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Mon, October 02, 2017

Sarah Hawley, Brian Zikmund-Fisher, and Reshma Jagsi are co-authors of a recent study published in Medical Decision Making, which was highlighted in MHealth Lab. Their study found that talking to clinicians is the best way for breast cancer patients to understand their recurrence risk. They also found that clinician discussions about recurrence risk should address uncertainty and the relevance of family and personal history. Kamaria Lee is first author of the article.

Wed, October 11, 2017

In an editorial in Nature Human Behaviour, Brian Zikmund-Fisher discusses the findings of a recent study about the unintended consequences of argument dilution in direct-to-consumer drug advertising. In a series of experiments, study authors, Niro Sivanathan and Hemant Kakker found that long lists of serious and minor side effects found in drug advertisements actually "dilute" consumers' judgments of the overall risk from side effects.

Thu, October 26, 2017

In a new analysis in Health Affairs, CBSSM's Jeffrey Kullgren and fellow researchers found that while the "Choosing Wisely" campaign to reduce overtesting and overtreatment is off to a strong start, more work is still needed to cut back on low-value care.

CBSSM Seminar: Jan Van den Bulck, PhD

Tue, November 28, 2017, 3:00pm
Location: 
NCRC, Building 16, Room 266C

Jan Van den Bulck, PhD
Professor, Communication Studies

Topic:
"Are the media (re-)defining how we interact with each other and with the world?

We know everything there is to know about people we have never even met. Through social media, we follow their every move. We even know their pets. Our media use interferes with healthy sleep, family meals, or even our work. Our children need levels of self-control to manage distractions that threaten their schoolwork. Or do they?"

Tue, November 28, 2017

In a study published in JAMA Internal Medicine, Jeff Kullgren and co-authors found that few individuals enrolled in High-Deductible Health Plans (HDHPs) in the United States are engaging in consumer behaviors.

Bioethics Grand Rounds -Nicholson Price, Asst Professor of Law

Wed, September 27, 2017, 12:00pm
Location: 
UH Ford Auditorium

Nicholson Price, Asst Professor of Law - "Black-Box Medicine"

Big data has been coming to health care for several years, and artificial intelligence is approaching even more rapidly.  What happens when these two phenomena meet in the context of clinical care?  How should clinicians deal with algorithms (whether embedded in EHRs or found on patients’ smartphones) that can predict outcomes, suggest diagnoses, and even recommend courses of treatment—all without explaining how they reach their conclusions?  This talk will describe the burgeoning field of black-box medicine, consider how the FDA can and should regulate this technology, and address liability and implementation concerns for clinicians today and in the near future.

 

Subjective Numeracy Scale

The Subjective Numeracy Scale (SNS) is a self-report measure of perceived ability to perform various mathematical tasks and preferences for the use of numerical versus prose information. The SNS has been validated against objective numeracy measures and found to predict comprehension of risk communications and ability to complete utility elicitations.

The 8-item scale contains no mathematics questions and has no correct or incorrect answers. Instead, it consists of 4 questions asking respondents to assess their numerical ability in different contexts and 4 questions asking them to state their preferences for the presentation of numerical and probabilistic information. The SNS is both reliable and highly correlated with the Lipkus, Samsa & Rimer (2001) numeracy measure, and it has been validated in both risk communication and utility elicitation domains.

For a PDF version of this document and the SNS instrument, click here: Subjective Numeracy Scale PDF.  

Please contact Angie Fagerlin for versions in Dutch, Japanese, Norwegian, Portuguese, and Spanish.

SNS Questions

For each of the following questions, please check the box that best reflects your answer:

  • How good are you at working with fractions? (Not at all good – Extremely good)
  • How good are you at working with percentages? (Not at all good – Extremely good)
  • How good are you at calculating a 15% tip? (Not at all good – Extremely good)
  • How good are you at figuring out how much a shirt will cost if it is 25% off? (Not at all good – Extremely good)
  • When reading the newspaper, how helpful do you find tables and graphs that are parts of a story? (Not at all helpful – Extremely helpful)
  • When people tell you the chance of something happening, do you prefer that they use words ("it rarely happens") or numbers ("there's a 1% chance")? (Always prefer words – Always prefer numbers)
  • When you hear a weather forecast, do you prefer predictions using percentages (e.g., “there will be a 20% chance of rain today”) or predictions using only words (e.g., “there is a small chance of rain today”)? (Always prefer percentages – Always prefer words)
  • How often do you find numerical information to be useful? (Never – Very often)

Scoring Instructions

All questions use 6-point Likert-type scales with endpoints as marked. Response values increase left to right (1-6). Scoring is based on these values, except Question 7 is reverse coded (6-1) for consistency.

  • SNS: Average rating across all 8 questions (w/ Q7 reverse coded)
  • SNS ability subscale: Average rating on Questions 1-4
  • SNS preference subscale: Average rating on Questions 5-8 (w/ Q7 reverse coded)

To cite the scale, please use the following reference:

Fagerlin, A., Zikmund-Fisher, B.J., Ubel, P.A., Jankovic, A., Derry, H.A., & Smith, D.M.  Measuring numeracy without a math test: Development of the Subjective Numeracy Scale (SNS). Medical Decision Making, 2007: 27: 672-680.

In any discussions about the validation of the scale, please use the following reference:

Zikmund-Fisher, B.J., Smith, D.M., Ubel, P.A., Fagerlin, A.  Validation of the subjective numeracy scale (SNS): Effects of low numeracy on comprehension of risk communications and utility elicitations. Medical Decision Making, 2007: 27: 663-671.

2018 Bishop Lecture featuring Barbara Koenig, PhD

Tue, May 01, 2018, 11:15am
Location: 
Henderson Room, Michigan League, 911 N. University Avenue, Ann Arbor, MI

The 2018 Bishop Lecture in Bioethics was presented by Barbara Koenig, PhD, Professor of Bioethics and Medical Anthropology and Director of UCSF Bioethics at the University of California, San Francisco. Professor Koenig presented a talk entitled, " Does Enhancing Individual Choice and Control Promote Freedom? Challenges in Contemporary Bioethics." The Bishop Lecture serves as the keynote address during the CBSSM Research Colloquium.

Abstract: Over the past three decades, the discipline of bioethics has advocated for enhanced patient choice and control over a range of medical decisions, from care near the end of life to participation in clinical research. Using two current policy challenges in California—1) the advent of legally sanctioned medical aid in dying and, 2) efforts to share UC Health “big data” from the electronic health record in research with private sector partners—Professor Koenig will explore how current bioethics practices may unintentionally and ironically impede our shared goals of promoting human freedom.

Barbara A. Koenig, PhD is Professor of Bioethics and Medical Anthropology, based at the Institute for Health & Aging, University of California, San Francisco. She is the Director of “UCSF Bioethics,” a nascent program that spans ethics research, clinical ethics, and ethics education across the university’s four professional schools. Prof. Koenig pioneered the use of empirical methods in the study of ethical questions in science, medicine, and health. Prof. Koenig’s current focus is emerging genomic technologies, including biobanking policy and using deliberative democracy to engage communities about research governance. Her work has been continuously funded by the National Institutes of Health since 1991. Currently, she: 1) directs the ELSI component of a NICHD award focused on newborn screening in an era of whole genome analysis, 2) is P.I. of UCSF’s Program in Prenatal and Pediatric Genomic Sequencing (P3EGS), part of the CSER2 national network, and, 3) is supported by NCI to conduct an “embedded ethics” study of the Athena “Wisdom” PCORI-funded clinical trial of genomic risk-stratified breast cancer prevention. Previously, she directed an NHGRI-funded “Center of Excellence” in ELSI Research. Prof. Koenig was the founding executive director of the Center for Biomedical Ethics at Stanford University; she created and led the Bioethics Research Program at the Mayo Clinic in Rochester, Minn. She received her Ph.D. from the University of California, Berkeley and San Francisco joint program in Medical Anthropology. She is an active participant in policy, having served on the ethics committee that advises the director of the CDC and the Department of Health and Human Services “Secretary’s Advisory Committee on Genetic Testing.” She recently served on a state-wide “Health Data Governance Task Force” which advised UC’s president.

Click here for the video recording of the 2018 Bishop Lecture.

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

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