EHR and Health IT Consulting
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EHR and Health IT Consulting
Technical Doctor's insights and information collated from various sources on EHR selection, EHR implementation, EMR relevance for providers and decision makers
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ONC Hopes to Move beyond the EHR for True Population Health | EHRintelligence.com

ONC Hopes to Move beyond the EHR for True Population Health | EHRintelligence.com | EHR and Health IT Consulting | Scoop.it
Electronic health records are only the first piece in the population health puzzle, says JASON in a new report.
The Office of the National Coordinator is focused on a lot more than increasing adoption of electronic health records these days, and is starting to turn its attention to leveraging the nation’s growing health IT infrastructure for the ultimate goal of achieving effective, individualized health for every patient. After recognizing the need to move far beyond the clinical documentation EHRs can record, HHS is seeking stakeholder comments on a new JASON report that investigates how to bring population health management into the healthcare system by expanding the use of data analytics to encompass what happens outside the physician’s office.
“If we’re to have an accurate picture of health, we need more than what is currently captured in the electronic health record,” write National Coordinator Karen DeSalvo, MD, MPPH, MSc, Jon White, MD, and Michael Painter, Senior Program Officer at the Robert Wood Johnson Foundation in a blog post for HealthIT Buzz. “That’s why the US Department of Health and Human Services (HHS) asked the distinguished JASON group to bring its considerable analytical power to bear on this problem: how to create a health information system that focuses on the health of individuals, not just the care they receive.”
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“Why is it important to pursue this ambitious goal? There has been an explosion of data that could help with all kinds of decisions about health,” the post continues. “Right now, though, we do not have the capability to capture and share that data with those who make decisions that impact health—including individuals, health care providers and communities.”
The JASON report promotes the idea of the “learning health system” that connects EHRs and other health IT infrastructure with multiple streams of data that are not traditionally associated with healthcare, including social media and socioeconomic information. Care coordinators can help providers synthesize these data streams while providing patients with a way to navigate the increasingly complex healthcare ecosystem.
Stakeholders can help to also encourage the development of data integration by creating products that take advantage of open APIs and rely on data standards that allow for interoperability. The health system should also take advantage of the work of focused non-profit institutions that promote causes related to specific populations, such as elder care or heart health. These institutions already enjoy strong community trust and a deep understanding of their targeted conditions or causes, which can help providers better support wellness and provide resources to patients.
“This report, done in partnership with the Agency for Healthcare Research and Quality (AHRQ) and the Office of the National Coordinator for Health Information Technology (ONC) with support from the Robert Wood Johnson Foundation, comes at a pivotal time: ONC is in the process of developing a federal health IT strategic plan and a shared, nationwide interoperability roadmap, which will ensure that information can be securely shared across an emerging health IT infrastructure,” DeSalvo and her co-authors explain. “We’re excited by the potential to take this emerging data and turn it into useable information to build a Culture of Health—a nation where everyone has the opportunity to live longer, healthier lives.”
“We encourage everyone — consumers, providers, employers, purchasers, health IT developers and others—to take a look at the report and share your comments. We look forward
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EHR + Geography = Population Health Management

EHR + Geography  = Population Health Management | EHR and Health IT Consulting | Scoop.it

Duke Medicine is combining the data of EHRs with geography information to create a program which can predict patient diagnoses.

Duke University Medicine is using geographical information to turn electronic health records (EHRs) into population health predictors. By integrating its EHR data with its geographic information system, Duke can enable clinicians to predict patients' diagnoses.

According to Health Data Management, Sohayla Pruitt was hired by Duke to run this project; she has a master’s degree in geographic information systems, or GIS. “I thought, wow, if we could automate some of this, pre select some of the data, preprocess a lot and then sort of wait for an event to happen, we could pass it through our models, let them plow through thousands of geospatial variables and [let the system] tell us the actual statistical significance,” Pruitt says. “Then, once you know how geography is influencing events and what they have in common, you can project that to other places where you should be paying attention because they have similar probability.”

iHealth Beat explains that the system works by using an automated geocoding system to verify addresses with a U.S. Postal Service database. These addresses are then passed through a commercial mapping database to geocode them. Finally, the system imports all U.S. Census Bureau data with a block group ID. This results in an assessment of socioeconomic indicators for each group of patients.

“When we visually map a population and a health issue, we want to give an understanding about why something is happening in a neighborhood,” says Pruitt. “Are there certain socioeconomic factors that are contributing? Do they not have access to certain things? Do they have too much access to certain things like fast food restaurants?”

Duke is working to develop a proof of concept and algorithms that would map locations and patients. They are also working on a system to track food-borne illnesses.

“It’s easy to visualize or just say, ‘Oh, this person lives in a low income neighborhood with lots of fast food restaurants.’ You could probably do that very quickly,” Pruitt says. ”But the only way to really understand the statistical significance of what’s going on and where else it’s happening or going to happen is through infrastructure development, by pre-downloading that data, prepping and pre-relating that data to every address and every EHR.”



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