICD-10 transition. The established benchmark practices came into play again three years after the implementation of ICD-10 when they were used to conduct coding productivity studies post-transition. Results from those studies included:

  • An ICD-10 study examining average inpatient coding times from more than 150,000 medical records in a five-month period beginning in October 2015, showing an initial dip in coding productivity immediately following the transition and increasing gradually in the weeks following.
  • A study evaluating more than 165,000 patient records beginning in March 2016 that noted an increase in coding productivity over a five-month span.
  • A survey to gather insights via phone from 156 HIM professionals, finding that approximately 74 percent indicated a change in productivity, 31 percent of which indicated an increase.

AHIMA has provided multiple ICD-10 coding standard examples for the industry based upon these results, and is now looking to evaluate coding’s next phase.

“With ICD-11 on the horizon, AHIMA is prepared to lead the way through ongoing research related to current and future versions of ICD and how they can help improve coding productivity, accuracy and quality,” Harris said. “In this way, accurately benchmarking coding productivity helps contribute to the long-term sustainability of the greater healthcare landscape.”

Click here to read the white paper in AHIMA’s HIM Body of Knowledge.

Mary Butler is the associate editor at Journal of AHIMA.

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