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

Funding Years: 2014 - 2016.

'Value-based purchasing' is a quality improvement strategy that links payment with healthcare outcomes, by paying less or not at all for poor outcomes. The Centers for Medicare and Medicaid Services (CMS) seeks to decrease the rate of hospital-acquired complications (HAC) and readmissions by holding hospitals financially accountable using risk-adjusted rates. CMS risk-adjustment models for outcomes of mortality and readmission include patient characteristics from routine administrative discharge data (e.g., diagnosis codes) with age and gender as the only socio-demographic variables. Research suggests other important patient characteristics such as functional status, mobility and level of social support also impact patients? risk for readmission and certain complications (e.g., pressure ulcers). To date, variables such as functional status, mobility and social support have not been included in risk-adjustment models because they are not available in routine discharge data; also, socio-demographic variables (e.g., income or education, which may relate to a patient?s ability to maintain functional status and secure social support) have not been included in risk-adjustment for outcomes due to concerns that adjusting for such factors would be akin to condoning poor care delivered to vulnerable patients. In order to determine how much socio-demographic factors relate as risks for poor hospital outcomes and readmissions (as intrinsic patient factors compared to factors extrinsic to patient and a function of the hospital), a more robust patient-specific data source is required than routine discharge data. To address this question, we will utilize a unique data source to extend our prior work examining the impact of value-based purchasing programs (including non-payment of HACs) on vulnerable patients and hospitals; we will use the nationally representative Health and Retirement Study (HRS) (with detailed data such as a patient?s functional status, mobility, social support, income and educational level) linked to patient-specific Medicare claims data. Our specific aims are:

  1. To assess change in performance of our recently constructed risk-adjusted model for complications of pressure ulcers and urinary track infections as HACs after enhancement with HRS patient-specific measures (e.g., functional status, mobility, social support).
  2. To assess change in performance of CMS?s risk-adjustment models for readmission (for pneumonia, heart failure, myocardial infarction) after enhancement with HRS patient-specific measures.
  3. To evaluate the performance of the HRS-variable enhanced risk-adjustment models for HACs and readmission after replacing some HRS variables with census derived, zip-code level variables (such as median level of education, and income).
  4. Using statewide Medicare claims data; to evaluate the performance of risk-adjustment models for HACs and readmission enhanced by census-data derived zip-code level socio-demographic variables.

PI(s): Laurence McMahon Jr

Co-I(s): Timothy Hofer, Theodore Iwashyna, Kenneth Langa, Jennifer Meddings, Mary AM Rogers

Funded by the National Science Foundation

Funding years: 2010-2013

Increasingly people are communicating with one another through new media such as text messages exchanged via mobile devices. At the same time, survey response rates continue to drop. These phenomena are related to the extent that respondents only use mobile devices (21% of US households no longer have a landline phone) and frequently rely on modes other than voice, most notably text (which is certainly the norm among some subgroups in the US and increasingly among entire populations in other countries). Yet we know little about the impact of multimodal mobile devices on survey participation, completion, data quality and respondent satisfaction.

The proposed research will explore these issues in two experiments that will collect survey data on iPhones in four modes defined by whether the interviewing agent is a live human or a computer, and whether the medium of communication is voice or text. The resulting modes are telephone interviews, instant message (IM) interviews, speech integrated voice response (IVR), and automated IM. This way of defining modes enables us to isolate the effects of the agent and medium. The first experiment explores the effect of the four modes on participation, completion, data quality and satisfaction; the second explores the impact on the same four measures of allowing participants to choose the response mode.

More information: http://www.psc.isr.umich.edu/research/project-detail/34963

PI: Kathryn Moseley

Co-I: Mick Couper

Funded by National Academy of Sciences

Funding Years: 2013-2014.

The internet broadly, and social media in particular, are revolutionizing how people form relationships, interact, and give and receive support, with potential wide-ranging implications for the psychological and physical health of both children and older adults. However, very little research has analyzed the use and outcomes of the internet/social media among middle-age and older adults (those aged 50+). This project greatly expands the opportunities for future research in this area by establishing a multidisciplinary network of graduate students, junior faculty, and senior faculty to identify key research questions and the data needed to answer those questions. Specifically, we will: (1) Develop new collaborations at the University of Michigan between Kenneth Langa, MD, PhD (Medical School, School of Public Health, and Institute for Social Research) and Nicole Ellison, PhD (School of Information) to link their respective expertise in the use and outcomes of social media and large-scale survey research on health and function in middle-age and older adults. (2) Organize a multidisciplinary conference of researchers and funders (e.g., NIA/NIH) to establish new collaborations, identify high-priority research questions, and assess current road-blocks, opportunities, and data needs for future research. And (3) analyze data from the Health and Retirement Study on the current use of the internet in a national sample of adults aged 50 years and older. These activities will expand and strengthen collaborations that started at the 2012 “Informed Brain in a Digital World” Keck Futures Conference.

PI(s): Ken Langa, Nicole Ellison

CBSSM Seminar: Paul A. Lombardo, PhD, JD

Thu, September 22, 2016, 3:00pm to 4:00pm
Location: 
NCRC Building 16, Conference Rm 266C

Paul A. Lombardo, PhD, JD
Regents' Professor and Bobby Lee Cook Professor of Law
Georgia State University College of Law

"From Psycographs to FMRI: Historical Context for the Claims of Neuroscience"

Abstract: In the U.S., announcement of the Presidential “Brain Initiative” has focused attention on “revolutionizing our understanding of the human brain” And neuroscience has begun to replace genetics as the field most likely to fill press headlines. The promise of more research funding for the field has led to extraordinary claims that research will soon lead to mind reading, lie detection, and unlocking the brain-based foundations of virtue and character. But these claims echo similar assertions from a century ago, many of which were eventually discarded as quackery, eugenics or misguided pseudoscience. Then the power of phrenology was touted, and machines like the “Psycograph” were offered to “thoroughly and accurately” measure “the  powers of intellect, affect and will.” Today similarly expansive claims are being made for color-coded functional magnetic resonance imagery. Are we facing true scientific triumph or mere recycled hyperbole? This presentation will explore the historical echoes of today’s most extravagant claims in the field of neuroscience, and analyze how our actual understanding of mental functioning compares to the hopeful assertions that are filling both the lay press and scientific journals.

Funded by National Institutes of Health; National Institute of Mental Health

Funding Years: 2012-2017

This project will test a practical intervention that uses low cost technologies to activate depressed patients' existing social networks for self-management support. The intervention links patients with a "CarePartner" (CP), i.e., a non-household family member or close friend who is willing to support the patient in coordination with the clinician and any existing in-home caregiver (ICG). Through weekly automated telemonitoring, patients report their mood and self-management status, and receive tailored guidance on self-management. The CP receives a corresponding update along with guidance on how to best support the patient's self-management efforts, and the primary care team is notified about clinically urgent situations. The intervention will be tested among depressed primary care patients from clinics serving low-income and underinsured patients, whom the intervention was especially designed to benefit. Specific Aim 1 is to conduct a randomized controlled trial to compare the effectiveness of one year of telemonitoring-supported CP for depression versus usual care (control) on depression severity. Specific Aim 2 is to examine key secondary outcomes (response and remission, impairment, well-being, caregiving burden, healthcare costs) and potential moderators. Specific Aim 3 is to use a mixed-methods approach to enrich our interpretation of the statistical associations, and to discover strategies to enhance the intervention's acceptability, effectiveness, and sustainability. If the intervention proves effective without increasing clinician burden or marginal costs, then its subsequent implementation could yield major public health benefits, especially in medically underserved populations.

PI(s): James Aikens

Co-I(s): Michael Fetters, John Piette, Ananda Sen, Marcia Valenstein, Daniel Eisenberg, Daphne Watkins

CBSSM investigators Holly Witteman, Andrea Fuhrel-Forbis, Angela Fagerlin, and Brian Zikmund-Fisher, along with CBSSM alumni Peter Ubel and Andrea Angott will give a plenary talk at the Society for Medical Decision Making's 32nd Annual Meeting in Toronto on Monday, October 25.  The talk is titled, "Colostomy is Better than Death, but a 4% Chance of Death Might Be Better Than a 4% Chance of Colostomy: Why People Make Choices Seemingly At Odds With Their Stated Preferences." 

Abstract:

Purpose: When asked for their preference between death and colostomy, most people say that they prefer colostomy. However, when given the choice of two hypothetical treatments that differ only in that one has four percent chance of colostomy while the other has four percent additional chance of death, approximately 25% of people who say that they prefer colostomy actually opt for the additional chance of death. This study examined whether probability-sensitive preference weighting may help to explain why people make these types of treatment choices that are inconsistent with their stated preferences.

Method: 1656 participants in a demographically diverse online survey were randomly assigned to indicate their preference by answering either, “If you had to choose, would you rather die, or would you rather have a colostomy?†or, “If you had to choose, would you rather have a 4% chance of dying, or would you rather have a 4% chance of having a colostomy?†They were then asked to imagine that they had been diagnosed with colon cancer and were faced with a choice between two treatments, one with an uncomplicated cure rate of 80% and a 20% death rate, and another with an uncomplicated cure rate of 80%, a 16% death rate, and a 4% rate of colostomy.

Result: Consistent with our prior research, most people whose preferences were elicited with the first question stated that they preferred colostomy (80% of participants) to death (20%), but many then made a choice inconsistent with that preference (59% chose the treatment with higher chance of colostomy; 41% chose the treatment with higher chance of death). Compared to the first group, participants whose preferences were elicited with the 4% question preferred death (31%) over colostomy (69%) more often (Chi-squared = 24.31, p<.001) and their treatment choices were more concordant with their stated preferences (64% chose the treatment with higher chance of colostomy; 36% chose the treatment with higher chance of death, Chi-squared for concordance = 36.92, p<.001).

Conclusion: Our experiment suggests that probability-sensitive preference weighting may help explain why people’s medical treatment choices are sometimes at odds with their stated preferences. These findings also suggest that preference elicitation methods may not necessarily assume independence of probability levels and preference weights.


Funded by VA Health Services Research and Development Career Development Award

Funding Years: 2015-2019

Heart attack and stroke, which together are called cardiovascular disease, cause over 1/3 of all deaths in VA patients. The current guidelines for the prevention of these conditions focus on lowering patients'blood pressure and cholesterol levels. A new treatment strategy, which I call benefit-based tailored treatment, that instead guides treatment decisions based on the likelihood that a medication would prevent a heart attack or stroke could prevent more cardiovascular disease, with lower medication use, and be more patient centered. The purpose of this Career Development Award is to develop and assess tools and approaches that could enable the implementation of benefit-based tailored treatment of cardiovascular disease, in particular a decision support tool and educational program for clinicians and a performance profiling system. The decision support tool will enable better care by showing clinicians patient-specific estimates of the likelihood that their medication decisions will prevent a cardiovascular disease event. The performance profiling system will encourage better care by assessing the quality of care provided at VA sites and in PACT teams based on how well the medical care provided follows this treatment strategy. The project will have three aims:
Aim 1 : In the first aim, I will seek to understand clinicians'and patients'perceptions of and receptivity to the use of benefit-based tailored treatment for cardiovascular disease. Information gained from qualitative research with clinicians will help assess and improve the usability and effectiveness of the decision support tool and educational program for clinicians, along with the acceptability of the treatment strategies in general. Information gained from focus groups with patients will help learn their priorities in cardiovascular disease prevention, to help identify ways to make the interventions and their assessments more patient-centered.
Aim 2 : In the second aim, the decision support tool and educational program will be assessed in a real-world randomized pilot study involving thirty clinicians. Half of the clinicians will be provided the decision support tool and education intervention for ten patients each, the other half will receive a traditional quality improvement program and treatment reminders. The study will have formative goals of ensuring that clinicians and patients believe the tool is valuable and does not disrupt care processes or workflow for anyone in the PACT team. This will be studied with qualitative and survey assessments. The primary summative outcome will be the influence of the intervention on clinicians'treatment decisions. Secondary outcomes will assess patients'satisfaction with their visits and their clinicians.
Aim 3 :
The third aim will develop and evaluate a novel performance measurement system based on benefit- based tailored treatment. First, the performance profiling system will be developed. Then the profiling system's ability to reliably differentiate high quality from low-quality care will be evaluated.

PI: Jeremy Sussman

Funded by Department of Health and Human Services - National Institutes of Health Subcontracts

Funding Years: 2014 - 2018.

This five-year prevention trial proposes to test an anti-amyloid drug in cognitively normal older volunteers who are at increased risk of developing late-onset Alzheimer’s because they inherited two copies of the APOE4 allele, the best known genetic risk for late-onset disease. The treatment, which has not yet been selected, will be tested in this randomized, controlled clinical trial at multiple sites. Participants will be assessed through cognitive tests, brain imaging and cerebrospinal fluid measurements to evaluate whether the drug impacts amyloid, other biological measurements and the memory and thinking problems related to the disease. The study will test the role of amyloid in the development of Alzheimer’s and will, through imaging and biomarker techniques, help identify faster ways to evaluate other promising prevention therapies in the future. It is anticipated that the study will also be supported with private funding.

PI(s): J. Scott Roberts

CBSSM Seminar: Jodyn Platt, MPH, PhD

Thu, October 08, 2015, 3:00pm to 4:00pm
Location: 
NCRC, Building 16, Room 266C

Jodyn Platt, MPH, PhD


Research Investigator
Department of Learning Health Sciences

Terms and Conditions for Trust in Learning Health Systems

The next generation of health information technology, organized as “learning health systems,” promises efficient, engineered solutions to the well-known and enduring maladies of the existing U.S. health infrastructure: escalating costs, poor health outcomes, ineffective use of technology, sluggish research pipelines, dangerous medical error rates, and failure to implement known clinical best practices. Learning health systems would capitalize on "big data" enterprises to accelerate the production and application of knowledge in health care. However, the sharing of health information required, both within and across institutions, greatly exceeds the public’s understanding.  These initiatives are riding a precarious edge as the gap between public expectations and the realities of institutional data sharing widens at an unprecedented rate.  This presentation considers the causes and consequences of trust and mistrust of health information systems, their data sharing practices, and their policy implications. 
 

 

Funded by National Institutes of Health

Funding Years: 2011-2017

The CoreValve US Pivotal Trial applies clinical best practices—including CT-based sizing—and is meticulously monitored, including the use of an independent echocardiographic core lab. Within the trial, the High Risk Study randomized 795 patients between surgical aortic valve replacement (SAVR) and Transcatheter Aortic Valve Implantation (TAVI) with the CoreValve System across 45 US sites. The TAVI procedure is used as an alternative to open heart surgery and allows access to the diseased aortic valve via an artery in the leg and is designed for patients with severe aortic stenosis who are at high risk for surgery due to age or other health issues.

PI(s): David Bach, G M Deeb

Co-I(s): Devin Brown, Stanley Chetcuti, Paul Grossman, Himanshu Patel, Michael Shea, Darin Zahuranec

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