Category: Health Care Misuse

Controlling Cheating: Health Care Payment Systems

Science predicts diagnosing and billing providers in health care payment systems will cheat. If they think others are cheating, their cheating will go up. With automated systems, people cheat more.  This is an inside-the-system problem. It is parasitic in nature, exploiting the trust required to make health care systems function.  It  doesn’t always meet the tests for fraud or corruption and mindlessly pursuing and investigations and prosecution route as the panacea of controls can destroy relationships with the very people who are the eyes and ears of misuse and abuse throughout the health care system.

Cheating should be a surprise to no one.  Biologists and zoologists discover that everything in nature cheats a little bit, from bacteria in a petri dish to humans. To believe humans have free will to refrain from “cheating a little bit” is to defy  science. It is less a question of if, than a question to what  acceptable degree? Sometimes cheating a little bit is the gateway to more serious abuses. And, if you don’t treat people with empathy, dignity and respect, it is akin to pouring gasoline on a fire.

How do we know this?

Stanford’s, Robert Sapolsky, introduces evolutionary biology at levels we non-scientist, prevention types can begin to understand.  Sapolsky’s message destroys the classical economics myth of man as a rational actor, always acting in his their own self interest, a mindset at the base of most controls systems. It no longer passes muster for anyone serious about controlling inside-the-system cheating.

Controlling inside-the-system cheating behaviour is complicated. One strategy applies the lessons of behavioural economics to nudge the right behaviours. The strategy introduced in this post is to understand and apply science on human behaviour to policies, business and monitoring systems.

I think it begins by developing a feel for one of three evolutionary building blocks of human behaviour: reciprocal cooperation (altruism).  All living organisms forgo aggression at some point when cooperation produces more optimum results. In this situation each organism has the potential to harm one of the others but doesn’t do so because the overall impact of those actions would hurt the original organism.

Robert Axelrod used computers for game theory to explore reciprocal cooperation. Biologists and zoologists  have affirmed the game theory models through observation in the natural world. Perhaps it is time to apply science to policy, guidelines, detection and harms reduction measures.

 

Modern Surveillance

Bruce Schneier is a security savant – at least in my opinion – who puts deep though into security and people. He has been writing a monthly security newsletter 1998, and has maintained a highly informative blog since 1998. He is the author of many books, ranging from cryptography engineering, to exploring trust and cooperation as the glue that holds societies together.

Mr. Schneier recently wrote a post on a move to ban facial recognition cameras and software in public places. He reflects on this and frames it withing the context of whole of modern surveillance in its many forms and aggregations to treat people differently.

Schneier’s thoughts are posted in their entirety. It is too comprehensive to summarized. Most directly related my interests at the ATRiM Group, is how significantly aggregation and brokerage of information increases the risks to critical infrastructure from dependency on identification and other documents to make business decisions. I think massive aggregation of data, the theft and brokerage of this information, and urbanization resulting in doing business with people we don’t personally know has created the perfect storm for predators.

Concerns about false personation and synthetic identity fraud range from security guards screening for physical access to nuclear facilities, to financial services companies opening new accounts and processing mortgage applications, to the issuing of health identification tokens which provide unlimited access to public health care:

We’re Banning Facial Recognition. We’re Missing the Point.

 

 

“Inside-the-system” billing abuse and predatory fraud not the same problem

Introduction

In 2016 Canada spent 10.53 % of GDP on health care benefits and services. The United States spent 17.07% of GDP.  Health care spending in Canada and the United States is ten times that of national defense. You might say, it is the largest cash dispensing sector of government. Health care is critical infrastructure (CI). It is an extraordinarily complex system with a large number of sub-parts (ecosystems). These sub-parts can be broken down to even smaller units.

In Chronic Condition: What Canada’s Health Care System Needs to Be Dragged Into the 21st Century, Jeffrey Simpson explored the options with a growing problem we have to grapple with, including cuts in non-health-care spending, tax increases, various types of privatization, and finding savings within health care itself. 

Similarly, Canada’s efforts at controlling abuse and predatory fraud lag well behind contemporaries in other single payer systems in Europe and the United States. As a smaller part of the entire system explored by Simpson, the next generation of abuse and fraud controls does not have to limit itself to reductionist thinking. It will deep dive into the inter-relatedness between parts. It can learn from the lessons of the Cory Commission in Ontario to clearly separate the culture, language and practice of billing integrity and abuse controls from going after predatory fraud by enterprise criminals and gangs.

Abuse

Efficient delivery of health care systems is built on a trust that diagnosing physicians and other health services providers will do the right thing.  It is hard to imagine a system working in any other way. Within this context, controlling billing behavior is foremost a people challenge. 

A new generation of controls considers innate behavioral traits, the role of affect (emotions) in judgment and decision making, and environmental conditions inducing unwanted behaviors. We know from science that everything in nature cheats a little bit to gain competitive advantage. When people think others are cheating, their cheating goes up. When people are reminded of their morality close to the time of the temptation, cheating goes down. Outlier (egregious – above the norms) cheating must be rationalized (the making of excuses), when mostly honest people are tempted to do bad things. The farther away from direct face to face exchange of cash, the easier it is for people to cheat (Ariely: Duke University). Finally, negative environmental conditions such as exhaustion, frustration, negative attitude and financial troubles can break down resistance to temptation. 

Automated billing systems are efficient. But, they are mostly designed without considering unintended consequences. In absence of hard work to maintain mutual respect, communicating trust and introducing mindful billing integrity strategies, online billing systems are the perfect storm for bad behavior.

Predatory Fraud

Predatory fraud is a horse of a different color. It requires a different approach than “inside the system” billing integrity. It is where the Rubicon is crossed to cold, calculated choices to attack health care payment systems for financial gain. These attacks are in two categories: “outside the system” and “inside the system”. They are in some cases separate, but can be inter-related.

Tough minded rhetoric and action on fraud , if not properly defined and managed, is counter-productive to building inside the system relationships and trust with physicians and other providers diagnosing and delivering health care. These are the people who witness misuse throughout the entire system, and whose cooperation is necessary – from fraudulent medical equipment invoices, to “pill mill” services and assistive devices/home oxygen, to rehabilitation services and hospitals.  Secondly, there is little evidence to support draconian enforcement measures as effective stand-alone deterrents to abuse and fraud.

A Formula for Effective Controls 

Think of your organization as a complex system, made up of many inter-related parts. A change to one part may have unintended consequences on another. Secondly, align subject matter expertise into billing integrity and internal investigations/counter-fraud groups as separate entities, both in reality and publicly perceived: 

  1. Inside the System Controls: Behavioral Insights teams nudge desired behaviors. Environmental threat risk assessment identifies conditions which provide rationalizations (excuses) for cheating when people are tempted to do bad things, and others which push away the “eyes and ears”- these trusted providers – from cooperation om reducing misuse throughout the health care system. Billing integrity employees are the nice folks. Their role is to bring clarity to the billing processes, to make things as least complicated as possible, and to help trusted billing providers stay out of trouble. In some cases it may involve civil recoveries from unwillingness to cooperate. If, in the course of meeting these responsibilities, egregious abuse is suspected, it is elevated for internal inquires by an “arms length” body. It is suggested that the term “investigator” be limited to those who apply the extraordinary powers of search and seizure under acts and regulations.
  2. Outside the System Controls: Countering fraud on the other hand is a nasty business. Data science teams design place/time sensitive algorithms for early detection of hot spots (geographic) and patterns (situational) that point to egregious behavior. Investigation determines if concerns meet the test of civil tort and/or criminal behavior. Situational crime prevention teams identify the egregious abuse/fraud attractors contributing to hot spots and patterns. They partner with billing integrity and other stakeholders to implement egregious abuse and fraud harms controls, often with multiple interventions to reduce the activity. Prosecution and civil recoveries are just some of the interventions applied to reducing outlier behaviors. As a result of this experience, fraud-specific ‘red flags’ are referred back to the billing integrity group for inclusion in their monitoring algorithms.  

A final thought.  Hyperbole from attitudinal surveys about the level of egregious abuse and fraud is on wobbly legs. Decision makers used to making business decisions based on numbers ‘feel’ in-authenticity. Abuse and predatory fraud controls system should be based on quantification consistent with science, and implemented in a way that makes sound business sense, rather than for security theater.

My recommendation to start is sound policy and guidelines combined with a learn by doing culture – “eating the  elephant a bite at a time” – in a situational health care fraud prevention approach that documents situation specific problems, undertakes initiatives and quantifies results of projects  in a way that financially justifies resources for tackling abuse and fraud.

Note: An inaugural health care specific  Situational Problem Solving Guides and a Situational Health Care Fraud Prevention Matrix with harms reduction strategies in five categories has been developed based on best known situational crime prevention practice.  The model is a problem-solving approach for the health care sector detailed in Part 4 of Malcolm Sparrow’s book: “A License to Steal: How fraud bleeds America’s health care system” [2002]. Dr. Sparrow is a professor at  at the J.F. Kennedy School of Government, Harvard University.