David Franklin
Coy Ingram
Steve Levin

By scoring self-pay accounts and prioritizing or segmenting them using expected cash value and payment behavior, hospital business staff can more effectively work these accounts-and yield higher collections.


At a Glance

Successful scoring approaches for self-pay accounts have three common characteristics:
 

  • Thoughtful selection of a scoring model and segmentation approach  
  • Deployment of workflows (either segmented or account prioritization) consistent with a hospital's capabilities and the likelihood of collection
  • Ongoing performance monitoring  

How can providers increase cash flow by up to 30 percent while lowering collection costs-without adding more manpower? Some business offices that have used analytic scores to segment accounts for follow-up are realizing such improvements while relying on existing service teams and IT infrastructure.

Scoring and segmentation may be one of the best solutions to the seemingly contradictory objectives in today's revenue cycle: delivering a high-quality patient experience while collecting more cash more quickly, and at a lower cost.

For teams that are new to scoring, cash value prioritization is proving to be a solid first approach. Under this approach, extra collection activity is focused on the minority of accounts expected to yield the majority of cash. Hospitals with more scoring experience or confidence find that implementing segmented workflows offers a further step up in performance. Segmentation involves assigning accounts to specific collection processes based on the approach that is likely to optimize net cash recovery (cash less the cost to collect). Collection processes may differ in regard to the number and timing of letters sent to customers and the frequency and intensity of calling programs, among other techniques.

The ROI of Self-Pay Segmentation

Because of today's tight budgets, hospital business office teams are focused on the ROI of their efforts. But business offices that are not leveraging scoring technology to govern self-pay collection are accepting dismal ROIs. Simply stated, working every account the same way is a bad investment.

In a typical self-pay portfolio, the lowest-scoring third of all self-pay accounts will generate less than $6.50 per account (see Exhibit 1). Efforts to contact these customers by phone are likely to cost more than the provider will ever recover. Among larger balance accounts, 75 percent will cost providers more than $2 in postage for billing statements, yet will return no cash, according to Connance research. Adding an outbound phone call to collection efforts only increases the negative ROI.

View Exhibit 1  

cf_franklin_exh1

Using analytic scores to help determine the right approach for account collection efforts can remove much of the uncertainty in collections-retaining cash while reducing costs for providers.

Start with Cash Value Prioritization

Prioritizing efforts based on cash value of the accounts will direct discretionary collection efforts towards the two-thirds of accounts that will generate more than 98 percent of the cash. It makes sense to "fish where the fish are."

The concept of cash value is to use expected collection as the variable around which to organize collection activity. Expected collection is not the same as balance due. Expected cash value is the actual amount an organization can expect to collect, whereas balance due is the most an organization can collect. Expected cash value is also not the same as propensity to pay, which simply predicts the likelihood of some payment, but does not tell you how much.

Many organizations prioritize collection efforts according to balance, focusing more energy on larger balances and vice versa. Often, this is an attempt to proxy cash value-assuming that larger balances have more cash value. The issue is that the majority of large balance holders will pay nothing. Thus, much of the extra collection effort that is being invested in those accounts will not yield any cash. One can buy a lottery ticket hoping for the big payday, but as we all know, most often the money used to purchase the ticket yields nothing.

For organizations that lack a dialer and other advanced collection infrastructure, the cash prioritization approach could be a good fit. Deployment could be as simple as producing a daily call list sorted according to the relative expected cash value of the accounts. Customer service teams would start by making outbound calls to the accounts with the highest expected cash value first. Each day, the list of untouched accounts could be reprioritized for representatives to continue their efforts.

In a representative deployment, one hospital business office increased cash recoveries by more than 40 percent after implementing a cash value prioritization approach. Previously, business office staff tried to call every account with a balance due of more than $500. Using cash prioritization, the same team was able to avoid investing effort on large balance accounts with very little true cash value. The capacity created by eliminating efforts on low-yielding large accounts allowed the team to connect with higher-value accounts in the $200 to $500 balance band. Focusing effort on the highest expected value accounts materially improved the hospital's resource utilization and results.

View Exhibit 2  

cf_franklin_exh2

Segmentation: A More Advanced Approach

For those organizations interested in further improving net cash, a proven next step uses predictive models to assign accounts to segmented work routines. Each work routine offers a collection approach designed to help resolve a specific type of account and optimize net cash to the hospital (cash collected less costs incurred in collection).

Much of a hospital's collection activity is actually a discretionary investment of time and money. To increase ROI, an incremental investment should occur only when it is expected to yield a meaningful increase in cash recovered. For example, if a business office could know which self-pay accounts were likely to pay their bill simply through the standard letter program, these accounts would not be put on a call list. That incremental collection investment would likely have little impact on cash and could risk annoying the customer. By comparison, there are other accounts that can be predicted to require customer service help to work through payment options or to explain the balance due situation. These accounts should be engaged earlier in the process with customer service representatives. This investment would have a positive ROI.

The theory of segmentation is commonplace outside of health care. Direct marketers send different catalogs, offers for discounts, and even different messages to households according to specific variables that help to predict the success of a marketing tool with particular consumers. It is profitable, and increasingly necessary, to deploy similar thinking in determining a hospital's approach to the collection of self-pay accounts.

In building a segmentation approach, design it with ROI in mind. Recognize that just because two accounts have the same cash value does not mean they should experience the same collection process. Cash value is only one variable. Other variables include some measure of payment behavior and the amount of help patients will need to resolve their obligations.

Better segmentation approaches seem to build from three basic delineations.

Accounts that are expected to generate virtually no cash. These accounts should be given the minimum collection effort allowed by the hospital's policies. Often these accounts become the priority for financial counseling and eligibility efforts.

Accounts that are expected to pay without much effort. Think of this group as "do it yourselfers." For this customer segment, a basic statement series will resolve most accounts. For those few accounts in this group that linger unpaid, a soft, outbound phone reminder might be appropriate late in the process.

Accounts likely needing some support to pay. These accounts require customer service help either to enable the account holders to understand their responsibility or to develop a payment program. Regardless, these are the patients that a business office should connect with as early as possible.

Additional splitting of these segments has been proven to yield substantial gains. By capitalizing on more nuanced differences regarding expected cash at risk or payment behaviors, it is possible to target discretionary resources more effectively. In our experience, an operation can deliver a very effective patient-centric collection experience that is cost-effective to operate using five segments.

Regardless of how many segments are used, each must have a collection process that meets that specific group's need. When implementing a segmentation scheme, it is important to incorporate decisions regarding:

  • The number and timing of letters
  • The message on each letter or statement
  • The use, frequency, intensity, and communications of broadcast messaging
  • The use, frequency, and intensity of outbound calling (usually with a predictive dialer)
  • Whether to use a dedicated desk of reps to resolve higher-value accounts that require extra support through the process or some other specific segment of accounts

These choices should be consistent with the organization's understanding of the segments and its objectives for their resolution (e.g., minimizing investment versus optimizing cash). By putting customers through different collection processes based on how their accounts are expected to perform, it is possible for a business office to provide customers with a more positive collection experience.

Using segmented workflows has been shown to improve cash yields by 20 to 30 percent over strategies that involve treating all customers the same. Moreover, the approach can help reduce costs. Letter expenses can be cut because this approach can better manage letter investment by segment. Customer service efforts can also be more effectively managed as many accounts are removed from early and frequent calling campaigns.

Measuring Success-and Driving ROI

It is tempting to measure success simply by tracking increases in cash recoveries. Although tracking cash is appropriate, it is also beneficial to ask two process questions. Are accounts assigned to the right follow-up segment? This question is explicitly a test of the predictive models and segmentation logic. An organization should see different liquidation performance from the different groups. It is also appropriate to compare underlying dynamics such as event rates (percentage of accounts that make some payment) and liquidation rates (percentage an account pays if they make a payment). If segments do not look different, then either the models aren't useful, or the business office may have averaged away the differentiation using too few segments.

Are the business office's efforts for each segment appropriate? The goal here is to check the efficacy of letters, messages, and timing. For example, after a letter mailing, check to make sure the expected follow-up response from patients has been received. If the expected response is missing, the message has probably not been heard. No process is perfect. Over time, and with more experience, new workflow ideas should be tested.

By exploring these two questions, business office teams can continuously improve their performance. Given changes in the market and consumer sentiment, there are always opportunities to reduce unproductive spending and better invest an organization's scarcest resource: staff time.

Making the Most of Self-Pay Collection Efforts

The continuing increase in self-pay collections for hospitals, which are growing at a rate of more than 10 percent annually, make it clear that a smarter approach to self-pay collections is needed. For many hospitals, account segmentation or cash value prioritization could be the answer.

In successful deployments, there are three critical elements to improving performance and driving self-pay ROI.

Choose the right approach for your organization, whether segmentation or cash value prioritization. Both approaches can deliver meaningful cash improvement. Determining which option to choose will depend on an organization's experience and capabilities.

Develop appropriate workflows. Give each group of accounts an experience that helps those customers resolve their bills. Develop target messages and experiences consistent with their needs.

Track performance. Consider both the outcome measures (e.g., collections per account) as well as the process elements, such as efficacy of the segmentation logic and work routines.

Following these three elements not only helps an organization's staff and enhances "collection ROI," but also helps patients by more thoughtfully addressing their ability to pay and by communicating with them more effectively about financial responsibility.


David Franklin is cofounder and chief development officer, Connance, Waltham, Mass., and a member of HFMA's Massachusetts-Rhode Island Chapter (dfranklin@connance.com).

Coy Ingram is director of self-pay management, patient financial services, Florida Hospital, Maitland, Fla., and a member of HFMA's Florida Chapter (coy.ingram@flhosp.org).

Steve Levin is cofounder and CEO, Connance, Waltham, Mass., and a member of HFMA's Massachusetts-Rhode Island Chapter (slevin@connance.com).


Sidebar 1: Common Scoring Terms

Expected cash value. The expected amount one will collect from a receivable. The value can range between the balance due and zero. Expected cash value models often deliver an index value, where smaller numbers are less valuable than larger ones.

Probability or propensity to pay. The probability that a receivable will pay something. Some models may set a minimum threshold (e.g., likelihood the guarantor will pay more than $50). Often, models of this type are defined in ranges, such as low-, medium-, and high-risk groups. Generally, smaller balances will have higher probabilities, and larger balances, lower ones.

Credit score. The delinquency risk associated with originating a new voluntary purchase (e.g., buying a car or television). These scores indicate the likelihood that the debtor will pay the amount in question as opposed to going into default. Standard credit scores tend to be an imperfect proxy for medical debt given the involuntary nature of this type of debt as well as the tendency of consumers to pay medical obligations differently than other forms of consumer credit. A material portion of healthcare account holders that do make payments do not have credit scores.

Sidebar 2: Two Flawed Arguments Against Scoring and Segmentation

"There is still money in the tail." The logic behind this argument is that, even though the cash collected from low-value accounts is small, with thousands of accounts involved, it can add up to thousands of dollars. The flaw is that most business offices have scarce resources. By investing resources in low-value accounts, business offices will forgo the opportunity to invest extra effort in their highest-value opportunities. Experience has shown that touching the higher expected cash value accounts tends to generate additional cash sooner.

"We need to treat everyone the same." The reality is that most policies and expectations establish minimum actions for accounts, but not maximums. The purpose of segmentation is to identify where and when to exert more than the minimum attention. Further, regulations simply require that similar efforts be made on Medicare and non-Medicare accounts. Proper segmentation and associated work efforts should not differentiate between Medicare and non-Medicare accounts.

Sidebar 3: Testing a New Scoring Solution: Florida Hospital's Champion Challenger Experience

The central business office for Florida Hospital, an eight-campus system based in Orlando, had been using a scoring system to segment uninsured and balance-after-insurance accounts follow-up. The solution had improved cash flow for the hospital, but with a rise in patient responsibility for account balances, the hospital's leadership team decided to investigate whether its approach could be improved upon.

The legacy segmentation approach undertaken by Florida Hospital used a consumer credit score to stratify accounts at bill drop into three categories: high risk to collect, medium risk to collect, and low risk to collect. Follow-up processes for these three groups differed primarily in the intensity of outbound calling.

Florida Hospital's challenger approach scored and segmented accounts using models that predicted expected cash value and repayment behavior. The scores were not generated using individual credit file information. Based on a combination of an account's expected collection amount and payment rate (as a measure of uncertainty and payment behavior), Florida Hospital's challenger process assigned each account to one of five follow-up segments. Efforts for collections varied for each segment, so that the right kind of attention would go to each account (more proactive efforts where they could deliver more cash, less where these efforts were unnecessary).

To compare the two approaches, the business office team used an alpha split to assign new accounts to either the challenger or established process. For accounts sent through the challenger process, Florida Hospital's business office also pulled a credit score so that it could track the differences between the scoring and segmentation approaches. Performance of the two groups was monitored over several months.

Overall, the cash value approach significantly outperformed the established credit-based segmentation scheme. Monthly cash collections hit record highs during the test, with the business office staff collecting almost 15 percent more cash using the new approach within only a few months.

Part of the success of the new processes used by Florida Hospital was the impact on collections from the hospital's "unscoreable" customers-the 17 percent of its customers for whom no credit score was available. Eighty percent of these "unscoreable" accounts belonged to insured patients with balance after insurance responsibility. The hospital's historical approach designated no-credit-score customers as being high-risk accounts, and assigned these customers to the hospital's high-risk process for collections. The new system was able to score these accounts and assign them to the segment consistent with their expected payment behavior. A review of the results showed that more than 30 percent of the accounts without credit scores were actually highly likely to pay.

Florida Hospital's business office team also studied the differences in performance and work flows related to each segment. In doing so, the hospital identified several opportunities to tweak the new process, sending out some correspondence earlier and changing calling frequency. These enhancements are expected to further reduce operating costs and accelerate cash collection.

Publication Date: Wednesday, September 01, 2010

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