Prospective Study to Reduce Clostridium Difficile Infection in Patients Receiving Autologous Stem Cell Transplantation

Background: Clostridium difficile infection (CDI) is a major complication facing patients undergoing autologous stem cell transplantation (ASCT) and can be associated with increased morbidity and length of stay (LOS). Various institutional and multicenter studies have reported incidence rates in this population ranging from less than 5% to more than 10% in this high-risk population. CDIs are not only problematic for individual patient care, but CDI also negatively impact hospital resource utilization by increasing post-transplant LOS. A prospective quality improvement study was initiated at the University of Virginia (UVA) to decrease CDI. Methods: To decrease CDI rate, a multidisciplinary team comprised of oncology and infectious diseases physicians, pharmacists, and nurses was formed. The group used quality improvement principles to identify and target areas of greatest significance. Retrospective chart review was done of 65 consecutive patient ASCT encounters from June 2016 to July 2017 to establish the baseline cohort. For each of these encounters, extensive patient demographics, clinical, and inpatient event data were collected. Analysis of the data identified 17% CDI rate (n=11) in the 30-day period following ASCT. The aim of study was to decrease the CDI rate by 33%. The team used qualitative and quantitative tools to understand factors contributing to CDI, including: process map and a priority matrix categorizing potential interventions based on impact and ease of implementation. A statistical process control chart (p-chart with 3 sigma limits) depicted rates of CDI in the baseline cohort and intervention groups. Results: The baseline CDI rate was 17%. Three Plan-Do-Study-Act (PDSA) cycles of interventions were implemented; post-intervention data were collected and analyzed. From August 2017 to June 2018, the first PDSA cycle consisted of eliminating ciprofloxacin prophylaxis between T+0 and count recovery (which was standard of care) due to hypothesis that the prophylactic antibiotic itself was leading to increases in CDIs. The first PDSA cycle resulted in an increased CDI rate of 19% (n=12) and worsening of sepsis events. Ciprofloxacin prophylaxis was reinstituted. A second PDSA cycle was executed between July 2018 and January 2020 incorporating ultraviolet (UV) light equipment into existing post-discharge cleaning practices, resulting in a decreased CDI rate of 9% (n=11). A third PDSA cycle was conducted from February 2020 through current (July 2021) and added a 2-step C. diff PCR and toxin assay into testing protocols, leading to a further CDI rate decrease to 7% (n=9). P-chart depicting CDI reduction is shown in Figure 1. A significant difference in CDI incidence was found comparing patients before and after implementation of UV light cleaning practices (p<0.01). Figure 2 is a XMR-chart showing a numerical decrease of hospital LOS from 14.6 to 13.8 days after the 3 PDSA cycles, although this did not reach statistical significance (p=0.055). Conclusions: This prospective study surpassed the goal to reduce CDI by 33% by using quality improvement methods to drive a clinically significant special cause variation reduction in the 30-day CDI incidence after ASCT and a trend towards decreased LOS at UVA. This study not only improved patient care, but likely represents increased patient quality of life and cost savings. Future PDSA cycles are scheduled and may include other cancer patients beyond those receiving ASCT. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Reducing Length of Stay for Patients with Acute Myeloid Leukemia Receiving Inpatient High-Dose Cytarabine Consolidation Chemotherapy

Background For patients receiving high dose cytarabine (HiDAC) at the University of Virginia Health System between 10/2019 and 10/2020, median length of stay (LOS) from time of clinic appointment to hospital discharge exceeded the expected standard treatment time (119.4 hours vs 112 hours). Despite the final dose of chemotherapy being scheduled for completion by 9:00 am on the planned day of discharge, only 50% of patients receiving HiDAC were successfully discharged by 12:00 pm (3 hours post-chemotherapy completion). Though there are no national standards for duration of inpatient stay for planned chemotherapy, LOS that extends beyond the standard treatment time results in increased cost, overutilization of hospital resources, delayed admissions for future patients, and patient dissatisfaction. Methods A multidisciplinary team of licensed providers, pharmacists, and nurses was formed. Due to inconsistency in admission times, the team focused on the percentage of patients discharged by 12:00 pm as a surrogate marker for LOS. The aim was to increase the percentage of patients discharged by 12:00 pm to 65%. Reviewing the baseline data revealed an unstable process with a 3-sigma XmR statistical process control chart. The team developed current and ideal process state maps, a Pareto chart, and a priority matrix to determine an action plan. The most common identified causes for delay in discharge included: lack of standardized discharge checklist, discharge order placed after 10:00 am, medications dispensed from the outpatient pharmacy after 11:00 am, licensed providers not prioritizing patients who were pending discharge, and medication reconciliation not completed prior to day of discharge. Results From 10/2020 to 5/2021, the first PDSA cycle focused on standardizing the discharge process to correct the instability in the process. A discharge checklist was created based on the ideal process map, which allowed providers to have a consistent process at discharge. A 3-sigma XmR chart demonstrated a newly stable process and an increase in percentage of patients discharged by 12:00 pm to 58% (14 of 24). The second PDSA cycle from 6/2021 to 8/2021 addressed the high impact/easy effort interventions identified in the priority matrix: providers completed medication reconciliation the day before discharge, prioritized seeing HiDAC discharge patients first during morning rounds, and ensured discharge orders were placed prior to completion of the last chemotherapy infusion. Following these interventions, the percentage of patients discharged by 12:00 pm increased to 66% (4 of 6). Conclusions Using quality improvement methodology, a multidisciplinary team developed an action plan for patients receiving HiDAC that has increased the percentage of patients discharged by 12:00 pm. This outcome may lead to decreased length of stay, reduced hospitalization costs, and increased bed availability for other hematology/oncology patients. Further PDSA cycles are planned and will focus on the pharmacy medication delivery service, and continuous evaluation of the process is ongoing. Figure 1 Figure 1. Disclosures El Chaer: Amgen: Honoraria, Research Funding.

Improving the quality of weekend medical handover on non-receiving medical hospital wards

IntroductionHandover is the system by which the responsibility for immediate and ongoing care is transferred between healthcare professionals and can be an area of risk. The Royal College of Physicians (RCP) has recommended improvement and standardisation of handover. Locally, national training surveys have reported poor feedback regarding handover at Glasgow Royal Infirmary.AimTo improve and standardise handover from weekday to weekend teams.MethodsThe Plan–Do–Study–Act (PDSA) quality improvement framework was used. Interventions were derived from a driver diagram after consultation with relevant stakeholders. Four PDSA cycles were completed over a 4-month period:PDSA cycle 1—Introduction of standardised paper form on three wards.PDSA cycle 2—Introduction of electronic handover system on three wards.PDSA cycle 3—Expansion of electronic handover to seven wards.PDSA cycle 4—Expansion of electronic handover to all non-receiving medical wards.The outcome of interest was the percentage of patients with full information handed over based on a six-point scale derived from the RCP. Data were collected weekly throughout the study period.Results18 data collection exercises were performed including 525 patients. During the initial phase there was an improvement in handover quality with 0/28 (0%) at baseline having all six points completed compared with 13/48 (27%) with standardised paper form and 21/42 (50%) with the electronic system (p<0.001). When the electronic handover form was expanded to all wards, the increased quality was maintained, however, to a lesser extent compared with the initial wards.ConclusionA standardised electronic handover system was successfully introduced to downstream medical wards over a short time period. This led to an in improvement in the quality of handover in the initial wards involved. When expanded to a greater number of wards there was still an improvement in quality but to a lesser degree.

1139. Reducing Collection of Tracheal Aspirate Bacterial Cultures: A Diagnostic Test Stewardship Intervention

Background Tracheal aspirate (TA) bacterial cultures are often collected in mechanically ventilated children to evaluate for ventilator-associated infections (VAI), including tracheitis and pneumonia. However, frequent bacterial colonization of tracheal tubes results in poor specificity of positive TA cultures for distinguishing bacterial infection from colonization, which contributes to antibiotic overuse for VAI. We performed a quality improvement project to reduce collection of TA cultures through implementation of a consensus guideline to standardize culture ordering, and measured its impact on antibiotic use in a tertiary PICU. Methods A multidisciplinary team including PICU, pulmonary, and ID clinicians developed the consensus guideline in November 2019-February 2020. The first Plan-Do-Study-Act (PDSA) cycle occurred in August 2020 and included provider education, providing a link to the guideline in the TA culture order, and signs and screensavers highlighting key guideline recommendations. The second PDSA cycle occurred in October-December 2020 and included weekly emails to on service PICU clinicians. Statistical process control charts were used to measure the number of TA cultures collected/100 ventilator days and broad-spectrum antibiotic DOT/100 ventilator days. The number of patients treated for VAI/100 ventilator days and guideline compliance were also measured. Results The baseline rate of TA culture collection was 4.58/100 ventilator days. A centerline shift to 3.33 cultures/100 ventilator days occurred in March 2020. Following PDSA 1 and 2 in October 2020, a second downward centerline shift to 2.22 cultures/100 ventilator days occurred (Figure 1). Broad-spectrum antibiotic days of therapy/100 ventilator days decreased in November 2019 coincident with the start of the project, but no further reductions occurred after PDSA 1 and 2 (Figure 2). The number of patients treated for VAI decreased from a baseline of 1.24/100 ventilator days to 0.66/100 ventilator days. Finally, the proportion of TA cultures ordered that were non-compliant with the guideline recommendations was unchanged throughout the study period (Table 1). Conclusion A consensus guideline reduced collection of TA cultures, with a modest reduction in the rate of antibiotic treatment for VAI. Disclosures All Authors: No reported disclosures

139. Improving Skin and Soft Tissue Infection Antibiotic Duration Concordance with National Guidelines in Pediatric Urgent Care Clinics

Background Skin and soft tissue infections (SSTIs) are the second most common diagnosis leading to pediatric antibiotic prescriptions in the outpatient setting after respiratory diagnoses. Children with SSTIs often receive &gt; 7 days of antibiotics, although current guidelines recommend 5-7 days for most diagnoses. At Children’s Mercy Hospital (CMH) urgent care clinics (UCC), only 58% patients received the recommended 5-7 days of antibiotics. We aimed to increase the percentage of patients receiving 5-7 days of oral antibiotics for SSTIs from 58% to 75% by December 31st, 2021. Methods We formed a multidisciplinary team in April 2020. A provider survey assessed factors influencing prescribing habits. We completed cause-and-effect analyses and developed a driver diagram (Figure 1). Interventions were chosen based on the potential for highest impact and lowest effort. Our first Plan-Do-Study-Act (PDSA) cycle provided an update on current guidelines for UCC providers. The second PDSA cycle updated prescription sentences in the electronic health record (EHR) and organized them from shortest to longest duration. The third PDSA cycle provided a project update via email to UCC providers. Our outcome measure is the percentage of patients receiving 5-7 days of antibiotics for SSTIs. Process measure is the number of updated prescriptions used. Balancing measure is the number of patients returning for SSTI within 14 days of their visit. Results are displayed using a run chart. Results After initiation of the project in April 2020, the percentage of patients receiving 5-7 days of antibiotics increased to 68% (Figure 2). This percentage increased to our goal of 75% after the 1st PDSA cycle (October-December 2020), 80% following the second PDSA cycle in February 2021, and 90% following the third PDSA cycle in April 2021. There was no change in balancing measure numbers. Run Chart Conclusion Prior to our project, only 58% of children seen in CMH UCCs for SSTIs received the recommended antibiotic duration. By addressing the primary drivers uncovered through QI methodology, we surpassed our goal of 75%. Additional PDSA cycles are planned along with expansion to other departments. This work will allow us to expand antibiotic stewardship efforts to other infectious diagnoses as well. Disclosures Brian R. Lee, PhD, MPH , Merck (Grant/Research Support)Pfizer (Grant/Research Support)

Implementation of a pediatric early warning score tool in a pediatric oncology Ward in Palestine

Background Pediatric Early Warning Scores (PEWS) are nurse-administered clinical assessment tools utilizing vital signs and patient signs and symptoms to screen for patients at risk for clinical deterioration.1–3 When utilizing a PEWS system, which consists of an escalation algorithm to alert physicians of high risk patients requiring a bedside evaluation and assessment, studies have demonstrated that PEWS systems can decrease pediatric intensive care (PICU) utilization, in-hospital cardiac arrests, and overall decreased mortality in high income settings. Yet, many hospital based settings in low and lower middle income countries (LMIC) lack systems in place for early identification of patients at risk for clinical deterioration. Methods A contextually adapted 16-h pediatric resuscitation program included training of a PEWS tool followed by implementation and integration of a PEWS system in a pediatric hematology/oncology ward in Beit Jala, Palestine. Four PDSA cycles were implemented post-implementation to improve uptake and scoring of PEWS which included PEWS tool integration into an existing electronic medical record (EMR), escalation algorithm and job aid implementation, data audits and ward feedback. Results Frequency of complete PEWS vital sign documentation reached a mean of 89.9%. The frequency and accuracy of PEWS scores steadily increased during the post-implementation period, consistently above 89% in both categories starting from data audit four and continuing thereafter. Accuracy of PEWS scoring was unable to be assessed during week 1 and 2 of data audits due to challenges with PEWS integration into the existing EMR (PDSA cycle 1) which were resolved by the 3rd week of data auditing (PDSA cycle 2). Conclusions Implementation of a PEWS scoring tool in an LMIC pediatric oncology inpatient unit is feasible and can improve frequency of vital sign collection and generate accurate PEWS scores. Contribution to the literature This study demonstrates how to effectively implement a PEWS scoring tool into an LMIC clinical setting. This study demonstrates how to utilize a robust feedback mechanism to ensure a quality program uptake. This study demonstrates an effective international partnership model that other institutions may utilize for implementation science.

Improving consistency and accuracy of neonatal amplitude-integrated electroencephalography

Objective: To improve the utilization of amplitude-integrated electroencephalography (aEEG) in a neonatal unit by improving aEEG documentation, aEEG knowledge and pattern recognition ability of neonatal staff. Methods: A quality improvement (QI) program comprising two plan-do-study-act (PDSA) cycles was conducted in a level 3 neonatal intensive care unit. The first cycle was focused on improving aEEG documentation with the primary outcome indicator being compliance with aEEG documentation. The second cycle was focused on aEEG interpretation in a healthcare professional education program with the outcome indicators being accuracy of seizure identification on aEEG and change in conventional EEGs (EEG) performed. Other outcome indicators included accuracy in identification of background pattern, sleep-wake cycles and artefacts. Process indicators included improvement in aEEG-related knowledge. Interventions: First PDSA cycle – lectures on aEEG interpretation, a bedside key and documentation form. Second PDSA cycle – online aEEG education pack, detailed aEEG guideline. Results: There was a significant improvement in aEEG documentation after the implementation of both PDSA cycles. 7 of the 46 patients (15.2%) had isolated electrographic seizures which would not have been identified in the pre-aEEG monitoring era. There was an increase in the number of patients with EEGs done, but a steady decrease in number of EEGs per patient. Conclusions: With the successful application of standardized QI methods, improvements in outcome indicators such as correct aEEG pattern recognition and improved coverage of at risk infants with EEGs were observed. Our QI measures were associated with improvement in aEEG pattern recognition.

TP9.1.5Optimizing Patient Outcomes and Improving Organization Efficiency through Enhanced Management of Low Back Ache and Sciatica

Aim This study was undertaken to tackle the rising incidence of Low Back Ache and Sciatica in a primary care government setup, which had contributed to a disabled and diminished workforce. The aim being improving patient outcomes by implementing changes in the current management protocol (measured against the standard NICE guidelines by an initial clinical audit) Method Two Plan-Do-Study-Act (PDSA) cycles were implemented post an initial clinical audit among 59 patients of the institution. Data was collected using self-made questionnaires and then analyzed. Re-audits were done to measure the outcome against a set standard. Results 20-30% (n = 12-18) of patients were aware of their risk category, understood various treatment modalities and use of orthotics in the initial clinical audit. 56% (n = 33), 73% (n = 43), 88% (n = 51) of the patients were absent from work or had diminished work output, were offered imaging and were put on medication respectively. 10% of the patients were offered psychological counselling. Post implementation of changes from the first PDSA cycle, the set target of 90% was achieved in most of the categories. Further, 24% (n = 14) of patients reported that they were still apprehensive about their condition. A second PDSA cycle was undertaken and post implementation of changes, the set standard of 10% or less patients being apprehensive was noted. Conclusions Increased awareness among patients through means of regular educational sessions, psychological counselling, updated management protocols have led to healthier patients, less absence from duty and improved work output thereby increasing the organizational efficiency as a whole.

EP.TU.854Happy Patients and Updated Open Wound Management Protocols

Introduction Open injuries have a potential for serious bacterial wound infections and may lead to long term disabilities, chronic wound or bone infection, and even death. This QI study was undertaken to ring in changes to the current management protocol and align them as per WHO guidelines. Method Implementing changes through a Plan-Do-Study-Act (PDSA) cycle post an initial clinical audit among 38 patients of the organization. Re-audits were done to measure the outcome against the standard and establish a new protocol. Results Initial audit showed only a dismal 37% (n = 14) of patients being managed as per WHO protocol. Patient satisfaction percentage (as measured by a questionnaire) was also low with only 54% of patients satisfied with the treatment. Significant variations were noted post implementation of changes after the first PDSA cycle where &gt;90% (n = 35) of patients reported that they noticed better wound healing, transition to optimal performance and were satisfied with treatment outcomes. Conclusions Timely wound dressings, appropriate antibiotic prophylaxis and increased patient’s awareness on wound hygiene through means of regular educational sessions and updated management protocols have led to healthier patients, lesser long term disabilities and happy patients.

Reducing length of stay for patients with acute myeloid leukemia receiving inpatient high-dose cytarabine consolidation chemotherapy.

257 Background: For patients receiving high dose cytarabine (HiDAC) at University of Virginia (UVA) Health between 10/2019 and 10/2020, median length of stay (LOS) from time of clinic appointment to hospital discharge was 119.35 hours. Standard treatment time should be 112 hours from premedication to end of chemotherapy. There are no national standards for duration of inpatient stay for planned chemotherapy, but only 50% of these patients were discharged after noon (over 3 hours post-chemotherapy completion). LOS that extends beyond the standard treatment time results in increased cost, overutilization of hospital resources, delayed admissions for future patients, and patient dissatisfaction. Methods: A multidisciplinary team comprised of licensed providers, pharmacists, and nurses was formed. The team focused on percentage of patients discharged by noon as a surrogate marker for LOS due to inconsistency of admission times; the aim was to increase patients discharged by noon to 65%. Reviewing the baseline data revealed an unstable process with a 3-sigma X-bar statistical process control chart. The team developed current and ideal process state maps, a Pareto chart, and a priority matrix to determine an action plan. The most common identified causes for delay in discharge included: lack of standardized discharge checklist, discharge order placed after 10 am, medications dispensed from the outpatient pharmacy after 11 am, licensed providers not prioritizing discharge patients, and medication reconciliation not completed prior to day of discharge. Results: From 10/2020 to 5/2021, the first PDSA cycle focused on standardizing the discharge process to correct the instability in the process. A discharge checklist was created based on the ideal process map, which allowed the providers to have a consistent process at discharge. 3-sigma Xbar chart demonstrated a now stable process and an increase of patients discharged by noon to 58%. During the second PDSA cycle starting in 6/2021, providers completed medication reconciliation the day before discharge, prioritized HiDAC discharges first during rounds, and ensured discharge orders were placed by completion of the last chemotherapy bag. Data collection is ongoing, and will be analyzed by August 2021. Future tests of change are planned to focus on the pharmacy medication delivery service. Hospital LOS has also decreased after the first PDSA cycle. Conclusions: Using quality improvement methodology, a multidisciplinary team developed an action plan for patients receiving HiDAC which to date has increased the percentage of patients discharging by noon and decreased length of stay. This outcome may lead to reduce hospitalization costs and increase bed availability for other oncology patients. Further PDSA cycles are scheduled and continuous evaluation of the process is ongoing.