Email: Ellen.Green [at] asu [dot] edu
Office Phone: (602) 496-2879
I am a health economist with interests in behavioral economics and experimental design. The goal of my research is to improve the quality of public policymaking such that it has a direct and positive impact on the health of our population.
My research is founded by the principle that a better understanding of the nuances of decision-making through behavioral economics will allow us to design more effective and innovative public policy. I use laboratory and framed field experiments to evaluate how clinical decision-making is influenced by public policy, with a specific focus on incentive systems and reimbursement structures for health care providers as well as other non-monetary motivators. This research has pertinent implications among both developed and developing economies.
Associate Professor (2021-Present)
College of Health Solutions
Arizona State University
Ph.D. in Economics, Virginia Polytechnic Institute and State University
Health Economics, Behavioral Economics, Experimental Economics, Public Policy
“A Cautionary Study on the Effects of Pay-for-Performance on Quality of Care: A Pilot Randomized Controlled Trial Using Standardized Patients” joint with Noel M. Arring, Janet O’Brien, Katherine Markiewicz, Katherine Peterson (first author). Forthcoming at BMJ Quality and Safety
“Gender Effects in the Credence Goods Labor Market” joint with Anjali Agrawal, and Lisa Lavergne. Economic Letters 2019
“Payment Scheme Self-Selection in the Credence Goods Market: An Experimental Study” joint with Hernán Bejarano, and Stephen Rassenti Journal of Economic Behavior & Organization 142 (2017): 396-403.
“Experimental and Behavioral Economics of Healthcare.” joint with Cox, James C. and Heike Hennig-Schmidt Journal of Economic Behavior and Organization 131 (2016) A1-A4“Angels and Demons: Using Behavioral Types in a Real-Effort Moral Dilemma to Identify Expert Traits.” Frontiers in psychology 7 (2016): 1464. “Payment Systems in the Healthcare Industry: An Experimental Study of Physician Incentives” The Journal of Economic Behavior and Organization 106 (2014): 367-378.
“Potential Impact Of Risk And Loss Aversion On The Process Of Accepting Kidneys For Transplantation.” joint with Raymond L. Heilman, Kunam S. Reddy, Adyr Moss, and Bruce Kaplan (second author) Transplantation 101.7 (2017): 1514-1517
"Compensation and Production in Family Medicine by Practice Ownership." joint with Essary, Alison C., and David N. Gans Health Services Research and Managerial Epidemiology 3 (2016)
“Lessons Learned from Implementing the Patient-Centered Medical Home.” joint with John Wendland, Colette Carver, Hughes Cortney, and Sun Ki Mun (first Author) International Journal of Telemedicine and Applications 6 (2012)
“Using behavioral economics to reduce the discard rate of viable kidneys: Validating new methods to identify factors that influence the acceptance of deceased donor kidneys.” R21. NIDDK. PI. ($449,864) 2021-2023
“A Simulation Study of the Medicare Access and CHIP Reauthorization Act.” R01. National Institute on Aging. PI. ($1,936,838) 2019-2024
“Using Behavioral Economics to Increase Comprehension and Knowledge of Risks and Benefits of Living Organ Donation.” ISSR Seed Grant. PI. ($8,000) 2017
“Using Behavioral Economics to Transform Health Care Policy: An Experimental Study of Payment Scheme Sorting” ISSR Seed Grant PI. ($6,000) 2016
“Using Behavioral Economics to Transform US Health Care Delivery and Disease Management” Mayo-ASU Seed Grant ($50,000) PI 2015
"The Impact of a Merit-Based Incentive Payment System on Quality of Healthcare: A Framed Field Experiment" joint with Noel M. Arring, Janet O’Brien, Katherine Markiewicz, Katherine S. Peterson. Revise and Resubmit
Despite their popularity, studies of merit-based incentive payment schemes have not demonstrated that outcome-based payment is associated with consistent improvement in performance or decline in costs of care (Emmert et al., 2012, Gillam et al., 2012; Rosenthal et al., 2006; Werner et al., 2011). The failure to find significant and consistent associations is likely due to the fact that policy changes to financial models are difficult to study in real-world contexts. Natural experiments or field studies typically do not allow the researcher to distinguish between the effects of implicit and explicit incentives, to adapt for measurement error, to implement exogenous changes to the models, or directly measure unintended consequences (Cox, Green, Hennig-Schmidt, 2016). Hence, novel research methods are necessary to isolate the potential impact of the proposed finance reform in the healthcare industry.To study the potential impact of merit-based incentive payment schemes on practitioner behavior, we used economic experiments that leverage healthcare simulations with patient actors. We recruited practicing primary care physician assistants and nurse practitioners to participate in a medical simulation. The providers were asked to evaluate standardized patients (performed by actors) and develop diagnostic and treatment plans for each. Treatments in the experiment varied by incentive scheme. Providers were assigned to either a control group or merit-based incentive payment system (MIPS) group. In the control group, providers were paid a flat rate for participating in the experiment. Under MIPS, providers were paid a (lower) flat rate plus a bonus for each of the self-reported incentivized outcome measures that they satisfied. This approach allowed us to implement exogenous changes to providers’ incentives within a controlled environment. Measurements of patient satisfaction, standards of care, and adherence to the incentivized outcome measures were collected and compared across study groups. Within our sample, we found that the MIPS increased the number of incentivized outcome measures met; however, the overall quality of care was lower for the MIPS group. Specifically, practitioners paid under MIPS had lower standards of care in collecting patient histories, conducting physical exams, and providing summaries of patient encounters. The MIPS group also had lower patient satisfaction scores. Further, practitioners paid under MIPS were more likely to inappropriately order the screening tests described in the PQRS measures. For example, practitioners paid under the MIPS were more likely to prescribe mammograms and colonoscopies for a patient under the age of 50, (i.e., outside the recommended age group). This is the first study to use health care simulations to study a policy change in financial models. This approach allows us to directly measure unintended consequences of an outcome-based payment scheme in a controlled environment. In our study, we confirm economic predictions and find that practitioners respond to outcome-based payment by diverting resources from unrewarded actions (standards of care) to rewarded actions (incentivized outcome measures) (Holmstrom and Milgram 1991, Pendergast 1999, Gravel et al 2010).
“Gender Effects in the Credence Goods Labor Market” joint with Anjali Agrawal and Lisa Lavergne. Forthcoming at Economic LettersIn this paper, we offer further explanation for the differences in earnings across genders by investigating the credence goods market in a laboratory experiment. Through our study, we reveal key differences in preferences across genders in the credence goods markets. First, in the credence goods market, women were no less likely to select variable rate payment schemes than men. However, overall earnings remained higher for men than for women. Disaggregating behavior by selected payment reveals that women who chose fee-for-service provided significantly fewer services than men who chose fee-for-service, explaining the lower overall earnings for women.
“A Primer in Healthcare Simulations: A New Laboratory for the Experimental Economist”
Healthcare simulations have been used to evaluate clinical performance in true-to-practice environments for teaching hospitals, medical schools, board licensure examinations, and continuing medical education programs without potential harm to patients by imitating the interaction between a clinician and their patient with hired actors, patient mannequins, or virtual patients in a scripted environment. The control offered by healthcare simulations provides researchers with a novel setting to evaluate policy changes under ceteris paribus conditions. However, healthcare simulations have been underutilized as a research method. In this paper, I provide an overview of healthcare simulations for an experimental health economist and recommend their adoption as a test-bed for studying policy change in the healthcare industry.
“Health Care Policy from Bench to Bedside” joint with Nilay Shah.
In 2019, health care providers will receive the first adjustments to their Medicare reimbursement rates as a result of the legislation passed in the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA). MACRA permanently repealed and replaced the long criticized Sustainable Growth Rate (SGR) formula that had been used to adjust Medicare reimbursement rates since 1998. The SGR was replaced by two scientifically-unvetted methods of reimbursement: The Merit Based Incentive Payment System (MIPS) and Alternate Payment Models (APMs). Though one aspirational goal of new reimbursement models was to promote high-quality care at lower cost, controlled experiments debunked this theory and reinforced the value of health care simulation research in evaluating health policy (Green, Peterson, Markiewicz, O’Brien, & Arring, 2017).
“Should I stay or Should I Go? An Experimental Study of Decision Support Devices and Hospital Discharge,”
joint with Sheryl Ball and Landis Atkinson.
Efforts to reduce frank medical errors and promote evidence-based clinical practice in the U.S. health system have reduced clinical judgment in discretionary decisions. With a specific application to hospital discharge, our experiment expands on Fehr, and Fischbacher (2008) by exploring how the dissemination of responsibility in clinical decision-making impacts patient outcomes. Our results suggest that when Clinical Decision Support devices are used in place of physician discretion, patients are less likely to penalize their physician for negative outcomes if the patient selects the use of a CDS. This suggests that there is less utility lost for bad outcomes when decisions are made by CDS devices, ceteris paribus.
Given heterogeneity in expert behavior across payment schemes in credence goods markets, it becomes important to understand the consequences of payment scheme selection. To study the effect on customer well being of expert self-selection, we recruited subjects to participate in a real-effort credence good laboratory market. Experts were either randomly assigned or faced with the choice of three payment schemes: fee-for-service, salary, and capitation. We found that experts who selected fee-for-service payment resulted in customers with significantly worse outcomes in comparison with experts who had been randomly assigned to fee-for-service. In contrast, experts who selected salary payment did not change customer outcomes relative to those who were randomly assigned.
“Potential Impact of Risk and Loss Aversion on the Process of Accepting Kidneys for Transplantation” joint with Raymond L. Heilman, Kunam S. Reddy, Adyr Moss, and Bruce Kaplan (second author) Transplantation 101.7 (2017): 1514-1517
Behavioral economic theory suggests that people make decisions based on maximizing perceived value; however, this may be influenced more by the risk of loss rather than of potential gain. Additionally, individuals may seek certainty over uncertainty. These are termed loss aversion and risk aversion, respectively. Loss aversion is particularly sensitive to how the decision is “framed.” Thus, labeling a kidney as high Kidney Donor Profile Index results in higher discard rates because this creates a nonlinearity in perceived risk. There is also evidence that the perceived loss due to regulatory sanction results in increased organ discard rates. This may be due to the overuse of terminology that stresses regulatory sanctions and thus perpetuates fear of loss through a form of nudging. Our goal is to point out how these concepts of behavioral economics may negatively influence the decision process to accept these suboptimal organs. We hope to make the community more aware of these powerful psychological influences and thus potentially increase the utilization of these suboptimal organs. Further, we would urge regulatory bodies to avoid utilizing strategies that frame outcomes in terms of loss due to flagging and build models that are less prone to uncertain expected versus observed outcomes.
“Angels and Demons: Using Behavioral Types in a Real-Effort Moral Dilemma to Identify Expert Traits.” joint with Bejarano, Hernán, and Stephen Rassenti Frontiers in psychology 7 (2016): 1464.
In this article, we explore how independently reported measures of subjects' cognitive capabilities, preferences, and sociodemographic characteristics relate to their behavior in a real-effort moral dilemma experiment. To do this, we use a unique dataset, the Chapman Preferences and Characteristics Instrument Set (CPCIS), which contains over 30 standardized measures of preferences and characteristics. We find that simple correlation analysis provides an incomplete picture of how individual measures relate to behavior. In contrast, clustering subjects into groups based on observed behavior in the real-effort task reveals important systematic differences in individual characteristics across groups. However, while we find more differences, these differences are not systematic and difficult to interpret. These results indicate a need for more comprehensive theory explaining how combinations of different individual characteristics impact behavior is needed.
"Compensation and Production in Family Medicine by Practice Ownership." joint with Essary, Alison C., and David N. Gans Health Services Research and Managerial Epidemiology 3 (2016)
The increasing focus on high performance, patient-centered, team-based care calls for a strategy to evaluate cost-effective primary care. The trend toward physician practice consolidation further challenges the primary care health care system. Productivity measures establish provider value and help inform decision making regarding resource allocation in this evolving health care system. In this national survey of family medicine practices, physician assistant (PA) productivity, as defined by mean annual patient encounters, exceeds that of both nurse practitioners (NPs) and physicians in physician-owned practices and of NPs in hospital or integrated delivery system-owned practices. Total compensation, defined as salary, bonus, incentives, and honoraria for physicians, is significantly more compared to both PAs and NPs, regardless of practice ownership or productivity. Physician assistants and NPs earn equivalent compensation, regardless of practice ownership or productivity. Not only do these data support the value and role of PAs and NPs on the primary care team but also highlight differences in patient encounters between practice settings. Rural and underserved community practices, where physician-owned practices persist, also merit further consideration. Further research is needed to inform both organizational and policy decisions for the provision of high-quality, cost-effective, and accessible primary health care.
“Payment Systems in the Healthcare Industry: An Experimental Study of Physician Incentives.” The Journal of Economic Behavior and Organization 106 (2014): 367-378.
Policy makers and the healthcare industry have proposed changes to physician payment structures as a way to improve the quality of health care and reduce costs. Several of these proposals require healthcare providers to employ a value-based purchasing program (also known as pay-for-performance [P4P]). However, the way in which existing payment structures impact physician behavior is unclear and therefore, predicting how well P4P will perform is difficult. To understand the impact physician payment structures have on physician behavior, I approximate the physician-patient relationship in a real-effort laboratory experiment. I study several prominent physician payment structures including fee-for-service, capitation, salary, and P4P. I find that physicians are intrinsically motivated to provide high-quality care and that relying exclusively on extrinsic incentives to motivate physicians is detrimental to the quality of care and costly for the healthcare industry.
“Lessons Learned from Implementing the Patient-Centered Medical Home” [First Author] joint with John Wendland, Colette Carver, Hughes Cortney, and Sun Ki Mun, International Journal of Telemedicine and Applications. 2012
The Patient-Centered Medical Home (PCMH) is a primary care model that provides coordinated and comprehensive care to patients to improve health outcomes. This paper addresses practical issues that arise when transitioning a traditional primary care practice into a PCMH recognized by the National Committee for Quality Assurance (NCQA). Individual organizations experiences with this transition were gathered at a PCMH workshop in Alexandria, Virginia, in June 2010. An analysis of their experiences has been used along with a literature review to reveal common challenges that must be addressed in ways that are responsive to the practice and patients’ needs. These are: NCQA guidance, promoting provider buy-in, leveraging electronic medical records, changing office culture, and realigning workspace in the practice to accommodate services needed to carry out the intent of PCMH. The NCQA provides a set of standards for implementing the PCMH model, but these standards lack many specifics that will be relied on in location situations. While many researchers and providers have made critiques, we see this vagueness as allowing for greater flexibility in how a practice implements PCMH.
Based on the results of this series of experiments on physician payment structures, I will be able to provide insight into the optimal physician payment structure. The optimal payment structure balances quality of care with the cost of care. With this information in hand, I will team up with medical schools or local healthcare providers to test the efficacy and efficiency of the novel payment structures in the field. Since earning my Phd in Economics, I have developed relationships with health care providers and local medical schools in the interest of this project. I will use these valuable network connections and the networking experience gained as a springboard for establishing new contacts in the healthcare industry. The benefits of these relationships are twofold: they provide invaluable feedback on incentive structures and implementation, and they offer new venues to test payment scheme efficacy. Through collaborations with the healthcare industry, we can design and implement new, efficient payment mechanisms that optimize patient outcomes.
Graduate Instructor of the Year, Dec. 2011
Department of Economics, Virginia Tech
“Barrett grad Anjali Agrawal off to medical school in the fall” Barrett Honors College, ASU online, January 2, 2018
University of Delaware (2012-2014)
Honors Principles of Microeconomics, Principles of Macroeconomics, Money and Banking, Intermediate Microeconomic Theory, Honors Colloquium: Behavioral Economics Honors Money and Banking
Virginia Tech (2009-2011)
Principles of Microeconomics
Advising at Arizona State University
Shiela Lokareddy (MS, SHCD); Jon Patterson (MS, SHCD); Ryan Greiger (MS, SHCD); Kyle Jahn (MS, SHCD); Gabrielle Knight (MS, SHCD); Azra Ariff (MS, SHCD); Alexandra Douglas (MS, SHCD); Nathanial Howard (MS, SHCD); Jonathan Underwood (MS, SHCD); Anjali Agrawal (Honors UG, Nutrition); Christopher Anastos (MS, SHCD); Tatyana Minafee (MS, SHCD); Michael Genau (MS, SHCD)
Arizona State University Student Comments
[selected from end of the year teaching evaluations]:
• she was probably the best professor I've ever had. She made class fun and easy to want to learn and be there.
• Very energetic and excited about the material. Always finds a way to apply it to everyday situations. She is always willing to help her student and knows how to be both honest and respectful! Such an amazing professor!
• Dr. Green has so much enthusiasm for this subject material and it was really awesome to see how it relates to healthcare.
• Sense of humor and attitude was always positive
• She's genuinely passionate about the course, and it makes everything much easier.
• Dr. Green is a fantastic teacher. She made this course interesting and a fun class to be in. I have learned that economics is much more interesting than I expected it to be and I am looking forward to taking my other economics class now! Thanks for the great semester!
University of Delaware Student Comments
[selected from end of the year teaching evaluations]:
• [Dr. Green] challenged the class with questions and demonstrations on the board that required the students to really think about and apply the concepts discussed in class.
• [Dr. Green] regularly interjects personal stores / examples of economics in action.
• [Dr. Green] gets the class thinking beyond just the concepts presented in the textbook.
• Her use of technology through research days reinforced the material and showed her willingness for progression in teaching methods.
• Dr. Green is so excited and positive and she really made class fun. She also draws excellent graphs. I really liked that we had a small class and she was able to engage us all and make an economics class bearable.
• Dr. Green's use of the iPad to display notes was really helpful. Notes were easy to read and well organized. It is obvious she knows a lot about her field and tries very hard to apply it to our lives.
• Dr. Green is by far one of the best teachers I have had so far at UDel. She is organized and explains the material thoroughly and in a way that is easy to understand.
• Favorite class of the semester, mostly because of Dr. Green's teaching.
• I loved how organized this class was, and it really helped me to understand the information better.
• She was always very enthusiastic about the material and made herself readily available with answering any questions we may have had. Although a short period, I learned a lot from her. By coming to class and filling out her power points and by reading the textbook, I was able to fully absorb the material at hand. I also thought her research days were a great choice because it gave the students a time to actively apply the concepts. In her lectures she also accompanied the terms or concepts with examples, which definitely helped reinforce the material. She did a great job!
• She's very dedicated and wants students to understand the course not just to pass her exams.
• Professor Green is an outstanding teacher. She makes Econ an informative yet enjoyable class.
As with any academic, I strive to for a healthy balance between my research, teaching, and extra curricular activities.
While in graduate school, I started running as a form of “motion therapy”. I ran my first 10k in my second year of my PhD program and have since completed several other races including my first half marathon in the fall of 2012 [the hilly Runner’s World Half in Bethlehem, PA].
My passion for running eventually spilled over to swimming and cycling. I have completed 3 Sprint and 2 Olympic Triathlons. Perhaps one of the most gratifying of my accomplishments was beating my older brother in an Olympic Triathlon in 2014. My personal goal is to complete a marathon and a century ride (my longest bike ride to date is 92 miles).
I also enjoy hiking and have trekked several mountains up and down the east coast as well as in Arizona. A recent victory was climbing Mount Washington via Huntington’s Ravine. Huntington’s Ravine is noted as the most difficult trail in the White Mountains and it lives up to its name.
If you find yourself in Arizona in the first two weeks of October, I highly recommend taking a hike on the Abineau-Bear Jaw Loop to see the Aspens' leaves turn a brilliant gold. This is my favorite hike to date.
Of course one must balance exercise with a healthy amount of culinary experimentation. Over the past couple of years I have sought to find the optimal recipe for several baked goods.
@ ellenpgreen, 2013. All rights reserved