How Health Information Exchanges Can Improve Data, Interoperability

The US health care system has seen drastic changes in data and transparency requirements in recent years. In this interview, Dr Jaime Bland provides insight into how health information exchanges (HIEs) can aid data collection and quality, not only to improve interoperability across the industry, but also to lower costs and optimize outreach.

Amid so much recent legislation surrounding transparency, can you comment on the current state of HIEs?

The transparency component in interoperability legislation is focused on data following the person. For legislation like price transparency, it is great that patients can shop for care, but data must then follow that person to their next encounter with the health care system.

If I get magnetic resonance imaging across the street, it might cost me half as much as it would in a large health system, but then the large health system must have that data in a format and quality they can consume and use. Entities like HIEs are critical to the actual operationalization of price transparency, as one example.

Additionally, patient access to data is part of the transparency needed to improve information sharing and cost equality.

Thank you. What would you say are the main challenges stakeholders face when it comes to data collection and analysis?

The biggest challenges in collection are their governance and trust. Trusted communities like those that are facilitated by HIEs are a critical piece in ensuring we have the most data sharing possible. Using trusted sources helps us understand data quality on maps.

Electronic health record (EHR) implementation varies from site to site, even if it is the same EHR. Those workflow constraints present in certain systems are not necessarily present in a competing system, which may result in some data quality issues during the extraction process. When we look at data quality, we are evaluating that from a population perspective and can help systems understand where their workflow may be obstructing information sharing.

Just one example of this is male/female. When we take that data in, it might be coded 1 and 2 in health system X. Then we go to health system Y, and that same data element is coded M and F. We must do the data quality work to understand what is male or female or other, which is something HIEs do well.

We also do patient matching to ensure the same person is recognized across systems regardless of where they access care. This also helps with data quality and matching, and leads to price transparency and other downstream efforts from a legislative perspective that require that type of infrastructure to be successful.

Going off that, how can improving data collection impact health plans, health systems, patients, anything else you want to add there?

The data can be used to not duplicate care, labs, and imaging that are not needed. If data quality is maintained and matched to the person, it can be used to reduce the individual class expenditure as far as out-of-pocket costs, as well as improve health plans’ management of patients from a quality perspective. For instance, data could aid in managing how much radiation a patient is exposed to over a lifetime from imaging. Did a patient get their mammogram or colonoscopy?

It helps with not having something over-medicalized too. If you do not need a colonoscopy until you are 45 years of age, having information that you underwent one helps prevent care managers from assigning resources that are not needed or contacting a patient who does not require outreach.

There are multiple use cases, from overutilization to improving quality and preventive care, when HIEs and health plans work together.

And what advice would you offer organizations that are hoping to improve their data?

I would say to work with the HIE and understand how the data looks when it is extracted from your system. Be open to different workflow modifications that will help improve interoperability.

Thank you. Is there anything else you would like to add today?

HIEs are evolving with these legislative initiatives, such as transparency and interoperability, to focus on multi-stakeholder use cases. You will hear the term ‘health data utility,’ and that means we fulfill private, commercial, and public health use cases, to work across the health care ecosystem. This is to ensure data moves with the person and supports costs, quality, and overall health care transformation.

About Dr Bland

Jaime Bland, DNP, RN, is president and chief executive officer of CyncHealth. Since being appointed CEO in 2018, Dr Bland has piloted CyncHealth’s strategic growth beyond the established health information exchange and Prescription Drug Monitoring Program to include three new entities—CyncHealth Advisors, the CyncHealth Foundation, Nebraska Healthcare Collaborative and CyncHealth Iowa. Under Dr Bland’s leadership, CyncHealth is transforming to become a regional health data utility.

Prior to CyncHealth, Dr Bland has held leadership positions in regional, national, and international markets within the public and private sectors. Dr Bland has extensive experience in establishing and leading care management, population health, and clinical quality initiatives. She holds advanced degrees in informatics and a Doctor of Nursing Practice in Public Health-Global Health Nursing from Creighton University.