Risk of False Demand

When organizations consider risk it is usually centric to mitigating sentinel events or Black Swans (Special Cause) and not usually focused on what is called common cause variation.  By definition these special cause events have a low probability to predict because it is a random from an unusual occurrence and is unstable and unpredictable.  Common cause or process variation is stable and predictable as it is part of the system which means we can identify and reduce variation which reduces risk.

By reducing variability translates to making processes more certain and predictable than if the process were to be left alone.  Organizations are accustomed to “bad processes’ that do not perform as desired and these processes can be improved to reduce patient and organizational risks by addressing variation. There will always be some variation present in all processes called common cause and is seen in the form of:

• Nature – Shape/size of leaves, snowflakes, etc
• Human – Skill, competency, speed of walk, etc.
• Mechanical – Weight/size/shape of product, etc.

Following this notion we can tolerate certain amounts of variation if:

• The process is on target
• The variation is small compared to the process specifications
• The process is stable over time, ie.. Variation is within our risk tolerance

When we talk about not meeting objectives as a risk, we need to consider daily process failures which have a significant impact on the organization and these failures create false or artificial demand. False demand is when there is no legitimate need for action but an action is taken creates a demand that does not exist.  An example would be prescribing a medication when it is not really necessary, do an unwarranted test, just in case or when a task is done incorrectly that requires rework.  The medication does not add to the patients’ wellbeing the test was addressing the “just in case situation” and rework is paying to have the same task done more than once.

This type of demand takes away capacity from the organization by wasting resources. It is an operational costs that has direct bottom line impact.

• No value is gained from the action to the patient or organization
• The organization is paying to do a singular task twice
• Rework by consuming resources a second time reduces productivity
  1. Capacity is reduced
  2. Cost increases
  3. Revenue is lost

If we consider a non-clinical task such as filing medical claims within the revenue cycle, McKesson did a study and found that 1 in 5 claims had some issue that required intervention, (McKesson 2016) and according to the American Medical Association (AMA), this process is “far from efficient and quite error-prone”.

For arguments sake let us consider a claim denial rate of 12%.  The 12% of claims will not be paid unless something is corrected which is rework (not done right the first time). This double effort reduces productivity, slows the processing time on average for each claim, and results in higher accounts receivable potentially crippling cash flow which has an opportunity cost.  Industry goal is a 95% accuracy rate for claim processing which is 1 of 20 claims that will have some level of rework (D’Amato 2008) (Physicians 2013).

In discussion with claims managers it is not uncommon to hear people state that the process is “the best we can do”, or that the process is “too complicated to expect better results”.  There is usually a caveat associated with the statement: If we just had more people or if the software allowed for greater automation of the process we could do better.  Adding people is not an option nor should it be to offset poor performance and automating a bad processes is neither a good option.

The pain is not limited to non-clinical staff. Follow up research to correct the claim may require the physician and or nursing staff to stop what they are doing to provide needed information.  This is effectively a stoppage of productive work moving from value added to non-value-added by taking professionals away from their core activities.   If clinical staff are not productive, they cannot perform medical services. “How come there is no time to do it right but we always seem to have time to do it over?” Do it once and do it right the first time. (Manley 2009)

Fixing a claim can take seconds to hours to research and correct.  Assuming an average of 15 minutes per claim to correct a single issue with 100 claims a day there with a 1 in 5 claim issue, 20 claims will require some level of rework.  The effort to correct 20 claims will cost 5 hours, multiplied daily for a year is 1300 hours and depending on the salary we start looking at real money in FTE’s or over time.  Then there is a delay in resubmission and at the payer side to re-review the claim which also is a cost to the payer.  The table below provides the cost associated with various types of providers.

(Pelaia 2013)

As such, false demand has a direct correlation to financial outcomes which influences capacity and financial stability.  Therefore, the risk for accepting the status quo has significant impact to the bottom line. Given the small margins that healthcare providers operate within, one would think that serious focus would be paid to improving processes. It is true that many organizations use Lean principles, but it is equally true that the majority of organizations do not make this a priority.   The cost to identify and reduce variation in processes costs far less and reduces risk than increasing capacity by adding FTE’s, but unfortunately this is the “norm”.  Small incremental improvements to reduce false demand will pay off large dividends.

References

D’Amato, C. (2008) Benchmarking coding quality. American Health Information Management Associatio
Manley, R. (2009). “Revenue cycle management.” Journal of Vascular Surgery 50(5): 1232–1238.
McKesson (2016) RelayHealth Financial Reports Claim Denial Trends.
Pelaia, H. (2013) Hospital  Denials  Management…  In-source,  Outsource  or Both.
Physicians, A. A. o. F. (2013) Evaluating Your Practice’s Revenue Cycle: Denial Rate

Bio:

Steven C. Bradt has 20+ years’ experience working with risk and continuous improvement efforts (Lean, Six Sigma, Leadership, Change, TQM) receiving his primary Continuous Improvement education from Johnson Controls (JCI) Toyota Business Unit (TBU) and Toyota US, UK and Australia and his Six Sigma education from the Six Sigma Academy (Mikel Harry).  Steven has supported and worked internationally for Retail. Software, three governments, Office of the Secretary of the Airforce (Chief Management Office), and numerous healthcare organizations in developing sustainable CPI and risk strategy.  Steven is currently pursuing his Master of Health Administration Milken Institute School of Public Health at The George Washington University and he was an Honorary Fellow at Manchester Business School.