Leveraging Patient Generated Data for Improving Patient Care
AMIA is pleased to announce the 5th Annual Student Design Challenge (SDC). In this challenge, we invite teams of graduate students from different scientific disciplines and of various backgrounds to propose creative solutions to a specified problem related to healthcare. We seek novel solutions that incorporate cutting edge computational and interactive technologies and take advantage of the considerable advances in such research areas as biomedical informatics, human-computer interaction, computer science, information visualization, pervasive and ubiquitous computing, among many others. A panel of distinguished members of the AMIA community will review the proposed solutions and select the best proposals based on a number of criteria, including their originality and transformative potential. Eight teams selected as finalists will be asked to attend AMIA Annual Symposium and present their solutions during the AMIA poster session. The top three teams as selected by the SDC panel will be invited to participate in a formal presentation at AMIA.
This year the Student Design Challenge is inviting submissions that focus on leveraging Patient Generated Data for improving patient care. Patient-Generated Data (PGD) has become a focus of increasing attention for both healthcare providers and patients. There is a growing recognition of its potential to provide new insights into individuals’ lives and health outside of the traditional clinical encounters. However, there remain considerable barriers to integrating PGD with Electronic Health Record (EHR) systems, and to using these data to improve patient care. In this challenge, we invite teams of students to envision new ways for integrating PGD with EHR and for using these data to improve clinical decision-making, patient care, and patient-provider communication.
- August 1, 2017 – proposal submission deadline
- September 1, 2017 – notifications to authors
- September 14, 2017 – final accepted revision submission deadline
Please read the entire Challenge description. If you have any questions about this process, please send an email to email@example.com
The growing popularity of technologies for self-monitoring of health and wellness is leading to a rapid increase in the volume of health data recorded outside of clinical encounters. These data, captured with specialized activity trackers, smart-phone applications, and wearable biosensors can reveal important patterns in individuals’ lifestyle and behaviors, as well as provide a more accurate picture of their health (1). Integrating these data into contemporary EHR can help clinicians incorporate these insights into their decision making and lead to more informed treatment choices. The critical importance of PGD is recognized by the Meaningful Use Program; integration of these data into EHR has been included as one of the Meaningful Use requirements (2,3). However, together with this excitement in regards to PGD, there remain considerable barriers to incorporating PGD into EHR and into clinical work. The high volume of PGD can further exacerbate information overload, disrupt clinical workflows, and increase concerns regarding provider liability (4–8). Moreover, multiple concerns have been raised in regards to reliability and trustworthiness of data generated outside of clinical settings and without clinicians’ supervision. Integrating these data with traditional clinical records may present new challenges to informatics solutions, for example due to differences in resolution and sampling rates. As a result, many healthcare providers are reluctant to incorporate PGD, despite its potential to improve patient care (8,9).
In this challenge, we call on undergraduate and graduate students and trainees in Biomedical Informatics and related fields to envision new ways of integrating PGD into future EHR systems with the goal of improving patient care. These solutions can focus on various aspects of clinical work, including diagnosis, selection of treatment options, monitoring for changes in a patient’s conditions overtime, evaluating efficacy of different treatment options, and promoting shared decision-making between providers and patients. They can range from novel ways to visualize PGD to help clinicians and patients identify important and actionable trends, to novel computational solutions to using these data together with the traditional EHR data to provide clinical decision support that may or may not include visual presentations.
Importantly, in this challenge our focus is on integrating PGD with EHR and on improving care within the clinical context, rather than on using these data outside of traditional care settings to promote health and wellness.
- Kumar RB, Goren ND, Stark DE, Wall DP, Longhurst CA. Automated integration of continuous glucose monitor data in the electronic health record using consumer technology. Journal of the American Medical Informatics Association. 2016 May 1;23(3):532–7.
- 2015 Edition Health Information Technology (Health IT) Certification Criteria, 2015 Edition Base Electronic Health Record (EHR) Definition, and ONC Health IT Certification Program Modifications [Internet]. Federal Register. 2015 [cited 2017 Jan 2].
- Medicare and Medicaid Programs; Electronic Health Record Incentive Program-Stage 3 [Internet]. Federal Register. 2015 [cited 2017 Jan 2].
- Issue Brief: Patient-Generated Health Data and Health IT - pghd_brief_final122013.pdf [Internet]. [cited 2017 Jan 4].
- Patient-Generated Health Data White Paper - rti_pghd_whitepaper_april_2012.pdf [Internet]. [cited 2017 Jan 4].
- Halford GS, Baker R, McCredden JE, Bain JD. How many variables can humans process? Psychol Sci. 2005 Jan;16(1):70–6.
- Mamykina L, Levine ME, Davidson PG, Smaldone AM, Elhadad N, Albers DJ. Data-driven health management: reasoning about personally generated data in diabetes with information technologies. J Am Med Inform Assoc. 2016 May;23(3):526–31.
- Cohen DJ, Keller SR, Hayes GR, Dorr DA, Ash JS, Sittig DF. Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign. JMIR Human Factors. 2016;3(2):e26.
- Mane KK, Bizon C, Owen P, Gersing K, Mostafa J, Schmitt C. Patient electronic health data-driven approach to clinical decision support. Clin Transl Sci. 2011 Oct;4(5):369–71.
To qualify for participation, teams should include only students in degree-pursuing graduate programs (including clinicians in training, such as residents and fellows, as well as post-doctoral fellows pursing MA or MS degrees) or Graduate Certificates. Undergraduate students are welcome to participate in design teams, provided that they are supervised by graduate students. Given the nature of the creative process, we suggest that teams include no more than 4 or 5 individuals. No faculty advising is required for participation; in fact, we encourage teams to work independently and with minimal faculty supervision.
Each team will be asked to identify a specific challenge related to the proposed theme. We recommend that teams select a specific context of use and target audience, for example “Using PGD to support shared decision making between Diabetes Educators and individuals with type 2 diabetes”, or “Using PGD to improve diagnosis of congenital heart disease among school-aged children”. In both of these scenarios the focus of the solution should be on new ways PGD can be incorporated into EHR and into clinical decision-making and workflow. Some potential areas of focus could include:
- Identifying new ways to integrate PGD into the Electronic Health Record and combine them with clinical data;
- New ways to present patient-generated data to patients and clinicians, including novel visualizations;
- Novel ways incorporate PGD into clinical decision-support systems;
- New ways of using PGD to facilitate shared decision-making between patients and providers.
To be considered for the inclusion in the challenge, the teams must develop their proposed solution in sufficient detail to demonstrate their fit to the problem, original approach, and technical viability. For interactive solutions, this would entail developing interactive prototypes or mockups that illustrate their functionality; for computational solutions, the teams will be asked to submit their source code as a text file or a link to the team’s github repository. Proposals to develop solutions in the future will not be considered.
Each team will submit an extended abstract (5 page maximum) discussing their description of the specific challenge related to Engaging Providers and Patients in Precision Medicine, the proposed solution, and their design process. Supplementary materials (including storyboards and mockups, or source code and sample output) are a required part of the submission, and can be included as a separate PDF. The supplementary materials would not count against the 5 page maximum. The submission process will be done through ScholarOne (more details on the submission process are to follow). The submissions will be evaluated through a peer-review process by the SDC steering committee.
The 8 best proposals will be asked to present their solutions during a poster session at AMIA 2017. At least one member from each of the 8 teams will be expected to attend the conference to present a poster illustrating their solution, discuss their solution, and the design process with conference attendees. AMIA will wave registration fee for one presenter from each of the eight teams, with the expectation that the presenter holds a student membership with either AMIA or ACM.
Three teams will also be notified prior to the symposium that their proposal has been selected as a finalist for the AMIA SDC Award. They will be asked to give a presentation about their solution during the AMIA Student Design Challenge session. The 3 finalists will give an oral presentation and, where appropriate, demonstration of their design to the panel of SDC Judges and AMIA attendees. The judges will rank the solutions and presentations to identify the winner and subsequent 2nd and 3rd place teams. The winners will be announced during the last day of AMIA Annual Symposium and acknowledged during the AMIA Closing Plenary.
The participants will prepare an extended abstract (five pages maximum) written in the AMIA format that must include:
- Definition of the selected challenge related to leveraging of patient-generated data for improving patient care grounded in deep understanding of an identified health problem
- Description of the proposed solution
- Discussion of alternative solutions considered
- Discussion of the strengths and weakness of the chosen solution as compared to the alternatives
- Proposed implementation and dissemination plan (what it would take for this solution to be adopted on a large scale)
- Proposed evaluation plan (the participants will be expected to outline potential directions for evaluation, but not to perform it)
The Supplementary Materials must include:
- For interactive solutions: a mockup or storyboard illustrating the proposed functionality and the interaction of the proposed solution, a link to a video demo of the system.
- For computational solutions: source code of the solution as a text file or a link to the team’s github repository as well as sample output file (in a PDF document)
The completed abstract and any supplementary documents should be submitted using ScholarOne by 11:59 p.m. EDT on August 1, 2017. If you do not already have a ScholarOne account, you will need to create one. AMIA member log-in will not provide access to ScholarOne. If you are not sure if you already have an account or if you have one, but do not remember your user name and password, please contact Dasha Cohen at firstname.lastname@example.org
All proposed solutions will be reviewed by the SDC Steering Committee, consisting of distinguished members from the AMIA and HCI communities. The members of the Steering Committee will review the abstracts and assess their quality, focusing on both the actual proposed solution, and its description and justification in the proposal, based on the following criteria:
- Understanding of the problem (does the solution address an important problem related to integration of PGD into EHR systems in a realistic way and does it demonstrate a deep understanding of the problem)
- Fit to the problem (how likely is the proposed solution to address the selected problem?)
- Effective integration of clinical experts or patients (whether the proposed solution relies on clinical expertise and/or deep understanding of patient perspective)
- Innovation (how novel and original is the solution?)
- Transformative potential (how likely is it to transform the nature of clinical decision-making or communication between providers and patients)
- Completeness (is the solution is well thought-out and complete)
- Clarity of the design process (how well the solution and the design process described in the abstract)
- Clarity of the strengths and weaknesses discussion (do the teams have a realistic and thoughtful assessment of the strengths and weaknesses of their solutions?)
- Appropriateness of the evaluation approach (is the evaluation plan appropriate for the solution?)
The SDC awards ceremony will take place during the last day of AMIA Annual Symposium.
- August 1, 2017 – proposal submission deadline
- September 1, 2017 – notifications to authors
- September 14, 2017 – final accepted revision submission deadline
If you have any questions about this process, please send an email to email@example.com
Lena Mamykina, PhD, Assistant Professor
Department of Biomedical Informatics, Columbia University
Dr. Mamykina’s broad research interests include individual’s sensemaking and problem-solving in context of health management, collective sensemaking within online health support communities, clinical reasoning and decision-making, communication and coordination of work in clinical teams, and ways to support these practices with informatics interventions.
Dr. Mamykina received her B.S. in Computer Science from the Ukrainian State University of Maritime Technology, M.S. in Human Computer Interaction from the Georgia Institute of Technology, Ph.D. in Human-Centered Computing from the Georgia Institute of Technology, and M.A. in Biomedical Informatics from Columbia University. Her dissertation work at Georgia Tech focused on facilitating reflection and learning in context of diabetes management with mobile and ubiquitous computing. Prior to joining DBMI as a faculty member, she completed a National Library of Medicine Post-Doctoral Fellowship at the department.
Madhu Reddy, PhD, Professor
Communication Studies, Health and Biomedical Informatics, Northwestern University
Dr. Reddy’s research focuses on issues of collaboration in healthcare. He is particularly interested in how healthcare providers collaborate during information seeking and decision-making activities and the role that HIT plays in supporting these types of collaboration in clinical settings.
Dr. Reddy received his M.S. in Health Care Administration from the California State University, Long Beach, M.S. in Information and Computer Science from the University of California, Irvine, and Ph.D. in Information and Computer Science from the University of California, Irvine.
Jonathan Nebeker, MD, MS
Associate Professor of Internal Medicine,
University of Utah, School of Medicine
Dr. Nebeker is currently interested in translating theoretical frameworks from social and cognitive psychology to medicine for designing and evaluating user interfaces for EHRs (with Charlene Weir and Frank Drews.) He led a project to translate the Contextual Control Model from a branch of Cognitive Systems Engineering. Guided by this translated model, his team developed a new paradigm for graphical user interfaces (GUIs) for EHRs. Instead of focusing on data, which is typical of current EHRs, the GUI focuses on thought- and workflow. The GUIs incorporate ideas from mindset, dual process, and communication theories. They featured information displays that are designed to reduce cognitive effort to understand what is going on with the patient. In a randomized controlled trial versus a widely used traditional interface, the new interfaces were significantly faster—despite minimal training in the unfamiliar interfaces.
Dr. Nebeker also has national leadership roles in VA. He is Director of VA Informatics and Computing Infrastructure (VINCI.) VINCI is a secure, powerful, virtualized computing environment with national clinical data back to 2000. In addition to directing the center, Dr. Nebeker leads GUI development for several applications. Dr. Nebeker is the Clinical Lead for the DoD-VA Integrated EHR Graphical User Interface. In this capacity he coordinates with national VA clinical leads and directs the vision for the new paradigm for the iEHR interfaces.
Wanda Pratt, Ph.D
Professor, Information School, Division of Biomedical & Health Informatics, University of Washington
Wanda Pratt is a Professor in both the Information School and the Division of Biomedical & Health Informatics in the Medical School at the University of Washington. She received her Ph.D. in Medical Informatics from Stanford University, her M.S. in Computer Science from the University of Texas, and her B.S. in Electrical and Computer Engineering from the University of Kansas. Her published papers span a wide range of topics whose central theme is to understand the problem of information overload in a variety of health contexts and to develop new types technology to address those problems. She received an NSF CAREER Award for her work on literature-based discovery systems.
Samuel Trent Rosenbloom, MD, MPH, FACMI
Dr. Rosenbloom is the Vice Chair for Faculty Affairs, the Director of Patient Engagement Technologies and an Associate Professor of Biomedical Informatics with secondary appointments in Medicine, Pediatrics and the School of Nursing at Vanderbilt University. He is a board certified Internist and Pediatrician who earned his M.D., completed a residency in Internal Medicine and Pediatrics, a fellowship in Biomedical Informatics, and earned an MPH all at Vanderbilt. Since joining the faculty in 2002, Dr. Rosenbloom has become a nationally recognized investigator in the field of health information technology evaluation. His research has focused on studying how healthcare providers interact with health information technologies when engaging patients, documenting patient care and making clinical decisions. Dr. Rosenbloom has successfully competed for extramural funding from the National Library of Medicine and from the Agency for Healthcare Research and Quality in the role of principal investigator. Dr. Rosenbloom’s work has resulted in lead and collaborating authorship on over 60 peer reviewed manuscripts, which have been published in Journal of the American Medical Informatics Association, Pediatrics, Annals of Internal Medicine, and Academic Medicine, among others. In addition, Dr. Rosenbloom has authored and coauthored 5 book chapters and numerous posters, white papers and invited papers. He has been a committed member of the principal professional organization in his field, the American Medical Informatics Association (AMIA). He has served AMIA in leadership roles, including participating in: a Scientific Program Committee, the Journal of the American Medical Informatics Association (JAMIA) Editorial Board, a national Health Policy Meeting Committee, the JAMIA Editor in Chief search committee, and a Working Group on Unintended Consequences. As a result of his research success and service to AMIA, Dr. Rosenbloom was the annual recipient of the competitive AMIA New Investigator Award in 2009, and was elected to the American College of Medical Informatics (ACMI) in 2011. In addition, Dr. Rosenbloom has participated in study sections for the National Library of Medicine and the Agency for Healthcare Research and Quality’s Healthcare. He has also participated as a member of the HL7 Pediatric Data Special Interest Group and the American Academy of Pediatrics’ Council on Clinical Information Technology. In addition, Dr. Rosenbloom is an active reviewer several journals covering general medicine, pediatrics and biomedical informatics.
Katie A. Siek, PhD, Assistant Professor
Katie Siek is an associate professor in Informatics at Indiana University Bloomington. Her primary research interests are in human computer interaction, health informatics, and ubiquitous computing. More specifically, she is interested in how sociotechnical interventions affect personal health and well being. Her research is supported by the National Institutes of Health, the Robert Wood Johnson Foundation, and the National Science Foundation including a five-year NSF CAREER award. She has been awarded a CRA-W Borg Early Career Award (2012) and a Scottish Informatics and Computer Science Alliance Distinguished Visiting Fellowship (2010 & 2015). Prior to returning to her alma mater, she was a professor for 7 years at the University of Colorado Boulder. She earned her PhD and MS at Indiana University Bloomington in computer science and her BS in computer science at Eckerd College. She was a National Physical Science Consortium Fellow at Indiana University and a Ford Apprentice Scholar at Eckerd College.