Precision Medicine concept
Is the value of "personalized medicine" over-promised? Why is the quality of health care declining for many people despite the pace of innovation? Do patients and doctors have conflicting priorities? What is the best path forward?
"How do we generate evidence for value, which is what everyone is asking for?"
Some of the country's leading medical experts recently debated these questions at the prestigious annual Personalized Medicine Conference, held at Harvard Medical School in Boston, and LeapsMag was there to bring you the inside scoop.
Personalized Medicine: Is It Living Up to the Hype?
The buzzworthy phrase "personalized medicine" has been touted for years as the way of the future—customizing care to patients based on their predicted responses to treatments given their individual genetic profiles or other analyses. Since the initial sequencing of the human genome around fifteen years ago, the field of genomics has exploded as the costs have dramatically come down – from $2.7 billion to $1000 or less today. Given cheap access to such crucial information, the medical field has been eager to embrace an ultramodern world in which preventing illnesses is status quo, and treatments can be tailored for maximum effectiveness. But whether that world has finally arrived remains debatable.
"I've been portrayed as an advocate for genomics, because I'm excited about it," said Robert C. Green, Director of the Genomes2People Research Program at Harvard Medical School, the Broad Institute, and Brigham and Women's Hospital. He qualified his advocacy by saying that he tries to remain 'equipoised' or balanced in his opinions about the future of personalized medicine, and expressed skepticism about some aspects of its rapid commercialization.
"I have strong feelings about some of the [precision medicine] products that are rushing out to market in both the physician-mediated space and the consumer space," Green said, and challenged the value and sustainability of these products, such as their clinical utility and ability to help produce favorable health outcomes. He asked what most patients and providers want to know, which is, "What are the medical, behavioral, and economic outcomes? How do we generate evidence for value, which is what everyone is asking for?" He later questioned whether the use of 'sexy' and expensive diagnostic technologies is necessarily better than doing things the old-fashioned way. For instance, it is much easier and cheaper to ask a patient directly about their family history of disease, instead of spending thousands of dollars to obtain the same information with pricey diagnostic tests.
"Our mantra is to try to do data-driven health...to catch disease when it occurs early."
Michael Snyder, Professor & Chair of the Department of Genetics and Director of the Center for Genomics and Personalized Medicine at Stanford University, called himself more of an 'enthusiast' about precision medicine products like wearable devices that can digitally track vital signs, including heart rate and blood oxygen levels. "I'm certainly not equipoised," he said, adding, "Our mantra is to try to do data-driven health. We are using this to try to understand health and catch disease when it occurs early."
Snyder then shared his personal account about how his own wearable device alerted him to seek treatment while he was traveling in Norway. "My blood oxygen was low and my heart rate was high, so that told me something was up," he shared. After seeing a doctor, he discovered he was suffering from Lyme disease. He then shared other similar success stories about some of the patients in his department. Using wearable health sensors, he said, could significantly reduce health care costs: "$245 billion is spent every year on diabetes, and if we reduce that by ten percent we just saved $24 billion."
From left, Robert Green, Michael Snyder, Sandro Galea, and Thomas Miller.
(Courtesy Rachele Hendricks-Sturrup)
A Core Reality: Unresolved Societal Issues
Sandro Galea, Dean and Professor at Boston University's School of Public Health, coined himself as a 'skeptic' but also an 'enormous fan' of new technologies. He said, "I want to make sure that you all [the audience] have the best possible treatment for me when I get sick," but added, "In our rush and enthusiasm to embrace personalized and precision medicine approaches, we have done that at the peril of forgetting a lot of core realities."
"There's no one to pay for health care but all of us."
Galea stressed the need to first address certain difficult societal issues because failing to do so will deter precision medicine cures in the future. "Unless we pay attention to domestic violence, housing, racism, poor access to care, and poverty… we are all going to lose," he said. Then he quoted recent statistics about the country's growing gap in both health and wealth, which could potentially erode patient and provider interest in personalized medicine.
Thomas Miller, the founder and partner of a venture capital firm dedicated to advancing precision medicine, agreed with Galea and said that "there's no one to pay for health care but all of us." He recalled witnessing 'abuse' of diagnostic technologies that he had previously invested in. "They were often used as mechanisms to provide unnecessary care rather than appropriate care," he said. "The trend over my 30-year professional career has been that of sensitivity over specificity."
In other words: doctors rely too heavily on diagnostic tools that are sensitive enough to detect signs of a disease, but not accurate enough to confirm the presence of a specific disease. "You will always find that you're sick from something," Miller said. He lamented the counter-productivity and waste brought on by such 'abuse' and added, "That's money that could be used to address some of the problems that you [Galea] just talked about."
Do Patients and Providers Have Conflicting Priorities?
Distrust in the modern health care system is not new in the United States. That fact that medical errors were the third leading cause of death in 2016 may have fueled this mistrust even more. And the level of mistrust appears correlated with race; a recent survey of 118 adults between 18 to 75 years old showed that black respondents were less likely to trust their doctors than the non-Hispanic white respondents. The black respondents were also more concerned about personal privacy and potentially harmful hospital experimentation.
"The vast majority of physicians in this country are incentivized to keep you sick."
As if this context weren't troubling enough, some of the panelists suggested that health care providers and patients have misaligned goals, which may be financially driven.
For instance, Galea stated that health care is currently 'curative' even though that money is better spent on prevention versus cures. "The vast majority of physicians in this country are incentivized to keep you sick," he declared. "They are paid by sick patient visits. Hospital CEOs are paid by the number of sick people they have in their beds." He highlighted this issue as a national priority and mentioned some case studies showing that the behaviors of hospital CEOs quickly change when payment is based on the number of patients in beds versus the number of patients being kept out of the beds. Green lauded Galea's comment as "good sense."
Green also cautioned the audience about potential financial conflicts of interest held by proponents of precision medicine technologies. "Many of the people who are promoting genomics and personalized medicine are people who have financial interests in that arena," he warned. He emphasized that those who are perhaps curbing the over-enthusiasm do not have financial interests at stake.
What is the Best Path Forward for Personalized Medicine?
As useful as personalized medicine may be for selecting the best course of treatment, there is also the flip side: It can allow doctors to predict who will not respond well—and this painful reality must be acknowledged.
Miller argued, "We have a duty to call out therapies that won't work, that will not heal, that need to be avoided, and that will ultimately lead to you saying to a patient, 'There is nothing for you that will work.'"
Although that may sound harsh, it captures the essence of this emerging paradigm, which is to maximize health by using tailored methods that are based on comparative effectiveness, evidence of outcomes, and patient preferences. After all, as Miller pointed out, it wouldn't do much good to prescribe someone a regimen with little reason to think it might help.
For the hype around personalized medicine to be fully realized, Green concluded, "We have to prove to people that [the value of it] is true."
The U.S. has the highest incarceration rate in the world, costing $182 billion per year, partly because its antiquated data systems often fail to identify people who should be released. A tech nonprofit is trying to change that.
Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”
People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.
The problems are vast
The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.
Sentencing miscalculations
To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.
In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states' data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.
Algorithms
Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.
Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s "descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.
Parole violation laws
Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn't send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.
It’s personal for the co-founder and CEO
“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.
“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who's broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.
As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'"
A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.
Recidiviz
As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.
As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.
The Solution
It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.
TED Talk: How bad data traps people in the U.S. justice system
TED Fellow Clementine Jacoby's TED Talk went live on Jan. 13. It describes how we can fix bad data in the criminal justice system, "bringing thousands of people home, reducing costs and improving public safety along the way."
Clementine Jacoby • TED2022
Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”
On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.
The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.
Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”
