It’s been quite a journey, but EHRs have turned the corner in terms of proving their usefulness. Studies are showing that EHRs save patient lives and promote efficiency within healthcare organizations. If that’s the case, we should probably be asking ourselves what’s next. In other words, how can EHRs be enhanced to be even more useful? And just as importantly, how can hospitals get more value from their EHR investment?
One answer to those questions is imaging services; specifically, better connections between imaging and clinical EHR systems that greatly benefit providers, patients, and healthcare organizations.
Hospital EHRs contain vast amounts of information in digital format. Having that data is wonderful, but most organizations lack the tools they need to manage it. In a way, it’s like trying to search the web without a search engine.
Currently, many radiologists must leave their department systems to search for EHR-based patient data that might affect their imaging interpretations. Having a relevant subset of clinical data from the EHR embedded into their imaging cockpit in the appropriate places of the imaging workflow would save them hours of time each week, reduce errors, and help avoid unnecessary follow ups. It might even save lives.
For example, imagine a radiologist identifies free air in a patient’s stomach from an abdominal CT. The cause could be a life-threatening situation such as a perfusion or a normal side effect of a recent laparoscopy procedure. Having access to the patient’s surgical history would allow the radiologist to make an accurate diagnosis and select the correct follow up (which, in case of perfusion, could save the patient’s life).
Or imagine a patient arriving at the ED with chest pain. He’s sent for a chest CTA to rule out pulmonary embolism, aortic dissection and coronary disease. An accurate diagnosis would be more likely if the radiologist had access to relevant lab results and the ED physician note to better understand the patient background (e.g., the patient just returned from a long trip overseas).
It’s difficult to predict which cases would benefit the most from better integration. Common sense suggests complicated cases would benefit the most (i.e., abdomen, chest, spine and brain CT and MRI studies). However, even a routine CR of a foot can turn out to be a complicated case and require the radiologist to go and look for complementary clinical data that will help guide the diagnosis.
Also important is the type of patient being diagnosed. Those who’ve had few known health problems (i.e. one-time out patients) will have little data in the system and won’t benefit as much from better integration. The opposite is true for frequent visitors that have amassed a lengthy health record. Combing through those types of records for relevant information is enormously time consuming for radiologists. Smart filters that serve up the most germane items (history and physical, ED notes, pathology reports, surgical history, discharge notes, lab results, allergies and medications, etc.) from the most recent encounters would eliminate that problem almost completely.
As imaging executives search for ways to increase the impact of imaging on healthcare organizations, they should consider the effect of context-sensitive, automated integration between imaging systems and the EHR. That future is filled with reduced manual labor, minimized duplicate exams, improved study appropriateness, better diagnosis accuracy and better value per study.
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