More than data science.
The volume of human health data is getting bigger by the minute. Increasingly advanced analytics are needed to break open previously hidden insights into the complexity of treating and preventing illness. The importance of more relevant data on value and outcomes is being validated by manufacturers, researchers and even regulators. And it’s all coming together in a more precise understanding of the human experience in healthcare.
But connections are everything. Sustainability is critical. And privacy is paramount.
To tap the potential of big data in health, and all its implications. To help humans (not just when they are patients) and to advance human health, you need more than just data science.
The Demand for a New Discipline
The Vision: To Reimagine Healthcare
Human Data Science in Action
The demand for a new discipline
03
04
05
Why now?
What makes healthcare data different?
What changes with Human Data Science?
01
What happens when patients are seen as people, rather than averages? When disease is understood in the context of the human experience, not as an aberration of it? When collaboration isn’t just about sharing outcomes, it’s about building an ecosystem of knowledge that can grow, and last.
IQVIA is working to create that world – where people are empowered to know that every healthcare decision they make is precisely the right one for them. Where connections aren’t just created between data sets, but between people and ideas. Where creativity meets analytic rigor, and thrives. Where privacy is never sacrificed for progress. And we believe Human Data Science will get us there. All of us.
That’s why IQVIA is known as The Human Data Science Company™.
Dive into the world of a human data scientist
Yilian Yuan,
Senior Vice President, IQVIA Analytics Center of Excellence
The vision: to reimagine healthcare
An emerging, and timely, discipline that integrates the study of human science with breakthroughs in data science and technology to advance our understanding of human health, and help everyone make better, more insightful decisions.
Human Data Science inspires and empowers everyone in healthcare – life sciences, consumer health, payer, government - to reimagine what is possible. To rise to the challenge of being more precise. To feel confident in their ability to approach challenges in new and creative ways.
01
There is a problem
You need to make a decision
Outcomes for patients like me
02
03
A story: Elizabeth and her twins.
Elizabeth was pregnant with twins. It was her first pregnancy. At her
20-week pregnancy scan, she learned that Twin B had a congenital diaphragmatic hernia (CDH) that would need to be repaired.
A number of options were put on the table, including experimental treatments. Each one focused on adjusting the risk of the affected twin.
But what about the other twin? What about Elizabeth?
If you don’t know the nuances in healthcare data,
you can get very tangled in the details. But if you don’t dig deep enough, you can draw the wrong conclusion. Human Data Scientists live in the sweet spot.
Michael Kleinrock,
Lead Human Data Scientist at the IQVIA Institute for Human Data Science
Human Data Science in action
Advancing Disease Prevention and Treatment
Enhancing value and delivery
Human Data Science can transform how we diagnose patients and treat their conditions, with minimal errors. How we can find patients faster – maybe even before they are patients. And develop treatments that truly provide the best outcomes for patients on the dimensions they
care about, too.
Finding patients
in Rare Disease
A breakthrough in Alzheimer’s Disease
01
02
03
Imagine
In rare diseases, finding patients is hard enough. Often you have to wait for a sign – a trigger for a clinician that indicates the presence of disease. But were there clues hiding in the months or years leading up to diagnosis? What if the clues were there, but they just weren’t big enough on their own to be seen?
Imagine if you could link together thousands of pieces of data – from healthcare utilization to behaviors to demographics – to identify subtle patterns. What if you could identify a high risk patient - before they became a patient?
Human Data Science is a new paradigm to tackle the challenges facing 21st century healthcare. And at IQVIA, it’s a powerful approach to advancing healthcare outcomes, patient access
and commercial results.
Alistair Grenfell,
President, Europe, Middle East, Africa and South Asia, IQVIA
It is an exciting time in human health.
02
Where did Human Data Science come from?
01
What is Human Data Science?
Real world, non-identified patient data is BIG. It requires new techniques such as machine learning and artificial intelligence to dig the insights out and to get precise and actionable.
IQVIA is the leader in Human Data Science because we are uniquely positioned to collect, study, de-identify and protect the data that helps us answer questions about human health. Using the IQVIA CORE™ we are able to integrate this data with advanced analytics, transformation technologies and domain expertise.
The result is a better way to answer questions, solve problems and think creatively with our customers and our partners about how to drive healthcare forward.
Learn more about the IQVIA CORE
01
There is a problem
Finding patients
in Rare Disease
02
Where did Human Data Science come from?
The same place as most great ideas – by understanding today’s challenges and being creative about how new innovations can accelerate new answers. And by burning a healthy amount of midnight oil, of course.
Read the inaugural article
Questions about human health are getting more specific – what mutation on what gene causes a disease? Why do some people respond to chemotherapy in certain ways? Medicine is getting more precise. But it’s also getting harder – what works? What doesn’t? WHY? So we need bigger data. And smarter analytics. And we need it all to speak the language of healthcare.
Why now?
03
Non-identified human data is often unstructured and ‘messy.’ It can be hard to access and even harder to connect. Language is subjective and definitions are fluid. And patient privacy must be protected without fail. Domain expertise here isn’t just important. It’s a prerequisite.
What makes healthcare data different?
04
What changes with Human Data Science?
05
Imagine making the right healthcare decision, for you. Not for the average person. Not for your predecessor. Not based on assumption or perception. Human Data Science puts more relevant insights within reach. It looks at the right data, in the right way.
No known analysis could translate the severity of the condition, or the impact of the decision, on outcomes. Elizabeth, a soon to be first-time mother, was expected to decide. But how? What had worked in the past? Precision medicine seemed very far away for the person impacted the most.
You need to make a decision
02
Elizabeth and her doctors needed more data. Data on people like Elizabeth, with her condition, her history. They needed analytics to better assess risk and predict outcomes, and feel confident that the decision they were making was the right one.
Elizabeth’s twins were born at 38 weeks, and with keyhole surgery two days later, both twins – and Elizabeth – emerged with no adverse effects. Elizabeth and her family continue to contribute to a long-term study, which includes genetic samples and follow ups (all without putting her privacy at risk); she is actively contributing to building a more precise knowledge of CDH so that others can make more informed decisions.
Outcomes for patients like me
03
Outcome
Disease detection accuracy improved from 1/70,000 to 1/7. The algorithm also enabled teams to identify doctors with high-risk patients, ensuring that education and support materials reached the right person at the right time, enabling more patients to find their way to a diagnosis, a trial or a treatment.
01
03
A breakthrough in Alzheimer’s Disease
01
02
03
02
Human Data Science in action
IQVIA has developed a pioneering predictive model that uses machine learning on a wide range of de-identified data to bring Alzheimer’s patients into focus, earlier than ever before. But not just any data – clinically relevant and interpretable predictors that mean something in Alzheimer’s disease – from treatments, to office visits; procedures to diagnoses. That means we’re not just figuring out a better way to treat the disease. We’re figuring out the disease itself, and using that knowledge to create a more insightful plan of attack.
Outcome
Earlier and more accurate diagnosis of Alzheimer’s disease will drive major advances in research, facilitating faster referrals to expert sites, decreasing screen failure rates, enabling testing of treatments on earlier stages of the disease and ultimately allowing better patient and primary care physician engagement.
03
Relevant evidence and analytics helps get the right treatment to the right patient at the right time. So we can know what works, and what doesn’t. And do something about it.
Creating a community of oncology innovation in the real world
Advancing Disease Prevention and Treatment
Enhancing value and delivery
01
02
03
Not one extra dose
Imagine
Treating a degenerative eye disease can be painful. Even one unnecessary dose is one too many.
Imagine if you could help physicians know, not guess, the right dosage choice for their patients in the real world. What if that decision saved money, uncertainty, and even pain?
01
Not one extra dose
Outcome
Using human data science reveals the optimal dose to gain a response, based on a much larger, more relevant data set. Even better, the predictive model allows for the decision to be tailored to the individual,
not the average. Both physicians and patient could take a more informed, and less painful, path.
03
Imagine
Innovations in the art and science of treating cancer is advancing. But the proliferation of options means decision is getting harder, and surprisingly little is known about how cancer is treated in clinical practice.
Imagine if you could bring together a community of clinicians to share data based on real-world clinical care. Imagine if you had a clear and up-to-date picture of how patients are being treated to inform your own decision making, address the challenges of financial sustainability, and minimize treatment variability in patient care.
01
02
Human Data Science in action
IQVIA has taken the lead in establishing the Collaboration for Oncology Data in Europe (CODE) which invites hundreds of treatment centers to contribute to a growing collaborative network, the Oncology Data Network (ODN), sharing information across Europe on the actual use of anti-cancer medicines in a clinical setting in near real-time.
But collecting and connecting this type of data is challenging, and time consuming – especially when you consider the complexity of systems, stakeholders and even treatment regimens at work. Here, a normal data science approach simply would not be sufficient; Human Data Science is necessary to recognize and organize the intricacies of data from an array of complex systems and processes. And it is the key to addressing the very human challenges that come with bringing a diverse group of people, data, and insights together.
Using Human Data Science, the technology platform underpinning ODN is able to work with existing systems and apply best-in-class, automated techniques that minimize the administrative burden on centers and meet exacting standards of data protection to ensure patient and clinician privacy.
Outcome
CODE is an ideal example of how Human Data Science empowers human solutions to human health; the more clinicians contribute, the greater the benefit to the whole cancer community. But to get at those insights, and to ensure that innovation can continue to thrive, a new approach to data, data analytics and data protection is needed. And CODE is presenting an elegant solution.
03
What is Human Data Science?
02
Human Data Science in action
Healthcare data is messy. It can be hard to find and harder to link together in a logical way. IQVIA’s Human Data Scientists tap into IQVIA CORE™ databases of over 200M de-identified patients and use gradient boosting trees on over 10,000 medical and demographic variables. Variables that are attributes of human health, not just current condition. The result is a robust, purpose-built algorithm that could identify predictors of the disease and high risk patients by picking up correlations a human could never find.
Imagine
By 2050 more than 14 million people in the US alone will be living with Alzheimer’s disease. There is no lack of passion or attention to finding a treatment, but it’s still a struggle. Because finding patients in time to treat them means identifying the disease earlier, at a time when patients (and their physicians) aren’t looking for it.
Imagine if machine learning could do more than just notice changes in MRI scans. Imagine if big data, machine learning and the expertise to know what questions to ask converged on a new approach that dramatically accelerated how sponsors find and recruit the patients they need to make treating Alzheimer’s disease a reality.
01
02
Human Data Science in action
Clinical recommendations outline an optimal dose (e.g. 12) based on trial data. It’s helpful, but it’s limited. And because it’s not based on real-world experience, it doesn’t give doctors the confidence they need to. So they may decide to do fewer doses (e.g. 10), based on their own qualitative experience and judgement, to try to save patients unnecessary pain.
By gathering real world observational data on 18,000 patients throughout their treatment journey, IQVIA was able to create a predictive model that could confidently identify the optimal number of doses for each patient based on their response to the first dose.
01
02
03
Creating a community of oncology innovation in the real world
Imagine
In rare diseases, finding patients is hard enough. Often you have to wait for a sign – a trigger for a clinician that indicates the presence of disease. But were there clues hiding in the months or years leading up to diagnosis? What if the clues were there, but they just weren’t big enough on their own to be seen?
Imagine if you could link together thousands of pieces of data – from healthcare utilization to behaviors to demographics – to identify subtle patterns. What if you could identify a high risk patient - before they became a patient?
01
01
There is a problem
Elizabeth was pregnant with twins. It was her first pregnancy. At her
20-week pregnancy scan, she learned that Twin B had a congenital diaphragmatic hernia (CDH) that would need to be repaired.
A number of options were put on the table, including experimental treatments. Each one focused on adjusting the risk of the affected twin.
But what about the other twin? What about Elizabeth?
01
What is Human Data Science?
An emerging, and timely, discipline that integrates the study of human science with breakthroughs in data science and technology to advance our understanding of human health, and help everyone make better, more insightful decisions.
Human Data Science inspires and empowers everyone in healthcare – life sciences, consumer health, payer, government - to reimagine what is possible. To rise to the challenge of being more precise. To feel confident in their ability to approach challenges in new and creative ways.
Learn More
It is an exciting time in human health.
You need Human Data Science.
It is an exciting time in human health. The volume of human health data is getting bigger by the minute, and increasingly advanced analytics are necessary to break open previously hidden insights into the complexity of treating and preventing illness. The need for more relevant data on value and outcomes.
The human experience of healthcare.
But connections are everything. Sustainability
is critical. And privacy is paramount.
To really tap the potential of big data in health – to help humans (not just when they are patients) and to advance human health
The Demand
for a New Discipline
The Vision:
To Reimagine Healthcare
Human
Data Science
in Action
The Demand for
a New Discipline
KEY QUESTIONS:
01
02
03
04
05
01
What is human data science?
An emerging, and timely, discipline that integrates the study of human science with breakthroughs in data science and technology to advance our understanding of human health, and help everyone make better, more insightful decisions.
Human data science inspires and empowers everyone in healthcare – life sciences, consumer health, payer, government - to reimagine what is possible. To rise to the challenge of being more precise. To feel confident in their ability to approach challenges in new and creative ways.
02
Where did human data science come from?
The same place as most great ideas – by understanding today’s challenges and being creative about how new innovations can accelerate new answers. And by burning a healthy amount of midnight oil, of course.
Read the inaugural article
03
Why now?
Questions about human health are getting more specific – what mutation on what gene causes a disease? Why do some people respond to chemotherapy in certain ways? Medicine is getting more precise. But it’s also getting harder – what works? What doesn’t? WHY? So we need bigger data. And smarter analytics. And we need it all to speak the language of healthcare.
04
What makes healthcare data different?
Non-identified human data is often unstructured and ‘messy.’ It can be hard to access and even harder to connect. Language is subjective and definitions are fluid. And patient privacy must be protected without fail. Domain expertise here isn’t just important. It’s a prerequisite.
Dive into the world of a human data scientist
05
What changes with human
data science?
Imagine making the right healthcare decision, for you. Not for the average person. Not for your predecessor. Not based on assumption or perception. Human data science puts more relevant insights within reach. It looks at the right data, in the right way.
Real-world, non-identified patient data is BIG. It requires new techniques such as machine learning and artificial intelligence to dig the insights out and to get precise and actionable.”
“
Yilian Yuan,
Senior Vice President, IQVIA Analytics Center of Excellence
The Vision: To reimagine healthcare
Human Data Science in Action
What happens when patients are seen as people, rather than averages? When disease
is understood in the context of the human experience, not as an aberration of it? When collaboration isn’t just about sharing outcomes, it’s about building an ecosystem of knowledge that can grow, and last.
IQVIA is working to create that world – where people are empowered to know that every healthcare decision they make is precisely the right one for them. Where connections aren’t just created between data sets, but between people and ideas. Where creativity meets analytic rigor, and thrives. Where privacy is never sacrificed for progress. And we believe human data science will get us there. All of us.
If you don’t know the nuances in healthcare data, you can get very tangled in the details. But if you don’t dig deep enough, you can draw the wrong conclusion. Human data scientists live in the sweet spot.”
Michael Kleinrock,
Lead human data scientist at the IQVIA Institute for Human Data Science
Advancing Disease Prevention and Treatment
Enhancing value and delivery
Human data science is a new paradigm to tackle the challenges facing 21st century healthcare. And at IQVIA, it’s a powerful approach to advancing healthcare outcomes, patient access and commercial results.”
Alistair Grenfell,
President, IQVIA North Europe, Middle East, Africa
Elizabeth and her twins.
There is a problem
Elizabeth was pregnant with twins. It was her first pregnancy. At her 20-week pregnancy scan, she learned that Twin B had a congenital diaphragmatic hernia (CDH) that would need to be repaired.
A number of options were put on the table, including experimental treatments. Each one focused on adjusting the risk of the affected twin. But what about the other twin? What about Elizabeth?
You need to make a decision
No known analysis could translate the severity of the condition, or the impact of the decision, on outcomes. Elizabeth, a soon to be first-time mother, was expected to decide. But how? What had worked in the past? Precision medicine seemed very far away for the person impacted the most.
Outcomes for patients like me
Elizabeth and her doctors needed more data. Data on people like Elizabeth, with her condition, her history. They needed analytics to better assess risk and predict outcomes, and feel confident that the decision they were making was the right one.
Elizabeth’s twins were born at 38 weeks, and with keyhole surgery two days later, both twins – and Elizabeth – emerged with no adverse effects. Elizabeth and her family continue to contribute to a long-term study, which includes genetic samples and follow ups (all without putting her privacy at risk); she is actively contributing to building a more precise knowledge of CDH so that others can make more informed decisions.
IQVIA is the leader in human data science because we are uniquely positioned to collect, study, de-identify and protect the data that helps us answer questions about human health. Using the IQVIA CORE™, we then link this data to our advanced analytics, transformative technologies and domain expertise to answer questions, solve problems and think creatively with our customers and our partners about how to drive healthcare forward.
Human data science can transform how we diagnose patients and treat their conditions, with minimal errors. How we can find patients faster – maybe even before they are patients. And develop treatments that truly provide the best outcomes for patients on the dimensions they care about, too.
Advancing Disease Prevention and Treatment
Finding patients
in Rare Disease
A breakthrough in Alzheimer’s Disease
Finding patients
in Rare Disease
Imagine
In rare diseases, finding patients is hard enough. Often you have to wait for a sign – a trigger for a clinician that indicates the presence of disease. But were there clues hiding in the months or years leading up to diagnosis? What if the clues were there, but they just weren’t big enough on their own to be seen?
Imagine if you could link together thousands of pieces of data – from healthcare utilization to behaviors to demographics – to identify subtle patterns. What if you could identify a high risk patient - before they became a patient?
Healthcare data is messy. It can be hard to find and harder to link together in a logical way. IQVIA’s human data scientists tap into IQVIA CORE™ databases of over 200M de-identified patients and use gradient boosting trees on over 10,000 medical and demographic variables. Variables that are attributes of human health, not just current condition. The result is a robust, purpose-built algorithm that could identify predictors of the disease and high risk patients by picking up correlations a human could never find.
Human data science in action
Disease detection accuracy improved from 1/70,000 to 1/7. The algorithm also enabled teams to identify doctors with high-risk patients, ensuring that education and support materials reached the right person at the right time, enabling more patients patients to find their way to a diagnosis, a trial or a treatment.
Outcome
A breakthrough in Alzheimer’s Disease
Imagine
By 2050 more than 14 million people in the US alone will be living with Alzheimer’s disease. There is no lack of passion or attention to finding a treatment, but it’s still a struggle. Because finding patients in time to treat them means identifying the disease earlier, at a time when patients (and their physicians) aren’t looking for it.
Imagine if machine learning could do more than just notice changes in MRI scans. Imagine if big data, machine learning and the expertise to know what questions to ask converged on a new approach that dramatically accelerated how sponsors find and recruit the patients they need to make treating Alzheimer’s disease a reality.
IQVIA has developed a pioneering predictive model that uses machine learning on a wide range of de-identified data to bring Alzheimer’s patients into focus, earlier than ever before. But not just any data – clinically relevant and interpretable predictors that mean something in Alzheimer’s disease – from treatments, to office visits; procedures to diagnoses. That means we’re not just figuring out a better way to treat the disease. We’re figuring out the disease itself, and using that knowledge to create more insightful plan of attack.
Human data science in action
Earlier and more accurate diagnosis of Alzheimer’s disease will drive major advances in research, facilitating faster referrals to expert sites, decreasing screen failure rates, enabling testing of treatments on earlier stages of the disease and ultimately allowing better patient and primary care physician engagement.
Outcome
Relevant evidence and analytics helps get the right treatment to the right patient at the right time. So we can know what works, and what doesn’t. And do something about it.
Enhancing value and delivery
Not one
extra dose
Creating a community of oncology innovation in the real world
Not one extra dose
Imagine
Treating a degenerative eye disease can be painful. Even one unnecessary dose is one
too many.
Imagine if you could help physicians know,
not guess, the right dosage choice for their patients in the real world. What if that decision saved money, uncertainty, and even pain?
Human data science in action
Clinical recommendations outline an optimal dose (e.g. 12) based on trial data. It’s helpful, but it’s limited. And because it’s not based on real-world experience, it doesn’t give doctors the confidence they need to. So they may decide to do fewer doses (e.g. 10), based on their own qualitative experience and judgement, to try to save patients unnecessary pain.
By gathering real world observational data on 18,000 patients throughout their treatment journey, IQVIA was able to create a predictive model that could confidently identify the optimal number of doses for each patient based on their response to the first dose.
Outcome
Using human data science reveals the optimal dose to gain a response, based on a much larger, more relevant data set. Even better, the predictive model allows for the decision to be tailored to the individual, not the average. Both physicians and patient could take a more informed, and less painful, path.
Not one
extra dose
Creating a community of oncology innovation in the real world
Imagine
Innovations in the art and science of treating cancer is advancing. But the proliferation of options means decision is getting harder, and surprisingly little is known about how cancer is treated in clinical practice.
Imagine if you could bring together a community of clinicians to share data based on real-world clinical care. Imagine if you had a clear and up-to-date picture of how patients are being treated to inform your own decision making, address the challenges of financial sustainability, and minimize treatment variability in patient care.
Human data science in action
IQVIA has taken the lead in establishing the Collaboration for Oncology Data in Europe (CODE) which invites hundreds of treatment centers to contribute to a growing collaborative network, sharing information across Europe on the actual use of anti-cancer medicines in clinical settings.
But collecting and connecting this type of data is challenging, and time consuming. Here, a normal data science approach simply would not be sufficient; human data science is necessary to recognize and organize the intricacies of data from an array of complex systems and processes. And it is the key to addressing the very human challenges that come with bringing a diverse group of people, data, systems and even treatments together, all while meeting exacting standards of data protection.
Outcome
CODE is an ideal example of how human data science empowers human solutions to human health; the more clinicians contribute, the greater the benefit to the whole cancer community. But to get at those insights, and to ensure that innovation can continue to thrive, a new approach to data, data analytics and data protection is needed. And CODE is presenting an elegant solution.
IQVIA is the leader in human data science because we are uniquely positioned to collect, study, de-identify and protect the data that helps us answer questions about human health. Using the IQVIA CORE™, we then link this data to our advanced analytics, transformative technologies and domain expertise to answer questions, solve problems and think creatively with our customers and our partners about how to drive healthcare forward.
Finding patients
in Rare Disease
Not one
extra dose
You need Human Data Science.