Rates of physician burnout are rising, and many physicians cite their electronic health record (EHR) as the primary culprit. That’s no surprise, since doctors spend twice as much time on electronic health record (EHR) systems and deskwork as they do directly interacting with patients. Let that sink in for a moment. Imagine if an airline pilot spent six hours documenting every detail of a three-hour flight. Such is the reality of modern medicine.

Proposed solutions have ranged from simplifying billing and quality reporting practices to abandoning EHR altogether. But we believe, perhaps ironically, that the most straightforward solution to our technological woes lies in more, and better, technology.

By embracing emerging healthcare technologies, we can jumpstart a new era of increased productivity and improved physician and patient satisfaction.  Below, we present three categories of innovations that we consider among the most promising because of their potential to save clinicians time and empower them to refocus their attention on patients.

More talk, less type

No matter how smart the EHR, physicians usually find themselves typing or dictating to record the details of each patient encounter, such as the physical exam, assessment, and plan. The result is often a recitation — from voice to text — of the words just exchanged. Scribes — assistants who stand by the doctor’s side and populate the EHR with all necessary information — were an early attempt to address this inefficiency.

Digital-age innovations are now disrupting this process. With one system offered by a company called Augmedix, physicians wear Google Glass while a remote scribe follows the live video and audio, as if in the room. The next step is for companies like this to combine the power of advanced voice recognition and artificial intelligence software (such as that found in Apple’s Siri and the Amazon’s Echo), so as to enable physician-patient encounters to be recorded, documented, and analyzed in real time. Natural language processing software has already shown promise, for example in locating key physical exam findings in free-text notes and classifying patients’ colorectal cancer screening status. Further integration of this software could obviate the need for dozens of checkboxes and hours of manual documentation. It could transform workflow such that while physicians are speaking to patients, the EHR is self-populating, freeing physicians to spend more time on clinical medicine, and less time buried in electronic data entry.

Machine learning

Today, providers input most orders individually. In a patient with fever and cough, the doctor orders a chest x-ray, complete blood count, and necessary treatments in piecemeal fashion. Clinical decision support consists of order sets and templates that can standardize and simplify ordering for common conditions. However, building order sets manually depends on availability of expert consensus, which is often hard to achieve.

Machine learning can fill this gap. By monitoring physician behavior and outcomes, it is possible to automatically generate order sets—similar to Amazon’s recommendations that “customers who bought A also bought B.”

This type of automation is in use today. Cloud-based EHR systems like Athena Health are implementing workflow optimization tools by tracking physician behavior; for example, how often physicians order a certain test and how long it takes them to do so. They can then use that data to cluster diagnostics and treatments that are commonly ordered together. Similarly, Chen and colleagues have used EHR data to build decision support within traditional, server-based EHR systems. Although these automated order sets will require additional validation, they provide recommendations that are consistent with standards of care.

Patient-generated health data

In many health systems, only physicians and support staff can access the EHR and input information. This often results in patient work being duplicated by clinical staff. Before seeing their physician, patients often complete forms detailing current medications, past medical history, social history and family history. If patients could input that data directly into the EHR via smartphones or tablets, health systems could improve communication and patient engagement while saving clinicians time.

Several medical centers are already using patient-generated health data to successfully capture patients’ family history, expectations for treatment results and home blood pressure and heart rate results. A multicenter initiative called OurNotes invites patients to contribute to their own electronic medical records.

Giving patients “write” access is not without risk. Duplicate or insufficiently detailed information may clutter the EHR. Physicians may fail to clarify incomplete patient-entered information, or overlook pertinent aspects of the medical history that they did not personally document. Conflict may arise between patient and physician perspectives.

However, experience thus far suggests positive results. In a study at Geisinger Health System, patients entered their medication data into the EHR, which was then reviewed by pharmacists before visits, resulting in significant time savings and increased patient and provider satisfaction. Although there will be continued challenges and the need to adjust workflows, we believe that physicians and support staff will become increasingly comfortable reviewing and verifying rather than asking and typing.

Conclusion

Today’s unhappy marriage between physicians and their EHRs has reached near-crisis proportions. Yet there is hope. Imagine a healthcare system in which physicians listen better and have more time to learn about their patients clinically and as individuals. Billing practices and quality reporting requirements eventually do need to change such that there is less emphasis on documentation and more on patients. But we must not sit idly and wait for these changes to occur. Ironically, the solution to technology-induced ennui in the doctor-patient encounter may be more, and better, technology.

Timothy Judson is an internal medicine physician. Robert Wachter is a professor of medicine, University of California, San Francisco. He is the author of The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Digital Age.

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