Dr. Murat Sincan went to medical school to care for individual patients. Now he explores the possibilities of using data to help other providers take better care of their patients.
Dr. Sincan grew up and pursued his education in Turkey. His life path ultimately brought him across the Mediterranean Sea and Atlantic Ocean to South Dakota, with a stop first in Maryland. He now serves as director of computational medical informatics for Sanford Imagenetics, along with a new role as a faculty member of Sanford Research.
It was an unusual and gradual transition from patients to computers — from one world that he loved to another. But he hopes his current focus can help many more people.
“With clinical practice, you see one patient at a time, and you apply your knowledge to that case at hand, and you try to solve that puzzle and try to help the patient,” Dr. Sincan said.
But while doing that, he spotted inefficiencies. He could see how inaccessibility to helpful data and a good information system hindered providers like him.
“You would think that if you had access to that information, then you would be able to do a much better job of providing the best care to that patient that you’re seeing,” he said.
If a patient had a rare condition, but the provider lacked knowledge of any others in his health care system, his view was limited to that individual.
“Whereas if you had that information system in place,” Dr. Sincan said, “you could find all 10 or 20 cases and identify that pattern, and maybe anticipate what was coming or do a better job of learning from other cases.”
From patients to genomes
Through his provider experiences and observations, Dr. Sincan felt driven to learn about how computer advances such as informatics and electronic medical records (EMR) could improve care.
At the same time, he found fulfillment in practicing medicine. “It is really a special privilege to be able to take care of a patient,” he said, “sometimes in a very challenging time in their life, and sometimes, in OB/GYN, you can be part of a very happy moment in their life.”
But eventually, Dr. Sincan decided to devote his skills to an area where he could help improve care for populations. He became a research fellow and then a scientist for the National Institutes of Health, where he worked with genomic sequencing, sequencing DNA. Sequencing results for each patient included about 20,000 gene mutations, or variants. But it would prove quite a challenge to review all 20,000 to look for as little as one mutation to help explain a patient’s disease.
“So I basically created methods to help computers process all that raw data coming from the machines and put that in a filtered, ranked, summarized list that the clinicians could review the top, maybe, 10 or the top 20 high-ranking variants. And that’s an easier task,” Dr. Sincan said.
Making EMR data usable
Dr. Sincan also serves as an assistant professor at the University of South Dakota Sanford School of Medicine and section head for clinical informatics.
Sanford Imagenetics, part of Sanford Health, aims to incorporate genetic information into the primary care of patients. To best help a patient, Dr. Sincan explains, that genetic information can be combined with their clinical information, usually found in the EMR, including diseases, symptoms, medications and medical and family history. Information collected from patients through, for example, questionnaires is also useful to complete the picture.
So in the three years since he started there, Dr. Sincan has been using his skills to help securely extract data from EMR, transform it to be computable, analyze it and combine it with the genetic data.
“We could be looking at an individual patient, or we could be looking at groups of patients and reporting on that” to answer a question, he said.
Project about genetic markers for disease
In his new role with Sanford Research, Dr. Sincan works on research projects involving data. He just received approval for a pilot grant through the Center for Health Outcomes and Population Health NIH COBRE program at Sanford Research. This project will use the database of genetic data that has been collected from Sanford BioBank DNA samples.
Adult Sanford Health patients have volunteered the BioBank blood samples. They are saved for the potential for future genetic testing to benefit the patient’s family, as well as for carefully regulated use by researchers who conduct large-scale studies on, for example, population genetics or cancer.
Dr. Sincan’s project will look at the relationship between patients’ conditions, which have been collected in EMR data associated with the BioBank samples, and two polygenic risk scores. A polygenic risk score, he explains, is a number calculated by looking at the number of certain individual genetic markers, or SNPs, that have been associated with a certain health outcome, such as type 2 diabetes or coronary artery disease. An SNP (single nucleotide polymorphism) could be associated with more than one disease as well.
Looking at a distribution of scores places some people in a category with a high probability of the disease, most with an average risk and some people with a low risk.
“When the researchers look at the relationship between these different groups of individuals … they observe a pattern of association between various health outcomes,” Dr. Sincan said.
Making precision medicine ‘even more precise’
Researchers have determined polygenic risk scores — more than 200 — for diseases ranging from Alzheimer’s to breast cancer. Each one is different, based on the SNPs.
And just as a single genetic mutation could have implications for more than one disease, a polygenic risk score for one disease could have an association with another disease as well, Dr. Sincan said.
His project, then, will examine the relationship between BioBank patients’ EMR data and the two polygenic risk scores developed by Dr. Cassie Hajek, physician chair for Sanford Imagenetics, for coronary artery disease and breast cancer. That should lead to greater understanding of the biological mechanisms driving those diseases, Dr. Sincan said.
“This type of research has the ability to generate many more hypotheses that we could study and learn, and make our approach to precision medicine even more precise. Because then we know if a polygenic risk score is only associated with a certain outcome, or if it has associations with many other outcomes,” he said.
Finding commonalities could help with predictions about health care, anticipation of future problems and preventive measures for patients.
Collaboration can help even more
Dr. Sincan said Sanford Health is well-poised to contribute to greater understanding of these types of genetic associations with patient conditions. It has a sizable amount of genetic and clinical data, collected over time, from a stable patient population.
“We owe it to our patients,” he said, to study the data that’s available.
“We need to be able to look at that and understand the things we don’t currently understand about diseases, individual patients, trajectories in time, why somebody’s benefiting from a certain treatment and somebody else is not, even though they look the same — they have the same disease,” Dr. Sincan said.
The COVID-19 pandemic, he added, has pointed out the value but also the difficulties of collaborating with other organizations to understand patterns of disease.
“We could only truly understand who is doing better, who is doing worse, what medications and what treatments work, what treatments don’t, by combining the data from every single health care organization into a central database,” Dr. Sincan said.
Current incompatability of EMR data makes that a huge challenge. But standardization could remedy that and, Dr. Sincan hopes, also lead to faster nationwide collaborations for many diseases.
Goal: Less suffering, faster healing
Perhaps such collaborations could do for many other diseases something similar to the evolution of cancer treatments, Dr. Sincan suggests. Rather than relying on one standard regimen of chemotherapy, a number of cancers now have targeted therapies that can result in better outcomes and fewer side effects for patients.
“The ultimate goal is to be able to prevent disease from happening,” Dr. Sincan said. “And when the disease manifests itself, to be able to treat that individual patient with the best, most precise treatment available that is tailored to that patient, to that molecular pathology, whatever the underlying cause of that patient’s disease in such a precise way that … nothing else is adversely affected.”
To this end, he studies many patients so he can identify how to help individual patients.
“Each patient will have a better outcome, and there will be less suffering. There will be quicker healing. Sometimes it will be less costly. Sometimes it will be less painful.”
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