H. Myra Kim is a Research Scientist at the Center for Statistical Consultation and Research and and Adjunct Professor at the Department of Biostatistics. She received her Sc.D. in Biostatistics from Harvard University in 1995 and worked at Brown University as an Assistant Professor from 1995 to 1997. She has worked at UM since 1997 and has collaborated with various researchers from around the UM community as well as from other universities.
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Funded by National Institutes of Health; Nationatal Institute on Aging
Funding Years: 2012-2017
A cornerstone of the nation’s social science research infrastructure, the Panel Study of Income Dynamics (PSID) is a longitudinal survey of a nationally representative sample of U.S. families. Begun in 1968, 36 waves of data have now been collected on PSID families and their descendents. Its long-term measures of economic and social well-being have spurred researchers and policy makers to attend to the fundamental dynamism inherent in social and behavioral processes. This project collects, processes, and disseminates three modules in the 2013 and 2015 waves of the PSID:
1.Health module: Including 15 minutes of survey questions on health status, health behaviors, health insurance coverage & health care costs. Linkages to the National Death Index and Medicare will be extended;
2.Wealth module: Including 10 minutes of survey questions on wealth, active savings, and pensions. Linkage to Social Security earnings and benefits records for active sample and decedents will be undertaken for the first time, and a new module to minimize errors in reports of wealth changes will be developed and implemented; and
3.Well-being module with related psychosocial measures: A mixed-mode (web/mail out) questionnaire to collect content from both respondents and spouses about their well-being and related psychosocial measures (e.g., personality, intelligence), with an experiment to identify (and allow researchers to adjust for if necessary) mode effects.
PI(s): Robert Schoeni
Co-I(s): Mick Couper, Vicki Freedman, Katherine McGonagle
Funded by Health and Human Services, Department of-National Institutes of Health
Funding Years: 2013 - 2015.
With the aging of society and restructuring of families, it is increasingly important to understand how individuals become disabled. New disability is associated with increased mortality, substantial increases in medical costs (often borne by public payers), and a heavy burden on families and caregivers. While the disablement process?as theorized by Verburgge & Jette and their successors?has traditionally been seen as chronic and gradual, there is increasing recognition that acute events play a critical role in disability. Medical illnesses are not the only potentially disabling events. NIA & NINR recently posted PA-11-265, calling for ?Social and Behavioral Research on the Elderly in Disasters? in recognition that natural disasters are common, but we know little about their impact on health and disability. The National Research Council?s Committee on Population published a report in 2009 documenting not only our ignorance in this area, but, importantly, the potential value of studying disasters to understand fundamental processes in disability and health.
Our long-term research agenda is (a) to test the hypothesis that natural disasters cause enduring morbidity for survivors that is not fully addressed by existing health and welfare programs, and (b) to discover remediable mechanisms that generate that enduring morbidity. Here we propose a nationwide test of the association of living in a disaster area with individuals? long-term disability and health care use. To perform this test, we will combine the unique longitudinal resources of over 16,000 respondents in the linked Health and Retirement Study (HRS) / Medicare files with a newly constructed mapping of all FEMA disaster declarations between 1998 and 2012. We will address key gaps in the existing literature of detailed single-disaster studies with a generalizable perspective across time and space via these Specific Aims:
AIM 1: Quantify the association between the extent of a disaster ? measured as the repair cost to public infrastructure and increases in level of disability among survivors. We will follow respondents for an average of 5 years after the disaster. AIM 2: Quantify the association between the extent of a disaster and increases in the likelihood of hospitalization among survivors. AIM 3: Test the hypothesis that increases in level of disability and likelihood of hospitalization after disasters are worse for those living in counties with higher levels of poverty.
This proposal is specifically responsive to PA-11-265. This proposal is innovative because long-term effects of disasters, particularly for vulnerable older Americans, have been systematically neglected in previous research. It is significant because it will address the public health consequences of a relatively common but understudied exposure. Further, a key contribution of this R21 will be to evaluate the feasibility of the National Research Council conjecture that natural disasters can be studied as exogenous shocks to the environment, and that we can thereby test and elaborate usually endogenous mechanisms in the development of disability.
PI(s): Theodore Iwashyna
Co-I(s): Kenneth Langa, Yun Li, Anne Sales
Reshma Jagsi, MD, DPhil, is the lead author on a new study showing that breast cancer patients who have had mastectomies and need radiation are less likely to receive these treatments than patients who have had lumpectomies. The article appears in the Journal of Clinical Oncology (online March 29, 2010). Additional authors are Paul Abrahamse, Sarah T. Hawley, Jennifer J. Griggs, Steven J. Katz, Monica Morrow, John J. Graff, and Ann S. Hamilton. Read a press release about the research here.
This will be the first year that CBSSM will be participating in Researchpalooza. Please come and enjoy the fun!
Wednesday, August 27, 2014
11:00 a.m. - 2:00 p.m.
Circle Drive in front of Med Sci I
All UMHS employees from the Hospitals and Health Centers and Medical School are invited to celebrate this annual event.
Stop by the University Hospital Courtyard and Medical School Circle Drive for:
- Ice Cream sundaes and sugar-free alternatives
- Karaoke and musical entertainment
- Festival Games
- Department and vendor tables with information and giveaways
Jeff Kullgren was recently awarded a MICHR pilot grant for “Translating insights from behavioral economics and self-determination theory to promote sustained weight loss among obese employees.”
Scott Kim, MD, PhD, is a Senior Investigator in the Department of Bioethics at the National Institutes of Health and Adjunct Professor of Psychiatry at the University of Michigan. Dr. Kim studies research ethics, especially the ethics of involving decisionally impaired persons in research, the ethics of high-risk research, and methodological issues in empirical bioethics research. He is also interested in the interface of conceptual and empirical methods of bioethics scholarship. Prior to joining the NIH, Dr.
With just a simple search term and a click of the mouse, a person can find a large amount of health information on the Internet. What role does the Internet play in how patients make medical decisions? Does using the Internet as a source for information to help patients make informed decisions vary by health condition? Does the Internet substitute for detailed discussions with a health care provider?
Consider the following:
Imagine that you recently visited your health care provider for an annual physical examination. During the exam your doctor told you that you are at the age where you should start thinking about getting a screening test for colon cancer. In this conversation your health care provider explained some of the reasons why you should get screened. At the end of the visit, you had more information about screening tests for colon cancer but had not yet decided whether or not you wanted to get tested.
- Don't know
How do your answers compare?
In a recent study published in the journal Medical Decision Making, CBSSM investigators Brian Zikmund-Fisher, Mick Couper, and Angela Fagerlin examined Internet use and perceived importance of different sources of information by patients making specific medical decisions.
In this study, US adults aged 40 years and older were asked about how they got information about 9 common medical decisions, including decisions about common prescription medication (for high blood pressure, cholesterol, and depression), cancer-screening tests (for colorectal, breast, and prostate cancer), and elective surgeries (for lower back pain, cataracts, and knee/hip replacement). In addition, they study compared participants' ratings of the Internet as a source of information with their ratings of other sources, such as their health care provider.
So, how did your responses compare to the average adult in this study's population?
Results from this study showed that most patients did not use the Internet to make specific medical decisions like the ones you considered. On average, about 26% of participants made use of the Internet for information to make decisions about colon cancer screening tests and about 47% used it to inform a decision about lower back pain surgery.
Among participants who chose to use the Internet for finding information about specific medical decisions, data show that Internet use varies significantly across different types of medical decisions. Internet users were more likely to use the Internet for information related to elective surgery (36%), such as lower back pain surgery, and prescription medication (32%) than for cancer-screening decisions (22%), such as colon cancer screening.
Another element of this study looked at participants' ratings of different information sources. You are unlike other participants in this study in that you did not consistently rate health care providers as the most important source for information about colon cancer screening and lower back pain surgery. The CBSSM study found that, for both Internet users and nonusers, health care providers were rated highest as a source for information for all 9 decisions studied. Among Internet users, however, the Internet was rated as their 2nd-most important source of information.
The researchers found that Internet use to inform specific medical decisions varied by age ranging from 38% for those aged 40 to 49 years to 14% for those aged 70 years or older. Approximately 33% of 50 to 59 year olds used the Internet to make these medical decisions and 24% for those in the 60 to 69 year age category. This result is consistent with previous research on the demographics of Internet use.
The study authors concluded that the Internet has an impact on people's access to health care information; however, "the data suggest that access is not the same as use, and use for one medical decision does not imply use for all health decisions." In other words, people use the Internet differently depending on the context. The authors end by stating, "Clinicians, health educators, and health policy makers need to be aware that we remain a long way away from having Internet-based information sources universally used by patients to improve and support the process of medical decision making."
For the full text of this article:
Couper M, Singer E, Levin CA, Fowler F, Fagerlin A, Zikmund-Fisher BJ. Use of the internet and ratings of information sources for medical decisions: Results from the DECISIONS survey. Medical Decision Making 2010;30:106S-114S.
What is the impact of medical advertising that is directly targeted at patients? What information do consumers of medical products and therapies need in order to make informed decisions about their health?
Consider the following:
Ms. J, a healthy 50-year old woman, drives by a billboard that advertises low-dose spiral computed tomography (CT) scanning to screen for lung cancer. Although she has no family history of cancer and has never smoked, several of Ms. J’s friends have been diagnosed with cancer recently. She worries that she herself may have an undetected malignancy.
Responding to this advertising, Ms. J decides to pay out-of-pocket for a CT scan at the imaging center advertised on the billboard. The radiologist at this imaging center profits from the number of scans interpreted. As a result of the CT scan, an abnormality is found, and Ms. J undergoes a biopsy of her lung. A complication occurs from this procedure, but Ms. J recovers, and the biopsy comes back negative. She is relieved to learn that she does not have lung cancer.
After reading this scenario and thinking about direct-to consumer medical advertising, which of the following statements best represents your views?
- STATEMENT A: Direct-to-consumer advertising improves patient education and patient-physician communication. Such advertising informs and empowers patients, so that their health care better reflects their needs and values. In particular, certain health services require complex medical equipment with high capital costs. Physicians who invest in such equipment do so because they believe in its promise, and they deserve payment to recoup their investment.
- STATEMENT B: Direct-to-consumer advertising often results in misunderstanding, increased costs, and disruption of the patient-physician relationship. Such advertising can skew information to portray products in a positive light and can prey upon patients’ fears. Physicians closely allied with a treatment cannot offer objective assessment to patients about the efficacy or risks of the treatment. Further, most patients are ignorant of the financial incentives to physicians for various procedures.
- STATEMENT C: I have not formed a viewpoint on direct-to-consumer medical advertising.
How do your answers compare?
CBDSM's Reshma Jagsi, MD, DPhil, has written a powerful challenge to the medical profession and medical industries in a recent issue of the Journal of Clinical Oncology. Dr. Jagsi argues that the increasing proliferation of direct-to-patient advertising has raised questions of how physicians can function as unbiased intermediaries between patients and industry.
In the article, she presents six case studies, one of which has been excerpted and adapted for this Decision of the Month. Dr. Jagsi uses these case studies to address serious issues related to both advertising and conflict of interest. Some examples:
- What implications does the frequently used advertising directive "Ask your doctor about X" have for the doctor-patient relationship?
- How ethical is it to disguise medical advertising—for instance, to hire celebrities to discuss treatments during interviews?
- Should a physician who prescribes a particular medical device be allowed to receive payment from the speakers' bureau of a company that produces that medical device?
- Should a physician who holds an ownership interest in an expensive treatment machine be required to explain alternate treatments to patients?
- When does a website about a medical treatment cross over from being informational to being promotional?
Dr. Jagsi argues that physicians have a strong ethical responsibility to their patients to call attention to potential conflicts of interest and to help interpret medical information in the best interests of their patients.
For more details about this study:
Should people with more severe health problems receive state funding for treatment before people with less severe health problems? See how your opinion compares with the opinions of others.
Imagine that you are a government official responsible for deciding how state money is spent on different medical treatments. Your budget is limited so you cannot afford to offer treatment to everyone who might benefit. Right now, you must choose to spend money on one of two treatments.
- Treatment A treats a life threatening illness. It saves patients' lives and returns them to perfect health after treatment
- Treatment B treats a different life threatening illness. It saves patients' lives but is not entirely effective and leaves them with paraplegia after treatment. These patients are entirely normal before their illness but after treatment will have paraplegia.
Suppose the state has enough money to offer Treatment A to 100 patients. How many patients would have to offered Treatment B so that you would have difficulty choosing which treatment to offer?
How do your answers compare?
The average person said that it would become difficult to decide which treatment to offer when 1000 people were offered Treatment B.
What if you had made another comparison before the one you just made?
In the study, some people were asked to make a comparison between saving the lives of otherwise-healthy people and saving the lives of people who already had paraplegia. After they made that comparison, they made the comparison you just completed. The average person in that group said it would take 126 people offered Treatment B to make the decision difficult. The differences are shown in the graph below
Why is this important?
The comparison you made is an example of a person tradeoff (PTO). The PTO is one method used to find out the utilities of different health conditions. These utilities are basically measures of the severities of the conditions. More severe conditions have a lower utility, and less severe conditions have a higher utility, on a scale of 0 to 1. Insurance companies, the government, and other organizations use these utilities as a way to decide which group to funnel money into for treatments.
On the surface, it seems like basing the money division on the severity of a condition is a good and fair method, since theoretically the people who are in the greatest need will be treated first. However, the PTO raises issues of fairness and equity that aren't accounted for in other utility elicitation methods like the time tradeoff (TTO) and rating scale (RS).
For example, when asked to decide how many people with paraplegia would have to be saved to equal saving 100 healthy people, many people say 100; that is, they think it is equally important to save the life of someone with paraplegia and a healthy person. Going by values obtained using the TTO or RS, an insurance company may conclude that 160 people with paraplegia (using a utility of .6) would have to be saved to make it equal to saving 100 healthy people. This would mean that less benefit would be gotten by saving someone with paraplegia, and thus they might not cover expenses for lifesaving treatments for people with paraplegia as much as they would for a healthy person. The PTO shows that many people would not agree with doing this, even though their own responses to other utility questions generated the policy in the first place.