Datavant is fostering an ecosystem of healthcare data to facilitate secure exchange of information and analytics that improve patient care. The company recently made headlines through a $7 Billion merger with Ciox, uniting Datavant’s world of de-identified data with Ciox’s domain expertise in patient identified records.
In this episode of the HealthBiz podcast, Datavant’s Chief Strategy Officer Jason LaBonte and Chief Operating Officer Bob Borek discuss the evolution of healthcare data, the Ciox merger, how the company has fared during the pandemic, and their long term vision.
Jason is reading Project Hail Mary by Andy Weir –whose fiction appeals to Jason’s training as a PhD scientist– and Bob likes Cadillac Desert by Marc Reisner about the history of water rights in the West.
Ray Hill grew up on a farm and took up rowing in college. So he’s always been a hard worker and an early riser. In this edition of the HealthBiz podcast, Ray brings us up to date on progress at CorEvitas. As CEO and Chairman he’s led the company’s expansion from a singular rheumatoid arthritis registry to a broader autoimmune and inflammatory company with registries, real world evidence, biorepositories, and patient engagement capabilities.
I was partial to the company’s former name, Corrona, but for some reason that one didn’t have the right connotations for the pandemic era. When not focused on CorEvitas, Ray continues to row and to cycle. And he’s also chair of Row New York, which combines rowing and academics for kids who not otherwise have access. Ray is proud of Row NY’s 99% graduation rate from HS and 85% graduation rate from four year colleges, a remarkable record.
Meanwhile, If your business needs strategy consulting support please reach out to me at dwilliams@HealthBusinessGroup.com. We have experience throughout healthcare and life sciences, including with real world evidence companies similar to CorEvitas.
When COVID-19 hit, hospitals knew they would see a decline in elective surgeries and routine visits. After all, they canceled them! But the volume of patients visiting the emergency room has also dropped dramatically, and no one can seem to fully explain it. Sure, maybe we could expect fewer car crashes and skiing injuries. But heart attacks and strokes? If anything it seems like those numbers should be going up due to higher stress levels. Yet, the analyses in cardiac care during the pandemic show a sharp decline not only in elective cardiac procedures, but also in cardiac catheterizations for acute heart attacks, specifically, those with ST segment elevations – the most life threatening type.
Conventional wisdom tells us that the drop in ER visits is a bad thing. Patients must be dying at home, outcomes must be worsening, and the patients that do survive will show up as train wrecks once the pandemic subsides. Those assumptions are probably true to a certain extent, but the open question is how true? Acute conditions and complications warrant acute care. But in the routine care of behavioral health and other chronic conditions such as diabetes and hypertension, extensive overuse of the emergency room rather than other ambulatory settings has been a prime area of concern and debate for several years.
We know that ERs are overused in normal times. And we think they’re underused now during the pandemic, but to what extent should be analyzed and debated as we inform the necessary adaptation of our systems of care. We expect to see an incredible amount of variation in ER utilization as the situation unfolds, by specific patient populations, urban vs rural settings, and geography-specific COVID-19 case burden.
We are encouraged that Datavant has convened a wide variety of industry players to construct a COVID-19 Research Database, a set of de-identified data sets made freely available to enable rapid studies at scale. The new initiative fills an important gap between quick observations that are available from small sets of real world data and clinical trials, which are robust but slow.
The ER phenomenon we’re discussing is not completely unprecedented. Researchers (and ER staff) have long observed the ‘big game effect’ – where ER visits decline as people defer them to watch their favorite team. (The Health Business Blog first reported on it in 2005:Red Sox’ success eases health care crisis.) Some, but not all, of those visits are avoided entirely without negative consequences. The COVID-19 pandemic provides an opportunity for a much longer time series. Let’s use it as a chance to study what’s going on so we can apply the lessons learned as we emerge.
What could explain sustained, lower utilization of the ER? There are a few possibilities:
Many seemingly serious problems resolve on their own when people just wait. If people avoid the ER out of fear, the ‘tincture of time’ will often do the job.
Less aggressive ambulatory settings are proving effective: the physician’s office, a telehealth visit, or home remedies.
The momentum and logic of the ER setting makes matters seem more serious than they really are. Once someone appears there’s always something to find. (As a doctor colleague once told me, “Show me someone who’s perfectly healthy and I’ll give him a full workup to demonstrate otherwise.”)
The ER is the entry point for admission to the hospital. Under fee for service, hospitals need to admit patients to make money. Depending on the proportion of available beds during these uncertain times, hospitals may be even more economically motivated than usual to fill open beds. So, once a patient arrives, they may be staying.
A significant portion of ER traffic is composed of so-called ‘frequent fliers.’ Usually, they are tolerated, but in the current environment, ER staff are motivated to triage non-COVID-19 patients away from the hospital as efficiently as possible. Once this becomes evident, the ‘frequent fliers’ ground themselves.
How many times have you called your doctor’s office or pharmacy and heard the recording say, “If this is a medical emergency, hang up and dial 9-1-1”? That definitely got people used to the idea that the ER is a good place for care. Clearly people are ignoring that messaging now!
So what should we do with this unexpected information?
More finely tune financial incentives to discourage unneeded utilization while not discouraging needed care. We know from experience that bluntly requiring large patient financial contributions drive down both good and bad utilization.
Educate people about the downside of ER visits (infection risk, treatment that’s too aggressive, likelihood of admission to hospital, provider that doesn’t know you) to balance out the current bias for ER care. People will be more receptive now and won’t immediately think that health plans are only trying to ration their care.
Consider other changes in benefit design to help the decreased utilization persist, including increased access and reimbursement for home services, telehealth, and remote management tools.
Encourage physician offices and others to make better efforts to intervene quickly and prevent people from going to the ER just for convenience. This could include on-demand availability of telehealth consultations and other digital/remote management for which they would be reimbursed.
Real World Evidence (RWE) is becoming more important in US healthcare, but the fragmented system and lack of interoperability makes it hard to collect and analyze. In this podcast, Life Image CTO Janak Joshi discusses the state of the field and how it’s evolving.
(0:12) How would you describe the evolution of medical data?
(2:36) Real world evidence and real world data are becoming more prominent in healthcare –and for good reason. What are some of the challenges in assembling RWD and RWE? How can they be overcome?
(6:36) Is it really true that unstructured notes are becoming quantifiable and useful?
(9:46) There are major efforts by the US government and private sector to improve interoperability and end data blocking. You have groups like CommonWell and Carequality –now working together. What’s the current state of play and how are things changing?
(13:56) You talk about data brokers like Datavant and HealthVerity. How much of their success is because the US system is so broken? Do you see them having the same success elsewhere?
(17:31) Promoters of AI and Machine Learning –including Life Image—tout the opportunity to revolution healthcare with these new techniques. Is it for real or overhyped? And how does interoperability tie in?
(22:20) What are you most excited about over the next few years?
The article itself is more balanced. Of course it quotes the parents of a couple of kids who take expensive meds, objecting to anyone putting a price tag on their lives. But it also quotes health economics experts pointing out that the price can’t be infinity.
The Institute for Clinical and Economic Review (ICER) follows a data-based approach to assessing the value of drugs, utilizing Quality Adjusted Life Years (QALY) and other well developed metrics. It provides guidance on what a drug could be worth, both on an absolute basis and relative to other treatment options. It doesn’t set prices or prevent a drug from being made available by a public or private health plan. At most, it helps contain the prices of drugs that enter the market and points out cases of outright rip-offs.
Elsewhere in the world (pretty much everywhere) there are real forces limiting drug prices and impacting access. In the UK for example, the National Institute for Health and Clinical Excellence (NICE) decides which drugs and treatments will be provided to patients in the National Health Service. Sometimes drugs are rejected or their use is heavily restricted. On the flip side, patients don’t pay for the drugs that are approved.
In the US the drug pricing forces are heavily weighted in favor of higher prices. We shouldn’t fret about an entity like ICER.
Many drug companies have decided to play ball with ICER by providing data to help justify the value of their products. Some, like Vertex and Serepta have pulled back, saying ICER is biased against drugs for rare diseases. I don’t read ICER’s analyses that way.
The quality of ICER’s research is high, but of course the reports are limited by the data and analytical techniques that are available to the organization. The correct response is to build up the availability of real world evidence (RWE), especially from clinical registries that demonstrate how a drug actually improves (or doesn’t improve) the lives of patients. Patient-generated data and information from claims and electronic medical records can be helpful as well.
With better data we can have answers we are more confident in, and we can accumulate evidence on how drugs perform after they are launched, which can offer a refined understanding of their value.
Thanks to the 21st Century Cures Act, enacted in 2016, there is an increased demand for the generation of RWE. The industry is ramping up its spending on RWE for drug approval, safety monitoring, and reimbursement. New analytical techniques and enhanced data availability from wearable devices and other electronic sources are ushering in a heyday for RWE.