The sphere of healthcare in the U.S. has shifted, as the open enrollment period for the Affordable Care Act comes to a close. A transition to data-driven healthcare is occurring, as more Americans gain coverage and more patient data becomes available.

The sheer amount of data coming in to healthcare providers requires organizations to face this new challenge in the growing volume of data coming in. But the real problem doesn’t stop with just the volume of data. Disparate systems, clinical and administrative documents, voice recordings, medical images, and patient data in legacy systems means that IT cost management and compliance raise serious challenges.

Data-Centered Patient Care

Certainly, we’re moving toward data-centered patient care, and the quality of patient care will be tied to the quality of patient data (and reducing the noise from disparate legacy systems).

To some degree, the rapid adoption of EMR systems has helped pave the way for a more complete, accurate picture of each patient from the electronic patient record. Despite rapid investment in EMR systems, only a portion of a patient’s data is electronic, many sites still have some data only in paper form. Sometimes clinicians run duplicate tests due to missing data, other times decisions are made with an incomplete clinical picture.

According to IDC Health Insights, 18% of medical errors are the result of inadequate availability of patient information.

Humans vs. Computers

When there’s a glut of information, computers can’t differentiate between what’s important and what’s not; humans can. Dr. David Denton reports in Information Week:

“Interestingly, however, while computers are great at sorting through data quickly and efficiently, humans aren’t. In fact, “more,” often clogs our ability to discern and decide. Additionally, computers can’t distinguish good data from bad data. At present, humans are still required to use the data to make decisions and care for patients. Until we have computers that can form therapeutic alliances, be compassionate, diagnose conditions, and provide and coordinate reasonable treatments, we are still dependent on fallible biologic beings to provide our medical care.”

Is Standardization the Answer?

Standardization on data entry methods and applying standard templates is one way to reduce the way to sort through data. But data entry standards are typically applied inconsistently across different providers, units, or sites.

Decision Support Systems

Another solution is to use a decision support system that integrates and filters meaningful patient data, presenting it to the clinician as needed, in a simple-to-read format. At AlertWatch, we strive to make disparate data systems more manageable by integrating live physiologic data with patient history, EMR, and lab data.

AlertWatch’s secondary patient monitoring systems provide a visual snapshot to the clinician, and as the patient case changes, alerts based on standard calculations notify the clinician of changing conditions. Example alerts can be found in our online demo.

The health informatics industry needs to remember that the primary purpose for its existence is to document useful information to providers so that high-quality care can be given using the most recent and accurate information possible. Clinicians care most about their patients. Each patient ID or registration number represents a human being that needs medical care: a person who shouldn’t be boiled down to a few checkboxes or edited templates along the way.