The Productivity Gap: Protecting Your Revenue When ICD-10 Goes Live

Now that the ICD-10 transition is roughly a year away, it is vital for HIM directors, CFOs, CIOs and other healthcare leaders to understand not only how it will affect their organizations, but how to prepare for the transition in a way that minimizes its impact on revenue, operations and more.

If global experience is any indicator, the productivity and financial ramifications could be extensive.

The move toward the "new" code set has been underway for more than two decades; more than 20 countries already have switched to their own uses of ICD-10. In many of these cases, coder productivity levels have plummeted following implementation. Canada, for example, saw a roughly 40 percent decrease in coder productivity at the outset.1 Although the productivity levels in Canada have improved over time, they have never returned to those sustained while using ICD-9, instead stabilizing at a long-term productivity loss of about 20 percent.  

Applying these data domestically, forward-looking HIM leaders are forecasting a 20 to 40 percent decrease in coder productivity when ICD-10 goes live in the U.S. next year. If left unaddressed by proper precautions, this kind of slowdown could easily lead to delayed cash flow or even lost revenue. To prevent these and other financial concerns, organizational leaders must anticipate and plan for coder productivity loss by:

  • Measuring and projecting productivity based on quantified data;
  • Educating and training coders effectively; and
  • Augmenting resources, where necessary, to address both the short- and long-term impacts of the ICD-10 changeover.  

Minimize productivity loss with effective education and training
Before a productivity gap can be projected, coders first must be educated on the new code set. Once they begin using the codes, an accurate baseline can be measured to determine how productivity trends over time. Based on the experiences of other countries, as well as the results of domestic studies, it is clear that sufficient education will be an essential component of a successful ICD-10 implementation.1,2 Most coders, for instance, will require about 50 hours of training in order to successfully use the new code set, according to the American Health Information Management Association.2
 
Several available options for training coders include translation software, double-coding, dual-coding and platform-based education. While each method can play a role in a comprehensive educational program, not all are equally effective.

At its most basic level, translation software automates the mapping of ICD-9 to ICD-10 codes. While it eases the process of identifying codes, a translation tool cannot help coders understand when they may appropriately use various ICD-10 codes — a critical factor in reducing both regulatory compliance and reimbursement risk. For this reason, the use of translation tools alone is not an effective method for educating coders.

Double-coding (coding natively in ICD-9 and again in ICD-10) and dual-coding (using tools that offer simultaneous ICD-9 and ICD-10 code output) may offer benefits like automatic mapping and code assignment. However, even these methods lack a mechanism for providing real-time educational feedback to ensure compliance. In addition, these solutions fail to provide benchmark data that can help organizations gauge coder productivity — and its potential affect on reimbursement.

By contrast, platform-based ICD-10 training programs allow coders to practice ICD-10 on real charts and in their own electronic health record, all while using the codes that are most relevant to the services their organization provides and the patient population it serves. Areas of concern can be identified in real time so that additional training can be provided to individual coders, or groups of coders, as needed.

By providing training in an environment closely customized to mimic the one that will exist when ICD-10 goes live, coders receive a valuable educational foundation. Furthermore, because platform-based solutions allow coding data to be measured and aggregated, organizations obtain a precise snapshot of productivity and accuracy levels that can be tracked over time to determine if productivity is decreasing, increasing or has leveled out.

Measure and project productivity loss
The importance of measuring coder productivity cannot be underestimated. Since coder productivity drives billing, having the ability to forecast short- and long-term gaps and prevent billing backlogs is the only way organizations can proactively protect and secure their cash flow.

Take the example of an organization that employs 10 coders, each of whom drives $1 million in revenue per day. Collectively they generate $10 million per day. However, if their productivity were to drop by 40 percent at ICD-10 implementation, the organization would generate only $6 million per day — creating a daily backlog of $4 million. After only five days, the organization would experience a $20 million billing backlog, dramatically affecting revenue flow. Since most organizations only carry about one month's worth of cash-on-hand,delaying or losing reimbursement impacts the ability to meet ongoing expenses such as payroll and other overhead facility costs.  

Recovering from a billing backlog of any amount can be challenging. Organizations must staff additional resources to not only clear the existing backlog and return to pre-backlog coding levels, but also to sustain productivity levels to prevent future backlogs from accumulating. When backlogs are left unaddressed, they rapidly develop into vicious cycles. The longer it takes organizations to staff those resources, the longer it takes to recoup revenue as the backlog continues to accumulate.

To successfully forecast and address ICD-10 productivity shortcomings, organizations will need to collect and aggregate quantified data from onsite and remote coders as they actually apply ICD-10 to patient charts. Both productivity and accuracy must be measured. Platform-based training programs that gather this data can help organizations to predict how productivity will trend over time, enabling them to forecast productivity levels for the months following ICD-10 implementation and identify both short- and long-term staffing needs to mitigate the gaps.

For organizations engaging other training methods, such as double-coding and translation software, productivity forecasts typically will be based on coders applying ICD-9 codes to patient charts and then automatically or manually translating them into ICD-10. This offers an unreliable view of how coders will actually perform when directly applying the new code set to patient charts. Additionally, when these types of programs are utilized, organizations often must manually measure, track and calculate coding accuracy and productivity loss. This creates an added challenge in instances where coders work remotely.

Boost resources proactively
Using quantified data to forecast coder productivity, organizations can identify required resources and plan to meet those needs early. Whether outsourcing or adding temporary or permanent staff, organizations will need to find ways to address their coding productivity shortfalls. An organization that predicts an initial decrease of 40 percent but a stabilized decrease of 20 percent, for example, might decide to hire additional permanent staff to address the long-term productivity decline and arrange for contracted coders to meet the temporary spike.

HIM directors, CFOs, CIOs and other healthcare leaders must work closely together to determine how to offset the productivity gap. Rather than wait, they should begin taking steps to fulfill those needs as soon as possible. A year away from implementation, coding and training resources already are limited due to existing coder shortages.4 The best resources always go first; organizations that postpone securing the resources needed to address shortfalls might easily be left with suboptimal — and higher priced — options. Too often, settling for second-rate resources or underperforming coders puts an organization at risk for lost revenue due to poorly coded charts, as well as potential regulatory compliance issues. Therefore, the time to act is now.

When ICD-10 implementation occurs on Oct. 1, 2014, all healthcare organizations will have a spike in coding resource requirements. How organizations fare during this time will depend largely on how effectively they prepare for the changeover. The earlier organizations know what their needs are going to be, the earlier they can plan for and secure those resources. By establishing a strategy to address productivity gaps early, HIM directors, CFOs, CIOs and other healthcare leaders will be able to allocate both temporary and permanent resources to reduce the impact of the changeover and protect their organizations’ bottom line.

George Abatjoglou is CEO of IOD, a leading provider of integrated HIM solutions for hospitals, IDNs, healthcare systems and clinics.

1 Johnson, K. (2004). Implementation of ICD-10: Experiences and lessons learned from a Canadian hospital. Journal of AHIMA. Retrieved from http://library.ahima.org/xpedio/groups/public/documents/ahima/bok3_005558.hcsp?dDocName=bok3_005558
2 Barnhouse T, Rudman W. (2013). You Are Here—ICD-10-CM/PCS Status Check: Three Hundred HIM Professionals Report. Journal of AHIMA,84(6),38–40.
3 Zirmed (2013 March 25). Countdown to ICD-10: Prepared for Success? Or, Prepared to Fail? (White paper). Louisville, KY.
4 Meyers, S. (2004, January). Coder shortage goes straight to the bottom line. Hospitals & Health Networks. Retrieved from http://www.hhnmag.com

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