This week, a great op-ed published in The Wall Street Journal called “Turn Off the Computer and Listen to the Patient” brought a critical healthcare issue to the forefront of the national discussion. In 800 words, the authors (Dr. Caleb Gardner & Dr. John Levinson) succinctly describe the current frustrations physicians experience with electronic medical records (EMRs), in particular the negative impact that these systems can have on patient interactions.

Discussing federal incentives, standardized guidelines, and the path towards widespread EMR adoption, Drs. Gardner and Levinson paint a clear picture of rigid computer programs and an industry controlled by “one-size-fits-all rules for medical practice.”

In particular, this point struck us as particularly salient: “Medical records are now used primarily as management tools for billing compliance and population-data collection.”

Both authors are accurate in their assertion that EMRs often require manual data entry and other time-intensive tasks that distract from patient-centered care – mostly for the sake of information collection and adherence to regulatory measures.

As any physician will tell you, there is substantial work needed to reform the way these systems are designed in order to streamline clinician workflow and help refocus time back on the patient. Both Drs. Gardner and Levinson reaffirm that the answer isn’t abandoning electronic systems, but rather striking a balance between EMR usability and the valuable information that they provide.

For companies like Cyft that specialize in analytics capabilities, it is our responsibility to make doctors’ efforts worthwhile now. It is unreasonable to expect a healthcare “Hail-Mary,” i.e. the industry to finally collaborate and create a string of interconnected data warehouses with perfectly structured information. There are simply too many motivations to prevent this from happening.

Rather, we need to adapt tools today that are capable of turning data in its current form into valuable insights. Beyond dashboards, reports, and other fee-for-service analytics, we must parcel through all available resources to cater our treatments to the patient population, and not the other way around.

Like other promising healthcare innovations, now is the time to prove that predictive analytics can make an actionable difference in patient care. Due to rapid advances in machine learning and natural language processing, we can garner true insights from unstructured data to answer value-based care’s most fundamental questions: What should happen, to whom, and when.

Doing so will allow us to direct attention to where it’s needed most, and ultimately, enable physicians to better do their jobs.