6 Things Happening in Healthcare Technology NOW
I was asked to join a panel for ASAE's Annual Meeting in Toronto, ON called What's Keeping Healthcare Executives Up at Night? and to put together the technology part of the program. This post is inspired by that work (or did that work inspire this post?).
What I was reminded of after conducting my research is how technology is being applied toward the greater good. This is in contrast to how we're most often exposed to technology every day: buying and sharing things, helping us do our jobs better (productivity), or entertainment.
I'm glad there are really smart people working on these important advancements. There are also some practical issues that healthcare providers face like any other business and that's part of the technology discussion, too. Read on to learn more.
Blockchain Medical Record Storage
Once data is recorded in a block, it’s linked permanently to the block before and after it - it can’t be altered after the fact without also altering all the other connected blocks.
Blockchains are often associated with cryptocurrency (e.g. Bitcoin). A blockchain can be used to contain any type of data, however. A “block” is simply a chunk of data. Blockchains are particularly well suited to permanent event-based data (e.g. medical records, transactions) because each block’s integrity is verifiable: a block is only valid if it’s connected with the block before and after it.
Medical record storage is clunky at best: expensive, repetitive (same patient, different providers), and difficult to secure. Blockchains aren’t stored in one spot, they’re distributed across many systems and maintained by groups called data miners (health care organizations, in this case). The data miners each have copies of the block and use specialized calculations to determine the information needed to create the next block. This makes them inherently secure since a perpetrator couldn’t just adjust one copy of the blockchain.
Each block can also be encrypted and unlocked with a password known to the patient giving the patient complete control over their records. The positive implications for cost control, security, and data integrity with blockchains for healthcare in the US and worldwide is staggering.
Physician Reputation Management
Hotels or IT consultants (ahem) can easily change their name in the wake of online reputation damage… you’re out of luck if you’re a practicing doctor, however. Artificial intelligence (AI) systems made by Salesforce and other competitors like Microsoft are capable of recognizing negative language in posts to social media and doctor review sites (e.g. Healthgrades, Yelp) and will route alerts to staff so they can respond.
Doctors must maintain patient confidentiality online so those responses need to made carefully. Writing Mr. French is upset I wouldn’t prescribe that drug yet I couldn’t due to his history of liver disease just isn’t possible. Even if it was, the best course of action is very non-technical: take the high road and use empathy and communication to address concerns. In IT, any project is 80% governance and 20% IT. The same ratio could be applied to the patient/doctor dynamic: 80% communication and “soft” needs (friendly staff, low wait times, easy parking) and 20% actual administration of healthcare.
Firms have sprouted up that offer reputation management for medical professionals (e.g. IHealthSpot, Empathiq) yet they’re no substitute for good old fashioned diplomacy. Seeing a reasonable response from the doctor to a negative review goes a long way toward putting a prospective patient at ease.
Smartphone Health Data Collection
Your smartphone contributes to the dissemination and consumption of traffic data [better take the HOV lanes to work today!]. It can do the same for medical research. Easier opt-ins and the ability to track participants for longer test periods have put a fresh perspective on the medical research landscape. Apple set the standard with its ResearchKit, an open source app development platform for iOS that allowed scientists to collect data from participating users’ iPhones (ResearchStack is the Android equivalent - created by Cornell University).
One issue with traditional medical studies is their geographic concentration around research institutions and participants’ honesty in reporting health-related issues. Smartphone-based collection solves these problems. With larger pools of research participants also comes larger pools of dropouts, however. Experimenting with showing users how they stack up against other participants is one way researchers are looking to curb turnover. GlaxoSmithKline is the first mainstream pharmaceutical company to carry out a smartphone-based study (on rheumatoid-arthritis fatigue, joint pain, and mood). At the time of writing, the results of the study have yet to be published.
Artificial Intelligence (AI) Drug Development
AI promises to speed-up the drug development process which could bring not only new drugs to market faster (to address an urgent need/pandemic, for example) but also bring innovative drugs to market that would otherwise not have made it at all (e.g. lopsided expense/risk to success/FDA approval ratio).
Computers can uncover patterns that humans may miss or may take longer to recognize. They can also crunch, for example, hereditary data to identify probability that a medicine would help a particular patient base which drives pharma companies toward or away from further investment in a new drug.
During the R&D process, AI can help determine which group(s) should be targeted for clinical trials (i.e. are likely to have the most success) which could clear a nice path for FDA clearance later. For example, if Native Americans are particularly responsive to a new drug in AI trials it makes sense to recruit Native Americans for FDA-mandated human trials.
The key differentiator between traditional drug trials and and AI ones is that there isn’t an up front hypotheses. Instead, the collective patients’ data creates the hypotheses. If you’ve followed AI and medicine previously, you may be saying AI is nothing new. The difference now is how the technology is being applied: not just to determine if a drug may attack a certain cell (for example) but also how that drug may affect a particular patient (e.g. 62 year old, male, Latino). Will AI revolutionize drug making so that a particular drug may have a dozen or more variants - each treating a different population of patient?
Digital Depression Therapy
Depression afflicts 300 million people worldwide yet only a fraction of those seek help. Mobile apps can cut through the social stigmas, cost, and other barriers. Using the internet to treat depression isn’t new - clinical psychologists did it in the early 2000s. The problem was the medium: how to inspire patients to check into a website or reference downloaded materials? This required a very deliberate act and one that had to be repeated with regularity to be effective.
Self-service treatment, if you will, comes with its own champions and dissenters. Everyone seems to agree, however, that getting some form of help is good. In the UK, a stepped approach to treatment is widely accepted (e.g. Step 1, see a professional; Step 2, try using an app; Step 3, in-person therapy).
Apps such as Ginger.io, Joyable (iOS only but also available through their mobile friendly website), and Lantern have sleek interfaces and are backed by big names. PsyberGuide is run by the One Mind Institute and is a round-up of hundreds of mental health apps, depression or otherwise, complete with ratings.
A unique player in the space is Koko which integrates with popular services like Twitter and Facebook Messenger. Post a concern or question to it and get support from others facing similar situations or get referred to those who can help. Koko started as a project at MIT and has evolved with support from several important academic institutions.
Mobile App Chronic Disease Management
Many of us are bad patients. We don’t listen to doctors’ orders, we skip a treatment step here or there, and we aren’t honest about what we’re up to. Sometimes it’s not our fault, though. It’s overwhelming for those who suffer from a chronic disease to keep track of all the medications, the appointments, and rigors of treatment every day. The low barrier of entry, thanks to the proliferation of mobile devices (particularly in emerging markets), makes using mobile apps a very attractive addition to health professionals’ treatment toolbox.
Patients get to take control of their own health and doctors get the data to see what’s working and why. As noted earlier in this article, with AI drug development, mobiles apps have the capability of delivering a personalized patient experience in contrast to the one-size-fits-all “do this” sheet we’re accustomed to receiving and putting on the fridge.
The most successful apps help those that suffer from heart disease, diabetes, high blood pressure, and pulmonary disease. With each ailment, research has shown the positive outcomes apps generate: lost weight, less missed medication, and fewer rehospitalizations (yes, this is a word) among other things.
Summary
Mobile devices will revolutionize healthcare in ways we haven’t truly appreciated yet. Healthcare providers continue to feel the squeeze - less time to spend with patients and less money from insurance companies for the time they do spend. As a result, patients will find themselves in the driver's seat more (e.g. controlling their treatment, medical records). Additionally, advances in AI will lessen the burden of bringing new drugs to the market, eventually making prescriptions more affordable for everyone. Now if we can only figure out how to make the food better in the hospital cafeteria...
- This post based on stories presented in the Wall Street Journal Journal Report on Health-Care Technology, June 26, 2017