ABSTRACT
Background: With the increase of multi-drug resistant organisms (MDRO) in the United States and abroad, good antibiotic stewardship has become an integral aspect of delivering appropriate care to patients. As utilization of retail clinics and urgent care centers increases in the U.S., it becomes especially important to evaluate the antibiotic prescribing practices in those settings. Existing research in this area has noted that urgent cares and retail clinics prescribe antibiotics for 39.0% and 36.4% of their visits respectively, compared to 13.8% and 7.1% for Emergency Department (ED) and medical office visits respectively [1]. At the pediatric urgent cares in our institution, we identified prolonged durations for antibiotic prescriptions for urinary tract infections (UTIs). Our aim was to reduce the proportion of cephalexin prescriptions for UTI with a prolonged duration from 81% to 20% within 6 months. Methodology: Our team in conjunction with our infectious disease colleagues implemented guidelines for appropriate antibiotic courses. We developed an algorithm that automatically abstracts data from the electronic health record (EHR) and evaluates the appropriateness ofantibiotic prescription in relation to diagnosis, taking into account both duration and dose. Plan-Do-Study-Act(PDSA) cycle #1 interventions were the development and dissemination of appropriate antibiotic dosingschedules for presumed UTI to our team and creating appropriate order-sets for antibiotic prescribing basedon diagnosis and age. PDSA cycle #2 interventions were continued provider education, dissemination ofguidelines to our moonlighting staff, and further improvement of order-sets. Our primary measure was thepercent of antibiotic prescriptions for UTI that were adherent with the guidelines set forth by the team.Discussion: From October to January 2019, 81% of antibiotic prescriptions for UTI had either a prolongedduration or a dose that was inconsistent with our internal guidelines. After PDSA#1, there was a notablereduction in the percentage of prescriptions that did not adhere to the recommended guidelines to 34%. AfterPDSA#2 we were able to reduce the percentage to 0% however after the COVID-19 stay-at-home order in ourstate was enacted we noted a sudden increase in our nonadherence to 62% which was well outside our goal of<20% (Figure 1). Conclusion: Our fully automated algorithm allowed us to quickly identify non-adherence toour prescribing guidelines, automatically produce tailored education to individual providers and reportswithout the need for manual chart review. Using QI methodology, we demonstrated that education and EHRorder-set implementation can successfully increase adherence to our organization's prescribing guidelines,leading to improved antibiotic stewardship. Unfortunately, the COVID-19 pandemic likely led providers tofocus on other areas of care leading to a sudden increase in nonadherence to guidelines. Therefore, we arecontinuing our efforts to develop additional decision to support to guide providers to the recommendedantibiotic duration.
ABSTRACT
Background: The unprecedented impact of SARS-CoV-2/COVID-19 worldwide pandemic on healthcare hasbeen profound. At our large quaternary care pediatric healthcare system, in response to change how wedeliver care, a telemedicine strategy was rapidly developed with a priority to address the needs of patientsrequiring specialty time sensitive ambulatory care. One obvious opportunity was to rapidly expandtelemedicine capabilities to address the impact quarantines and stay at home orders would have on thedelivery of care to children with chronic conditions. We had some telemedicine capabilities in certainpopulations, however when our community shut down we responded with an immediate plan to expandtelemedicine services in a large multi-specialty practice. During the first week of the stay at home order, ourambulatory volumes drop by 69% reinforcing concerns regarding delays care (Fig. 1). Methods: We establisheda leadership model, task forces, and communication plan. We rapidly adapted to ongoing changes andaddressed specific needs including clinic workflow, patient populations, patient capabilities to utilize telehealth, education of clinical teams, and daily visible tracking tools. We measured daily telemedicinevolumes by practice, total visits, and proportion of telemedicine visits. Results: The 69% decrease inambulatory volume was countered with a 42,300% increase in telemedicine visits. Prior to COVID-19, weaveraged 4 telemedicine visits weekly and currently complete over 2,000. Through telemedicine, we aremaintaining a clinic volume of 57% of expected with 68% of all those visits being provided throughtelemedicine (Figure 2). All specialty services provide telemedicine. Certain specialty clinics adapted totelemedicine easier than others;allergy/asthma (98%;n = 581), pulmonary (97%;n = 390), neurology (96%;n =1,004), dermatology (95%;1,175), and otolaryngology (91%;n = 1,314) clinics experienced the greatest degreesof success over the past month while ophthalmology (55%;n = 531), cardiology (35%;n = 576) and orthopedics(14%;n = 1,713) faced challenges. Additionally, 30% of all completed telemedicine visits were for new referralvisits. Conclusion: We rapidly expanded telemedicine to provide time sensitive care in a large ambulatoryspecialty practice. Certain specialties were more amenable to telehealth for various reasons--vital signsavailable from home monitoring, ability to assess neurologic function in natural settings, etc. We realized thatevery specialty could do some aspect of telemedicine yet for others it was more challenging due to the needfor ancillary tests (Echocardiogram, x-rays, ophthalmology adjuncts, etc.) or lack of a good substitute forphysical exam findings (murmurs, abdominal exams, etc.). We successfully completed new referral visits (aprevious concern in specialty practices). Future steps to sustain our telemedicine practice are to continue torefinine best telemedicine practices, identifying appropriate populations and visit types, track financial impact,and measure patient outcomes.