Research: HIE Policies Such as Automatic Query, Patient Consent, Help Increase Volume of Data Exchanged | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Research: HIE Policies Such as Automatic Query, Patient Consent, Help Increase Volume of Data Exchanged

June 16, 2016
by Rajiv Leventhal
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Automatic querying and limited consent requirements are organizational health information exchange (HIE) policy decisions that impact the volume of exchange, and ultimately the information available to providers, according to new research published in the Journal of the American Medical Informatics Association.

Researchers from the Stanford University School of Medicine, University of Michigan, and elsewhere, looked at data on organization-level HIE policy decisions and their impact on HIE volume from a diverse set of healthcare systems using the same electronic health record (EHR)-based HIE platform. The study focused on clinical summary exchange over a two-year period. The researchers wanted to answer:

  • What proportion of organizations chose to engage in automatic querying and what is the associated impact on volume of clinical summary exchange?
  • When automatic querying is enabled, what proportion of patient linkages are established automatically (representing information at another institution that the provider did not know to seek) vs manually (representing information the provider knew to seek)?
  • What proportion of organizations chose not to require patient consent for HIE and what is the associated impact on volume of clinical summary exchange?

“Understanding the impact of local organizational HIE policy decisions on the volume of exchange activity is important in ensuring that future efforts to promote HIE will consider these decisions. Without sufficient attention to these critical policies, technical interoperability may not translate into availability of needed health information for clinicians at the point of care,” the researchers noted.

For the study, the researchers looked at the Northern California HIE Collaborative and 11 of its systems. Nine of the 11 provider organizations (82 percent) enabled automatic querying during the study period. Consent decisions were more varied. Four of the 11 provider organizations (36 percent) required point-of-care patient authorization, one (9 percent) required authorization if a patient had a prior encounter in a confidential department (eg, mental health), and six organizations (54 percent) did not require any HIE-specific authorization, according to the research.

A total of 6,909,416 clinical summaries were retrieved by participating organizations within the regional HIE network over the time frame of the study. In January 2013, six organizations were participating and retrieved 57,000 clinical summaries. By February 2015, all 11 organizations were participating and retrieved 826,000 clinical summaries, representing a 1,349 percent increase in exchange volume.

Indeed, the initiation of auto-query resulted in a significant increase in the monthly volume of clinical summaries received. In the pre auto-query period, exchange volume increased by 635 summaries per month. In the post auto-query period, exchange volume increased by nearly 10,000 summaries per month.

Meanwhile, provider organizations that required consent experienced a marginally statistically significant increase in clinical summary exchange volume of 510 summaries per month. Provider organizations that did not require consent experienced a significantly greater increase of 4,571 summaries per month. While no consent organizations started at a lower exchange volume overall, after six months they surpassed the consent organizations. Results were similar when we limited the data to the post auto-query period.

The researchers concluded, ” Specifically, both enabling automated patient record querying and information retrieval and minimizing patient consent processes appeared to substantially increase exchange volume. Perhaps most critical is our finding that auto-query identifies a large volume of information that was not sought out manually, suggesting that providers either did not know about this information, did not have the time to retrieve it, or did not consider it to be clinically relevant. These findings highlight that local organizational policy decisions have a significant impact on the extent to which information is available to clinicians to support decision-making.”

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