Abstract

Physician practices, once the foundation of private banking departments, are disappearing within larger medical groups and hospital-owned physician organizations. Physician practices are under increased pressure from the economics of the practice of medicine and are seeking shelter in larger organizations. Risk mitigation, lifestyle issues and practice continuation strategies are the dominant themes for physicians today.

If physician practices are disappearing, how do banks adjust their marketing and services to meet the demands of these consolidated medical systems? What challenges does this consolidation present? What happens to the physician groups that remain independent? What bank services are needed to meet the demands of these healthcare systems in the future?

Physicians, the Perfect Bank Customer

Physicians have always been a significant part of any commercial bank’s private banking division as they are traditional small commercial banking customers with all of the traditional banking needs, little competition and much higher than average revenues and incomes. They are also local relationship businesses that use the following traditional bank services:

• Depository services
• Working capital and equipment loans
• Merchant card services
• Mid-to-high net worth personal banking services
  • Residential mortgages
  • Depository services
  • Revolving lines of credit
  • Investment services
  • Trust department services

Healthcare and, more specifically, physician groups may be the last bastion of an industry that uses a broad array of these services, whereby multiple vendors and price sensitivity are not readily in demand by the customer. Even little commercial businesses today understand the need for LIBOR-based pricing, limited or no personal guarantees, sweep accounts and the value of competitive banking needs. Physicians as a group truly value long-term relationships with people they trust. Sound familiar?

There are numerous similarities between the healthcare industry and the banking industry that warrant another study. The object of this article is to identify the historical value of physician bank customers, identify current healthcare trends that affect this market segment, and describe the impact of these changes on future banking services.

Healthcare Reform

While no one can predict the ultimate outcome of the healthcare debate and the impact at the provider and patient level, we can assume the following related to healthcare beyond 2009 that will have an impact on physicians and banking:

• Pressure on reducing the cost of healthcare will continue.
• Physicians and hospitals will face lower reimbursement and income.
• Demand for proving clinical quality will increase.
• Demand for technology applications and capital expenditures will rise.
• Operating costs of running medical practices will continue to increase due to health insurance premiums and operations of enhanced technology applications.
• Patients will pay more for health insurance with fewer benefits and more out-of-pocket payments.
• Taxes will increase to fund the shortfall in national healthcare expenses.
• Traditional healthcare payments structure and systems will be changed dramatically.
• Healthcare payments per clinical encounter or bundled payments will be the choice for many chronic disease states.
• Traditional competition will cease and new, more viable competition will emerge.

Impacts of Healthcare Reform on Physician Practices

First, the credit quality of physicians and their practices will be adversely impacted as their operating margins will be squeezed between less revenue per unit of work and higher fixed cost of operation. The operating fixed cost will grow due to the complexity and technology cost of new systems to stay compliant with the clinical quality initiatives mandated by healthcare reform. Not only will term credit demand increase, but the operating cost to implement and manage these new technologies will adversely impact the physician practice operating margin and, correspondingly, the ability to repay such term debt.

Secondly, the payment system for physicians will change dramatically as the payment structure moves from a corporate insurance payer to a series of payment requests from the patient, primary insurance and secondary insurance. The second largest payer of any medical practice today is the patient payment segment. This payment segment will increase due to higher deductibles, less covered services and higher coinsurance requirements. The cycle times for payment resolution, when the balance due equals zero on a transaction, will increase as there are more partial payers resulting in a higher cost of collection to the physician practice. There will be a significant amount of instability in physician payments due to changes in technology system, along with heightened pressure on over-the-counter patient collections.

In addition, the increased pressure for payments from the patient will convert a higher percentage of payments from electronic means to wholesale lockbox or traditional personal check deposits. The over-the-counter deposits from the physician practice should increase at local branch locations. Selling wholesale lockboxes to these practices is a challenge due to the lack of knowledge of the value of a wholesale lockbox and inability to consume the cost and bank technology package to manage their daily cash activity.

Lastly, a dramatic change is that the healthcare payments structure has the ability to change the ultimate payer structure as new entrants will emerge that collect, manage or control the flow of payment to the physician practice. For example, the medical home concept, whereby primary care physicians direct patient care throughout the healthcare system, will serve as clinical gatekeepers, but may also serve as clearinghouses for healthcare payments for patients assigned to their medical home. Capitation from the early 1990s will emerge as a new and revised form of healthcare payments through the bundling concept and medical home concept. More entrants into the payment cycle means more cost and more time to collect. Ultimately, the revolving line of credit demands to mitigate this slowdown of cash payments will increase dramatically while the credit quality for these facilities will degrade.

Where Are Your Physician Customers?

Physician groups are converging in larger groups and are more likely to formalize their relationships with their local hospitals. Hospitals and physicians are realizing a symbiotic relationship is necessary to survive the waves of healthcare reform in any form. Physicians have financial, technological and risk avoidance motivations to formalize a relationship with the local hospital. Hospitals need to formalize their physician relationships to initiate clinical care patterns for quality measurements, as well as begin to understand their patient case management. Today, a hospital is much like a restaurant that does not have the ability to forecast or manage its daily customer base. With changes in the healthcare payment structure, hospitals will have to gain the ability to better manage their daily inbound patient volumes and discharge volumes. Quality healthcare for a hospital sits outside the hospital walls today in the offices of their affiliated physician offices.

Physician-hospital alignment models are generally categorized as one of two types: (1) physician employment and (2) community service models. Both models have the characteristics of formal contracts, financial and service components and some amount of exclusivity of these relationships. Due to the physician practice pressures listed above, the employment model appears to be favored as the true differences in these two physician employment models are (1) compensation; (2) managed care contracting; and (3) ownership of practice fixed assets.

After a review of these differences in the right physician-hospital alignment model, many physicians turn to an employment-type model. The physician’s motivation for the right physician-hospital alignment model lies in the fact that a physician can earn the same or more money today in a physician-hospital relationship than in an individual practice, with much less headache and financial risk. Many physicians believe that the hospital is the best solution (versus any improvement in the current payments environment) for the continuation of their practices. Hospitals and their physician services organizations have the ability to remove many of the physician practice pressures related to technology capital and operating costs, staffing costs and additional practice capital expenditures.

Impacts on Banks

What impact will these changes in our healthcare payments systems and the convergence of hospitals and physicians have on the traditional healthcare banking ustomer? Banks healthcare customers are facing an unprecedented amount of uncertainty from financial and technological demands. Additionally, today’s strategic decisions may be grounded in solid business fundamentals, but may burst under the unknown future changes of healthcare reform. Here are some thoughts to consider about the impact to banks from current healthcare reform and provider response to healthcare reform.

1. All healthcare is local. There is little correlation in healthcare market strategy between markets due to population demographics, payer differences, market competition, employers, etc. Unfortunately, what works in Peoria will probably not work in Kansas City. Each market must be underwritten on its own merit eliminating the ability to replicate healthcare banking services nationwide.
2. Customer underwriting will be deeper with more emphasis on strategy versus current financial viability. A key to the healthcare credit portfolio will be dependent upon the market share, capital structure, operating cost structure and leadership of the customer. There has never been a time whereby management affects the ultimate results of a high-stakes poker game. For the next three years, this evaluation of the customer’s ability to withstand change and make the right investments will be critical to its organization, as well as to the financial results of healthcare banking services.
3. Credit demand for technology and working capital will increase as healthcare reform will adversely impact all participants in the cost of collection as well as the cost to implement and measure quality healthcare. Increasing participants in the healthcare payments business and payer technology requirements will slow down the adjudication of payments regardless of the abilities of the customer. The paradox for these healthcare participants and healthcare bankers will be the increasing demand for term and revolving credit while margins and credit quality will decline.
4. The sheer convergence of physicians into larger physician groups and physician-hospital alignment models will consolidate the banking customer. While the task of finding fewer and larger prospects may be easier, more banks will seek the same prospect list, ultimately, generating more competition for treasury management and credit needs. The margin for bank services for the physician will erode as these groups grow and become part of a larger healthcare system. With an expected decline in bank revenues and, therefore, margins due to this convergence and consolidation, banks must revise their thinking related to branch locations, over-the-counter deposits and proximity to healthcare delivery systems. Imagine a branch bank in a medical office building. Imagine a healthcare office in a retail shopping center. Both of these scenarios exist today.
5. Treasury management services will continue to expand on a basic level to more consolidated groups at lower, more competitive prices. Due to increased patient payments, we expect more cash transactions and a higher percentage of paper transactions in healthcare. While payers may consolidate, the patient will be the key as more payments from patients will be expected due to higher deductibles, higher coinsurance and fewer covered services. While remote deposit capture and traditional wholesale lockbox services will continue to increase, so will the number of zero balance accounts and less available DDA balances.
6. Bank marketing and sales will be consolidated, and healthcare customers will purchase based on price and expertise. Healthcare is an incestuous business as healthcare leadership rotates around healthcare companies, and the industry is very adept at networking at its various trade organizations. Being in the loop at these organizations will be critical for not only sales and marketing but, more importantly, for strategies, trends and challenges that affect a bank’s credit underwriting. Healthcare believes that it is a unique industry, and having the language of healthcare and network awareness will be the key for a bank to establish and re-establish itself in this new healthcare world.

Summary

Historically, the healthcare industry has been a profitable market segment for banks as healthcare providers are relationship-driven and have not had significant bank competition for services due to the local and fragmented nature of our healthcare delivery system. However, the pending healthcare reform activities will change the payments structure, market structure and viability of the various participants in a material way. Banks will have to adapt their marketing, sales and underwriting guidelines to ensure each bank understands the local healthcare market dynamics and make some significant forward bets on the management team and market position of its bank customers. While the healthcare market will continue to be a large market segment for banks and our economy as a whole, determining the winners and losers in the future will be a fine art.

About the Author

John R. Thomas is President and Chief Executive Officer of MedSynergies, Inc., Irving, Texas.

Abstract

In the late 1980s Financial Services was at a crossroads in identifying and preventing fraud. Tools and technology were immature and the strategy used was a “loss and chase” rules-based judgmental approach to “follow” fraud schemes. Culturally, key stakeholders were inclined to look at their solutions with a retrospective approach and only within their own credit portfolio. At that time, Financial Services did not have an understanding of the scope of fraud or an approach to even measure the amount of fraud. The majority of fraud rings went undetected. The industry required a change of culture and practice supported by new technology that bridged data silos with highly structured and proprietary data systems. In today’s healthcare world a similar challenge faces the proponents of medical banking with information technology platforms bridging institutions. In the end, the financial services industry leaned there was more to gain by limited cooperation and data exchange in order to prevent billions of dollars in credit card fraud. The same lessons apply to healthcare information technology investments and applications that range from fraud mitigation to comparative effectiveness research.

Introduction

In the late 1980s fraud mitigation in Financial Services was a rules-based approach based upon a small number of frauds detected from prior experience. Rules were judgmental, retrospective and put in place by hard-coding them into a credit card issuer’s processing system. The rules did not adjust for new types of fraud schemes. It was very typical that an issuer would have hundreds and in some cases thousands of lines of code as they continued to implement new rules over time. Criteria consisted of rudimentary decision trees. Examples include:

• Velocity of purchases – a judgmental cutoff of purchases over a specific period of time, not considering a consumer’s historical purchasing patterns.
• Merchant category codes – certain types of purchases were deemed to be more risky than others, such as cash or jewelry.

Fraud analysts “worked” transactions by reviewing computer printouts on their desks. This methodology did not allow the capability to effectively or efficiently stop fraud before it occurred.

The detection methods at the time could not measure how much fraud was prevented or if a new test strategy or treatment was more or less effective than the previous strategy. It was easy for perpetrators to go undetected. If a perpetrator was identified it was usually after numerous fraudulent transactions. Ultimately, perpetrators would discard stolen credit cards and move their scheme to another issuer. Additionally, there was not a process to determine if the merchant was party to the fraud or if the merchant was colluding with a fraudulent credit card holder. Credit card issuers did not share information; they operated within the silo of their own business and within their own market.

Many fraud transactions were inaccurately charged-off as credit losses because issuers did not have the capability to identify them as fraud or the account holders could not be located. Sometimes legitimate consumers “paid for the fraud” because they did not carefully check their monthly statements. This was a result of transactions showing up on their statements from charges made by fraud perpetrators. This issue understated the true estimate of fraud in the industry and further perpetuated fraud losses.

Catalyst for Change – 1993

Predictive Models & New Technology

The catalyst for change started with the introduction of predictive models for identifying fraud. Predictive modeling had historically been utilized in the Financial Services industry for the underwriting of credit and loans. It was an accepted and proven method within the industry several decades prior. The introduction of predictive modeling to prevent fraud was an extension and enhancement of that methodology.

The introduction of predictive modeling to detect fraud was not a simple task. The solution had several obstacles to overcome in order to be effective. The industry had legacy mainframe technology as the core business processing system. Integrating a transaction-based fraud detection system into the core business with strict time-processing standards was just one of many obstacles. This issue was overcome by the fact that the savings from preventing fraud losses were many times greater than the investment to integrate and run the fraud scoring systems. The new solution was designed to perform real-time scoring and assessments on 100% of all transactions. Queuing, a workflow management and workstation methodology, was introduced to automatically and efficiently present only high-risk transactions to the system for automatic rejection or for review by a fraud analyst.

Market Implementation

Getting a first customer to pilot the new fraud technology solution was initially difficult. Credit card processors were the first to be approached to launch and pilot the solution, but they declined. They did not have economic incentive to do so because they were not negatively impacted by fraud. They made their revenue by billing their customers for each transaction processed, whether it was fraud or not. As a normal course of business practices, they simply raised prices if expenses increased.

The next step was to approach one of the nation’s largest credit card issuers to pilot the solution. They accepted the proposal and implemented the system. They found that the results far exceeded their expectations. The issuer was able to identify fraudulent transactions that previously would have gone undetected. They were now able to implement real-time prevention processes, such as calling consumers, when suspicious out-of-pattern purchases were identified.

Because the solution was expensive to implement, it initially met some resistance from credit card issuers. However, as its value was demonstrated to individual issuers, its acceptance started to grow. Credit card issuers were discovering that their initial return on investment was generally between 10:1 and 30:1. This means that for every dollar spent on the system, the credit card issuer saved between $10 and $30 in fraud losses avoided. Market expansion became dramatic and immediate. Since the results of the initial implementations were so compelling, other credit card issuers immediately requested to have the solution implemented on their systems. They recognized not only the positive results but the automated infrastructure used to interact with each consumer. Initial fears that the consumers, the credit card account holders, would react negatively to being “contacted” and asked if they were using their credit card proved to be unfounded. In fact, the approach of calling consumers and stressing the “fraud protection” intent of the call became a public relations success.

The predictive modeling solution proved to be much more accurate in identifying fraud. It was more cost-effective to “work” the high-risk transactions and it was received favorably by each issuer’s consumers. The success of this solution has been universal. Now all credit card issuers utilize a real-time solution, which includes predictive modeling and workflow management, to prevent fraud within their portfolio.

Lessons Learned

Building an effective fraud detection system is a continuous learning and improvement process. Each successive system or model enhancement improves upon previous versions. That is one of the reasons why a “feedback loop” is required to update and improve the statistical algorithms.

While there were several items that were learned as part of the development and initial launch of the real-time fraud prevention solution, even more was learned after the launch because of the infrastructure built to measure and track results.

Indicators of Fraud

One of the riskiest transactions was identified as a part of the new methodology. It was a gas station transaction for less than $10. Fraud perpetrators would test stolen credit cards by discretely attempting a transaction at an unattended gas terminal. If the transaction was approved, that meant the card was good to use. This tactic by fraud perpetrators of “pinging” a gas pump became a typical indicator of subsequent fraud. However, it was soon abandoned by fraud perpetrators because they knew the real-time predictive modeling system had “learned” this scheme. If the logic of not analyzing all transactions prevailed in credit card scoring, this small dollar amount transaction would most likely have never been scored or detected.

Model Robustness

Predictive models continued to improve over time with each re-development. The feedback loop created to provide strategy outcomes (transactions tagged as fraud or non-fraud) continued to enhance each new model. Subsequent models created and implemented identified previously undetected fraud perpetrators.

Real-Time Assessment

The real-time platform provided the credit card issuers and their staff the ability to assess and review transactions as they were taking place. Previously, the fraud perpetrators could make a large number of transactions before the fraud was discovered. Often, the fraud was not discovered until the consumer received a bill with a large number of fraudulent transactions. Now, it is not uncommon to shut down a fraud perpetrator as they are attempting their first fraudulent transaction. The real-time capability provided the Financial Services industry the ability to move proactively from a detection strategy to a prevention strategy.

Accuracy

Initially, there was concern by credit card issuers about having to be 100% accurate when identifying fraud. This was overcome by implementing fraud strategies and processes that ranked the riskiest of transactions and then applied the appropriate action, intensity or investigation technique to the most questionable transactions. For example, the highest-risk transactions were declined for payment, while other transactions may have required merchants, via a real-time message, to verify credit card holder identification at the point of sale. The new approach provided a quick and non-obtrusive method to verify if purchases were fraudulent. Those transactions identified as less risky were queued for more research and investigated by a fraud analyst. All investigations were online, where previously they were paper-based manual reviews.

There were always false-positives (high scoring accounts that “looked like” frauds, but were not). However, the economic benefits of preventing fraud far-outweighed any negative impact to accounts that turned out to be non-frauds. The “goods” were quickly resolved in a customer service-type approach and were rarely negatively impacted. In fact, most credit card issuers used the chance to contact “good” customers as a positive public relations opportunity to demonstrate that they were taking action to “protect” the consumer from fraud.

Measurements

The infrastructure developed as part of this solution provided the foundation for the ability to measure return on investment. It also provided the opportunity to continuously improve and achieve the maximum effectiveness in keeping pace with ever-changing fraud patterns.

Silo Mentality

Initially real-time predictive fraud solutions were implemented at separate credit card issuer and processor sites. At the time, this seemed to be a natural approach to product market penetration. Later it was learned that this approach actually provided the industry with a less than optimal fraud prevention solution. The ideal solution would have been for all issuers and all processors to have housed their transaction data at a central site. This would have resulted in several benefits:

• Capability to capture the history and behavior of the same card holder across all of his/her credit card purchases, regardless of the issuer or processor.
• View across all issuers and processors to identify fraud rings – identification of a fraud ring in one portfolio would have allowed the ability to alert all other issuers and have quicker detection and prevention.
• Comprehensive view of merchants to detect merchant fraud and collusion.
• Feedback loop on fraud perpetrators across the Financial Services landscape would have allowed the predictive models to learn even quicker.

Access to Data – Known Frauds

It was difficult to build the first fraud statistical model because not much information existed on known fraud transactions. Generally, statistical models are developed with a known outcome (either “good” or “bad”). Since there were very few examples of “fraud” in Financial Services, other techniques had to be used until the feedback loop was established and frauds were labeled as such. In this case, predictive solutions inferred negative behavior based upon analysis. While this method was not optimal, it identified previously undetected perpetrators missed by rules-based strategies. A constant feedback loop allowed for refinement of the initial models.

Integration

Installing a fraud detection system into the core of a credit card processor’s business processing system was a long, cumbersome and expensive proposition. It often took as long as 12 months to implement and test the system. This approach could have been avoided with a modular solution. Under this scenario, only a data feed would have been required to complete a real-time assessment and communicate back a score, reason code and a treatment recommendation.

Results

Originally, the value proposition of the new fraud solution was to reduce resources used to “work” suspect fraud cases manually. The idea was to “throw away” the computer printouts used by the fraud analysts and allow the predictive solution to present the highest-risk transactions, ranked by score, in an online capacity. The initial hypothesis was that it would take fewer resources because the fraud analysts no longer had to research the nature of the fraud scheme. Instead, they could concentrate on only those transactions scoring in the highest-risk range. Specifically, the staff size could be reduced and salaries could be saved. The end result was much different. The new model identified new types of fraud and fraud rings that previously went undetected. In fact, initially credit card issuers actually added more staff, because on average, each fraud analyst was saving many times his or her salary in fraud dollars per year. Overtime, however, the number of analysts and number of transactions have been significantly reduced due to the success of predictive modeling approaches to prevention and detection of fraud. From 1993 to 1997 fraud was reduced by approximately 50% over expected results.

Parallels to Healthcare

The Problem of Healthcare Fraud

Although healthcare fraud and abuse estimates vary widely, constituents agree that the problem is enormous and growing each year. In testimony before the United States Senate Committee on the Judiciary, on May 20, 2009, Malcolm K. Sparrow, a prominent expert on fraud, said that healthcare fraud and abuse cost hundreds of billions of dollars per year, with the actual figure anywhere from $100 billion to $400 or $500 billion.¹ In 2002, a study by the Government Accountability Office estimated that 1 out of every 7 dollars paid to Medicare is lost to fraud.² This means that in Medicare alone, there was almost $70 billion in fraud and abuse for 2008 (projection of $466 billion in total Medicare spend for 2008³). If we extrapolate this assumption for 2017, Medicare would have over $120 billion in fraud and abuse (projection of $857 billion in total Medicare spend for 2017⁴). According to experience and research, it is estimated that the vast majority of fraud and nearly all of the abuse is perpetrated by healthcare providers.⁵

The most common approach in healthcare fraud and abuse detection today is to apply rules-based or judgmental methodology and technology. Rules are intended to imitate and automate human judgment. They are typically retrospective if/then statements are hard-coded into the back-end of a claims system. The terminology for implementing judgmental criteria is called ‘edits.’ This approach also mimics the manual process to identify claims that are outside of normal policy. This strategy has done little to mitigate healthcare fraud and abuse.

With the continued escalation of healthcare costs and healthcare reform on the horizon, it is imperative that payers and healthcare constituents implement new or improve existing solutions to identify, prevent and reduce healthcare fraud and abuse. There is an immediate opportunity to advance beyond the existing healthcare system’s approach today and meaningfully reduce the cost of healthcare through more innovative fraud and abuse mitigation solutions.

In order to make a meaningful impact on fraud and abuse in healthcare, new technology and predictive models with real-time assessments must be utilized to review suspect claims prior to payment. Today, these claims are paid and reviewed afterward to ascertain if they violated documented healthcare policies. If they are found to be questionable, organizations such as Medicare then seek reimbursement through a “pay and chase” strategy. CMS recently started to recover payment errors by utilizing Recovery Audit Contractors. CMS contracts with Recovery Audit Contractors (RACs) to guard the Medicare Trust Fund.

Financial Services Approach to Prevent Fraud

There are several parallels of early Financial Services practices before the advent of real-time assessments and statistical scoring and healthcare’s current approach to fraud mitigation:

1. Pay and Chase Strategy – similar to early, unsophisticated and inefficient Financial Services procedures, claims are paid and then researched for recovery opportunities.
2. Judgmental Criteria – healthcare solutions are rules-based and do not adjust for changes in fraud patterns.
3. Batch Assessment Approach – claims are reviewed based upon batch processing on the back-end of the data flow.
4. Lack of Fraud Performance – claims tagged as fraud or providers identified as perpetrating fraud or abusive behavior do not exist.
5. Silo Approach to Prevention – claims data and fraud outcomes are not shared at a central location.

Culture to Change

Currently, there is not a proactive, sophisticated, effective and efficient fraud prevention solution in the healthcare industry. Similar to Financial Services in the early days, it is as though no one is “minding the store.”

The current industry strategy and processes utilized breed a culture of acceptance of fraud and abuse. Adding to this is the fact that there are few, if any, incentives by key stakeholders to try new approaches to mitigate those costs. It is most often just easier to pass along the increased costs associated with fraud and abuse to consumers, employers or the government. If this laissez-faire attitude to prevention is to change, the following actions must be implemented across the healthcare landscape by Medicare, Medicaid, Tri-Care, private insurance and third party administrative companies:

• Implement statistically sound, empirically-derived score modeling systems that are designed to prevent (versus detect) fraud and abuse.
• Mandate that healthcare payers submit transaction data such as Medicare’s “Common Working File,” Medicaid files and private insurance claims data to a pooled data repository that will support the build of fraud detection models that have a comprehensive view of all provider and consumer activity across all payers.
• Fraud scoring models must score ALL transactions before any edits or other screening process removes claims from the data source.
• Use historical data to build and redevelop scoring models.
• Provide a “feedback loop” where ALL payers provide post-payment information about the eventual status of a claim as “Normal,” “Fraud,” “Abuse” or “Education Required” – this transactions feedback loop will also enable healthcare agencies to measure the actual amount of fraud, and fraud savings, in the system.
• Score ALL claims “promptly.” For Financial Services this was real-time; generally, in healthcare, this would mean claims are aggregated and scored within a one-day period. Results would be returned on the day after the claim is submitted.

Conclusion

In 1993, Financial Services launched the first transaction-based real-time fraud solution. The system used proven predictive modeling techniques, combined with innovative technology to identify previously undetected fraud transactions and fraud rings. Prior to the launch, the strategy in Financial Services was a “loss and chase” strategy. Detection methods utilized judgmental rules and edits that were hard-coded into legacy processing systems. The industry as a whole was not able to estimate fraud or adjust its detection methods to the changing patterns of fraud perpetrators. It took the changing of internal cultures to launch the first pilot. The first pilot project implementation resulted from a mixture of innovative thinking, risk taking and an attractive return on investment potential.

The healthcare industry is in nearly an identical place as Financial Services was almost two decades ago. The solutions to identify fraud and abuse are judgmental rules-based, ineffective and inefficient. The strategy is one of “pay and chase.” Now there is an opportunity to use the lessons learned and proven technology of the Financial Services’ transaction solution and refine it and apply it to healthcare. The opportunity for success and the return on investment is even more attractive than it was in the Financial Services industry. As the Financial Services industry was at a crossroads in the late 1980s, the healthcare industry is at its own today. It can pursue a new and innovative integrated fraud and abuse prevention program or continue to suffer enormous losses with the current outdated detection system.

References

¹Sparrow MK. Criminal prosecution as a deterrent to health care fraud: Testimony before the Senate Judiciary Subcommittee on Crime and Drugs, Washington, DC, May 20, 2009.

²United States General Accounting Office (“GAO”), Report to Congressional Committees, Medicare Fraud and Abuse: DOJ Continues to Promote Compliance with False Claims Act Guidance, April, 2002.

³http://www.cms.hhs.gov/NationalHealthExpendData/downloads/proj2008.pdf; page 5.

⁴http://www.cms.hhs.gov/NationalHealthExpendData/downloads/proj2008.pdf; page 5.

⁵Coalition Against Insurance Fraud. Go Figure: fraud data. http://www.insurancefraud.org/stats.htm. Accessed July 27, 2009

About the Authors

Allan Klindworth, MBA, is Principal of TerraMedica LLC, Wayzata, Minnesota.

Stephen T. Parente, PhD, is Professor of Finance, Carlson School of Management; Director, Medical Industry Leadership Institute, University of Minnesota; and Chief Health Economist, TerraMedica LLC, Wayzata, Minnesota.

Abstract

In 2009 members of the Medical Banking Project, comprised of technology firms, banks, an academic health system, a consumer technology firm, consultants and others, convened at the Vanderbilt Center for Better Health to “design the healthcare financial network of the future.” Executives were led through a patented, rapid-learning exercise by Vanderbilt’s executive team. Findings were collected, synthesized and appropriate next steps were sought to proactively implement such a network today. Results will be critiqued by experts representing four stakeholder groups—banks, providers, payers and employers—during a keynote panel at the 8th National Medical Banking Institute at the 2010 Annual HIMSS Conference & Exhibition. Final recommendations by the group included the creation of an industry-neutral forum to advance standards and best practices that address existing and emerging industry requirements for the creation of a healthcare financial network, including federal adoption of an industry enforcement mechanism to speed innovation, and prospective investment by banks and financial institutions in the emerging nexus of banking and healthcare systems.

Introduction

The U.S. healthcare system represents some $2.5 trillion annually and growing. Hidden within the cost of the infrastructure are the diversity of methods used to manage money and associated remittance data. Incremental advances in this area could result in systemic savings across the healthcare stakeholders. While existing regulations under the Health Insurance Portability and Accountability Act (HIPAA or “the Act”) recognize the value of this critical area (as specified in the Administrative Simplification provisions of the Act), the advancement of industry-wide and systemic programs, best practices and standards to capture this value have proven remarkably tedious and slow to implement.

A good example of unrealized value in this area is the comparative cost to transfer funds and remittance data in other industry segments (an area called ‘financial electronic data interchange’ or ‘FEDI’), at $5 more or less, versus a cost of $11 per payment or more in healthcare (Banker’s EDI Council, 1994).¹ Extrapolation of this data suggests that the healthcare industry could save $35 billion annually by implementing electronic payments, inclusive of the ability to trigger workflow automation across the complex healthcare revenue cycle, like automating contractual allowances, denial management, contract management and more (Casillas, 2001).² More recently, a new “Healthcare Efficiency Index” estimates a $30 billion savings could be attained by making improvements that include this vital area (see http://www.save30billion.com).³

Aligning Stakeholders

Current financial platforms often contribute to misalignment among stakeholders and result in poor visibility into payment data. For example, while an insurer may desire to process payments electronically, a care provider (or the provider’s bank) maybe unable to process EDI associated with electronic payments. Enabling this function has, in the past, resulted in unidentified cash and subsequent confusion about how to follow up on a claim.

In healthcare, the data associated with a payment is often complex, yet required for accurate reconciliation of books and records. Inability to identify credit balances, for example, has resulted in substantial fines (and in severe cases, imprisonment) in the Medicare program. This creates a disincentive to implement digital payment programs at the expense of new organizational efficiencies and savings, however compelling.

Bank “Infomediary”

Beyond the movement of payment data, banks could offer an “infomediary” function as they apply investment into new areas in healthcare. This is to suggest that banks have learned that they can add value to data that is flowing through payment channels, creating a new profit center while driving and delivering greater efficiencies to their clients and customers. New value models are being positioned for businesses, like hospitals and other provider settings, and consumers, using online banking platforms as a trusted and high-visibility delivery channel.

The Health-Wealth Paradigm

In addition to payment processing and value-added data programs that improve revenue cycle for the provider and offer savings for payers (and ultimately employers), banking groups are rapidly investing in “health-wealth” programs that link lifestyle, wellness and healthcare information and educational resources for consumers with tools that enable them to manage their healthcare spending. Indeed, one bank has teamed with a prominent national healthcare provider to offer stress training programs at bank branches—the first of a series of wellness programs—tapping into strong consumer demand for information and programs that improve lifestyle and health.

Along these lines, a national bank has opened up new “retirement centers” at their branch locations to offer end-of-life assistance coupled with financial instruments like reverse mortgages, HSAs and more. The bank believes that, in as much as industry reports suggest that a disproportionate part (some believe over 80%) of our average healthcare spending occurs during the last two years of life, it makes a great deal of sense to create specialized programs to help consumers to address this critical issue.⁴ According to a research report published in The American Journal of Medicine, 62.1% of all personal bankruptcies were related to the inability to pay medical expenses (Himmelstein, et al, 2009).⁵ This type of financial profile is likely to continue to drive commercial banks with large consumer lending portfolios to find innovative and consumer-friendly methods that are designed to protect financial interests.

As banks increasingly invest into the healthcare arena, they are finding specialized ways to bring new value to all the stakeholders. These new value models primarily stem from forming non-traditional partnerships with healthcare information technology companies, introducing traditional, highly regulated bankers to a new panel of mission critical standards in healthcare that are unfortunately quite diverse and appear not to be wholly standardized at all.

As the nucleus of medical banking activity revolves around new capabilities in payment and data processing, such as specialized lockbox programs, real-time payment exchanges and integration of new credit programs, there is growing recognition that in order to stabilize this area in ways that can efficiently address emerging needs (e. g., integration of financial programs that enable mobile payment in healthcare in areas like telemedicine), there is a need to standardize transactions and define best practices. Building this new “trading platform,” however, requires gaining consensus among the stakeholders. For example, rationalizing denial reason codes could decrease costs for routine claims processing but to do so with the greatest impact requires cooperation between payers and providers and gaining this type of interaction is frequently difficult due to market tension between the two groups. Still, new focus on medical banking is emerging along multiple industry fronts and will almost certainly create new stresses and/or functional requirements on a payment system that appears ill-equipped or prepared to process many of today’s healthcare payment transactions and the associated remittance information.

A Common Platform

To better enable the creation of new healthcare services by banks and speed investment into useful programs that improve healthcare, many believe that a common platform is required. The advantages of such an approach are improved transactional efficiency (getting to a cost point that is cents per transaction versus dollars per transaction), standardization of best practices that can speed adoption of new efficiency programs and the subsequent ability to create stable training, certification and accreditation programs that can be accessed by all the stakeholders.

Within this context, education plays a large role to assist bankers to understand the needs of the healthcare financial network and frankly this works the other way too. Healthcare executives can gain much from understanding the potential of banking and financial services programs to transform and improve fiscal programs and business practices, including but not limited to earlier and/or targeted consumer engagement that improves collectability of patient-owing balances in healthcare, an ever-increasing concern across the healthcare arena.

In this article, this platform of standards and best practices is referred to as “the Healthcare Financial Network of the Future” or “the Network” for short. As industry forces focus on programs that lie at the nexus of banking and healthcare systems, the Network is likely to continuously evolve tocapture cross-industry value that supports mission-critical and emerging functions that meet business and enterprise needs as well as the often erratic and finicky requirements and preferences of the emerging medical consumer.

Case Study: Meeting Activities and Outcomes

The Medical Banking Project convened its members to define “the Network,” including isolating new functions that the Network will likely need to support over the next few years (please see Addendum for a listing of the participants). Keynote speaker Dr. Mark Frisse, Director at the Vanderbilt Center for Better Health where the meeting was held, challenged the group to think creatively about functions that are not obvious today but that could be required based on the direction of consumerism, health reform and other areas. Each individual was then asked to respond to the following scenario: The Network has been built and it’s 2012. What does it look like? What are the characteristics?

A series of follow-on questions were also asked. Table1 synthesizes and prioritizes these based on answers and comments provided by the attendees.

Following this exercise, participants, pre-assigned to one of seven groups in a manner that emphasized diversity within groups, reviewed and discussed the individual work assignments completed by each of the participants within the group. A spokesperson for each person was selected and the entire group then reconvened to synthesize results and eliminate duplicate ideas. The results were documented and categorized into four strands of thinking and the group was asked to retire, think about the results and come back the following day, prepared to further synthesize findings.

The next day, Dr. William Stead, a prominent authority in healthcare informatics who is the lead faculty member over the Center, led with a keynote presentation describing his interest in medical banking, particularly as it relates to the bank’s ability to create algorithms that accurately simulate consumer experience and how that capability could be deployed in the healthcare setting. He was followed by H. Stephen Lieber, CEO of the Healthcare Information and Management Systems Society (HIMSS), who focused on the merger of the Society and the Medical Banking Project, and the strong commitment by HIMSS to create an educational platform that addresses ongoing convergence issues as banks invest in healthcare information technology to improve healthcare, a key element of the mission of the global HIMSS’ organization.

The entire group was then lead through a facilitated, and often negotiated process, that reduced the four strands of thinking captured the previous day to two synthesized functional areas of the Network. These two areas may be described as follows:

1. Create an efficient data and funds transfer platform that can, among other things, support the volume of data typically associated with healthcare transactions; and
2. Create a “health-wealth” oriented program that supports existing and emerging functional requirements and preferences of the medical consumer.

Following this exercise, two groups were formed to discuss the two synthesized areas and to then design a project or demonstration program that could help the industry to isolate industry and functional requirements (e. g., technical standards, privacy and security, best practices). The following two projects were recommended:

Deploy New DRI Tool. This project involves the completion of an existing program that was initiated by members of the Medical Banking Project. Dubbed the “Dispute Resolution Initiative” (DRI), the project deploys an online tool, freely available to the industry, that progressively crosswalks the universe of payer denial codes with a set of 20 action steps. The tool helps to rationalize claims-management work routines that providers experience when processing denied claims. It is considered a first step in a more universal process to address this inefficiency in the healthcare claims payment process.

Design Bank-Enabled HIE Program. Access to a consumer’s electronic healthcare records continues to be a systemic challenge in our national healthcare system. What if banks could link online banking, used by 69.7 million households and growing 27% annually,⁶ to a health information portal that includes a personal health record (PHR)? What if the online banking portal linked to an employer’s portal, typically used once per year by the employee for plan selection versus online banking that is accessed three-to-five times a week? What value can be derived from this integration in terms of spurring consumer adoption? What is the business model for this approach? A project could address these and other issues, and could be designed by tethering a PHR to an online bank account so that a consumer/employee can, with prerequisite authorization, access authorized records that are provided and/or stored by a health information exchange (HIE) that is integrated into the technology platform.

The concept of an online banking PHR that is tethered to one or more HIE sources, or other repositories of secured healthcare records for that matter (such as “health record banks” for individuals choosing to monetize their health data), requires further explanation. The concept was first described in a white paper that was distributed to the members of the Medical Banking Project at a prior Leadership Forum (Casillas, 2003).⁷ While evidence remains outstanding as to the true value of the PHR in healthcare, at least one national bank is offering a secure vault that can store health records (and other records) for consumers while another is teaming with an organization that offers health information that includes a PHR for the consumer. Indeed, one global financial technology firm has acquired a Certification Commission for Health Information Technology (CCHIT)-certified electronic health records vendor and is offering PHR-functionality to a client base of over 5,000 banks and financial institutions.

A pilot program could demonstrate the usefulness of this type of program and facilitate industry innovation along these lines, especially as it relates to increasing consumer engagement with their healthcare and/or the healthcare of immediate family members (e. g., elder care).

As this dynamic unfolds in the marketplace, another structural element is evolving in the prospective model, the creation of health information exchanges or HIEs. HIE support systems (financial, governance, etc.), primarily include private foundations, healthcare and community groups, government-supported efforts, commercial ventures and other formations. A key factor in the development of HIEs is sustainability—what is a workable business model?

A “bank-enabled health information exchange” (as advanced by the Medical Banking Project in 2003), could support consumer-initiated and authorized requests for medical records from within the security of the online banking portal. This potential alliance, which addresses a prospective but convincingly emerging functional capability of a healthcare financial network, could provide a cornerstone of the new “health-wealth” paradigm: namely, the provision of easily accessible information and tools that consumers need to better manage their health and healthcare, with the added incentive of improved availability of retirement funds in the future in exchange for healthier lifestyle practices today a compelling or at least provocative health-wealth connection. Tools to manage those funds would also be placed in the portal, of course.

Within this context it is useful to point out that training and educating consumers are a mainstay in banking for things like using ATMs for cash withdrawals and deposits, using online banking instead of branches, using checks, debit and credit cards instead of cash, mobile banking (especially relevant in other areas of the world) and other areas. Thus, the idea of “health coaching” tools and information that more deeply couples a bank with the consumer’s spending and savings in healthcare (e. g., health savings accounts, health reimbursement accounts or other account-based health plans) could become attractive. Indeed, some banks that offer health savings accounts are actively investing in such tools today. What functional requirements will this dynamic bring for the Network?

The attendees believe that forming a common effort to implement a healthcare financial network is required to spur the creation of much-needed standards and best practices in the cross-industry area of medical banking, an area of discipline that is inherently complex and involves multi-domain shifts (cross-industry compliance and regulations, organizational design and transformation, cross-industry technology optimization and convergence, medical consumerism, globalization of healthcare, etc.). The degree of complexity in medical banking often stifles innovation and acts as a deterrent to banking investment in healthcare, even as emerging models suggest that such investments can provide systemic improvement in transactional efficiency, consumer and community engagement in health and healthcare and even address “green issues” that are contained in the United Nation’s Global Millennium Development Goals as adopted by the World Bank (Goal 7: Ensure Environmental Sustainability). Characterizing the mitigation of the extreme paper chase in healthcare as an environmental issue was a message advanced by the Medical Banking Project during its 2008 Institute.

Conclusion

The findings of executives participating at the leadership forum may be summarized as follows: (note that the summary also provides the initial draft goals of the Healthcare Financial Network of the Future).

1. Visibility across all transactions.
2. A common effort will spur creation of needed standards and best practices. This requires an ongoing effort/neutral forum that engages major stakeholders, isolates emerging market needs and facilitates solutions that can be applied systemically across the Network.
3. A quasi-government body is needed to enforce the necessary standards across all the stakeholders (e. g., Health Federal Reserve-type of scenario).
4. Common standards are mandatory for the Network.
5. All players should share the value of the Network.
6. The Network needs to support evolving industry requirements in payment processing and data transfer, including real-time mechanisms, supporting the potential creation of consumer-authorized personal healthcare records and other areas that provide value to the healthcare stakeholders.

From this initial idea set we can extrapolate at least two industry requirements as follows:

• Create a neutral industry forum that can facilitate the Network and continuously isolate functional requirements. To address this requirement, HIMSS Medical Banking Project is attempting to organize a new “Chairman’s Roundtable of G7 Panels’’—initially, four industry stakeholder panels comprised of providers, payers, banks and employers—that will address this industry requirement. The development of white papers, demonstration projects and other initiatives that are guided by this effort will facilitate the orderly development of the Network.
• Support a legislative effort that creates an enforcement body that speeds adoption of the Network (standards and best practices, not a specific technology platform). To address this requirement, HIMSS Medical Banking Project is working with the Society’s government relations team to articulate and/or support the advancement of regulatory requirements that enable the creation of an enforcement mechanism that can be used to efficiently implement electronic payments and remittance advices and other related transactions. We note that much of the work required to effectuate a regulatory provision in this area has already been introduced in the healthcare reform bill passed by the Senate on December 24, 2009 (Section 1104 of  H.R. 3590).

Finally, a series of recommended functions were documented during the session and will be provided to panel experts who will convene at the 8^th National Medical Banking Institute at HIMSS10, a working conference. Along with the experts, attendees will then participate to further define requirements of tomorrow’s healthcare financial network. A final proceedings report will guide ongoing discussions and facilitate engagement of healthcare stakeholders around what is arguably one of our nation’s most critical resources—our healthcare financial network.

Addendum

Participants at the 2009 Medical Banking Leadership Forum

John Casillas, Senior Vice President, HIMSS Medical Banking Project

Tom Dean, CEO, Revenue Management Solutions

Ed Dodds, Communication Strategist and MBlog Editor, Conmergence

Phillip Dolamore, Vice President, Business Development, Aequitas Capital Management

John English, Senior Lecturer, BA, MA, Vanderbilt University

Mark E. Frisse, MD, MBA, MSc, Accenture Professor of Biomedical Informatics, Director, Volunteer eHealth Initiative, Vanderbilt Center for Better Health

B.P. Fulmer, Managing Partner, Exchange EDI, LLC

Mary Hyland, Assistant Vice President, Regulatory Affairs, Chief Privacy Officer, The SSI Group, Inc.

Glen Johnson, Vice President of Marketing and Product Development, Claimtrust, Inc.

Kimberle Kennedy, Senior Vice President, U.S. Bank

William D. Kirsh, DO, MPH, Chief Medical Officer, Sentry Data Systems, Inc.

Scott Krah, Director of Banking Services, CareMedic Systems,Inc.

Ken Kubala, Vice President, NPDP, Senior New Business Development Manager, BNY Mellon Treasury Services

Peter Lang, President & Principal Consultant, Trellis Integration Partners

H. Stephen Lieber, CAE, President & CEO, HIMSS

Tom Lloyd, Director, Consulting Operations, Vanderbilt Center for Better Health

Pamela Matthews, Senior Director, Business and Financial Information Systems, HIMSS

Tyson McDowell, CEO, Benchmark Revenue Management, Inc.

Tom McHale, Vice President of Business Development, Allviant

Elizabeth Meadors, Vice President, Global Product Management, Comerica Bank

Emory Meeks, Vice President, Business Development, Cairn Software, LLC

Richard Mobley, Vice President, Healthcare Services, BancTec

Richard Morrison, President, Medical Banking Rx

Foster D. North, Business Development Executive, Ingenix/CareMedic Systems, Inc.

John Peebles, CIO & Vice President of Operations, Sentry Data Systems, Inc.

John Phelan, PhD, Technology and Management Consultant, Technology and Operations Solutions, Milliman Inc.

Sheila Schweitzer, Chairperson & CEO, Ingenix/CareMedic Systems, Inc.

Gordon Sellers, Director, Healthcare & Medical Banking Solutions, Systemware, Inc.

William W. Stead, MD, Associate Vice Chancellor for Strategy/Transformation & Chief Information Officer, Vanderbilt University Medical Center

June St. John, Senior Vice President, Healthcare Product Manager,Wells Fargo

Maureen L. Turo, Vice President, MS, CTP, Healthcare Market Specialist, BNY Mellon Treasury Services

References

¹Cantor A, Connor M, Falconer T, Fisher C, Foote A, Garr J, Gilliard B, Green L, Podraza R, Rosdorff R, Sebald M (Banker’s EDI Council). HealthCare Financial EDI User Guide. National Automated Clearinghouse Association; 1994.

²Casillas J. A Medical Banking Roadmap for America, Version 1. The Medical Banking Project; 2005; p 17.

³http://www.save30billion.com.

⁴Wennberg J, Fisher E, Goodman D, Skinner J. Executive Summary: Tracking the Care of Patients with Severe Chronic Illness. In The Dartmouth Atlas of Healthcare 2008. The Dartmouth Institute for Health Policy and Clinical Practice, Center for Health Policy Research; 2008;p 1. (Available at http://www.dartmouthatlas.org/atlases/2008_Atlas_Exec_Summ.pdf).

⁵Himmelstein D, Thorne D, Warren E, Woolhandler S. Medical Bankruptcy in the United States 2007: Results of a National Study. The American Journal of Medicine. 2009. (Available at http://www.pnhp.org/new_bankruptcy_study/Bankruptcy-2009.pdf.)

⁶Silva J. Delivery Channel Volumes in the United States, 2006-2010.‘In Line’ to Online. The Tower Group; May, 2007. (Also see Fiserv-sponsored Consumer Bills and Payment Trends Survey conducted by The Market Workshop and Harris Interactive, available at http://investors.fiserv.com/releasedetail.cfm?ReleaseID=396336.)

⁷Casillas J. Bank-driven Electronic and Personal Healthcare Records. The Medical Banking Project; 2006.

About the Author

In 2001, John Casillas founded the Medical Banking Project, an industry think tank and civil society organization that facilitates the convergence of banking and healthcare systems to improve global healthcare. The firm was acquired in November, 2009 by HIMSS and now offers a comprehensive education, policy research and industry action forum for banks, financial institutions and related groups to isolate best practices for integrating financial and healthcare technologies to improve healthcare. Mr. Casillas is now Senior Vice President, HIMSS Medical Banking Project.

The lion’s share of healthcare in America is provided in hospitals, under the direction of physicians, subsidized by insurance, and facilitated by pharmaceutical and surgical treatments. Healthcare has grown over the last century from a locally-funded, community-based cottage industry to a third-party funded, medical industrial Goliath. In 1960, 5% of America’s gross domestic product was dedicated to healthcare services. Today, it is nearly 20%.

Healthcare in America is perched on a precipice. Many parts of the current healthcare delivery system—a $2.8 trillion annual enterprise—have become unsustainable. But every crisis presents an opportunity. So it is with America’s healthcare conundrum. For those with vision, entrepreneurial spirit and a willingness to explore for solutions, there has never been greater opportunity to develop a better approach to healthcare than now. A new methodology, with new funding mechanisms, new technologies, and new venues of care, cries out for invention.

E. Buckminster Fuller, one of the 20^th century’s greatest inventor-philosopher-thinkers once said, “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” Healthcare’s new model will require creative adjustments in every sector of the American economy. And it will require a new definition of social, personal and community health.

Financing Health

The problem in America is not that healthcare is too expensive. It is that America has not figured out how to make health valuable. Prevention gets very little play in American healthcare. “Treatment” is everything. Our healthcare system relies more on sickness than it does on health. The healthcare reform debate rages on, yet by every measure our health is deteriorating before our eyes. Can we figure out a way to make health a priority over sickness? Is there a way for health to “pay” for those of us who “earn” it? Is there a way to subsidize health, per se, rather than health insurance? Is there some incentive that can work to move us toward health, or are we forever consigned to growing prevalence of obesity, heart disease, cancer and stress?

One model holds promise. Proponents believe it will enable individuals and communities to reap the benefit of health—physically, psychologically, emotionally and financially—by essentially “banking” our health for a rainy day. It puts healthcare providers in the wellness business, banks into the health-loan business, and citizens in their own health management driver’s seat. One component of this new approach is called “Medical Banking™.”

Medical Banking™

In The Innovator’s Prescription,¹ Clayton Christensen charts the course to a new way of thinking about our healthcare system and its need for a fundamental overhaul. He examines healthcare in all aspects, including its financing mechanisms, evaluating the pluses and minuses of various health insurance approaches—commercial managed care, single-payer government plans, for-profit v. non-profit plans, and so on. His conclusion: the financing mechanism that will best enhance health and cut healthcare costs is the one that combines the incentive of capitated health management (for providers) with health and wealth management (for consumers). His reasoning is simple. Chronic conditions currently account for the bulk of our healthcare costs, yet they are most effectively “treated” and managed through individual behavior change. As such, Christensen concludes, the system most likely to both reduce healthcare costs and improve quality requires an integrated, capitated (read—at risk) caregiving system, one that compensates providers for health over sickness, and a hybrid between banking and health insurance that not only finances treatment through high-deductible health plans (HDHP), but motivates self-care through financial health incentives embedded in health savings accounts (HSA). It is a shared risk approach between patient, provider and payer that relies on the basic premise that when an employee’s 401K statement shares space with an HSA and a healthcare provider is motivated to both control costs and increase revenue by improving health, the health-money-behavior connection creates a partnership that values health over sickness.

HSA detractors point out that healthcare, per se, does not function well as a market-driven commodity. People tend not to shop around when they are sick.² Patients may forego needed care when they must pay, worsening health outcomes, especially for low-income individuals.³ And richer, healthier patients (the kind HSAs seek to create!) retain their healthcare funds (which is the behavior-change motivator!), thus depleting the available dollars to care for the sicker, poorer patients.⁴ Conversely, proponents argue that HSAs emphasize prevention over treatment, with over 80% of plans providing first-dollar coverage for preventive care, thus encouraging health and lower healthcare costs.⁵ Further, HSA accounts offer consumers significant financial advantage over flexible spending accounts (FSAs), since unspent deposits roll over and accumulate year after year. If significant assets accumulate (i. e., the depositor stays healthy), HSA funds may also be used for retirement on a tax deferred basis.⁶

Enter “Medical Banking™.”⁷ Medical Banking (MB) creates a new set of relationships between banks, the healthcare providers and the depositor/patients. MB turns on a few basic assumptions. First, employees and individual insurance policy holders opt for the HDHP/HSA insurance model, under which they make personal-health deposits that supplement (and reduce) sick-care insurance premiums. The trade-off: lower insurance premiums and higher treatment deductibles in exchange for keeping their own money under their own control as a personal health investment. Individuals bank on their own health. Second, banks receive the deposits and manage the health savings accounts, but they do more than just manage money. They recognize the investment they now have in their depositors’ health, so they become “medical banks.” Third, through their MB services, banks partner with healthcare providers to promote depositor/patient health. Such services as health coaching, geriatric care management, and health information monitoring, to name a few, will flow through this partnership. Banks profit as healthier depositors make fewer withdrawals. Healthcare providers profit as patient health measures improve and their fixed reimbursement rates-now tied to treatment outcomes and patient health-go up. Depositors/patients benefit as they become both healthier and wealthier. And the money saved on sick-care now belongs to the health earners—i. e., us!

The Community Health Consortium

In a system that provides care to those with care insurance, it should come as no surprise that as fewer people have that insurance, fewer will access care, and individual and community health will decline. This is the central argument for expanding America’s health insurance pool. For those without insurance often opt to go without the care they cannot otherwise pay for. This usually results in a worsening of conditions, which results in need for more treatment than would have been needed had the care been provided early. The result: a downward spiral in individual, community and social health.

But good community health is good economics. Every sector of our economy benefits when the collective health of a family, a neighborhood, a town or a city improves. We might think of communities as similar to a beehive. The economic activity is, of course, making honey. The more healthy bees in the hive, the more honey gets produced. Extending the analogy, economic growth (more honey) depends on community health—i. e., not just the health of those who carry bee-care insurance. Here MB will play a key role not just in improving depositors’ health, but a community’s health as well. It will do so as a key player in a new Community Health Consortium.

A community is an enclave of people in a place. Bank lobbies are a “place,” as are physicians’ offices, as are retail outlets, and so on. So it stands to reason that if economic health and community health are interrelated, if only for enlightened economic self-interest, the owners of the places that people visit for services should encourage health as much and as often as possible. A healthy customer is a good customer. Sick customers do not earn money to either save or spend or carry insurance. The MB mechanism serves as a kick-start for a set of relationships that link banking, healthcare and legal services to support community health, and thus, the economy. It requires an integrated, capitated healthcare delivery system, consumer buy-in and financial-management know-how. Here’s how it works:

Bill works as a supervisor at the paper mill. He earns a middle-class income, has a few weeks off a year, and has health insurance through the mill. His family is covered by his HDHP/HSA. His HSA is at Main St. Bank. Bill’s wife, Helen, works part-time in her own business and cares for their two children, checking in regularly on Bill’s mother as well. Bill’s mother, Marge, is getting on in years. Bill and Helen worry about Marge, who has been hospitalized twice in the last month. They are thinking of taking Marge in to live with them.

During a visit to Main St. Bank, Helen notices the flyer for the Bank’s new ElderCare Planning service, part of the bank’s commitment to helping its depositors and its community. Bill and Helen, as HSA depositors, can make a complementary appointment with an ElderCare Planner to discuss Marge’s long-term care options. They make the appointment. From the planner they learn that Marge’s care at their home could be paid for through a community program. They also receive information about managing diabetes (for Helen) and managing high blood pressure (for Bill). They learn about the importance of advance directives for Marge’s healthcare security, as well as their own, and are referred to Main St. Bank’s ElderLaw partner. Finally, they learn of the Community Health Consortium that connects all these services with local healthcare, legal and social services. They are taught of the benefits of considering membership in a local accountable care organization (ACO) that is part of their HDHP. They are also given a home care agency referral that is connected with Marge’s doctor.

Result: Bill sleeps better. Helen manages her diet better. Marge feels more secure. And the bank, the elderlaw attorney, the home care agency and the physician group (ACO) create a healthier community-sustainably and profitably.

And Helen tells two friends, and they tell two friends. . .

Creating the Future

In truth, there are no social-service, healthcare or financial-service “systems” that live on their own. Every socioeconomic “system” is a set of agreements between human beings. To function properly, these “agreements” rely on resources. And every resource is interlinked in community-from the emergency room, to the bank lobby, to the grocery store, to the high school classroom. In synergy, the total effect of these interrelated resources is far greater than the sum of the individual parts. The key to success in any endeavor is channeling the resources to the greatest synergistic effect. Synergy means 1 + 1 + 1 = 4. Medical Banking™ is “1.”

Creating a Community Health Consortium is a health-care/banking/community service model that costs little, but will lead to much. It involves a novel use of “place” to facilitate greater efficiency in already-existing activities (healthcare, banking, planning, family care coordination, etc.) that are not currently achieving their best outcomes. At the core, Medical Banking™ is a critical component. It holds great promise as a value innovation in banking, improved healthcare, health management and, ultimately, healthier, wealthier communities.

References

¹The Innovator’s Prescription. Clayton B. Christensen, Jerome Grossman and Jason Hwang. McGraw Hill Publishers. New York, NY. 2009

²The Economics of Health Reconsidered. Second Edition. Rice, Thomas. Health Administration Press, 2003, 342 pgs.

³“Myth: User Fees Would Stop Waste and Ensure Better Use of the Healthcare System,” Canadian Health Services Research Foundation. Eurohealth 11(1), 2005

⁴PNHP Fact Sheet: Health Savings Accounts – No Savings. Physicians for a National Health Program. Chicago, IL. http://www.pnhp.org/facts/hsa.pdf. Accessed 2/9/10.

⁵“A Survey of Preventive Benefits in Health Savings Account (HSA) Plans, July 2007.” AHIP Center for Policy and Research. Washington, D.C.

⁶US Dept. of the Treasury, Office of Division Counsel/Associate Chief Counsel (Tax Exempt and Government Entities) Notice 2004-50, Health Savings Accounts-Additional Qs&As. http://www.treas.gov/press/releases/reports/hsanotice200450072304.pdf. Accessed 2/9/10.

⁷Medical banking is a trademark of the Medical Banking Project (a.k.a. MBProject). Readers are referred to http://www.mbproject.org and http://www.ccnhelp.org to learn more about the Medical Banking Project and how healthcare and banking are on convergent paths.

About the Author

Joseph A. Jackson, LICSW, is CEO of EquaCare, Inc., Lenox, Massachusetts.

SWIFT (Society for Worldwide Interbank Financial Telecommunications) is sometimes referred to as the “UPS” of financial transactions because of its extremely tight security, guaranteed delivery, non-repudiation, and global standard message formats. Now that SWIFTNet has opened itself to the corporate market, could it be a natural fit for the intersection between financials and healthcare?

SWIFT has been around since 1973 and claims never to have lost a message. Outside of banks and some corporate treasury groups, it is the little known, yet very critical global bank messaging network connecting over 8,800 financial institutions. SWIFT offers standardized messaging for a multitude of transactions ranging from high and low value (bulk) payments, trade services, electronic bank statements, securities and FX settlement, and some nifty new features like the emerging bank account management (eBAM) and even SWIFTMail for secure document exchange.

The importance of global cash management and the interconnectedness of financial markets became painfully obvious watching the “domino effect” between the U.S. mortgage crisis and other global economies. U.S.-based corporations across all industries continue the trend toward off-shoring which began in India and has now expanded to China, the Philippines, and other areas. If SWIFT is already a trusted and global financial exchange, and we expect demand for global healthcare infrastructure to increase, maybe it is time to explore whether SWIFT is a fit for fast, secure transmission of healthcare information that is not reliant upon getting to a single standard format for the record contained inside.

SWIFT Goes “Corporate”

If SWIFT had never opened its doors to corporations, it would have remained the little known private banking network it was originally meant to be. For several reasons however, SWIFT leadership voted nearly unanimously in 2006 to allow a standardized corporate access model (SCORE). This new access model has generated considerable interest and resultant signings from multinational corporations such as GE, Microsoft, Merck, eBay/PayPal, Caterpillar, Intel and Chevron to name a few, and for good reason. First of all, global liquidity management has never been more critical than it is right now. Corporate treasury groups are pressured to squeeze margins out of their cash portfolios, achieve near real-time global visibility to cash positions, simplify international bank account management, optimize foreign currency exchange for payments and receivables, and centrally control their assets. With SWIFT access, they now have a single pipe for transmitting data from the corporation to the global bank or financial institution. This secure pipe has even more appeal when looking at the plethora of existing bank connection types used today by many corporations, which include a hodge-podge of FTP (File Transfer Protocol), Internet, leased lines, fax, pedaling messengers, etc., with few if any message standards for exchange of data. With the average corporate bank connection cost hovering around $25,000/year, most larger corporations can make a strong business case for joining SWIFT based on just connection simplicity alone. From a pure message cost perspective, SWIFT is a non-profit and is owned by global banks. As such it rewards members with rebates as more members join and use the network. Sweetening the strategic business case, SWIFT is piloting and driving most of the global financial exchange standards such as ISO20022 and using them on emerging exchanges such as SEPA. (Single European Payments Area). Some fast facts include the following:

• The growth of worldwide financial transactions is two times that of worldwide gross domestic product (GDP) growth.
• Standards and regulations both in the medical information and financial arenas are forcing better traceability, exchange standards and privacy compliance in support of SOX and HIPAA.
• SWIFT has seen a tenfold increase in the number of corporations connected in just the past four years (mostly due to the simplified SCORE model).
• SWIFT is seeing heavy growth in corporate treasury markets, payments, and securities. Many corporate payments are for employee benefits, payroll, and other A/P.
• The Fed Bank system has begun including key new remittance matching data in all Fed wire transactions which will further enable “straight-through processing.”
• SWIFT FileAct (mostly for bulk payments) is growing 500% a year in corporate usage and leverages XML as the message schema.
• The SWIFT network has seen increased traffic and remains highly secure:
  • 3.5 billion messages per year
  • 8,800 + customers
  • Average daily traffic of 15.2 million messages
  • Peak day of 17 million messages
  • 99.999% network availability
  • 24/7/365 “follow the sun” support.

Contrasting SWIFT with Medical Banking Evolution

The complexity of the global financial ecosystem seems relatively simple compared with the current state and requirements for the healthcare community. Standards of any kind are less pervasive and yet the demand for secure network transport and straight-through-processing is huge. The national and global focus on streamlining healthcare access, clinical data, insurance, payments and records management coupled with the high security requirement represent a daunting challenge.

Some so-called standards exist in the area of medical payments and data needed for remittance and record transfer today. HL7 (Health Level 7), for example, is an all-volunteer, not-for-profit organization of collaborating healthcare experts and scientists that prescribes electronic interchange guidelines. Next there is the CCR (continuity of care record) developed by yet another standards institution called ASTM along with MMS (Massachusetts Medical Society) and others including HIMSS. This standard format has been adopted by Google Health. In addition, there is the CCD (continuity of care document) which is an XML-tagged format developed to appease the middle-ground between CCR and HL7. On the transactional exchange side there are the common EDI 270/271 (for eligibility) and 837/835 (for claim and remittance) message sets from yet another standards group ASC (Accredited Standards Committee, which is chartered under ANSI to provide EDI message standards), and lastly the ISO13606 from the International Standards Organization for the electronic health record. If arriving at a standard medical record is a requirement for free exchange of medical payment and claim information, it may never happen since there are many variations domestically, let alone globally.

Unlike in global financial exchange where the core data elements are relatively finite, healthcare innovation drives ever-changing procedures, codes, billing methods, tests, regulations, and emerging treatments for many of the same clinical problems. Even though global banks and exchanges are adopting the ISO20022 financial standards, the banking community has not exactly embraced anything to do with HIPAA compliance standards, while demand for medical banking instruments such as HSAs (health savings accounts) continues to grow. Meanwhile, medical payments and highly secure medical information exchange is becoming more and more critical and still the two have yet to be combined in any meaningful way. It is difficult to imagine the Internet and ACH networks handling the volumes, standard exchange, and security needs of such record transfers. Could SWIFT become the transport for medical payments and other medical records management for correspondents? To answer that, we must take a closer look at the healthcare industry requirements for messages and transport and compare it to what the SWIFT network use case scenarios might be. There are really two major parts to secure messaging exchange: the message itself and the transport process (network exchange).

1. The Message – Includes defined fields, data, and a schema with associated taxonomy reference. The message can be broken down further into key components similar to a regular mail letter.
   • The Header – Analogous to an address on an envelope for sending a bill, payment or other invoice detail. We can use the header of the message to include enough information about the contents and destination to allow for proper routing, delivery, and description similar to what you might find on a FedEx tagged box.
   • The Payload – Analogous to the contents of the envelope or box which may contain multiple invoice items, multiple line items for payment, item level tracking detail, remittance detail, fees being charged etc.
2. The Transport – How the message will be sent and received on a given network or electronic ecosystem. This includes handling logic such as secure access, routing, business rules, parsing for assembly and disassembly, and error handling based on the header information.

Enter SWIFTNet FileAct!

SWIFT FileAct – XML

FileAct is SWIFT’s payload-agnostic secure message delivery service. Unlike older SWIFT formats such as the “MT” series in which the message and routing information were combined and the capacity of the message was relatively small, FileAct is more like an “electronic box” where the header represents a bunch of information about what is in the box but does not expose the actual content to anyone except the sender and the receiver. The header includes the usual routing instructions, item count, and fee agreement information, and some descriptive information about the content which so far has been primarily around bulk payments. With a new service profile, however, it could just as easily be used for defining medical banking information (EOB, CCD/CCR, 835, remittance data, etc.). In this model, either the size of the file or the count of the transactions in the file can be used to assign proper billing charges. At first glance, since the contents are non-standard, many may see that as a limitation. However, since virtually all participants in the healthcare supply chain use their own formats or variations of so-called “standards” anyway, yet still require guaranteed secure delivery and variable sized content, FileAct seems like a Utopian fit!

Health Vaults/Network Storage

The emerging sector of so-called “cloud computing” has a material application in the form of “health vaults.” Major software companies such as Microsoft (HealthVault) and Google Health offer record storage centers for patients to keep their history in a central place and share them with providers. These vaults allow for software providers to write applications to use the data or functions of the vaults but it still remains the patient’s responsibility to create and maintain their information. When looking at the security issues surrounding the transfer of medical records and resultant HL7, HIPAA and other compliance measures, it is easy to see why providers cannot and will not take an active role in putting records into a patient’s vault. Assuming that we will never achieve any global or even national standard record format, and patients are hardly in a good position to maintain a system of record for their own medical history, treatment, payments, etc., it seems logical that the best solution is one that does not force a standard format, but is payload-agnostic while remaining highly secure and standardized in its message protection and delivery!

Naturally, any central location solution offering physician-based transfer, upload of bulk records for EOBs from corporations and insurance providers, or pretty much any other medical banking business process would require specific “opt-in” of the patient. SWIFT would be secure enough to guarantee message delivery of the package, while not interrogating nor allowing others to interrogate the secured payload. If regulation hurdles result in delays for approval of “provider-to-vault” physician transfers, just the volume of B2B transactions if sent over SWIFT would be huge. B2B often drives B2C adoption in many markets, so it follows that corporate payments for medical benefits, insurance payments, EOBs, group invoicing, payment remittance and settlement of the financial side would be a large crack in the medical banking nut.

Is There Value in a Single Pipe?

The value of a secure, single tunnel system for health information seems valid. For example, when trying to send EDI835 messages today, members use whatever spaghetti infrastructure method they have in place for connecting. Usually these consist of fax, Internet, CD-ROM, diskette, tape, physical paper mail, or RAS. All of these choices suffer from one or more of the following shortcomings:

1. Non-standard;
2. Varying delivery performance;
3. Varying security application;
4. Lack of guaranteed delivery;
5. Significant manual intervention for processing; and
6. Lack of guaranteed non-repudiation.

Without fully calculating the impacts, it stands to reason that there is a cost associated with these shortcomings in the form of manual processing, longer collection cycles, high error rates, and maintenance costs of proprietary message infrastructures that do not communicate with each other. SWIFT, on the other hand, is standardized, pervasive and trusted by financial institutions, highly secure, offers guaranteed delivery, and of course is heavily audited. If implemented correctly it offers full STP (straight-through-processing) between member counterparties in both store and forward and near real-time modes.

The Last Mile

In the banking industry, the counterparty agreements for the exchange are the official record of what each sender/receiver are prepared to process in terms of formats. By ignoring the massive task of trying to get to a single standard health record, and instead focusing on just correct, standard and reusable transport, routing and delivery, the industry would have its first-ever platform for universal health records exchange. It would be the equivalent of making standard tags and container sizes for loading export commodities on ships. The container shape, size, construction, loading and unloading hooks and transport regulations around them would be standardized while the content within them still varies greatly allowing the sender and receiver to use their own business relationship to drive the format requirements they need. If we were to compare international healthcare payments and records to the shipping industry today, we would have ski boats, rafts, yachts, tankers and submarines carrying every piece of health information, every document size of every kind of patient in every size of container all over the planet. There would be no standard “ports of call” with the necessary security, infrastructure and procedures for packaging, loading and unloading the goods. If we look at the health information exchange (HIE) as a “port-of-call,” this could launch the global exchange ecosystem for medical banking.

There are a few hurdles that would need to be addressed before SWIFT could support bulk or individual medical payments or other health record information within FileAct. For one, SWIFT members must be either financial institutions, or part of an FATF (Financial Action Task Force) member country. (See http://www.fatf-gafi.org) At last count, 43 of the major trading countries are part of the FATF and recognize the importance of AML (anti-money laundering) protections. Recently, the rule that corporate members had to be publicly traded was relaxed. Today, some major pharmaceutical companies, some insurance corporations and of course most major banks are already on SWIFT and more are in the process of joining. Secondly, a pilot project is needed to prove the following:

• SWIFT can actually support estimated volumes and package sizes now or in the future.
• SWIFT would be willing to create defined service profiles for FileAct headers that would contain healthcare industry relevant payloads (e.g., a new FileAct header profile for EOBs).
• The business scenarios for use on the network could be written such that they clear the SWIFT rules against corporate-to-corporate messaging (e.g., a bank or other financial institution must be either the sender or receiver unless SWIFT relaxes that rule at some point). Still, for the financial exchange scenarios, a financial institution would always be involved.
• The cost and complexity of joining SWIFT is something the healthcare counterparties would be willing and able to embrace. (SWIFT requires some skill sets to set up and administer the network components and the straight-through-processing to line-of-business applications.) This specific hurdle could be aided by both the use of existing service hubs that are “SWIFT Ready,” and for smaller volume users, the newly launched “SWIFT Alliance LITE” offers a token-based Web connection directly to SWIFT through a client workstation.

It is clear that there is demand for such a secure healthcare network service similar to what SWIFT does for financials. Since SWIFT has 26 years of developing the network delivery points, security and expertise, it seems easier to make use of SWIFT rather than attempting to create from scratch anything with the kind of global reach and security it already has. Lastly, since SWIFT is a non-profit consortium, message costs decrease as traffic increases and that is returned in the form of member rebates.

About the Author

Peter W. Lang, is the President and a principal consultant of Trellis Integration Partners, a firm based in Kirkland, Washington, that specializes in consulting and integration services for corporate access to SWIFT. He has over 16 years of experience serving in a variety of functions such as enterprise architecture for Global 1000 corporations, program management, and IT governance. Peter holds a masters of business administration degree from Pepperdine University and is Microsoft certified on BizTalk Server and SharePoint Server.