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“Integration” Ain’t What It Used to Be
ACR CHAIR’S MEMO JAMES A. BRINK, MD
“Integration” Ain’t What It Used to Be Like many parents, I recently experienced the sinking feeling that comes from looking over your child’s shoulder only to realize that you can no longer do his or her homework. In my case, my uneasiness went way beyond not being able to do the homework; it involved the realization that I had no idea where to begin. My daughter Laura is a graduate student in electrical engineering, and even though I have an undergraduate degree in the same discipline, I could not begin to solve the problems she dutifully addressed on the pages before her. However, I couldn’t help but notice the endless integral symbols on her paper, denoting complex integrations that collectively formed the solutions to her problems. As I lamented the loss of my ability to solve such problems, I realized that “integration” has morphed from a critical mathematical function in my earlier years to a critical survival function for radiologists in the modern era. Modern health care systems are like the “circle of life” in The Lion King. Disruptions in one discipline can greatly affect other disciplines, both positively and negatively. The best way to survive such perturbations is to integrate with other disciplines in ways that advance the quality of care we provide to our patients while ensuring our relevance to the health care ecosystem. Several years ago, I led a department that was faced with a proposal to field radiologists in a new cancer center, potentially embedding
radiologists in the care delivery teams. The cancer center director hoped that by embedding radiologists in specific cancer care clinics, they could be part of the care team, offering opinions on outside imaging examinations and communicating clinical findings on current examinations to oncologists for immediate understanding and clinical application. At that time, the proposal was met with rather strong resistance. Radiologists were concerned about hampering their productivity and their ability to get through the day’s work, should they be encumbered with consulting with medical oncologists and other caregivers in the cancer center. In the end, the cancer center used the space that had been reserved for reading rooms on each floor for other clinical work spaces, and the proposal fizzled. I couldn’t help but feel that an important opportunity had been missed. Fast-forward to 2017 and a culture in which Imaging 3.0 has been dominating the radiology airwaves for the past few years. Popularized by its creator, Bibb Allen, MD, the Imaging 3.0 initiative is about getting radiologists out of the mind set of “report generator” and being part of a care delivery team and hospital ecosystem. Last month, the urology clinic at my current institution proposed that we field radiologists in their clinic to enable the radiologists to be part of the urologic care delivery team, with hopes of providing immediate interpretation of outside imaging examinations and translating
ª 2017 American College of Radiology 1546-1440/17/$36.00 n https://doi.org/10.1016/j.jacr.2017.09.040
clinical findings on current studies into immediate clinical application. Moreover, by embedding radiologists in the clinic, opportunities for academic collaboration are likely to escalate as clinical problems are mixed with imaging expertise during direct dialogue between urologic and radiologic practitioners. This time, I was pleased to discover a strong willingness on the part of our radiologists to consider this option. Although it remains in evolution pending space and other logistic requirements, I was pleased to see a distinct willingness on the part of these radiologists to embrace the opportunity to engage directly with their clinical counterparts from other disciplines. Moreover, I am optimistic that such a move could help mitigate against rising burnout among radiologists, as I’m confident that one important antidote to burnout is joy in the workplace. By embedding radiologists with care delivery teams, radiologists may find greater meaning in their work and greater appreciation for their expertise. Sometimes, I feel badly for radiologists who toil away for long hours in a dark reading room when referring physicians do not avail themselves of the opportunity to interact directly with them in their own environment. In this regard, the technical advances of the information age may improve the efficiency of our work, but they also lead to greater isolation and the potential for burnout. Although the efficiency of our radiologists who work in a
1379
clinical setting may decrease, I am optimistic that any potential decrease in efficiency is balanced with an increase in engagement and appreciation of our radiologists’ expertise. Integration may also occur at a different level within health care ecosystems. At the recent ACR Radiology Leadership Institute Summit at Babson College earlier this month, I had the pleasure of hosting David Louis, MD, pathologist-in-chief at Massachusetts General Hospital, as the keynote speaker for the afternoon session focused on artificial intelligence. Dr Louis spoke about “computational pathology,” a discipline that marries classical histopathology and laboratory medicine with data analytics and machine learning to better process the vast amounts of data housed within tissue samples, biopsy specimens, and laboratory samples. Although the details that underpin Dr Louis’s lecture go beyond the scope of this article, suffice it to say that one impressive experiment he showed highlighted the possibility that imputed laboratory values, derived from other clinical markers, may be more precise than the actual values that are measured from direct laboratory samples, in part because of inherent variability and error in the measurement of such values. In a subsequent breakout session, the group concluded that
ideally, radiologists and pathologists should “integrate” their expertise as information specialists, as the line between these two disciplines is becoming increasingly blurry. Biomarkers for specific diseases may be applied in vitro for analysis of pathologic samples or in vivo for improved diagnostic performance of imaging examinations. Moreover, integration of laboratory with clinical and imaging data through big data analytics and machine learning will only further blur the distinction between our specialties. Just as the interventional radiology community and the diagnostic radiology community realized the potential benefit of further integration through a joint training program, perhaps it’s time for radiologists and pathologists to consider poking at ways in which joint training programs may be developed that integrate these two specialties, focused on a specific medical discipline or subspecialty. Although I recognize that mastering both specialties completely will lead to unrealistic prolongation of medical training, it may be possible to find ways in which radiologists can integrate pathology into their practice and vice versa, to harness the opportunity to function jointly as true information specialists [1]. Although mathematical integration may have escaped my faculties
with advancing age, the importance of integration for radiology has become ever more important as integration with other medical specialties is a means to secure our place in the health care ecosystem. By embedding ourselves in the care delivery teams that refer patients to us for our services, we may ensure our relevance going forward, regardless of what artificial intelligence and machine learning may bring to our profession. Moreover, close-knit collaborations with other specialties may reduce burnout thanks to increased opportunities for collaboration, joint research, and interpersonal relationships with the colleagues that we serve. In addition, integration with other diagnostic disciplines such as pathology and laboratory medicine may help advance clinical diagnostics by shrinking the barriers that have existed between our specialties for the past many years. Integration ain’t what it used to be when we were students, but it is now the ticket to our success in the ever evolving world of health care ecosystems, big data analytics, and artificial intelligence.
REFERENCE 1. Jha S, Topol EJ. Adapting to artificial intelligence: radiologists and pathologists as information specialists. JAMA 2016;316: 2353-4.
The author has no conflicts of interest related to the material discussed in this article. James A. Brink, MD: Massachusetts General Hospital, 55 Fruit Street, FND-216, Boston, MA 02114-2698; e-mail: jabrink@ partners.org.
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Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
“Integration” Ain’t What It Used to Be Like many parents, I recently experienced the sinking feeling that comes from looking over your child’s shoulder only to realize that you can no longer do his or her homework. In my case, my uneasiness went way beyond not being able to do the homework; it involved the realization that I had no idea where to begin. My daughter Laura is a graduate student in electrical engineering, and even though I have an undergraduate degree in the same discipline, I could not begin to solve the problems she dutifully addressed on the pages before her. However, I couldn’t help but notice the endless integral symbols on her paper, denoting complex integrations that collectively formed the solutions to her problems. As I lamented the loss of my ability to solve such problems, I realized that “integration” has morphed from a critical mathematical function in my earlier years to a critical survival function for radiologists in the modern era. Modern health care systems are like the “circle of life” in The Lion King. Disruptions in one discipline can greatly affect other disciplines, both positively and negatively. The best way to survive such perturbations is to integrate with other disciplines in ways that advance the quality of care we provide to our patients while ensuring our relevance to the health care ecosystem. Several years ago, I led a department that was faced with a proposal to field radiologists in a new cancer center, potentially embedding
radiologists in the care delivery teams. The cancer center director hoped that by embedding radiologists in specific cancer care clinics, they could be part of the care team, offering opinions on outside imaging examinations and communicating clinical findings on current examinations to oncologists for immediate understanding and clinical application. At that time, the proposal was met with rather strong resistance. Radiologists were concerned about hampering their productivity and their ability to get through the day’s work, should they be encumbered with consulting with medical oncologists and other caregivers in the cancer center. In the end, the cancer center used the space that had been reserved for reading rooms on each floor for other clinical work spaces, and the proposal fizzled. I couldn’t help but feel that an important opportunity had been missed. Fast-forward to 2017 and a culture in which Imaging 3.0 has been dominating the radiology airwaves for the past few years. Popularized by its creator, Bibb Allen, MD, the Imaging 3.0 initiative is about getting radiologists out of the mind set of “report generator” and being part of a care delivery team and hospital ecosystem. Last month, the urology clinic at my current institution proposed that we field radiologists in their clinic to enable the radiologists to be part of the urologic care delivery team, with hopes of providing immediate interpretation of outside imaging examinations and translating
ª 2017 American College of Radiology 1546-1440/17/$36.00 n https://doi.org/10.1016/j.jacr.2017.09.040
clinical findings on current studies into immediate clinical application. Moreover, by embedding radiologists in the clinic, opportunities for academic collaboration are likely to escalate as clinical problems are mixed with imaging expertise during direct dialogue between urologic and radiologic practitioners. This time, I was pleased to discover a strong willingness on the part of our radiologists to consider this option. Although it remains in evolution pending space and other logistic requirements, I was pleased to see a distinct willingness on the part of these radiologists to embrace the opportunity to engage directly with their clinical counterparts from other disciplines. Moreover, I am optimistic that such a move could help mitigate against rising burnout among radiologists, as I’m confident that one important antidote to burnout is joy in the workplace. By embedding radiologists with care delivery teams, radiologists may find greater meaning in their work and greater appreciation for their expertise. Sometimes, I feel badly for radiologists who toil away for long hours in a dark reading room when referring physicians do not avail themselves of the opportunity to interact directly with them in their own environment. In this regard, the technical advances of the information age may improve the efficiency of our work, but they also lead to greater isolation and the potential for burnout. Although the efficiency of our radiologists who work in a
1379
clinical setting may decrease, I am optimistic that any potential decrease in efficiency is balanced with an increase in engagement and appreciation of our radiologists’ expertise. Integration may also occur at a different level within health care ecosystems. At the recent ACR Radiology Leadership Institute Summit at Babson College earlier this month, I had the pleasure of hosting David Louis, MD, pathologist-in-chief at Massachusetts General Hospital, as the keynote speaker for the afternoon session focused on artificial intelligence. Dr Louis spoke about “computational pathology,” a discipline that marries classical histopathology and laboratory medicine with data analytics and machine learning to better process the vast amounts of data housed within tissue samples, biopsy specimens, and laboratory samples. Although the details that underpin Dr Louis’s lecture go beyond the scope of this article, suffice it to say that one impressive experiment he showed highlighted the possibility that imputed laboratory values, derived from other clinical markers, may be more precise than the actual values that are measured from direct laboratory samples, in part because of inherent variability and error in the measurement of such values. In a subsequent breakout session, the group concluded that
ideally, radiologists and pathologists should “integrate” their expertise as information specialists, as the line between these two disciplines is becoming increasingly blurry. Biomarkers for specific diseases may be applied in vitro for analysis of pathologic samples or in vivo for improved diagnostic performance of imaging examinations. Moreover, integration of laboratory with clinical and imaging data through big data analytics and machine learning will only further blur the distinction between our specialties. Just as the interventional radiology community and the diagnostic radiology community realized the potential benefit of further integration through a joint training program, perhaps it’s time for radiologists and pathologists to consider poking at ways in which joint training programs may be developed that integrate these two specialties, focused on a specific medical discipline or subspecialty. Although I recognize that mastering both specialties completely will lead to unrealistic prolongation of medical training, it may be possible to find ways in which radiologists can integrate pathology into their practice and vice versa, to harness the opportunity to function jointly as true information specialists [1]. Although mathematical integration may have escaped my faculties
with advancing age, the importance of integration for radiology has become ever more important as integration with other medical specialties is a means to secure our place in the health care ecosystem. By embedding ourselves in the care delivery teams that refer patients to us for our services, we may ensure our relevance going forward, regardless of what artificial intelligence and machine learning may bring to our profession. Moreover, close-knit collaborations with other specialties may reduce burnout thanks to increased opportunities for collaboration, joint research, and interpersonal relationships with the colleagues that we serve. In addition, integration with other diagnostic disciplines such as pathology and laboratory medicine may help advance clinical diagnostics by shrinking the barriers that have existed between our specialties for the past many years. Integration ain’t what it used to be when we were students, but it is now the ticket to our success in the ever evolving world of health care ecosystems, big data analytics, and artificial intelligence.
REFERENCE 1. Jha S, Topol EJ. Adapting to artificial intelligence: radiologists and pathologists as information specialists. JAMA 2016;316: 2353-4.
The author has no conflicts of interest related to the material discussed in this article. James A. Brink, MD: Massachusetts General Hospital, 55 Fruit Street, FND-216, Boston, MA 02114-2698; e-mail: jabrink@ partners.org.
1380
Journal of the American College of Radiology Volume 14 n Number 11 n November 2017