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Gaming Healthcare Delivery

May 4, 2012 2 comments
Patient Non-compliance: What is the Cost?

Do you take your medicine? It’s a very important question. When patients don’t take their prescribed medication the costs are enormous – not just to the patient but to the health system.

A 2011 study by Capgemini shows a 40% drop in refills for prescriptions after the first six months, resulting in more than $300 billion of unnecessary costs to the healthcare industry each year.   Studies conducted by the World Health Organization, the NIH and others support this result.

This is not a new problem, but with healthcare consuming almost one in five dollars in this economy, real solutions to patient non-adherence are necessary. One promising approach is making a game of medication.

How does gaming work? Three key elements work to engage the user:

  • The challenge to adopt healthy behaviors
  • win condition where events and accomplishments combine to enable success
  • Rewards and  feedback that reinforce positive feelings
Turning Diabetes Treatment into a Game

Let’s look at an example. Treatment of Type 2 Diabetes consumes over 25% of the world’s healthcare expenditure. Roughly 50% of patients fail to meet their blood sugar goals. The main reasons are failure to take their medicines and failure to change their behavior around diet and exercise. Glucose level monitoring and tracking is painful and boring. Diets don’t “feel good”, and wellness by itself is not a sufficient motive for many patients.

Proteus Biomedical from San José, CA is testing a new approach which uses technology to automate most of this process and gamification to create incentives for compliance.  Patients take a pill with a unique computer chip made from food ingredients. This pill senses the patient’s vital signs and transmits this data to a patch worn on the skin. Once the patient gets within 30 feet of their mobile phone data streams are captured and automatically and securely shared with the network of caregivers chosen by the patient. This might be family, friends or their physician – the people most influential in their care.

Proven Medications Plus Technology

This system, “Equa” enables tracking and display of summary and longitudinal data on the cell phone so that patients understand the relationship between behavior and health outcomes.  It uses the data collected and tracked on the phone to educate and motivate the patient. It’s a three-step cycle to frame what is known, prompt an action and reinforce the belief.

The games are Power Challenge Personal (PCP) and MedMatch.  PCP uses a system of tracking heart rate, fitness and sleep goals within a group of “contestants”. There are points earned, a leader board and prizes such as gift certificates to a sporting goods store for best in class accomplishments.  MedMatch uses altruism for adherence. Healthy behaviors result in charitable donation.  Every 20,000 steps walked results in donating a pair of shoes to children in need. Every six hours of sleep a night results in donating a blanket to a homeless shelter. Every medication pill taken on time results in donating a pill.

Are these approaches sustainable over the long term? Just ask anyone who has played and tired of a video game after a time. Social elements which share outcomes data with family and friends is key to maintaining interest. And hopefully the benefits of feeling better will keep patients engaged. But keeping games fresh and engaging will be a challenge.

This will be an interesting space to watch, and perhaps play in over the next several years.

What is your opinion? Is gamification a viable long term strategy to improve patient compliance and health outcomes? Or is it a fad? Click on comments link above to share your view.

Genetic Testing – Should Your Insurer Know the Results?

April 27, 2012 4 comments
Genetic Testing is in Your Future

Genetic testing is the cornerstone of personalized medicine. It enables physicians to understand whether a patient’s DNA makes them more susceptible to certain diseases.

Currently patients with family history of various cancers are genetically screened for them. In the future, genome sequencing may become part of the screening that babies undergo after they’re born. This raises a number of ethical issues:

  • who owns your genetic information?
  • who has access to it?
  • where is it stored?

After a recent blog post, “Personalized Medicine in 3 – 5 Years?”  I received questions from readers on how results of genetic testing might affect their insurance coverage. They expressed concern that if insurance companies know their genetic weaknesses, they will raise rates or deny coverage.

The Law: Genetic Testing Nondiscrimination Act

The good news is that in the US, it is illegal for health insurance companies use genetic information to set rates or deny coverage. It is also illegal for employers to use genetic information in their employment, promotion or compensation practices. The law passed in 2008 and took effect in 2009. The name of the law is the Genetic Information Nondiscrimination Act or GINA.

Under GINA, health insurers can not ask any questions about genetic testing as part of the application process, at renewal or as part of any health screening or wellness program, if there is a penalty or benefit associated with those questions.

Importantly, this includes any discussion of family history. If your health insurer or your employer questions you about whether your father smoked, had a heart attack or if your mother had breast cancer, they violate GINA.

GINA applies only to health insurers and employers. It does not apply to long-term care coverage or life insurance. This is because of something insurers call “adverse selection“.

An example of adverse selection – someone learns they are likely to die at an early age, then buys large amounts of life insurance to assure surviving family members’ security. The insurer, unaware of the high risk plan member, cannot adjust its pricing to the risk profile. This hurts the rest of the policyholders in that insurance pool whose rates will rise to fund higher claim payments.

When Your Insurer Can See Your Results

Be careful; there are circumstances when a health insurer can ask that an individual undergo genetic testing and share in the results.

Sometimes the choice of proper treatment depends on a patient’s genetic makeup. In that case, to decide whether the treatment is medically necessary and whether the insurer will pay for the treatment, genetic testing is needed.

If the patient refuses to take the test before taking the treatment, the insurer can refuse to pay the claim. However, the insurance company can only see the information needed to decide the proper treatment and payment.

This is a very complex arena, and I don’t pretend that I am an expert.

The best advice is to discuss these issues in detail  before being tested. Understand your options for sharing and storing this information. Talk with your doctor, the testing company and finally, discuss with your family.

If your insurer is requiring the test for medical appropriateness, understand what information they will see and get a written statement from the insurer that the request is permitted under GINA and that it will not affect your rates or coverage.

For more detailed information go to this link at The Genetics and Public Policy Center, Johns Hopkins University.

What’s your opinion? Should genetic information be shared with insurance companies? Should your employer have access to this information? Post a comment and share.

photo credit: Cave of Knowledge

Related articles

Personalized Medicine in 3 – 5 Years?

March 23, 2012 30 comments

Healthcare Delivery Symposium

The optimism was overflowing at the Aspinwall Symposium at WPI yesterday.  The healthcare transformation is on with distributed care, quality payment models, analytics and big data on display.

Most interesting were the panel presentations and discussions. Recently I wrote about the need to accelerate building our health information infrastructure nationwide. This enables a faster transition to digitized health records, I argued.  The news for me at this conference is that an interoperable  infrastructure in the traditional “plumbing” sense may become less important.

Distributed Care Models

David Dimon at EMC spoke about the growth of distributed care models which rely on an “exostructure”. Virtual data centers enable caregivers to connect with patients in a variety of settings outside the doctor’s office or hospital.  Monitoring patients vital signs at home is certainly less expensive than at the hospital and may change some treatment protocols around length of stay.

Dale Wiggins, CTO of Phillips Patient Care and Clinical Informatics shared an example of how one distributed care model works. Phillips eICU is a virtual Intensive Care Unit. Its aim is to end the need for multiple, highly trained and highly paid Intensivists – the physicians who specialize in the care of ICU patients.

The center of the eICU is a cockpit where an Intensivist works, monitoring patients’ vital signs and video real-time over distance.  This model extends the ability to dramatically improve outcomes, particularly among patients in more rural settings. The eICU is now deployed at UMass Memorial Hospital system.

The next logical step is to extend the ICU to the home, reducing readmission during the critical 30 day period after release from the hospital.

Analytics, Predictive Informatics and Big Data.

Robert Friedlander IBM Master Inventor spoke about the promise of breakthroughs in distributed data processing create massive computing power. Google’s open source MapReduce framework and its successor Hadoop have given researchers in biotech and pharma an unprecedented ability to query very large data sets quickly and with great flexibility.

Prior to Hadoop, a large data set like the human genome was impossible to analyze and query in-depth. Relational databases are  efficient with tabular data. Medical research requires analysis of very large  “heterogeneous” data sets which don’t fit into tables.

Medical breakthroughs can happen by applying predictive analytics which involve many complex queries of these massive data sets.  All this happens easily and relatively inexpensively through distributed massively parallel processing powered by Hadoop and MapReduce frameworks.

Bob predicted that these technologies may radically change the way healthcare is delivered and in the foreseeable future. “The promise of truly personalized medicine may become a reality in the next three to five years.”

Can the healthcare system handle that kind of disruption? Let me know your thoughts.

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