Shahir Kassam-Adams is one of the most knowledgeable and outspoken people in healthcare. In this episode, Shahir shares his initially unsettling but ultimately reassuring view that “data will eat public health.” He opines on interoperability and explains how his company, Datavant has promoted data sharing on COVID-19, leading to a plethora of interesting and potentially useful projects, including one that models the tradeoffs for specific American cities to reopen.
Russia –yes the Russia that exerts special influence on our president– has done a poor job of keeping the COVID-19 virus in check. But now they claim to have a safe and effective vaccine that’s ready to go.
Some suggest that the vaccine may not be safe – or effective.
“It’s obvious that the Russians are rushing the vaccine to market without adequate testing,” David Eugene Williams, president at Health Business Group, told International Business Times in an email. “It’s possible that the vaccine will work, but there hasn’t been enough time to verify that it’s both safe and effective. The Russians haven’t released any data that would support their claims.”
“I don’t think people will travel to Russia to receive the vaccine because, 1) they won’t trust that it will work, 2) they could get COVID-19 on their travels to Russia, and 3) the Russians may allocate it to their own citizens,” he said.
It would be great if the Russian vaccine works. But we’ll have to wait and see –which is something the developers haven’t done.
Patients have been receiving a megadose of virtual care since March. How’s it going and what will it mean long-term? Provider search and scheduling company, Kyruus asked 1000 patients for their opinions and published the findings.
Kyruus Chief Medical Officer, Dr. Erin Jospe and I had a chance to catch up on the report and speculate about its implications in this podcast.
Here’s what we discussed:
(0:15) Key findings and surprises
(1:54) Baby Boomers’ affinity for virtual care
(3:40) Paradox that Baby Boomers are big utilizers of virtual care but not so likely to switch doctors to get it
(6:21) Downsides and limitations of virtual care
(10:55) Impact of virtual care on disparities
(13:47) Potential to launch a virtual-first practice
Purposeful –aiming to meet the objective of educating children in person while keeping them and staff members safe
Timely –coming at the end of the school year, with updates promised over the summer
Evidence based –relying on the latest medical and public health guidance and the experience of schools abroad
Appropriately detailed –with enough specifics to guide decisions that need to be made now without being overly prescriptive
Circumscribed –acknowledging and accounting for issues of racism and disparities without purporting to solve every problem
Balanced –recognizing that we are living in the real world (such as it is!) and that COVID-19 is part of it. None of the measures (hand washing, masks, staying home when sick, social distancing) on their own will prevent the spread, but taken together they have and will
I’m not an easy grader, so my A for this assignment is real. I have publicly criticized Massachusetts’ reopening plan and its testing plan for being vague, non-evidenced based, and irrational. Privately, I’ve admonished the local school system for its defeatist attitude toward COVID-19.
The plan doesn’t set a cap on the number of students in classrooms
COVID-19 testing is not mandated
Daily temperature checks are not required
It mandates only 3 feet of social distancing even though officials have been telling us 6 feet
Superintendents need to develop 3 sets of plans (in person, hybrid, virtual)
No clear guidance on whether state should go back to in-person classes when school reopens
Doesn’t adequately address challenges of urban schools that serve children from disadvantaged backgrounds and have limited space
Racism is not connected to students’ mental health in the plan
It doesn’t say how many students can ride the bus
People don’t like the idea of wearing masks all day
The report itself anticipates and addresses these criticisms. The Globe notes some but not all. Here is the reasoning
Number of students isn’t capped because the relevant constraints are adequate space between desks and proper behavior. If a room is larger it can accommodate more students. The report encourages use of new spaces like libraries and cafeterias
No one in the country (or world?) is seriously suggesting testing all school age kids. It’s expensive, slow, unpleasant, impractical and unnecessary. Maybe there will be cheap, spit tests at some point. They can be used if the need is real
Daily temperature checks produce too many false negatives and false positives, offering a false sense of security and causing students to miss school when they don’t need to. These checks are good for other illnesses, like the flu where fever is a good indication of active infection, but it’s of limited use for COVID-19
There’s no magic in 6 feet. Three feet seems to work fine in other countries’ schools, especially in combination with other measures, like wearing masks. Schools with 3 feet of distance abroad have not had outbreaks. Kids aren’t going to be safer out of school
Superintendents need to develop plans for different scenarios. Of course they do! If they just developed one plan it would have to be for remote instruction only. Is that what we want?
Of course the guidelines can’t be definitive in June about whether students can go back in September. But the goal is to get as many back as possible. To make that happen requires everyone to behave well over the summer (adults, especially!)
Although the plan isn’t going to eliminate disparities or solve racism, there are extra funds to help all schools and especially those with extra needs. And the best way to reduce disparities is with kids in school. Disparities widen (as I’m sure they did this spring) when normal routines are thrown off. For extra space, the guidelines suggest working with local community centers, libraries, etc.
Kids will need to wear masks on the bus. If the bus is crowded then buses will need to be added or kids will need to get to school in other ways. They can keep windows open, too.
It’s true that people don’t like wearing masks all day. The guidelines call for mask breaks and make special mention of how to work with people with breathing or communication problems. If we all behave there’s a good chance we can take our masks off sooner rather than later.
Notably, these guidelines are endorsed by people who know what they’re talking about and have children’s interests at heart. The healthy approach is to work within the guidelines to plan a return to in-person classes this fall. We should continue to challenge the guidelines and expect them to be updated as we learn more and as the situation on the ground evolves.
Meanwhile, we can all contribute to a safer back-to-school scenario by continuing to follow public health guidelines that are knocking the virus down in Massachusetts. The lower the level of community spread, the safer any reopening plan will be.
Healthcare analytics company Cotiviti has launched a COVID-19 tracker to predict infection outbreaks based on insurance claims data. It says its model has a high degree of accuracy and is useful for health ecosystem players and government authorities that need to decide where to allocate resources.
In this interview, I asked Cotiviti EVP, Jordan Bazinsky to explain.
What are the needs for COVID-19 tracking in the US?
To make decisions on how to best protect their citizens and employees while also limiting harm to their economies, policymakers and business leaders need accurate and timely data about how far COVID-19 has spread in their communities. But unfortunately, we’ve seen that in too many areas, COVID-19 tests are not being administered to everyone who should receive one due to lack of resources. Therefore, in the absence of this testing, we sought to develop a model that would help to forecast which geographic areas were likely to see a substantial number of COVID-19 cases using other factors such as flu testing and flu diagnoses.
How could this model impact/shift the U.S. approach to combating this health crisis (at private, federal, and state/local levels)?
We’re already seeing many states and local governments move to re-open their economies even as COVID-19 testing remains scarce. While this is understandable given the economic devastation this pandemic has caused for many, these decisions should be guided by accurate data to protect those who are most vulnerable. We hope this approach will encourage everyone to proceed with the utmost caution as they make decisions that could have far-reaching impacts.
What is the unmet need you saw at Cotiviti? And what approach are you taking to address it?
This project originated the same day the WHO declared COVID-19 a pandemic. We assembled a team to explore how Cotiviti could help respond to the outbreak by using our Caspian Insights data and analytics platform. The team began examining leading indicators such as telemedicine, rapid flu testing, and chest x-rays, that can help predict potential areas of concern before COVID-19 testing takes place.
The primary deficiency we are aiming to solve is the widespread lack of COVID-19 testing resources, which has left states unable to confirm the true impact and reach of the virus in their communities. Instead, our approach relies on other leading indicators of COVID-19, such as flu testing and diagnosis. By comparing current flu testing data seen in the CPT codes processed through our systems against confirmed flu diagnoses seen in ICD-10 codes, we can spot significant discrepancies that could indicate a “hidden outbreak” is occurring.
What are the use cases? Are people using it for purposes beyond what you originally envisioned?
Our focus is on helping all healthcare stakeholders to prepare for what’s ahead given the unpredictable nature of this virus. As healthcare organizations seek to gain more data and use that data to extract meaningful insights, we are offering this resource to supplement their existing resources.
We have fielded questions recently regarding how this data may support contact tracing. We have also had inquiries from retailers wanting to use this data to inform decisions about when to open stores in various parts of the country. While neither of these were uses we initially envisioned, they reflect the need from all stakeholders to have access to reliable, timely COVID-19 data.
Now that states are looking at loosening their social distancing mandates and re-opening previously shuttered businesses, Cotiviti has unveiled a second map that shows which states have seen a downward trend of influenza-like illness and COVID-like syndromic cases to aid in decision making. It will be critical to maintain active surveillance of any early spikes that may be predictive of COVID-19 resurgence.
How does it compare with other initiatives, like the Johns Hopkins model?
While Johns Hopkins has assembled an excellent, informative COVID-19 dashboard that aggregates data to track cases around the world and show trends over time, it specifically focuses on confirmed cases, which can only be identified through COVID-19 testing. Similar dashboards and tracking tools released by other organizations are also limited to tracking confirmed cases. Our approach looks at where there are a significant population of unconfirmed but likely cases to help forecast the hidden impact of this outbreak.
What are the data sources? How did Cotiviti ensure data quality and accuracy?
Our data source is Cotiviti’s Caspian Insights data and analytics platform—the engine behind our healthcare analytics solutions—which processes millions of claims per day and comprises longitudinal data for more than 130 million Americans. It combines financial and clinical information alongside a multitude of other healthcare data types, such as social determinants of health, medical records, pharmacy, dental, and lab information to give health plans and providers actionable information at their fingertips.
We have both automated data quality standards and rigorous processes to ensure data quality and accuracy at all levels. For example, healthcare data is known to be inconsistent across disparate systems—the same individual might be listed by different names in the different data feeds we receive. To overcome this challenge, we leverage a unique combination of probabilistic and deterministic models to establish linkages between data sources, while also ensuring the data is de-identified. Finally, we have a strong organizational commitment to quality at all levels of Cotiviti.
How accurate are the predictions? How is that changing?
We made our first forecast on March 12, and 80 percent of our predictions were realized by March 22. We have continued to maintain this level of accuracy while refining our data and algorithms, and we continue to see indications of potential hidden outbreak in certain states. However, as COVID-19 testing becomes more available, we know that hidden outbreaks will diminish and transition to confirmed outbreaks. Therefore, our team is preparing to shift to a more sophisticated modeling approach that identifies “COVID-like illness” based on the unique care pattern of COVID-19 that can be seen in the claim, clinical, prescription, and lab data for a patient. This approach will allow continued monitoring of the virus until a vaccine is available.