Tag Archives: Andrew Naugle

Five healthcare analytic trends

Naugle-AndrewIt goes without question that the U.S. health insurance industry is in a state of flux. Americans are buying individual products through health insurance marketplaces, new insurance carriers have entered the market, and Medicaid has been expanded in 29 states and the District of Columbia. These market changes, in addition to other reform provisions already introduced and others just starting to take hold have subjected the market to an unprecedented level of change.

It is said that insurers like risk but hate uncertainty. What is for certain today is that the old strategies of accepting good risks and repelling poor risks are no longer a recipe for success. To thrive in this new environment, health insurers must make smart decisions using data to keep ahead of the competition.

Within that context, here are five areas where Milliman clients are using data and analytics in innovative ways to bring some order to the chaos:

1. Provider network optimization. Despite bending the cost curve, one of the great lessons of the health maintenance organization (HMO) era was that consumers value choice. For years, preferred provider organizations (PPOs) competed on network size; employers cared more about network disruption affecting their employees than the cost/volume trade-off. In the face of cost pressures, employers and consumers are now starting to accept that smaller networks may be worth the disruption. To meet this need, plans are deploying sophisticated modeling that combines traditional network access and adequacy measures with reimbursement and quality analytics to develop new “smart” networks.

2. Value-based incentive programs. It’s widely accepted that fee-for-service (FFS) reimbursement rewards volume over value. As a replacement for FFS, many payers are promoting value-based incentive strategies that shift reimbursement from fee schedules to bonus pools that pay additional incentives when quality and/or cost targets are met. Analytics are key to selecting measures, setting thresholds, and assessing provider performance. They also aid providers trying to operate under these new risk arrangements, identifying gaps in care, and benchmarking peer performance.

3. New trend dynamics. While predicting the actual numbers requires the proverbial “crystal ball,” the health insurance industry has a reasonably mature understanding of the drivers of healthcare cost trend. But things are getting more complicated as physician practice patterns change, populations age but live longer, millions of new consumers flood into the individual and Medicaid markets, and burgeoning innovation (e.g., telemedicine/telehealth, wearables, smartphones, home visits, retail clinics, etc.) disrupts how and where care is provided. Analytics are key to understanding the “trends in trend” in this new world.

4. Transparency. The healthcare market has earned a reputation for opaqueness. Consumers are more likely to rely on word-of-mouth when selecting a physician, the price of services depends on who’s paying and has little relationship with the actual cost of services, and information on outcomes and quality is kept locked away from prying eyes. Not so in a post-reform world. Consumers can now shop on the basis of price and quality. They can go online and find out how much an appendectomy costs at hospital A or B and which one has a higher success rate. Health plan quality ratings are there for all to see when selecting an exchange plan. Big data and analytics make all of this possible.

5. Care management efficiency. Gone are the days when health insurers had unlimited funding for care management programs. Today, plans must make judicious use of limited administrative dollars to meet medical loss ratio minimums while still managing complex and catastrophic cases. Analytics help plans optimize their care management programs, prospectively identifying those members most likely to benefit from care management, and then enrolling them in the right program.

With many of their traditional performance management tools neutralized by reform, health insurers have had to get smart about how they leverage data and information. They use analytics to design benefit plans, develop marketing strategies and consumer segmentations, select network providers, develop reimbursement strategies, improve clinical quality, and optimize their remaining cost and quality management tools. In today’s market, how a plan leverages analytics, turning data into actionable information, will make the difference between survival and demise.

This article first appeared at Milliman MedInsight.

Tips for ensuring quality encounter data submission in Medicaid managed care programs

Naugle-AndrewOne area of data management within the healthcare industry that is getting new emphasis and interest from regulators is a focus on encounter data. Today, the majority of Americans receiving healthcare services funded through the Medicaid program are enrolled in some form of managed care. Under this scheme, states contract with managed care organizations (MCOs) that take on responsibility for providing Medicaid services in exchange for a fixed capitation payment. This approach is in contrast to the traditional fee-for-service (FFS) program where providers submit claims directly to the state for payment.

It is widely recognized that the FFS approach to provider payment creates perverse incentives for delivery of unnecessary services and uncoordinated care. Medicaid managed care gets away from this by providing a fixed capitation amount to the Medicaid MCOs, giving them incentives to more effectively manage care. The MCOs often pass along those same incentives by paying certain providers using capitation as well.

Notwithstanding the undesirable incentives that FFS creates, one area where FFS excels is the collection of timely and complete data about the services rendered to each patient and information about the price of those services. Because FFS claims are essentially invoices, this approach offers strong incentives for providers to submit claims in a timely manner (for prompt payment) and to ensure those claims are a complete reflection of services rendered (for complete payment).

Under capitation the payment mechanism is decoupled from the data collection process. In lieu of claims MCOs must collect encounter data from their providers and then submit that data to the states. Unfortunately, this takes away the direct financial incentives providers have for timely and complete data submission. As a result many states have struggled to collect credible information about the services delivered under Medicaid managed care. Such data is essential for important activities such as rate setting and program management.

Viewing submission of encounter data as an MCO function, many states have implemented strict contractual requirements coupled with tough performance guarantees and financial penalties to motivate MCOs to improve the quality and timeliness of the encounter data they submit. Failure to perform can have significant consequences for MCOs, including financial penalties, corrective action plans, bad press, and even contract termination. Based on our experience working with states and MCOs to help improve encounter data quality, we have identified a few things that can help improve the results:

1. Evangelize the importance of encounter data among providers. Once decoupled from the payment process it can be hard to convince providers of the importance of collecting and reporting encounter data. Ensuring that these constituents understand the value of encounter data and are submitting complete and timely information is key for MCOs to meet their contractual obligations to the state. Regardless of how strong the processes are within the MCO to ensure complete and timely submission, if the source information coming from providers is incomplete what goes to the state will also be incomplete. In addition to including encounter data requirements in their provider contracts, MCOs should include encounter data as a topic in their provider communication/education plans, and evangelize its importance whenever they can.

2. Develop clear submission requirements, definitions, and data specifications. In any situation where data is being submitted to a third party, lack of agreement and understanding of the actual submission requirements, definitions, and data specifications is a setup for downstream conflicts. Among states the requirements for submission often vary and sometimes change during the term of a contract. States and MCOs should engage in a collaborative process to ensure that all parties are working from the same guidance and interpretation of the submission requirements.

3. Establish an interdisciplinary team. Many MCOs view encounter data submission as one department’s responsibility—typically finance, operations, or information systems. In reality, it takes skilled and knowledgeable resources from throughout the organization to drive a high-quality process and result. MCOs should establish an interdisciplinary team that brings together the experts and makes everyone involved accountable for the outcome. That team may be led by someone from one of those primary departments but requires support from others.

4. Implement automated data validation and reconciliation processes. Submitting encounter data typically involves collecting data from multiple sources, transforming it into a new format, and then submitting it to the state. There are many opportunities for errors along the way. To provide an early warning of potential errors and to facilitate root cause assessment when errors are identified, MCOs should implement data validation and reconciliation processes that run parallel with the encounter submission preparation process. Often states will have internal processes they run on the data when they receive it; mirroring these processes can proactively reduce error rates. In addition, where possible, it makes sense to reconcile financial information against financial systems such as the general ledger, not just what’s in the claim system.

5. Track and resolve errors promptly and completely. When submitting encounter data some errors are unavoidable and thus both MCOs and states must have resources and processes in place to support timely and complete resolution of those errors. Errors can be caused by changes in the way data is collected within the MCO, changes in the state’s internal validation processes, or simply anomalies in the data. Regardless of the reason, each error should be tracked and resolved to completion. Root causes should also be identified to allow for error prevention.

As states have made the transition from FFS to managed Medicaid, the quality of utilization and cost data they receive has eroded. With the majority of Medicaid beneficiaries today receiving healthcare services through managed care plans it is more difficult for states to perform effective oversight of these programs. Multiple encounter data improvement initiatives have emerged as this has become an area of focus for both states and the federal government. MCOs should expect this scrutiny to continue, but should also recognize that through a systematic approach to managing and reconciling data and a collaborative posture with their state partners many of these challenges can be overcome.

This article first appeared at Milliman MedInsight.

The importance of administrative cost benchmarking

In the late 1990s, online travel agencies revolutionized the airline industry by publishing fares and allowing consumers to search for and purchase tickets. No longer would consumers have to rely on an agent to filter and present options; travelers could search across all vendors and use their own criteria to evaluate their options and purchase a ticket. The individual and small group health insurance markets are poised for the same sort of dramatic change, driven by the now familiar concept of the online marketplace, known in the health insurance industry as the exchange.

Although the operation of a health insurance exchange is quite different from that of an online travel agency, these distribution channels are similar in their impact on price transparency. Under the old travel agent model, consumers would first search for tickets based on convenience factors (e.g., travel dates and times, routes, etc.) and then use price to differentiate among a few options. Likewise, in the individual and small group health insurance markets, price is often presented after the purchaser has already narrowed the options to a few that meet non-price criteria. In both of these situations, price is applied as a deciding factor after the consumer has already narrowed the universe of choices to a subset of similarly appealing options; and the consumer lacks visibility to the prices of choices that were eliminated in that process. Online markets, on the other hand, allow consumers to see the prices of all or most options at the same time, making price a primary determining factor when making a purchase decision. This new presentation format, which allows consumers to choose one product over another based on a small dollar price difference, discourages significant price variation among competitors for similar products.

For most health insurance products, price is comprised of three primary components: benefit expense, administrative expense, and risk margin. Although benefit expense makes up the lion’s share of the premium or price, administrative cost differentials among health insurers can also materially contribute to premium differences. These differences will become more pronounced and may affect consumer purchasing decisions as the benefit expense component of premium is constrained by the medical loss ratio (MLR) requirements of the Patient Protection and Affordable Care Act (PPACA). These rules effectively create a benefit expense floor, requiring that health insurers in the individual and small group markets spend no less than 80% of premium on benefits (85% in the large group market), or pay a rebate to policyholders. It is likely that MLRs for individual and small group products will eventually settle around the 80% level or higher. In this new world, the importance of managing administrative cost will increase as price competition puts pressure on overall premiums and the MLR rules force administrative cost and risk margin into a fixed share of the premium dollar.

Benchmarking is one of the most effective tools available to help health insurers manage administrative expense. For insurers working to achieve MLR targets through administrative cost reduction, a benchmarking assessment can offer a function-by-function comparison of administrative expenses and staffing levels versus competitors and peers. Such an analysis can help organizations figure out where to target their cost reduction initiatives or determine what cost level is appropriate for a given department, cost center, or function.

For insurers that have already achieved the MLR targets, administrative benchmarks combined with a dashboard view can allow for monitoring of administrative expense variation throughout the year. Optimizing administrative cost is not something that can be achieved overnight; it takes time to plan and implement cost management initiatives, and months or years before the benefits accrue to the bottom line. Thus a dashboard coupled with benchmarks can provide management the tools they need to effectively manage their price competitiveness in this new distribution paradigm.

This article first appeared at Milliman MedInsight.

Electronic funds transfers

Managed Healthcare Executive looks at the move toward standardized electronic funds transfers. Here is an excerpt:

Savings of $4.5 billion over 10 years is the projection by the federal government relative to a new rule to standardize electronic funds transfers. HIPAA-covered entities have until January 1, 2014, to comply.

Payers will need to develop infrastructure and processes to support electronic remittances, but much of the work to implement this rule will fall on providers, says Andrew L. Naugle, a principal at consulting firm Milliman. The biggest piece of the puzzle is what the provider does with the electronic remittance advice.

“Although most health insurance companies already have the capability to send an electronic remittance advice, the typical healthcare provider is not set up to accept this electronic transaction or automatically post the payment to the corresponding receivable,” says Naugle.

Indiana posts exchange papers

The state of Indiana has posted a number of issue briefs written by Milliman consultants. The issue briefs concern Indiana’s state exchange and health reform in general. The full library is available here. Of particular interest:

50 states…50 Health IT solutions?

Managed Healthcare Executive poses this question with regard to the establishment of state exchanges: Will each state build their new statewide health IT infrastructure from scratch? Fortunately not.

The idea that states will be able to share some core exchange components is driving $241 million in HHS “early innovator” grants awarded in February to Kansas, Maryland, New York, Oklahoma, Oregon, Wisconsin, and a multi-state consortium led by the University of Massachusetts Medical School.

In Kansas, the grant will fund a solution that lives “on the cloud,” which other states can use. New York will build from its Medicaid management information system (MMIS), which already processes payments for about one of every three healthcare dollars paid in the state.

“What’s interesting is that there are no two states that are thinking about it the same way,” [Brian] Russon [of Microsoft] says. “But from a core exchange component, we’ll see heavy similarity in the consumer portals and the ability for the exchange engine to plug into what we’re hoping to see: very data hub-centric approaches, especially as states look at connecting into federal systems.”

Andrew Naugle, a principal with the consulting firm Milliman, notes the challenges associated with the many different MMISs in use.

“Hopefully, the federal government will come up with a standardized way to access its systems,” Naugle says, “but on the state side, there could be many different ways to interface with the various state Medicaid systems. So there will be a lot of customization even if a state pursues a commercial product off the shelf.”

Whether states build their exchange technology from existing systems or start with a commercial exchange solution, linkages to other state and federal data systems, which currently are silos of information, need to be built. The biggest challenge right now is the infrastructure, says Naugle.

New book: The Healthcare Imperative

The Institute of Medicine, as part of its “Learning Health System Series,” has published a book called “The Healthcare Imperative: Lowering costs and improving outcomes.” The book is available for free download here. The book includes an essay called “Excess Health Insurance Administrative Expense,” by Milliman principal Andrew Naugle. The essay includes both an estimate of total administrative cost in the system:

We estimated 2008 total administrative expense for fully insured commercial products using benchmarks developed from administrative expense data collected from more than 100 payers. According to these proprietary benchmarks, median payer administrative expense for fully insured commercial products, expressed as a percentage of fully insured commercial premiums, was 11.3 percent. Note that this definition of administrative expense is inclusive of external broker commissions, but excludes premium taxes.

Using the combination of the total fully insured premiums in the commercial market and the median administrative expense level (using the median to approximate the mean) we calculated an estimate of $42.4 billion ($375 billion × 11.3 percent) to represent total payer administrative expense for fully insured commercial products.

If that is the starting point, what is the potential for more efficient administration? Here’s a key excerpt:

In terms of administrative expense, we defined the best-practice level, based on our experience, to be approximately 7.6 percent of fully insured commercial premiums. Although it is possible for organizations to operate effectively at lower administrative expense ratios, we find it is more common for organizations with administrative costs below this level to exhibit characteristics of poor performance (e.g., high claims turnaround times, long customer service call hold times, inadequate or ineffective medical management programs) that are due to insufficient staffing.

Continue reading

ICD-10: Urgency setting in?

Even with the direction of reform now in question, change continues throughout healthcare. One evolution that should be well underway is the mandated, industry-wide conversion to ICD-10. Here is a summary from GovTech:

They say it’s a bigger deal than the Y2K bug.

Not so much in terms of mass hysteria, but in scope: In 2013, the U.S. will upgrade to the latest version of the International Classification of Diseases (ICD) system — the standard diagnostic taxonomy by the World Health Organization — a move which represents “the largest health-care systems modernization effort in history,” said Bartlett Cleland, senior director of policy at TechAmerica, a technology industry association.

As hospitals switch to the latest disease diagnosis and procedure codes, industry observers say, the technical and economic impact to the U.S. government and health-care community could eclipse the much-hyped system upgrades at the turn of the century.

“It’s going to affect anybody who touches the health-care system,” Cleland said. “If not done correctly, this change has the potential to be even more painful than anything in the health-care debate that’s going on.”

ICD-10 is starting to get more press and attract a greater sense of urgency. This blog article has appeared several places. Why the increased attention? First, because 2013 no longer seems so far away; and second, because many in healthcare are not yet prepared for the conversion. The industry’s preparation was recently highlighted in this survey.

Continue reading

Optimizing administrative expenses

Administrative costs are often mentioned as a source of waste in healthcare financing.

We asked Andrew Naugle to tell us what is driving spending and where savings may be found.

Q: How much do health plans spend on administration and can they reduce that cost?

Andrew Naugle: If a health plan gets a dollar in the door, it spends about 85 cents of it on benefits, about 12 cents on administration, and it gets to keep about 3 cents as profit or surplus. Those numbers come from a study I did looking at the annual statements of about 900 health plans. Of course there is some variability, but the numbers hold pretty true.

Health plans spend a lot of their time and attention trying to manage benefit costs. That’s not an unreasonable area to focus on if 85% of the premium dollar goes to pay for benefits. However, reducing benefit costs can be a real challenge, as it requires changing member and provider behavior—a tall order.

On the other hand, while administrative expense represents a much smaller piece of the premium pie, health plans tend to be in control of their own administrative spending. Managing administrative cost, therefore, ought to be easier, as plans need only change their own behaviors rather than the behavior of third parties that don’t appreciate being told what to do.

Too bad it’s not that simple, because managing administrative expense can be very painful for organizations for a whole host of reasons. Ultimately, I have seen clients achieve significant improvement in their administrative expense positions. However, real bottom-line impact requires a comprehensive strategy, management buy-in and commitment, and major investments of time and energy.

Continue reading