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Intermountain Readies Tests For Hereditary Cancer Syndromes

Posted on February 23, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or

Intermountain Healthcare has begun the process of validating and launching several tests designed to identify disease-causing hereditary genetic patterns. The work will be done through Intermountain Precision Genomics, which analyzes a patient’s genetic makeup. The data is then used by a team of molecular tumor specialists to plan a patient’s specialized course of treatment.

In a prepared statement, Intermountain notes that one area in which genetic testing can be particularly fruitful is in women with a history of breast and ovarian cancer. The statement cites a study noting that fewer than one in five individuals with a family history of breast cancer or ovarian cancer meeting certain guidelines have undergone genetic testing. Moreover, most have never discussed testing with a healthcare provider.

In its efforts, Intermountain hopes to find both individuals previously diagnosed with cancer and healthy individuals with hereditary cancer gene mutations. When these individuals get genetic counseling and testing, it sets the stage for them to get more frequent cancer screenings at younger ages, which in turn leads to critical early detection and treatment of many of these cancers.

In investing heavily in cancer prediction and treatment, Intermountain is hardly alone. What once was at best a specialty practice by cancer-specific hospitals is quickly becoming mainstream.

The practice of screening women for genetic triggers that might boost the risk of certain cancers has moved quickly from idea to action among hospitals. I don’t have a number to hand, but I remember reading that it can take decades before a scientific discovery in healthcare actually impacts patients.  Clearly, the growth of precision medicine is a dramatic exception.

Given the increasing benefits to be had from genetic testing and targeted treatment, we are seeing nothing less than an explosion in awareness and investment. Not surprisingly, hospitals are jumping into the market with both feet as, to be a bit crass, there’s a lot of money in effectively treating cancer.

Of course, some of the buzz around precision medicine may turn out to be just that, buzz. As my colleague has pointed out, EMR systems weren’t built to enable precision medicine, but rather, billing engines. He also notes that these systems aren’t built for real-time availability of data analytics, which makes it hard to use them for personalized medicine. As he puts it, “I’ve heard precision medicine defined as a puzzle with 3 billion pieces.”

Still, as a middle-aged lady with a history of cancer in her family, these developments give me hope. Someday, genetic testing like Intermountain’s will improve my care should I ever face breast or ovarian cancer. If nothing else, we are off to a good start.

Smart Bottles, Incentives & Social Support Not Enough for Adherence

Posted on July 10, 2017 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

The Journal of the American Medical Association recently released the results of a study that looked at the effect of technology and behavioral interventions on patient outcomes following a heart attack.

The researchers found no significant difference between the medication adherence or clinical outcomes of those in the control group vs those that were given a combination of technologies and incentives.

According to one of the study’s authors, Dr. David Asch, executive director of Penn Medicine’s Center for Health Care Innovation, “It was a surprise. We went into this study thinking that it would be effective and it wasn’t”. Fellow author, Dr. Kevin Volpp echoed that same sentiment: “What we found was a little bit surprising and a little bit disappointing”.

The study was conducted at the University of Pennsylvania Health System (UPHS) over a span of 12 months. There were 1,509 patients involved in the study; all hospital inpatients who had experienced a heart attack and had been hospitalized between 1 and 180 days. The average age of the study group was 61 and they were all insured with five carriers who had Medicare fee-for-service arrangements with UPHS. All of the patients had been prescribed at least two daily medications (statin, aspirin, beta-blocker or antiplatelet).

The control group of 506 patients was given the standard post-discharge medication instructions and treatment. The remaining 1,003 patients were given additional tools to help them post-discharge:

  • A smart pill bottle that tracked whether or not it had been opened at the prescribed intervals
  • Participation in a daily lottery with a 1 in 5 chance of winning $5 and a 1 in 100 chance of winning $50 each day medications were taken as prescribed
  • An option to enlist a friend or family member to receive notifications if the participant failed to use the smart pill bottle twice in any 3-day span
  • Access to social work resources
  • A hospital-based advisor to answer questions and reinforce medication adherence over the phone

On the surface, the failure of this level of support and intervention is disheartening for anyone developing medication adherence technology or involved with helping a loved one recover from being hospitalized. However, if you listen to the post-study podcast or spend time looking at how the incentives/technology was administered to the study group, important clues emerge as to why this failure may not mean abandoning hope for technology-based interventions.

First, only 878 of the 1,003 patients activated their smart pill-bottles and only 70% of that same group fully participated in the incentives and technology. This indicates that the lack of adherence may not have anything to do with technology when its working, but rather that there is a challenge to get patients using that technology in the first place.

Second, the fear of another heart attack may have been enough of an incentive to keep patients on their medication regimens. Put another way, perhaps the control group already had sufficient incentive to follow their prescriptions and thus technology would have little impact.

Third, and perhaps most significantly, an average of 41 days elapsed between the time the patients were discharged from the hospital and the time they were activated on the incentive/intervention program. This delay was attributed to the delay in the insurance process. According to Dr. Volpp:

If we had been able to engage these patients earlier, for example. If this had been a hospital-based intervention and this could have started at the time of discharge [rather than weeks later], then we would have had a greater opportunity to influence these patients and change the course of their care

I personally found this last point by Dr. Volpp fascinating. This study may have inadvertently shown that the timeliness of implementing post-discharge behavior and technology incentives matters as much as the types being implemented. 41 days after discharge is a long time – almost a month and a half.

Consider this example. Say you get caught for speeding and as part of the ticket-writing process the police officer activated a reminder system in your car that (a) warned you when you were 5 miles over the limit and (b) sent a message to your significant other whenever you receive two such warnings in the same day. From personal experience I can tell you that the week after I got a speeding ticket, I followed every posted speed limit. Why? Because the trauma of getting caught was still fresh in my mind.

Now imagine the same scenario but instead of immediately activating the warning system it took until 41 days after getting your ticket. By the time the system was in place you would have already fallen back into old habits and assured yourself that you were “fine” driving the way you were.

It would be interesting to see if analysis of this study’s data revealed a correlation between the length of time before incentive implementation and adherence. Even if it doesn’t, this study holds a cautionary tale for anyone in HealthIT – timeliness of implementation may matter as much as your solution itself.

Genomics is Going to Really Blow Up Our Interoperability Issues

Posted on June 12, 2017 I Written By

John Lynn is the Founder of the blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Today I slipped over to the Precision Medicine Summit in Boston that’s hosted by HIMSS Media. I heard some good speakers which I’ll write about in the future including legal issues related to genomics and gene editing. However, this tweet from the conference really stuck with me:

This is a sad example of the reality of healthcare interoperability today. Healthcare organizations have problems even sharing something as standard and simple as a PDF. Once we have real genomic data and the markers behind them, EHRs won’t have any idea how to handle them. We’ll need a whole new model and approach or our current interoperability problems will look like child’s play.

By the time we figured that out, our proverbial child might be graduating high school.