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Funded by Patient-Centered Outcomes Research Institute (PCORI)

Funding Years: 2014 - 2016.

Obesity is increasingly considered among the most important public health problems of our times. Bariatric surgery is arguably the only treatment that has proven effective in producing long-term weight loss for patients with morbid obesity. Bariatric surgery also results in resolution of obesity related comorbid conditions, improvements in quality of life, and increased survival.

There are currently four different bariatric surgical procedures in use: adjustable gastric banding, gastric bypass, sleeve gastrectomy, and duodenal switch. Bariatric surgery is considered a highly preference sensitive medical issue. Existing decision aids in bariatric surgery are limited in that they provide information about the average comparative risks and benefits of the treatment options, but do not provide customized estimates of the risks and benefits of the different procedures for individual patients. As a result of these draw-backs, decision aids are not frequently used in making treatment decisions in bariatric surgery.

Our proposal is highly innovative in that our decision support tool integrates data from a large clinical registry with individual patient data to provide patients with real-time, customized, accurate information regarding the risks and benefits of the treatment options to better inform decision making. This tool will be continuously updated to ensure that the data on risks and benefits that it provides are accurate and current. Our tool also provides information about other attributes of the treatment options that bariatric surgery patients and other relevant stakeholders feel are important for patients to consider in deciding whether and what type of bariatric surgery to have.

The proposed research promotes shared medical decision making for patients who are considering bariatric surgery for the treatment of morbid obesity. If our intervention proves effective, it will result in improved decision quality and outcomes of care for patients. It may also result in improved efficiency of care to the extent that it serves to augment or guide communication between the patient and physician to promote shared medical decision-making.

PI(s): Nancy Birkmeyer

Co-I(s): Lawrence An, Mousumi Banerjee, Angela Fagerlin, Sarah Hawley, Edward Norton, Lisa Prosser,

Funded by Patient-Centered Outcomes Research Institute (PCORI).

Funding Years: 2013-2016.

The birth of a child with a disorder of sex development (DSD) is stressful for parents and members of the healthcare team. The "right" decisions about gender assignment (is it a boy? a girl?) and the best course of action (e.g., should there be surgery? what kind? when?) are not obvious. While there have been large advances in diagnostic assessments like genetic and endocrine testing, the tests do not always show what caused the DSD. And, even when the tests do reveal an explanation for the DSD, knowing what happened genetically or hormonally does not usually lead to a single "correct" treatment plan. Instead, it is likely that there are different acceptable treatment options - and parents will need to make decisions based, in part, on their personal preferences, values, and cultural background. Adding more stress to the situation is knowledge that many of the decisions that need to be made by parents early in a child's life are irreversible and exert life-long consequences for the child and the family.

To support parents becoming actively involved in making such decisions, and to reduce the likelihood of future worry and regret about decisions that have been made, the investigators will create a decision support tool (DST). The DST will help educate families about typical and atypical sex development of the body, the process by which DSD are diagnosed (especially how to interpret genetic test results), and possible relationships between diagnostic/genetic testing, decisions about care, and known consequences of those decisions on their child and entire family. The DST will be used by parents of young children together with their child's health care provider.

The investigators will bring together a network of researchers, health care providers, representatives of patient support and advocacy organizations, and parents of children with DSD to share their experiences. Participants of this network will be involved at each stage of creating the DST, revising it, and putting it into practice. At the end of this project, the investigators will have a fully formed and tested DST that will be available for parents to use with their child's health care team as they are first learning their child may have a DSD.

PI(s): David Sandberg

Co-I(s): Edward Goldman, Catherine Keegan, Beth Tarini, Beverly Yashar


Funded by the National Institutes of Health.

Funding Years: 2011-2016. 

While substantial progress has occurred recognizing community expertise in Research, and involving Communities in Decisions about Research aims and methods, community influence on Research Funding priorities remains limited. Building on experience with developing, Testing and using the successful CHAT (Choosing Healthplans All Together) tool, we plan to modify an existing priority setting simulation exercise to develop a tool to engage minority and underserved Communities in setting priorities for clinical and translational Research, evaluate it from the perspective of those who participate, and examine the extent to which it actually influences Research priorities. This tool could be valuable to Research Funding organizations, community-academic partnerships, community organizations asked to participate in Research, and others aiming to engage Communities in Research. For more information, visit NIH Reporter

PI(s): Susan Goold

Co-I(s): Kathryn Moseley 


Funded by the Department of Veterans Affairs.

Funding Years: 2012-2013.

Diabetes is a complex, chronic disease encompassing many domains of treatment. VHA and others have created diabetes guidelines to help support providers and patients in making choices about optimal treatment approaches. However, most guidelines are broad in nature, and offer relatively little guidance on how to personalize care in order to maximize treatment benefits, minimize the intensity and negative effects of treatment, and best align with individual treatment preferences. 

We will test the effectiveness of a personalized decision support program. Our long term goals are:

  • To test and implement a decision support program, including decision coaching supported by an interactive, personalized decision support tool, in clinical practice via our Patient-Aligned Care Team (PACT) laboratory.
  • To assess the impact of personalized decision support on patient-centeredness, patient satisfaction, and the effectiveness of risk communication and treatment decision making.

We propose an interventional study to examine the effectiveness of personalized decision support. The intervention will consist of two key components: a decision coach  and a personalized diabetes decision support tool. The decision support tool has mostly been developed via AHRQ and local pilot funding mechanisms, and is informed by personalized estimation of treatment benefits for blood glucose, blood pressure, and lipid treatment based on extensive modeling work done by our investigative team. The personalized benefit information is communicated through graphical risk communication methods (pictographs).  

PI(s): Angela Fagerlin 

Geoff Barnes wrote a recent perspective piece and was featured in a UM Health Lab blog about anticoagulation clinic and assisting patients and providers with decision making.

Research Topics: 

PIHCD: Jacob Solomon

Wed, March 09, 2016, 2:00pm
B004E NCRC Building 16

Jacob Solomon will be brainstorming about several ideas to study how users' ability to control decision aids affects their decision making.

Thu, February 01, 2018

Breast cancer patients face complex decisions about their treatment. Sarah Hawley, Reshma Jagsi, and colleagues developed an interactive online tool to help patients understand their treatment options. In a study published in the Journal of Clinical Oncology, they found that patients using the interactive tool had higher knowledge and felt more informed about options and felt better prepared to make a treatment choice.

Parents' decision-making about medicating infants (Jul-13)

Imagine that you are the parent of a 1-month-old infant. Your infant spits up a lot. Often there is so much spit-up that you are amazed that there is anything left in your infant’s stomach.  After spitting-up, your infant cries a lot. The crying and spitting seems especially bad after eating. But sometimes it seems like she is uncomfortable most of the time. It seems like there is nothing that you can do to stop the crying or to soothe your infant. You are worried that an infant who is this uncomfortable, and that spits up this much, might not be healthy. So, you decided to take your infant to the doctor to be checked.

After listening to your story and examining your infant, your doctor says, “You infant has something called GERD, or Gastroesophageal Reflux Disease. GERD happens when infants have a weak valve at the entrance to their stomach and, as a result, food and acid from the stomach can travel back up toward the infant’s mouth. When this happens, the infant may spit-up, and the acid in the spit-up may make her uncomfortable, and cause her to cry. Some doctors prescribe a medication that is often used to treat infants with GERD. Most infants grow out of GERD on their own, but medication is an option if you want it. However, studies have shown that this medicine probably doesn’t do anything to help improve symptoms in babies with GERD. This is the same medication that is taken by adults who have bothersome heartburn. This medication is generally considered safe for infants, and rarely causes serious side effects. I’ll give you this prescription and leave it up to you to decide whether or not you want to give it to your infant.”

Fri, December 09, 2016

Kenneth Langa's national study, published in JAMA Internal Medicine, was cited in a New York Times article discussing US dementia trends. Despite concern that dementia rates were increasing, Langa found that it is actually decreasing. He found that population brain health seemed to improve between 2000 and 2012 and that increasing educational attainment and better control of cardiovascular risk factors may have contributed to the improvement. However, the full set of social, behavioral, and medical factors contributing to the improvement is still uncertain.

Research Topics: 

Funded by Health and Human Services, Department of-Agency for Health Care Research and Quality

Funding Years: 2013 - 2016.

Both patient-centered care approaches and health information technology advances (e.g. patient portals to electronic health records) are increasing how often patients are directly presented with medical test results that identify health concerns, monitor health status, or predict future health risk. In principle, such data enable patients to actively mange health conditions and participate in care decisions. In practice, availability of data may not result in understanding, as test results are often presented in confusing formats with little context. Many patients, especially those with lower numeracy skills (i.e., poor ability to draw meaning from numbers), may be unable to interpret test outcome data and use it in decision making. For these patients, knowing test results or risk estimates does not ensure that they understand what those numbers imply or what actions they need to consider. Such data can be, quite literally, meaning-less, and patients are likely ignore such information in decision making even when they are fully informed.
We propose to draw on research methodologies from design science, decision psychology, human-computer interaction, and health communication and integrate them into a single, highly innovative research process that will tackle the problem of how best to present Hemoglobin A1c values and similar test results to patients with diabetes as an exemplar of the larger problem of meaningless medical test data. We will (a) define the problem space from multiple perspectives, (b) clarify what we can hope to achieve when we present diabetic patients with their test results, and (c) and identify possible approaches for improving data meaningfulness. Our iterative research approach involves three phases. In Phase 1, we will use intensive deep dive design sessions (a methodology borrowed from design science) with a multidisciplinary team combining experts in health communication and human-computer interaction with both practicing clinicians and expert patients. These sessions will identify discrepancies between patient needs for test result data and the formats in which such data are provided to patients, identify when low numeracy skills will be a barrier to patient interpretation and use of such data, and brainstorm potential solution concepts. In Phase 2, we will conduct rigorous comparative evaluations of proposed designs using (a) user-experience design sessions, and (b) an iterative sequence of large-sample, multi-factorial, randomized-controlled experiments in order to identify what formats make test data most meaningful and useful for facilitating informed patient decisions about medical care. In Phase 3, we will take our identified test results communication best practices and develop, program, and disseminate a test results display generator application that will be able to be integrated with existing electronic health record systems and other applications and will be made available to patients via a freely available website.

PI(s): Brian Zikmund-Fisher

Co-I(s): Angela Fagerlin, Reshma Jagsi, Predrag Klasnja, Kenneth M. Langa, Beth A. Tarini,, Sandeep Vijan