Guidelines for Submission
To submit a paper for consideration, upload a 500-1,000 word abstract here. You will need to create an account, and the system will guide you through the submission process.
All abstracts must be submitted online between April 15 and July 31, 2019. Submitted abstracts will be reviewed by the HSRM steering committee. Notification via email of decisions to accept or further review abstracts will take place by August 31, 2019.
For more information, please contact Lesly Ger at firstname.lastname@example.org
Topic 1Advances in Collecting Health Survey Data
This session will explore advances in health survey data collection, including the use of innovative measures as well as design strategies to maximize participation. Innovative measures may include new questionnaire designs as well as the use of data not produced by self-report, e.g. biomarkers and direct measures of respondent behavior and characteristics. Design strategies may include mixed-mode designs, new contact strategies, or new technology and data collection methods. Papers may also consider the data quality implications for any of these approaches. Questions that we hope to address in this session include but are not limited to the following:
- What are the key challenges to combining data across modes or from different data sources, and how do such combinations affect estimates and data quality?
- What alternative and emerging measures of health and health behavior exist, and what are the challenges to using them?
- For what purposes are nonprobability samples useful or justified?
- What are the latest strategies for dealing with less than optimal circumstances, such as incomplete frames and response bias?
- What are the most promising approaches for selecting modes to maximize data quality and cost-effectiveness?
- How do mode choice, responsive/adaptive design, incentives, and interviewers affect participation and data quality?
- What are the cost implications for these and other approaches used to maximize response?
- What are the most effective ways to measure data quality, and to communicate about limitations of quality to decision makers who are not survey experts?
Topic 2Enhancing Health Survey Data with Alternative Data Sources
Declining response rates, increasing costs, and the explosion of electronic administrative records, social media, and other forms of “Big Data,” have led researchers to explore ways of supplementing, enhancing or even replacing survey data with other resources. Methodologies to mine and leverage such data remain under development as researchers struggle to find reliable and replicable methods to combine, clean, organize, and analyze data, and to evaluate what insights can be gleaned from non-survey data alone. Researchers also explore cutting edge analytic techniques based on machine learning, artificial intelligence, and agent-based modeling for these emerging data sets.
We welcome research and overviews of new approaches that address these topics, potentially including:
- What are some promising examples of enhancing or replacing survey data with “extant” data (e.g., administrative records or other data not originally designed for research purposes), and what challenges were overcome to produce those results?
- What are current practices and new approaches for linking data from different sources?
- How have different data sources been used to triangulate findings—or, how do we evaluate disparate findings?
- How do we determine whether extant data (alone or in combination with survey data) adequately covers populations of interest, and how coverage might affect generalizability of results?
- What studies have examined interoperability of data sources?
- How does source of data relate to data quality? What mitigation strategies are available and how do these relate to survey costs?
- What are the most promising ways to evaluate and communicate with non-specialists about the quality of extant and merged data?
Topic 3Strategies for Hard-to-Survey Populations
This session will explore strategies for overcoming growing barriers to hard-to-survey populations in health research, to ensure that the data we collect are accurate, representative, and useful. We are interested in methods that have proven effective in addressing various challenges throughout all phases of health survey data collection: hard-to-sample, hard-to-identify, hard-to-reach, hard-to-persuade or hard-to-interview. Questions to consider include:
- What strategies are helpful in sampling rare subgroups or vulnerable populations?
- What approaches have been used to improve the accuracy of screening and identifying the target population of interest?
- What methods are valuable in tracing health survey respondents?
- Given declining response rates, what approaches are useful in persuading health survey respondents to participate?
- To what extent are incentives used, with what populations, for how much, and how are survey costs impacted?
- What protocols are used to interview special populations like young children or proxy respondents?
Topic 4Privacy and Confidentiality Challenges in Health Survey Research
This session will address the concepts of privacy and informed consent in health survey research: how they have changed over time; how they are challenged by mixed modes, blended survey and administrative designs, and by surveys enhanced with social media and other big data sources. Novel methods complicate longstanding principles of research ethics.
Survey research is grounded in three principles: respect for persons, beneficence, and justice (the Belmont Report). This grounding is challenged by the legal underpinnings of consent and privacy in the context of big data research. In an environment where each of us sheds thousands of data items every day that collectively reveal virtually every aspect of our identities, researchers need to think differently about privacy, anonymity, consent, and harm.
How can we square these antithetical principles in health research that blends survey data and big data? We welcome papers that address difficult questions along these lines, and other related topics:
- In the survey research tradition, what are best practices for conveying consent to data usages and linkage?
- How have changes in the environment and stresses in the survey paradigm impacted the concept of privacy?
- What impact do we expect from revisions to the Common Rule, and the European policies, including the right to be forgotten?
- In blending data from different sources, how do we monitor and maintain control of data when different subjects have provided different permissions? This raises the possibility of linkage bias and the relationship of consent in various forms to data quality.
- Do the policies and practices applying privacy and confidentiality to human subjects apply well to data subjects?
- What guidance can be provided to researchers and data users for navigating use restrictions, as well as considering implications for cost and quality?
Topic 5Timely Health Topics and Survey Measurement
This session will focus on how survey data may be used to help inform and address the most pressing issues facing the health care system today and possible emerging future issues. Examples include presentations that address measurement issues and research gaps on the following topics:
- The Opioid Epidemic
- How can survey measurements contribute to a better understanding of opioid use, abuse, and treatment in light of the changing landscape of opioid production and addiction treatment?
- Papers may examine how to define opioid use and opioid treatment utilization, interviewer effects when asking sensitive questions, and methods of measuring the broader social impacts of opioid use.
- Mental Health
- With rising prevalence of certain mental health diagnoses and an increase in the U.S. suicide rate, what survey measurements will be necessary to inform the future of mental health diagnosis and treatment?
- Papers may examine how to measure a spectrum of mental health issues ranging from functionality to disorders, reconciling measurements across different data collection mechanisms, and mode effects in measurements of mental health issues.
- Aging Population
- How can surveys help inform the set of health system issues that arise as the U.S. population ages and an increasingly larger cohort of older adults are living with serious chronic illnesses including diseases like Alzheimer’s that affect cognitive functioning?
- Papers may examine how to measure cognitive function and decline in surveys, the use of proxy respondents, measuring caregiver burden, and interviews in long-term care settings.
- Health Care Costs
- The combined trends of rising health care costs, provider consolidation, and shifting burden of costs onto consumers present challenges and opportunities for health care surveys.
- Papers may examine how to measure individual cost burden and define health care affordability for individuals, how to reconcile measurements of health expenditures from different data sources, or how to paint a complete picture of cost in a fragmented system where information is stored differently across provider types.
- The Changing Treatment Landscape
- The rise of phenomena such as telemedicine and self-treatment poses interesting challenges for survey measurement.
- Papers may examine how to measure telemedicine use, how surveys determine what qualifies as “treatment” (including things like self-care), and other important questions related to the changing definition of treatment use in survey data collection.