Eliminating Healthcare Claims Payment and Submission Mistakes
By RONALD HILDEBRANDT, co-founder of Enkata, a San Mateo, Calif.-based provider of products to help service organizations drive operational performance
Insurers and providers are wasting billions of dollars disputing and reconciling healthcare claims submissions. According to recent report by the consulting firm McKinsey & Company, more than $20 billion annually is spent resolving claims pricing and denials equally split between insurers and providers. Worse yet, this $20 billion in administrative costs is just the beginning. Claims pricing disputes also saddle the healthcare industry with poor cash cycles for providers, inaccurate data for insurance pricing and uncertain obligations for members--each adding billions more in avoidable costs.
While some of this waste is due to the complexity and byzantine rules and regulations governing health insurance, a large majority of the errors and costs are simply due to mistakes--mistakes by insurers in paying a claim and mistakes by providers in submitting a claim.
On average, these mistakes total 5 percent to 10 percent of all claims submitted. This error rate is astounding for an industry with trillions of dollars of transactions per year. To be fair, this rate has improved steadily over the last 20 years with advances in automation, but the current error rate is far from acceptable.
For comparison purposes, drug wholesalers have pricing discrepancies just 0.44 percent of the time, according to McKesson. And yet surprisingly, of the 5 percent to 10 percent of mistakenly paid claims, the large majority (between 50 percent to 70 percent) of them are avoidable mistakes. Assuming that 60 percent of mistakes are avoidable, this means that there is an opportunity to save $12 billion per year if claims accuracy could be brought to the 99-plus percent achieved by all other commercial industries.
Below is a listing of the five most common avoidable mistakes that cause healthcare claims adjustments, in order of frequency:
1. Manually priced complex claims errors (insurer mistake)
2. Manually completed claims submission errors (provider mistake)
3. Manual contract setup errors for coordination of benefits (insurer mistake)
4. Manual contract setup errors for in- and out-of-network providers (insurer mistake)
5. Incorrect payment rules for auto-adjudication system (insurer mistake)
As you can see, most of the avoidable mistakes are tied to manual processes, and four of the top five are from insurers.
Fortunately, attaining higher claims accuracy is in everyone's best interest, especially insurers that can reduce claims adjustment costs, penalties, interest and call-center costs from better claims accuracy.
WHY ERRORS PERSIST
Healthcare systems face many challenges that cause pricing and submission errors to persist, all of which are borne of their inherent complexity and multiple administrative layers.
One reason why pricing and submission accuracy has been such a stubborn problem is the complex multiparty contracts. A myriad of insurers, providers, employers and individuals who use healthcare cause billions of permutations of pricing scenarios that needs to be managed and understood. In addition, these contracts do not spell out every fine detail of pricing, leaving room for human error in interpreting the translation of terms to prices.
A second reason is the timing of price determination. Unlike most products that consumers purchase, healthcare procedures are not priced at the point of sale where the validity can be immediately checked by the consumer. Healthcare prices are presented post-sale after a provider submits and a health insurer adjudicates the claim. This lag time removes the demand for pricing simplicity and transparency that keeps other industry pricing errors low.
And errors persist because of the long mistake recovery period. In most consumer transactions, if a pricing mistake occurs that benefits another party, then that party benefits. For example, if a big-box electronics store charged you $50 less for a flat-panel TV, a discount you probably would not even realize happened, you would not expect a bill for $50 three months later.
But this is exactly what happens in health insurance where insurers can recover overpayments to providers months after payment. This recovery option is a disincentive to claims accuracy that does not exist in most industries.
Another potential risk to claims accuracy is the rise of the use of outsource firms to complete manual steps, ranging from claims adjudication to contract loading. While outsourcing has no inherent negative impact on quality, outsourcing can reduce insurers' vigilance towards claims quality.
Essentially, insurers' "cost of poor quality" is lower in an outsourced model where labor arbitrage reduces the cost of the entire claims operation--regardless of quality. This has the risk of stalling efforts to further improve quality and worth keeping an eye on, in light of the below suggestions.
HOW INSURERS CAN ELIMINATE AVOIDABLE PRICING MISTAKES
It would seem that the cards are stacked against attaining high pricing accuracy for claims. Given the above challenges, it is a fair question to ask: Is it really possible for only 1 percent to 2 percent of claims to be mistakenly paid, saving billions?
In my experience, the answer is a clear yes. The key to success is to gain top-down commitment to pricing accuracy, adopt a "zero defect" culture in operations, and relentlessly mine your under and overpayment data to identify and fix points of failure.
Companies should be aware that there is no silver bullet insight that will drive down pricing inaccuracy. It is a process that requires the elimination of 0.1 percent to 0.2 percent of inaccuracy at a time.
Below are five practical steps that have helped companies improve their claims accuracy and reduce claims payment and submission mistakes by 1 percent to 3 percent.
1. Create a permanent claims accuracy group. Best-in-class insurers have claims accuracy groups with three to five analysts dedicated to identifying the root causes of under- and overpayments. This group's charter is to drive down pricing mistakes using data and analytics.
To get the group off the ground, the claims accuracy group needs the following at a minimum: executive sponsorship, top-level accuracy improvement target, the right analytics tools, structured collaboration with the groups that will "own" the mistakes to fix, and monthly and quarterly meeting schedules to report on progress.
2. Measure claims accuracy with an actionable level of detail. Finding pricing mistakes are like finding a needle in a haystack. You need a powerful magnifying glass that exposes granular details of the claims that were adjusted in order to uncover why and how they were paid incorrectly.
Typically today, insurers do not have this magnifying glass. In fact, their reporting systems are no more useful than sunglasses because they only include highly aggregated data. The claims accuracy group needs a powerful analytics product to gain actionable insights into pricing mistakes.
3. Set claims accuracy targets overall and by operational area. The first task that the claims group must do is to benchmark and set claims accuracy targets 12 months out for both the operational areas (claims operations processors, claims operations automated, provider network operations) and the company.
For example, for claims operations automated, if the current adjustment rate is 3 percent, the target might be 2 percent in 12 months. For provider network operations, if the current adjustment rate for a particular hospital is 9 percent, the target might be 6 percent in 12 months.
4. Manage to claims accuracy metrics in claims operations and provider network operations. After targets have been set, the fastest payback from a claims accuracy program is to fix manual mistakes on pricing and coding. These fixes are fast because they require no IT or system changes--just behavioral changes.
This is enabled by providing operational managers with rankings of claims processors and providers by adjustment rate so they can address the outliers. Because processors and the staff that code claims have a high turnover rate, managers need to constantly use performance management to eliminate claims pricing and submission mistakes.
5. Learn from past mistakes and mine claims adjustments and overpayments for root causes. As organizations, we can often learn the most from our past mistakes if we take the time and have the right tools. This is especially true for claims pricing and submission mistakes.
By data mining overpaid and underpaid claims populations, it is possible to pinpoint the tens of systematic mistakes being made due to incorrectly setup contracts, systems and benefits. The complexity of discovering the systemic drivers of adjustments leads most claims groups to select newly available specialized, health-insurance-specific analytics solutions.
A handful of insurers have reduced their manual pricing mistakes and overall adjustments by 25 percent to 45 percent in just 12 months by following these steps.
A CASE STUDY
One such case involved a leading health insurer that had calculated its costs of mispricing claims at more than $50 million per year, including labor costs, penalties, late payment interest and additional contact center expense.
As is the case with many companies that have successfully improved claims accuracy, the vice president of operations directed that this waste be cut by 25 percent within 18 months by improving the adjustment rate of 8 percent to 6 percent. To reach this goal, a claims accuracy group was created with seven analysts. Reduction targets were set for the operational areas such as manually adjudicated claims, auto-paid claims and provider managers.
The company discovered that 40 percent of its adjustments could be tied back to manual pricing errors made by processors. To immediately address these operational pricing mistakes, the company provided personalized claims adjustment dashboards and reporting to the claims processor teams and claims audit teams. Over the course of six months, processor pricing mistakes declined by 30 percent.
For the other 60 percent of adjustments, the claims accuracy group used root-cause analytics to identify and rank about 100 systemic errors. Business cases for more than 20 fixes were funded and rolled out over the next three to six months. Systemic pricing mistakes dropped by 25 percent within one year.
In total, this company reduced pricing mistakes by more than 25 percent and dropped its adjustment rate to 5.5 percent at the end of 12 months. Its target for the next 12 months was 4 percent.
As you can see, the economic benefits and provider relationship benefits of targeting healthcare claims waste can be game-changing for your organization, and eventually for the entire industry.
October 1, 2008
Copyright 2008© LRP Publications