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The emergence of the novel influenza H1N1 virus resulted in a multitude of email updates for providers in our healthcare system. The emails came from different providers and health care organizations and correspondingly contained different types of information. Because of H1N1’s novelty, this information changed on a near daily basis. One day an email may have specified both nasopharyngeal and oropharyngeal swabs were needed for collection, but the next day, a new email specified only a nasopharyngeal swab was needed. These kinds of emails which had specific information that is useful for clinical care were buried amongst other H1N1 related emails from the public health department, a local infectious disease expert, the medical director, etc. Also, even though these emails contained information useful at the point of care, email was not easily accessible in patient rooms. Therefore, during a situation of rapidly changing clinical protocols, email can be a poor informational technology tool. Below we describe how a simple EHR charting tool was rapidly adapted into an effective clinical decision support tool.
At our local organization, a more efficient approach of dispersing clinical protocols was tried in conjunction with the ongoing emails described above. The approach depended on three elements: 1) an electronic health record (EHR) available in each patient’s room, (our clinics use Epic; Epic Systems Corporation, Madison, Wi), 2) an EHR charting tool that is “shareable”, and 3) individuals who can abstract information from the daily H1N1 emails. Within our available EHR is a charting tool (SmartPhrase) that allows providers to create their own shorthand of commonly used phrases, e.g. typing “.bv” generated the text “bacterial vaginosis” in the patient’s chart. Furthermore, this shorthand (“.bv”) can be accessed and used by any other provider, an important feature for the application we are describing here.
Within the first week of the H1N1 outbreak, we generated a new SmartPhrase “.SWINEUPDATE”. Rather than a short phrase, typing “.SWINEUPDATE” would generate the entire H1N1 protocol (who to test, how to test, indications for treatment, etc) within the patient’s EHR chart. (see Figure 1) Once referred to, the SmartPhrase material could be deleted in its entirety from the patient’s chart, and the provider could continue with the visit. “.SWINEUPDATE” was kept current by our medical director who abstracted relevant information from the daily emails and meetings. As a result, ~70 urgent care providers had access to the latest H1N1 protocols within their patient rooms by simply typing
Benefits of using a shareable charting tool as a clinical informational tool:
About 3 months after “.SWINEUPDATE” was implemented, an informal survey was distributed by email. There was a general positive response from those providers who accessed the charting tool with ~70% answering “Yes” to the question “Did ‘.SWINEUPDATE’ save you any time?”. Surprisingly, many providers were not even aware of the charting tool adaptation with 30% answering “No” to “Are you aware of the existence of the EPIC SmartPhrase ‘.SWINEUPDATE’”? This unawareness likely reflects the fact that providers were primarily notified of the charting tool adaptation by email and no formal demonstration was provided. Presumably usage and satisfaction would increase with formal explanation of the rationale and a demonstration of the charting tool adaptation.
We describe a workaround method to provide clinical recommendations within a health care system where no formal EHR clinical decision support tools are available. Overall the feedback has been positive within our clinical setting. While our clinical setting uses the EPIC EHR, likely there are similar charting tools in other EHR's and that can make this process reproducible. This is one more tool to help decrease clinical protocol confusion during the next influenza outbreak.
Support was provided by the Health Innovation Program and the Community-Academic Partnerships core of the University of Wisconsin Institute for Clinical and Translational Research (UW ICTR), grant 1UL1RR025011 from the Clinical and Translational Science Award (CTSA) program of the National Center for Research Resources, National Institutes of Health. Additional funding for this project was provided by the UW School of Medicine and Public Health from The Wisconsin Partnership Program. In addition, the author would like to acknowledge John Frey, MD, Bruce Slater, MD, Steve Tyska, MD, and Sandy Wright for their thoughtful comments, advice and information.