Featured Members

Featured Members

MPOG membership includes clinicians, quality experts, software developers, statisticians, and administrators from institutions across the U.S. and Europe.  MPOG builds upon the outstanding research, education and quality work from these individuals.  The featured member profiles highlight the work of MPOG members around the world.

OCTOBER & NOVEMBER 2018

Karen Domino, MD, MPH

Professor and Vice Chair for Clinical Research in the Department of Anesthesiology and Pain Medicine
Adjunct Professor of Neurologic Surgery
University of Washington, School of Medicine in Seattle

BIOGRAPHY

I have a long standing interest in clinical outcome research utilizing cohort, case control, and mixed methods research methodologies. For over the past 15 years, I’ve directed the Anesthesia (formerly ASA) Closed Claims Project and Registries, which investigates adverse outcomes of patients undergoing perioperative anesthetic care using analysis of closed files at malpractice insurance organizations and use of specialized patient registries. In recognition of my research contributions to our specialty, I’m giving the 10th John W. Severinghaus Lecture in Translational Science at the ASA Annual Meeting in October.  I’m the MPOG and ASPIRE champion for University of Washington hospitals.

What are you thinking about:  

I’m thinking about the importance of risk-predictive models to guide clinical decision-making. Although quantitative risk-stratification models have been in use for decades, they are seldom used in clinical decision-making by physicians and patients.

Why is this interesting to you:  

Many patients and families are concerned with the quality of life after medical and surgical treatments. However, physicians often only discuss the percentage of successful response or probability of death or major morbidity after a treatment, instead of outcomes that matter to patients. For instance, geriatric patients may fear the loss of ability to drive or ability to live independently, more than death.

What are the practical implications for healthcare: 

With the emphasis on patient empowerment and shared decision-making in healthcare, risk-stratification and prediction of outcomes relevant to patients/families is needed. Addition of patient-centered and patient-reported outcomes to “big” data would enhance the ability for physicians to provide individualized risk predictions and improve patient engagement in decision-making, according to their values and preferences. Making treatment decisions that result in outcomes important to patients would reduce costs and improve quality of healthcare.

How are you involved with MPOG?

I’m the MPOG and ASPIRE Champion for the University of Washington Hospitals: the University of Washington Medical Center (a university hospital) and Harborview Medical Center (the only level 1 trauma center in the 5 state northwest US region).  I’ve been a long-term believer in multi-center outcome and quality research to adequately reflect the diversity of patients and practices in medical care. I’m especially excited about the use of the MPOG infrastructure as the basis for prospective enhanced observational and pragmatic clinical trials to study patient-reported and longer-term outcomes.

AUGUST & SEPTEMBER 2018

Robert Schonberger, MD

Associate Professor

BIOGRAPHY

Dr. Schonberger’s clinical work is in the Section of Cardiac Anesthesia where he cares for patients undergoing cardiothoracic procedures at Yale-New Haven Hospital. In his NIH-funded research, he studies the role of anesthesiologists in improving longitudinal cardiovascular risk-factor recognition and treatment among surgical patients. Other interests include 1) novel methods of extra corporeal circulation, 2) clinical informatics, and 3) methods of reducing and treating microembolic events in several clinical scenarios including cardiopulmonary bypass, ECMO, and decompression sickness. Dr. Schonberger is also the site PI for Yale’s participation in the Multicenter Perioperative Outcomes Group (MPOG) consortium.

What are you thinking about:  

I am thinking about what it means for anesthesiologists to be good doctors. While safe intraoperative and ICU care are what the anesthesiology community is known for, I believe we must also ask what other obligations and opportunities for helping our patients to live longer and more fulfilling lives are allowed to pass in front of us every day.

Why is this interesting to you:  

It is clear to me that if anesthesiologists do not think about our work in terms of “how to be a good doctor,” we will miss out on the greatest public health opportunities of our daily practice – specifically, how to help our patients engage in improving their postoperative health trajectories (e.g. getting folks engaged in preventive medical care, identifying and addressing poorly controlled hypertension, encouraging smoking-cessation, improving lipid management, and identifying other threats to our long-term health).

What are the practical implications for healthcare: 

The implications for healthcare are simply that we should try our best to deliver more of it in ways that matter.

How are you involved with MPOG?

As a site-PI on the PCRC, I get tremendous satisfaction watching the diversity of investigators – and the projects they create – within MPOG. It is gratifying to play my own small role in making those projects possible, and it would be nice to bring more national and international recognition to MPOG from beyond the anesthesiology community. I think one of the keys to that effort is to compete for extramural funding using the MPOG infrastructure, and I am glad to see several projects heading in that direction.

JUNE & JULY 2018

Kai Kuck, PhD

President, Society for Technology in Anesthesia (STA)
Professor of Anesthesiology
Adjunct Professor of Bioengineering
Harry C. Wong Presidential Endowed Chair in Anesthesiology
Director of Bioengineering, Department of Anesthesiology

BIOGRAPHY

Throughout my work, I have been involved in the research and development of innovative medical technologies with a focus on anesthesia and critical care. My areas of focus include cardiorespiratory monitoring, intelligent decision support, and ventilation.

My experience covers the whole range from hands-on engineering for hardware, software, algorithm, and graphical user interface development all the way to managing projects, programs, and large teams of researchers. In my last position I oversaw the research of Dräger, the global market leader in anesthesia equipment and critical care ventilation, Since 2014, in my role as Director of Bioengineering at the University of Utah’s Department of Anesthesiology, I have the privilege of working closely with clinicians and learning about real-world needs and opportunities for technologies.

Because transforming healthcare increasingly involves innovations at the system and workflow level, this collaborative approach is essential to creating technologies that address real needs in the clinic.

What are you thinking about:  

I am thinking about how to take perioperative and anesthesia related data, learn from it, and then translate the learnings into clinical tools that can be used to help improve anesthesia patient care. With my biomedical engineering background, it also fascinates me to think about combining data and devices – both in terms of devices (think: wearables, mobile devices) that capture data and in terms of devices that use data.

Why is this interesting to you:  

Industries, such as retail, financial services, marketing, are way ahead of healthcare and anesthesiology when it comes to using data to improve what they deliver. Currently, health IT has only begun to scratch the surface of its potential to improve care delivery. As these other industries are showing us, there is so much more potential. MPOG is building the infrastructure for data collection, multi-site collaboration, enhancing electronic data with context, data-based research, and translation into clinically usable tools.

What are the practical implications for healthcare: 

Practical implications include the fact that we could then provide clinically useful information and decision support to clinicians who put so much work into entering data into electronic health records (EHR). We will likely be able to personalize healthcare delivery in a much more accurate manner than today. And finally, we could relieve anesthesiologists from some of the more tedious tasks, which computers are much better at than humans (store massive amounts of data, and then recall, select, and filter the data to be more relevant to one specific patient).  As a result, patient outcome will be better and healthcare delivery more efficient than today.