EHR timestamps can track productivity
Medical clinics looking to identify efficiency and productivity shortcomings should look no further than their EHR system.
Researchers at the Oregon Health and Science University discovered timestamps within EHRs can provide valuable information regarding workflow inefficiencies. By observing workflow at four outpatient ophthalmology clinics and comparing that to EHR timestamps, the researchers found the data buried in medical records offer an accurate portrayal of workflow that can be used to create simulation models and analyze EHR use. (JAMIA study)
Patient data ownership will drive transformation
A trio of digital health researchers says healthcare is “poised for transformation,” but only if patients have broader access and control over their health data.
Specifically, the researchers say this can be accomplished by creating common data elements, providing patients with a “patient encounter data receipt” that is automatically pushed to their complete digital record and drawing up an explicit contract in which providers and vendors turn over control of health data to the patient. (JAMA Viewpoint)
Geisinger partners with pharma to create prediction model for diabetes patients
Pennsylvania-based Geisinger Health announced a partnership with Boehringer Ingelheim and Eli Lilly that will tap the health system’s EHR data to build a risk prediction model that can identify diabetes patients at risk for cardiovascular disease, kidney failure and heart failure. The predictive model could help physicians provide more targeted treatments for people with type 2 diabetes and improve long-term health outcomes. (Announcement)
Indiana University to build "data commons" for genetic information
Indiana University and the Regenstrief Institute have announced a partnership with an Indianapolis-based company called LifeOmic to build a “data commons,” a single repository to store genetic information for millions of patients that can be analyzed by researchers. The databank will allow the system to develop personalized treatment plans by clinicians with new information to support diagnosis and treatment. (Announcement)