May 26, 2015
IT-centric notes on the future of health care
It’s difficult to project the rate of IT change in health care, because:
- Health care is suffused with technology — IT, medical device and biotech alike — and hence has the potential for rapid change. However, it is also the case that …
- … health care is heavily bureaucratic, political and regulated.
Timing aside, it is clear that health care change will be drastic. The IT part of that starts with vastly comprehensive electronic health records, which will be accessible (in part or whole as the case may be) by patients, care givers, care payers and researchers alike. I expect elements of such records to include:
- The human-generated part of what’s in ordinary paper health records today, but across a patient’s entire lifetime. This of course includes notes created by doctors and other care-givers.
- Large amounts of machine-generated data, including:
- The results of clinical tests. Continued innovation can be expected in testing, for reasons that include:
- Most tests exploit electronic technology. Progress in electronics is intense.
- Biomedical research is itself intense.
- In particular, most research technologies (for example gene sequencing) can be made cheap enough over time to be affordable clinically.
- The output of consumer health-monitoring devices — e.g. Fitbit and its successors. The buzzword here is “quantified self”, but what it boils down to is that every moment of our lives will be measured and recorded.
- The results of clinical tests. Continued innovation can be expected in testing, for reasons that include:
These vastly greater amounts of data cited above will allow for greatly changed analytics.
- Right now, medical decisions are made based on research that looks at a few data points each for a specially-recruited sample of patients, then draws conclusions based on simplistic and questionable statistical methods.
- More sophisticated analytic methods are commonly used, but almost always still to aid in the discovery and formation of hypotheses that will then be validated, if at all, using the bad old analytic techniques.
- State of the art predictive modeling, applied to vastly more data, will surely yield greatly better results.
And so I believe that health care itself will be revolutionized.
- Diagnosis will be much more accurate, pretty much across the board, except in those limited areas where it’s already excellent today.
- Medication regimens will be much more personalized. (Pharma manufacturing may have to change greatly as a result.) So will other treatments. So will diet/fitness regimens.
- The vulnerable (elderly, hospital patients) will be more accurately and comprehensively monitored. Also, their care will likely be aided by robotics.
- Some of the same things will be true of infants and toddlers. (In other cases, they get such close attention today that I can’t imagine how it could be greatly increased. 🙂 )
I believe that this will all happen because I believe that it will make health care vastly more successful. And if I’m right about that, no obstacles will be able to prevent it from coming into play — not cost (which will keep going down in a quasi-Moore’s-Law way), not bureaucratic inertia (although that will continue to slow things greatly), and not privacy fears (despite the challenges cited below).
So what are the IT implications of all this?
- I already mentioned the need for new (or newly-used) kinds of predictive modeling.
- Probably in association with those, event detection — which in many but not all cases will amount to anomaly detection — will be huge. If one goal is to let the elderly and ailing live independently, but receive help when it’s needed — well, recognizing when that help is needed will be crucial. Similar dynamics will occur in hospitals.
- And in support of that, there will be great amount of monitoring, and hence strong demands upon sensors and recognition. Potentially, all five human senses will be mimicked, among others. These technologies will become even more important in health care if I’m right that robotics will play a big role.
- Data quality will be a major challenge, especially in the doctors’-notes parts of health records. Reasons start:
- Different medical professionals might evaluate the same situation differently; diagnosis is a craft rather than a dumb, repeatable skill.
- If entries are selected from a predefined set of options, none may be a perfect match to the doctor’s actual opinion.
- Doctors often say what’s needful to have their decisions (care, tests, etc.) approved, whether or not it precisely matches what they really think. Thus, there are significant incentives to enter bad data.
- Free-text data is more central to health care than to many other application areas, and text data is inherently dirty.
- Health records are decades later than many other applications in moving from paper to IT.
- Data integration problems will also be and indeed already are huge, because different health care providers have addressed the tough challenges of record-keeping in different ways.
As for data management — well, almost everything discussed in this blog could come into play.
- A person’s entire medical record resembles the kind of mess increasingly often dumped these days into NoSQL — typically MongoDB, Cassandra, or HBase.
- There are plenty of business-transaction records in the mix, of the kind that have long been managed by RDBMS.
- There are a whole lot of diverse machines in the mix, and managing the data to keep such a menagerie running is commonly the job of Splunk or streaming-enhanced Hadoop.
- There’s a lot of free text in medical records. Also images, video and so on.
- Since graph analytics is used in research today, it might at some point make its way into clinical use.
Finally, let me say:
- Data-driven medicine cannot live up to its potential unless researchers can investigate data sets comprising private information of large numbers of people.
- Researchers will not have the appropriate permissions unless privacy law moves toward a basis in data use, rather than exclusively regulating data possession.
Related links
- The New York Times and Hacker News discussed the benefits of using your own medical records a couple months ago.
- I wrote about the monitoring/early response aspects of health care in February, 2015.
- Perhaps my most recent survey of privacy issues was in September, 2014.
- A pretty good survey of the debate about statistical methods in medical research came out in December, 2013.
Categories: Business intelligence, Cassandra, Data integration and middleware, Hadoop, HBase, Health care, Log analysis, MongoDB, NoSQL, Predictive modeling and advanced analytics, RDF and graphs, Splunk, Streaming and complex event processing (CEP), Surveillance and privacy, Text
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6 Responses to “IT-centric notes on the future of health care”
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In the next 100 yrs, I believe collecting data for welfare of human beings will not have that much traction as collecting data about plants / animals / enviroment
That’s where big data should find its trumpcard
Curt,
Can’t argue with any of it, but I’d temper it with a few things:
1. If you think the whole medical/hospital/pharma nexus will give up their $3 trillion good thing without a vicious fight and immense obfuscation you are wrong
2. There are as many doctors who finished at the bottom half of their class as the top. As clinicians, they are stubborn, narrow and defensive because they don’t know anything and they have to pretend they do
3. EHR is still a mess, mostly useful for generating invoices but not records. Patients hate doctors tapping away instead of making eye contact. More is needed here
4. Most journal articles are reversed in the first 5 years, but the downstream effect of the mistakes can last much longer
The whole system is a big cesspool and technology can only address part of it
Curt – I share your optimism. Here’s a great proof point that I’m well acquainted with;) – https://www.cerner.com/Identifying_Sepsis_Before_it_is_Too_Late/?langtype=1033
The biggest hurdle right now is the way EMRs are being used and perceived. Doctors need to see data-driven medicine as something that helps them (rather than a tool Big Brother is using to look over their shoulder – which is more typical these days). There’s been so much focus on cost control and it needs to shift to ‘better care’ – we’re getting there but it’s still going to take time.
Neil, Chris,
By no means do I want to minimize the difficulties.
But I’d also note that not ALL technology needs to be adopted US-first. Perhaps certain healthcare IT will wind up being adopted first in countries with comprehensive national health services.
As usual, you bring up many good insights. A few observations from the perspective of a BI Analyst at a physician practice group:
– Diagnosis is ‘typically’ not where the difficulty lies, it’s in managing the treatment.
– Today’s EHR’s are pretty much revenue/compliance oriented, not care oriented.
– EHR technology will be used in a meaningful way when it has more to offer beyond just ticking off the right checkboxes on a patient screen in order to get your bonus or avoid penalty.
– there is little room for innovation in today’s healthcare environment. The risk:reward ratio is skewed in favor of status quo. Innovation is largely going to have to come from the top-down because the current structure does not allow much deviation. Bureaucracies ‘can’ innovate, but it’s not usually their hallmark. That being said, there’s an enormous amount of low-hanging fruit to be picked.
– a lot of budgets took a huge hit in recent years to ‘go electronic’; it will be a while before many of them can start tech shopping to fill the large gaps that came with their shiny new EHR. IT costs are in many cases the straw that’s breaking the smaller providers’ backs. Leaving the larger, less responsive organizations to figure out how to leverage IT. An unfortunate twist.
Just how open is EPIC?
https://open.epic.com/
“EHR vendors do not have a business case for seamless, affordable interoperability across vendor platforms.”
http://www.beckershospitalreview.com/healthcare-information-technology/epic-defends-its-interoperability-at-senate-hearing.html
Word on the street one EPIC EHR interface ends up costing about $75,000 – $50,000 coding + $25,000 in other fees.