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March 2020

HIT Happenings: Why Are HIEs Not Meeting Expectations?
By Randy Jones
For The Record
Vol. 32 No. 2 P. 26

The health information exchange (HIE) offers a great deal of promise as a methodology to improve the speed, quality, safety, and value of patient care by enabling shared access to patient information between health care facilities—whether or not they are in the same system.

The effective sharing of vital patient information is key to informing better decision making, avoiding costly medical errors and readmissions, assisting in the nullification of duplicate records and other patient identity issues, improving diagnoses, and decreasing duplication of testing.

While the industry has made strides toward achieving these goals, one must wonder why, in a world in which consumers can easily and securely access the full spectrum of their financial data and where retailers are using artificial intelligence to know that a customer needs to purchase more paper towels before even the customer does, is it still so difficult for doctors and patients to conveniently access their health care information—often between floors of the same building?

Potential Roadblocks to an Industry Transformation
For those who are not part of the health care industry and are simply on the outside looking in, the scope of the challenge in successfully maintaining patient record accuracy is likely underappreciated. Quite frankly, this view is sometimes held by those inside the hospital itself, leading to a reluctance to invest in comprehensive data clean-up and clarification. Too often, hospital management operates under an assumption that its patient data are clean only to realize when it becomes an expensive problem that this is not the case.

To counter this, hospitals must first understand and accept that they cannot improve what they are not first measuring, and that unclean data are a pervasive problem that must be addressed throughout the organization, from the C-suite down to the individual contributor level. In a real-world environment, the transfer of patient data between floors or units of the same hospital can be operationally difficult, not to mention the problems associated with exchanging information between hospital system members and across large geographic areas.

Complicating this endeavor is the consolidated nature of today’s health care industry, in which a large share of patients is essentially corralled into a handful of major provider networks. As these enterprise organizations merge, so too begins the back-office process of integrating disparate systems and databases of literally millions of patient records.

At the same time, a host of new urgent care centers and lab facilities are opening and coming online, and with them the potential for exponentially more points of entry for patients and their data. For example, a patient who checks into a walk-in clinic with tightness in the chest may then be redirected to a hospital emergency department. At both points of entry, patient data are going to be collected and entered into a database. In the emergency department setting, the standard imperative is to get the patient through the intake process, triaged, and in front of caregivers as quickly as possible. Walk-in clinics don’t typically face the same intensity of purpose, and their staffing levels may not always support the accurate capture of patient data at admission.

Assuming a hospital takes the initiative to evaluate the quality of its database, duplicate records and data issues must be flagged and cleaned up at the point of entry to avoid recurrence. The question then becomes, what are the true incentives to invest the time and the resources to correct these issues? Many hospitals and other health care facilities incur no meaningful penalties (eg, in the form of additional charges) for continuing to submit bad data.

In some instances, it’s been discovered that the HIE’s compensation and performance incentives are tied to its total number of open or active patient records, so there is a perceived negative financial impact of eliminating duplicate or mismatched records. By reducing the number of records in a database by 10% to 20%, this could make so-called “performance” metrics look worse; it is entirely possible that some employees and executives would see their corresponding bonuses reduced as a reward for doing the right thing. This creates an internal conflict that is at the root of the HIE’s limited success to date.

Patient behavior and reticence in response to recent high-profile data breaches also impacts the level of nationwide HIE adoption and efficacy. A recent Black Book consumer survey of more than 12,000 patients found that 57% of respondents were “skeptical of the overall benefits of health information technologies such as patient portals, mobile apps, and electronic health records mainly because of recently reported data hacking and a perceived lack of privacy protection by providers.”

Additionally, survey respondents cited concerns that pharmacy prescription information, mental health notes, and chronic condition data may be shared beyond their personal physicians and insurance companies with retailers, employers, and even the government without their permission or acknowledgment. Perhaps most alarming is that 89% of respondents indicated that they have personally withheld health information during visits to their provider, which impacts the overall quality of the data that the HIE is designed to share, threatening to undermine the program’s success.

The Road to Better Expectations and Better Outcomes
At a macro level, pursuing record accuracy and contributing to a more efficient and effective HIE far outweigh the costs, both in terms of patient safety and an estimated $1.5 million of annual savings per hospital. The concept of embracing a better HIE can begin with the following improvement areas that can be addressed with relative ease:

• consider that 90% of patients can be readily identified through a simple combination of ZIP code and birthdate;

• incorporate a more effective auditing system, one that focuses on identifying underbillings as well as overbillings; and

• move away from the focus on referential data (front-end rather than back-end data), as it can worsen match rates. Third-party sources can often add to false-positives.

For health care organizations, the question of whether to take a hard look at their databases and the accuracy of their patient data is not an “if” but a “when.” The Office of the National Coordinator for Health Information Technology has established a guideline that calls for a duplicate patient record rate of less than 0.5% for health care organizations by the end of 2020.

By adopting the philosophy and methodology of cleaning up existing patient data and ensuring that any new data are clean the first time, health care organizations can best position themselves to realize significant cost savings over time, both from a billing standpoint and from a reduction in readmission penalties. Most importantly, it better ensures the highest quality of care for patients.

By addressing these issues where they stand and having industry associations play more of a leadership role as advocates for this endeavor, HIEs can achieve what they were conceptualized to accomplish.

— Randy Jones is a senior health care solutions leader at Argo.