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Asking Population Health's Unanswered Questions

August 23, 2012
by Jennifer Prestigiacomo
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The Query Health initiative could help providers give better care to their populations and meet Stage 3 requirements
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Pilots under the Query Health project are testing two standards: the HQMF standard that expresses an e-measure in machine-readable electronic format; and a query envelope for the secure exchange of queries.

In efforts to turbocharge the understanding of population health, performance, and quality, the Office of the National Coordinator place for Health Information Technology (ONC) in September 2011 founded the Query Health project to develop standards for distributed population queries. The goals of these queries are to deliver insights for local and regional quality improvement and to facilitate performance measures and payment strategies for communities based on aggregated de-identified data. This summer three of the five pilots are kicking off to test specific data package and transfer standards.

“There are a lot of people who are doing distributed queries out there, but it is a heavy lift every time,” says Richard Elmore, former coordinator, Query Health, and vice president of strategic initiatives for the Chicago-based Allscripts. “There are no standards like there are now for patient-level exchange that [focus on] asking questions around a patient population.”

Farzad Mostashari, M.D., national coordinator, ONC, started the underpinnings of Query Health when he was the director of the Primary Care Information Project (PCIP) at the New York City Department of Health and Mental Hygiene, which is one of the current pilot sites. A year and a half ago, Mostashari asked Elmore to lead the Query Health project to come up with the standards, policies, and services that would enable distributed health queries, since there were no regulated query standards.

Possible Basis for Public Health Research
After the pilots are completed next year, pilot participants will give feedback to inform and improve already drafted standards and provide reference implementation. Depending on future research and funding, these standards could be used for public health initiatives, research, for application in federal partnerships, and for Stage 3 meaningful use.

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“In Stage 3 [meaningful use], the goal is improved outcomes through the implementation of a learning health system, and being able to have these rapid feedback loops and to get these insights on a patient population, which can inform patient care in significant ways,” Elmore says of Query Health’s potential impact.

Two main standards will be tested in Query Health pilots. One is the HL7-developed Health Quality Measure Format (HQMF) standard, which expresses a health quality measure, or “eMeasure,” in a machine-readable electronic format. Through standardization of a measure’s structure, metadata, definitions, and logic, the HQMF attempts to provide quality measure consistency and unambiguous interpretation to support meaningful use reporting. The second standard to be tested is the query envelope that facilitates the secure exchange of queries and results between information requestors and responding organizations according to their business workflows and data agreements.

Groundwork by Pilot Sites
Many of these pilot sites had been blazing trails in distributed queries even before Query Health came to fruition. For example, the Massachusetts Department of Public Health Network (MDPHnet) had previously received ONC grant funding to create its distributed query infrastructure to perform queries to inform diabetes and influenza-like illness surveillance, says Jeffrey Brown, Ph.D., Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine at the Harvard Pilgrim Health Care Institute/Harvard Medical School. MDPHnet is currently staging environment for queries. “For us some of the success is doing it in a way that can be easily replicated, and make sure we’re not [creating] throwaway pieces, which you often do in software development,” says Brown.

Another pilot that Brown is involved in is the Food and Drug Administration (FDA) Mini-Sentinel pilot. The Mini-Sentinel project began prior to Query Health in 2009. Rich Platt, chair of the Harvard Medical School Department of Population Medicine and principal investigator for the Query Health pilot, says the FDA seeks, through distributed queries, to accomplish three goals: ask a question of the distributed network that would help assess if a concern that has arisen is valid; evaluate the impact of regulatory action on a specific product; and monitor new products at the earliest warning of a problem.

The FDA used queries previously to test the validity of a culmination of incidents reported in the Adverse Event Reporting System of patients using hypertension medication Olmesartan  and who were developing celiac disease. The distributed query was used to identify users of Olmesartan and to look at their first diagnoses of Celiac disease. What was found was Olmesartan was right in the middle of the pack of other hypertension medications for celiac diagnoses, which resolved the incident.

In August, the New York City Department of Health and Mental Hygiene PCIP will begin query tests with a community health center and a solo provider practice, says Michael Buck, Ph.D., the department’s biomedical informatics R&D manager.

In the future, Buck foresees Query Health protocols as likely to be handled directly by the vendor, instead of by a third-party organization like his. “My sense is that this is like the requirements that the EHR vendors are to build to the Direct protocol, and eventually they would be required to build to the Query Health protocol and offer that as a part of their certification [package],” he says.

Buck adds that what makes Query Health different is that it should be less onerous, with fewer governance and legal difficulties, because the data that is queried is aggregate data, which is not considered protected health information (PHI), and it stays at the organization’s site. From a technological standpoint, the system has a smaller footprint than a data warehouse solution, so it should take months rather years to implement, he adds. “We want to see that Query Health delivers value quicker and with fewer resources required and fewer governance and policy issues because you’re able to protect patient privacy by leaving the PHI at the site,” Buck concludes.

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