1. SUNDAY, SEPTEMBER 2, 2012
Towards a Learning Health System
This article was originally published on It Takes a Community, the Allscripts blog
This past year, I took a leave of absence from All scripts to serve as the Office of the National
Coordinator for Health IT (ONC) coordinator for Query Health, an Open Government Initiative that is
establishing standards, policies and services for distributed population queries of clinical records. It
comes at a unique moment in time – at the confluence of broad deployment of Electronic Health
Records, the compelling need for standards for secondary use of that healthcare information, and a
Stage 3 Meaningful Use strategy that focuses on a “learning health system.” That is, a system
in which the vast array of health data can be aggregated, analyzed, and leveraged using real-time
algorithms and functions.
I’m thrilled to be back and sharing what I learned about what we can do to implement a learning health
system that benefits patients on a national scale.
Our work began in August 2011 in Washington D.C., with a “Summer Concert Series” environmental
scan of the best work on distributed queries happening around the country. I collaborated with some of
the top folks in the industry from the more than 100 member organizations. It was energizing to be
engaged with colleagues so deeply committed and passionate about improving health care.
My job was to lead the overall initiative representing ONC. Clinical, operations and technical
workgroups, each with around 40 members, delivered the functional and operational requirements, the
technical approach, the proposed standards and reference implementations. We actively engaged with
the National Coordinator, the HIT Standards Committee, the HIT Policy Committee and the Privacy and
Security Tiger team to ensure that Query Health aligned with broad national priorities and strategies.
Understanding Population Health
Distributed population queries can be applied to a variety of secondary uses. Distributed population
queries enable an understanding of population measures of health, performance, disease and quality,
while respecting patient privacy, to improve patient and population health and reduce costs.
Distributed population queries are a central component of ONC’s strategy for a learning health system.
These queries “send questions to the data” and return aggregate population measures that keep
patient-level information protected at the source.
We use distributed population queries today for a variety of purposes. For example, public health tracks
diseases, including flu-like illness, and evaluates optimization of scarce resources. The FDA evaluates
signals related to drug safety once drugs are released to the market. Researchers compare the relative
effectiveness of drugs and treatments.
Putting It into Practice

2. There are five Query Health pilots kicking off this summer and fall.
The New York City and State public health departments are sending questions to both provider practices
and RHIOs related to diabetes and hypertension.
The Food and Drug Administration is sending questions to a clinical data source at Beth Israel Deaconess
Medical Center to evaluate which post-market drug surveillance questions can be supported by clinical
data.
The Massachusetts Department of Public Health is sending diabetes-related questions to community
health centers and provider practices.
The Centers for Disease Control is applying Query Health standards to its BioSense 2 cloud-based
distributed data repository for situation awareness and disease syndromes.
All scripts is testing the applicability of Query Health to dynamically query for clinical quality measures.
Query Health standards are being prepared for standards ballot by HL7 and ONC’s Office of Science and
Technology. The standard for Queries is based on an improved, more parsimonious version of the
Health Quality Measure Format or HQMF. The standard for Results is the Quality Reporting Document
Architecture or QRDA (Categories 2 & 3). The target data is aligned with the S&I Framework Clinical
Element Data Dictionary, the National Quality Forum’s Quality Data Model and the HL7 Consolidated
CDA.
You can find more information about the project at QueryHealth.org.
What’s your take on how the Query Health initiative can improve how we use health IT for the benefit of
patient and patient populations? Do you have new ideas we haven’t yet considered? Share your
thoughts below.
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Source: - http://news.avancehealth.com
“The key is integration of standards that would bring a host of activities and features under one roof. As
a next step one needs to put these learning systems to optimum use as training and hands-on
experience is a must to enhance the rate of adoption of these solutions, which is very low at present”,
feels Dr. Charu Chitalia – Director Operations Acroseas Global Solutions