For the past decade, AskMayoExpert has served as a central repository to capture, organize and deliver concise, Mayo-vetted medical knowledge for Mayo Clinic and Mayo Clinic Care Network providers at the point of care. Much has changed since its inception, with more providers looking to AskMayoExpert and its care process models as not only vital information on what type of care to deliver, but also as change agents for improved and consensual practice standards leading to better patient care.
AskMayoExpert is an online point-of-care tool that gives health care providers access to Mayo-vetted information, including disease management protocols, care guidelines, treatment recommendations and reference materials.
Recently, a study published in the Journal of Oncology Practice, Standardizing Febrile Neutropenia Management: Antimicrobial Stewardship in the Hematologic Malignancy Population validated AskMayoExpert as a quality improvement tool in clinical practice.
“AskMayoExpert has previously been shown to be an effective tool for rapid, point-of-care access to accurate clinical data. Our study, to our knowledge, is the first to demonstrate a clinical outcome related to AskMayoExpert,” says John (Jack) C. O’Horo, M.D., an internal medicine doctor and health care delivery researcher at Mayo Clinic, in Rochester, Minn.
Through the creation of a care process model on febrile neutropenia, Dr. O’Horo and his research team hoped to standardize the way doctors treat febrile neutropenia. They sought to improve the appropriate use of antimicrobials and diagnostic tests for patients with this condition. (Febrile neutropenia refers to a high fever coupled with low levels of neutrophils, a type of white blood cell important for fighting certain infections.)
Throughout a yearlong period, the care process model helped guide providers through evidence-based antimicrobial selection and diagnostic evaluation of patients with febrile neutropenia.
The end result? Improved adherence to best practices.
“At baseline, 71% of patients with febrile neutropenia had at least one critical deviation from best practice. During the project, the percentage decreased to 27.3%; 4 months after the project was completed, the percentage was 33.3%,” says Dr. O’Horo.
Building the Evidence Base and Care Process, Determining Best Practice
Initially, the team developed a care process model based on available information about febrile neutropenia diagnosis and treatment, along with expert infectious disease physician inputs.
This new care process model for Mayo Clinic, and other AskMayoExpert users, was reviewed monthly for clinical errors or adverse outcomes and refined and updated every other month on both the AskMayoExpert site as well as the Mayo Clinic intranet site for the Department of Hematology. Ongoing improvements to the care process model were based on input from Mayo Clinic’s hospital internal medicine, hematology, and oncology disease-oriented groups. Concurrently, key metrics were identified for monitoring of adherence to best practices.
“When we were trying to determine the best way to reduce antibiotic overuse in patients with febrile neutropenia, we thought the best thing would be to provide some guidance for how an infectious disease expert would approach a specific patient,” says Dr. O’Horo. “The care process model in AskMayoExpert provided the perfect platform for delivering this data in a step-by-step approach. The model allowed for a virtual consult, identifying the key decision points a specialist would address in the first 24 hours of care for this vulnerable population.
“This also allowed us to converge medical practice across the enterprise and tap into the expertise of the entire institution, which ultimately reduced antimicrobial overuse,” he says.
The ability to reach across all of Mayo Clinic and gain the input from many experts in a particular disease or condition is what makes AskMayoExpert an exceptional resource for clinicians.
Dr. O’Horo’s study illustrates illustrates both how to build a treatment algorithm and care process model, optimizing consensus-based, best-practice evaluation and treatment knowledge, as well as successful dissemination and implementation. It further highlights the successful implementation of this algorithm to modify clinician practices and to standardize care across a large, disperse organization.
This study was supported by the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery and the Center for Clinical and Translational Science.
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