This post is adapted from DeSalvo’s talk at the annual meeting of the Health and Information Management Systems Society in Chicago last week.
I am optimistic about the bright future we have to leverage health information technology to enable better health for everyone in this country.
One year ago, we called upon the health IT community to move beyond adoption and focus on interoperability, on unlocking the data, so it can be put to the many important uses demanded by consumers, doctors, hospitals, payers, and others who are part of the learning health system.
ONC spent the year listening to the health IT community to understand the challenges and opportunities and developing strategic roadmaps to guide our way. Our goal was to evolve to be best able to lead where appropriate, and partner wherever possible, as we all shift the national strategic focus towards interoperability. I hope you all have felt that shift.
The essence of controlling Ebola is surveillance. To accept surveillance, the population must trust the system responsible for surveillance. That simple fact is as true in Liberia as it is in the US. The problem is that health care surveillance has been privatized and interoperability is at the mercy of commerce.
Today I listened to the JASON Task Force meeting. The two hours were dedicated to a review of their report to be presented next week at a joint HIT Committee Meeting.
The draft report is well worth reading. Today’s discussion was almost exclusively on Recommendations 1 and 6. I can paraphrase the main theme of the discussion as “Interoperability moves at the speed of commerce and the commercial interests are not in any particular hurry – what can we do about it?”
Health information technology in the US is all about commerce. In a market that is wasting $1 Trillion per year in unwarranted and overpriced services, interoperability and transparency are a risk. Public health does not pay the bills for EHR vendors or their hospital customers.
It’s a provocative question, but it’s also the wrong one.
The question ought to be: When will healthcare fully embrace technology and all it has to offer?
It’s widely known that the $2.8 trillion US health system has significant waste and errors – between 25% and 30% of our health dollars go to services that do not improve health. Technology has the ability to put a big dent in that through standardization, real-time insights, convenient gadgets and complex data analysis the human brain simply cannot perform.
Consider some of the early innovators. There’s the heart monitor in the phone. The wristbands that count steps. And then there’s Oto, the cellphone attachment that snaps an image of the inner ear sparing frazzled parents one more trip to the doctor’s office for yet another infection.
All medical students learn about the dose response curve in pharmacology lectures. The dose-response curve informs us of how we should dose a medication in the context of its efficacy and its toxicity. Too little medicine won’t have the desired effect, and too much medicine can be toxic.
In the era of digital health, data have become the new “big pharma,” and we are facing the emergence of a data-response curve in which access to too little data is inactionable, and access to too much data can be overwhelming. Digital health devices abound today, and has enabled quantification of nearly every health and wellness metric imaginable. Sadly, in our exuberance about these new sources of data, we often conflate “more data” with “better data.”
In the era in which data have become the booming commodity of exchange in healthcare, we describe an emerging data-response curve. Large data sets can be at best clarifying or at worst self-contradictory. Too little data on the data-response curve, as with medication dosing, can be insufficient for effective action or decision-making. Too much data can be toxic to the user such as the physician, leading to poor decisions or worse, to analysis paralysis.
We live in a world of exploding data, and we need to be thoughtful. Medicine is a people business in need of data, not a data business on need of people. In reductive form, all humans make decisions based on inputs (data) from their environment and on individual analysis of the data in the form of non-linear, non-quantifiable perception. When we as doctors, policy-makers, or simply as human beings receive these inputs, one of three things happens: 1. We make a decision to do something (for example a treatment decision based on abnormal data), 2. We make a decision to do nothing (for example, normal data which we believe requires no action), or 3. We need more data in order to make an informed decision to do item #1 or item #2. More does not necessarily equal better data. More data is simply more.
Better data are actionable data wrapped in the context of the patient and the patient’s condition. Imagine each piece of objective data connected to concurrent subjective data, and surfaced in the context of a specific condition relevant to the patient. HealthLoop enables patients to generate contextual objective data married to their subjective symptoms and served to a clinician in an actionable context. High signal and low noise are the digital health equivalents of on the dose-response curve of a favorable therapeutic window.
See where some folks live on the Chart. Where do you live?
An article in Information Week caught my eye recently . It reviews a new program offered by Texas A&M with support from Dell to help medical students and other healthcare professionals “come to terms with the ways technology is changing their jobs”. The article, Doctors Can Go Back to Tech School, says Texas A&M will launch its new health technology academy later this year as part of its continuing medical education program.
Now, don’t get me wrong. I’m all for education and career improvement. I’m just not sure that the best way to improve Health IT is to get more physicians trained in IT so they can, as the article suggests, move into IT roles. How about giving full time clinicians who have an interest in improving Health IT some extra support and time so they can help those who work in IT better understand what clinicians need to do their jobs efficiently and safely? How about just a little paid time away from the daily treadmill of patient care to educate IT about the nuances of medicine and clinical workflow? I believe understanding that would do more to help IT deliver better solutions.
Over the course of my career, I’ve been many things. First and foremost, I am a physician. Only a true clinician understands how clinicians think and work. For many years, I continued to practice even when it no longer made a whole lot of sense with regards to my income or available time. I was a biology major in college. I went to medical school and did a residency in family medicine. I never had any formal training in either business or technology. I learned the ropes by doing. It was often trial by fire. I’ve had my share of success as well as a few failures along the way. When I advanced into the role of a hospital CIO and CMIO, it wasn’t because I knew tech. When my then CEO asked me to step into the CIO role, I’ll never forget what he said to me. He said, “I want to put a civilian in charge of the military”, meaning a doctor in charge of a department that existed to serve clinicians and their patients but had become a renegade army running out of control and way over budget.
According to Ben Franklin, John Adams, or someone else (I could not find a reliable source), “Every problem is an opportunity in disguise.” This bodes well for clinical care software because the number of complaints about current EHR systems grows louder each day. We know the problems: poor usability, lack of workflow support, reporting difficulties, decreased productivity, to name a few. How can these problems be turned into opportunities?
Obviously, solving these problems by designing better software offers an opportunity for software sales; however, I think there is more to it than that. Current EHR products grew out of a particular mindset and way of thinking about software and sales, and that mindset, I believe, has a lot to do with the problems EHR users voice.
When computers were new, they were sold primarily to businesses. The advent of the PC turned computers into consumer products. However, software and computer sales to businesses continued as they always had, which I think contributes to the issues small independent practices have with selection and implementation. Here is an example of what I mean. I have been buying software since I bought my first computer. This was always a straightforward process: find the software, pay for it, done. I remember my bewilderment while at UAB when I wanted to buy statistical software that had data mining algorithms. Since I was at the university, I was told I had to buy it through the university sales channel. I wanted a single copy. I could never find a salesman who would give me a price or tell me how to buy a single copy. I called the local, regional, and finally the national sales office. After a few weeks, I gave up. I never got the software, or even a price. What I did get were repeated promises that a sales rep would call.
Federally funded health centers are making strides adopting and using electronic health records (EHRs) to treat some of the nation’s poorest and most at-risk patients since the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act, according to a new first-of-its-kind study.
We know that health IT can help improve care quality. ONC and the Health Resources and Services Administration (HRSA) are working hard to ensure that all providers adopt and use EHRs. In the past, some researchers found that there might be a digital divide in health IT use, meaning that providers who mostly serve certain groups of people – particularly the poor and racial/ethnic minorities or people in rural areas – may be using health IT less than others.
Community health centers remain the largest provider of health care to underserved individuals in the US. They provide health care to more than 20 million Americans every year, including many who are poor, uninsured, or have no regular source of care.
In the past, health centers used health IT at a lower rate than other providers. In 2006, a survey showed that only 26% of health centers had any EHR capacity at all.
To ensure that the benefits of health IT and care transformation be available to all Americans, regardless of insurance, wealth, or location, the HITECH Act provided federal resources to help health centers adopt EHRs.
Scott Erven is head of information security for a healthcare provider called Essentia Health, and his Friday presentation at Chicago’s Thotcon, “Just What The Doctor Ordered?” is a terrifying tour through the disastrous state of medical device security.
Wired’s Kim Zetter summarizes Erven’s research, which ranges from the security of implanted insulin pumps and defibrillators to surgical robots and MRIs. Erven and his team discovered that hospitals are full of fundamentally insecure devices, and that these insecurities are not the result of obscure bugs buried deep in their codebase (as was the case with the disastrous Heartbleed vulnerability), but rather these are incredibly stupid, incredibly easy to discover mistakes, such as hardcoded easy default passwords.
For example: Surgical robots have their own internal firewall. If you run a vulnerability scanner against that firewall, it just crashes, and leaves the robot wide open.
The backups for image repositories for X-rays and other scanning equipment have no passwords. Drug-pumps can be reprogrammed over the Internet with ease. Defibrillators can be made to deliver shocks — or to withhold them when needed.
Doctors’ instructions to administer therapies can be intercepted and replayed, adding them to other patients’ records.
You can turn off the blood fridge, crash life-support equipment and reset it to factory defaults. The devices themselves are all available on the whole hospital network, so once you compromise an employee’s laptop with a trojan, you can roam free.
You can change CT scanner parameters and cause them to over-irradiate patients.Continue reading…
Did you hear the one about the CMS administrator who was asked what it would take to delay the 2014 ICD-10 implementation deadline? An act of Congress, he smugly replied, according to unverified reports.
Good thing he didn’t say an act of God.
So, now that CMS has been overruled by Congress, who wins and who loses? Who’s happy and who’s not?
The answers to those questions illustrate the resource disparity that prevails in healthcare and, mirroring the broader economy, threatens to get worse. The disappointed Have-a-lot hospitals are equipped with the resources to meet ICD-10 deadlines and always felt pretty confident of a positive outcome; the Have-not facilities were never all that sure they would make it and are breathing a collective sigh of relief.
First off, it is necessary to recognize that ICD-10 is far superior to ICD-9 for expressing clinical diagnoses and procedures. Yes, some of the codes seem ridiculous … “pecked by chickens,” for example. But people do get pecked by chickens, or plowed into by sea lions, so I believe the intent is positive, as will be the results.
An example: I saw my physician this past week at a Have-a-lot health system in San Francisco and I asked what she thinks of the ICD-10 extension.
“We’re already using (ICD-10) in our EHR and it is much better than ICD-9,” she said. “When I want to code for right flank pain, it’s right there. I don’t have to go with back pain or abdominal pain and fudge flank in. It’s easier and more accurate.”
“If I was still on paper and not our EHR, which I like,” she added, “my superbill would go from 1 page to 10. SNOMED works.”
During National Minority Health Month, we acknowledge the potential for health information technology (health IT) – from electronic and personal health records to online communities to mobile applications – to transform health care and improve the health of racial and ethnic minorities.
Lack of access to quality, preventive health care, cultural and linguistic barriers, and limited patient-provider communication are factors that aggravate health disparities.
By increasing our investment in health IT policies and standards, we can help improve the quality of health care delivery and make it easier for patients and providers to communicate with each other – a huge step toward addressing the persistence of health disparities.
The Pew Research Center’s Internet & American Life Project found in 2012 that African Americans and Latinos are more likely to own a mobile phone than whites and outpace whites in mobile app use, using their phones for a wider range of activities.
The study showed that African Americans and Latinos use their mobile phones more often to look for health information online. This has very important implications for personal management of health and interaction with the health care system.
However, barriers to widespread adoption of health IT remain.
For example, a 2014 consumer engagement report found that minorities were less likely to adopt online patient portals to access their health information than were non-Hispanic whites.