The ABATE Infection trial, an NIH Collaboratory project led by Dr. Susan Huang, is featured in the September 12 Health section of the Wall Street Journal. The article describes several studies aimed at preventing the hospital-associated infection MRSA (methicillin-resistant Staphylococcus aureus).
In the Reduce MRSA trial, published in 2013, Dr. Huang’s team demonstrated that treating ICU patients with a germ-fighting soap plus a nasal antibiotic ointment, an approach called “universal decolonization,” was superior to standard approaches in preventing MRSA infections. The ABATE Infection trial examines similar approaches to decolonization for all patients in non–critical care medical and surgical units, comparing the use of an antiseptic bath and nasal ointment to standard bathing and showering. More than 1 million showers and baths were taken over the course of the study, which has now completed enrollment. Data from ABATE are currently being analyzed, with the results expected to inform whether this strategy is effective in reducing hospital-associated infections.
“These are preventable infections and we should be able to drive them down to zero.” Susan Huang, MD
The authors elaborate on four required components of the framework:
Searchable libraries of explicitly defined phenotype definitions
Knowledge bases with information and methods
Tools to identify, evaluate, and implement existing phenotype definitions
Motivated users and stakeholders
Read the entire eGEMs open access publication here. eGEMs (Generating Evidence & Methods to improve patient outcomes), a product of AcademyHealth’s Electronic Data Methods (EDM) Forum, is a peer-reviewed, open access journal that seeks to accelerate research and quality improvement using electronic health data.
Related resources:You can find extensive information on computable phenotypes in the Living Textbookchapter and in Tools for Research.
In a commentary published this week in Modern Healthcare, Eric Larson, MD, MPH, and Karin Johnson, PhD, of Group Health Research Institute, argue that greater collaboration is needed between clinical researchers and healthcare system executives to address a “a gap between research approaches and delivery system needs.” Perspectives gathered through a survey and Institute of Medicine workshopwith healthcare executives indicated that research is not conducted fast enough or designed in a way that facilitates translation of evidence into clinical practice. The NIH Collaboratoryand National Patient-Centered Clinical Research Network (PCORnet)are cited as examples of effective partnerships between researchers and healthcare leaders; these research programs are addressing high-priority clinical questions and generating actionable knowledge. According to Drs. Larson and Johnson, pragmatic clinical trials and big data offer opportunities to create a learning health system, but this will require combining the perspectives and expertise of researchers and stakeholders from healthcare delivery systems. Drs. Larson and Johnson are part of the NIH Collaboratory’s Health Care Systems Interactions Core, a working group that “aims to support and facilitate productive collaboration between researchers, clinicians, and health system leaders.”
A new study examining public attitudes about the sharing of personal medical data through health information exchanges and distributed research networks finds a mixture of receptiveness and concerns about privacy and security. The study, conducted by researchers from the University of California, Davis and University of California, San Diego and published online in the Journal of the American Medical Informatics Association (JAMIA), reports results from a telephone survey of 800 California residents. Participants were asked for their opinions about the importance of sharing personal health data for research purposes and their feelings about related issues of security and privacy, as well as the importance of notification and permission for such sharing.
The authors found that a majority of respondents felt that sharing health data would “greatly improve” the quality of medical care and research. Further, many either somewhat or strongly agreed that the potential benefits of sharing data for research and care improvement outweighed privacy considerations (50.8%) or the right to control the use of their personal information (69.8%), although study participants also indicated that transparency regarding the purpose of any data sharing and controlling access to data remained important considerations.
However, the study’s investigators also found evidence of widespread concern over privacy and security issues, with substantial proportions of respondents reporting a belief that data sharing would have negative effects on the security (42.5%) and privacy (40.3%) of their health data. The study also explored attitudes about the need to obtain permission for sharing health data, as well as whether attitudes toward sharing data differed according to the purpose (e.g., for research vs. care) and the groups or individuals among which the data were being shared.
The authors note that while data-sharing networks are increasingly viewed as a crucial tool for enabling research and improving care on a national scale, they ultimately rely upon trust and acceptance from patients. As such, the long-term success of efforts aimed at building effective data-sharing networks may depend on accurately understanding the views of patients and accommodating their concerns.
An article published online this month in the Journal of the American Medical Informatics Association (JAMIA) outlines research challenges that must be addressed to achieve a high-functioning learning health system (LHS) that uses data to generate knowledge and improve care in continuous cycles. The article, titled “Toward a Science of Learning Systems: A Research Agenda for the High-Functioning Learning Health System,” is the product of an international workshop sponsored by the National Science Foundation. The workshop involved 45 prominent interdisciplinary researchers, who examined use cases for a national-scale LHS to determine a path toward this goal.
“…the LHS can succeed only by creating novel combinations of role, process and technology. This must occur by working back from the future, not by figuring out how to fix the various problems with a current system that fails to learn rapidly, routinely, and at scale.”
The group synthesized a research agenda in the form of key questions targeted at four system-level requirements for a high-functioning LHS. The authors further propose that addressing these questions will involve evolution to a new interdisciplinary science of “cyber-social ecosystems” in which diverse stakeholders collaborate to drive innovation.
Additional information from the workshop, including participants, slides, and use cases, is available online.
Article authors include NIH Collaboratory Coordinating Center Co-Principal Investigator Richard Platt, MD, MSc, and Co-Chair of the NIH Collaboratory Electronic Health Records Core, Jeffrey Brown, PhD.
The workshops brought together health system leaders and researchers to discuss partnerships for progress toward a learning healthcare system in which the continuous generation of knowledge informs better care. Attendees identified challenges and established priorities in integrating clinical research into healthcare delivery systems. There was a particular focus on the recently established National Patient-Centered Clinical Research Network (PCORnet).
A learning healthcare system is [one that] is designed to generate and apply the best evidence for the collaborative healthcare choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in health care .
Also included in the topic chapter are ethical and regulatory implications for learning healthcare systems, patient and public engagement, the application of electronic heatlh records and other information technology, logistical and organizational challenges to bulding learning healthcare systems, and early examples of such systems in practice.
1. Institute of Medicine. The Learning Healthcare System: Workshop Summary. Olsen L, Aisner D, McGinnis JM, eds. Washington, DC: National Academies Press; 2007. Available at: http://www.iom.edu/Reports/2007/The-Learning-Healthcare-System-Workshop-Summary.aspx. Accessed April 4, 2014.
The meeting was open to the public via webcast. Archived meeting presentations will be made available; a link will be provided in an update to this post. Workshop-related tweets can be found with the hashtag #IOMPCORI.