Large Healthcare System Research Articles

253. Clinical Presentations of Hospitalized Adult Patients Infected with SARS-CoV-2 during the Omicron Variant Surge in South Florida

Abstract Background Patients infected with COVID-19 Omicron variant, may be hospitalized for reasons other than COVID-19 pneumonia. We describe the clinical presentations of hospitalized adult patients with COVID-19 Omicron variant in a large healthcare system in South Florida. Methods Laboratory-confirmed COVID-19 adult patients hospitalized during January 1-14, 2022 were retrospectively reviewed. Clinical presentations were divided into one of three admission groups: COVID-19 pneumonia or respiratory infection (Group 1), severe extrapulmonary manifestations of COVID-19 (Group 2), and completely incidental diagnosis of COVID-19 (Group 3). Risks of in-hospital mortality and intensive care admission were estimated using logistic regression models. Results Among 500 consecutively hospitalized COVID-19 Omicron patients, the median age was 69 (IQR, 53-80) years, and 271 (54.2%) were women. The most common comorbidities were hypertension (326; 65.5%), diabetes (160; 32%), and chronic kidney disease (120; 24%). 260 (52%) patients were fully vaccinated (defined as a patient who received 2-dose vaccines), and 32 (6.4%) were previously infected with COVID-19. 257(51.4%) patients were classified as Group 1, 82 (16.4%) in Group 2, and 161 (32.2%) in Group 3 (Figure 1). Compared to Group 3, patients in Group 1 and Group 2 had a higher risk for ICU admission, with odds ratios (ORs) of 7.45 (95% CI, 2.62-21.23; p< 0.001) and 4.84 (95% CI, 1.44-16.23; p=0.011), and for in-hospital mortality, with ORs of 27.76 (95% CI, 3.78-204.3; p=0.001) and 12.63 (95% CI, 1.49-106.78; p=0.020), respectively (Figure 2). In multivariable-adjusted models, patients in Group 1 remained at higher risk for ICU admission and in-hospital mortality compared to Group 3, while patients in Group 2 remained at a higher risk for ICU admission, but with no difference in in-hospital mortality compared to Group 3 (Figure 2). Figure 1.Clinical characteristics of consecutively hospitalized patients stratified by clinical presentations at admission.Figure 2.Crude (Upper panel) and multivariable-adjusted (Lower panel) odds ratios for ICU admission and in-hospital mortality from logistic regression models. Group 3 represents patients with a completely incidental diagnosis of COVID-19. The variables included in the final multivariable models were age, gender, history of hypertension, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, coronary artery disease, malignancy, transplantation, HIV, vaccination status, and previous SARS-CoV-2 infection. Conclusion This case series illustrates the clinical presentations of hospitalized adult patients infected with the COVID-19 Omicron variant. Significant differences in in-hospital mortality and ICU admission exist when comparing patients admitted for a COVID-19 related respiratory infection to those admitted with a completely incidental COVID-19 diagnosis. Disclosures All Authors: No reported disclosures.

1121. Does Anti-Vaccine Equal Anti-Antibody? Differing Rates of Veteran Acceptance of Monoclonal Antibody Therapies for COVID-19 By Prior Vaccination Status

Abstract Background We assessed correlation between prior acceptance of COVID-19 vaccination and acceptance of monoclonal antibody (MAb) treatment for mild-to-moderate COVID-19. Methods Adult outpatients evaluated for treatment with MAb between August 31st, 2021 and April 23, 2022 in a large tertiary care VA healthcare system were included. MAb therapies administered over the period included casirivimab-imdevimab, sotrovimab, and bebtelovimab. All patients were screened by a small central clinician team with experience discussing COVID therapies under Emergency Use Authorization (EUA). Baseline characteristics, rationale for not offering MAb, and rates of vaccination and acceptance of therapy were recorded. In addition, rates of acceptance for the initial 4 months were compared to rates during the second 4 months of the program, using Chi-square or Fisher’s exact test. Results 203 patients (mean age 68, 91% male) with early COVID-19 were screened for MAb. 68% were vaccinated. 158 (78%) of those screened were offered MAb. The most common reason MAb was not offered was duration of illness longer than specified by EUA (65%). 112 (71%) patients offered MAb accepted, and 94 (84%) received MAb. Of 106 vaccinated patients offered MAb, 81 (76%) accepted. In contrast, of 52 unvaccinated patients offered MAb, only 31 (60%) accepted (Chi-square p = 0.046). However, when analyzed over time, unvaccinated patients were significantly more likely to accept MAb during the second 4 months of the program (7/7 patients, 100%) than during the first 4 months of the program (24/45 patients, 53%, Fisher’s exact p = 0.033). This disparity was not seen in vaccinated patients, who accepted MAb at a rate of 73% during the first half of the program, and 88% during the second half (Chi-square p = 0.19). Conclusion Vaccinated patients were significantly more likely to accept MAb therapy for COVID-19 than unvaccinated patients, suggesting that willingness to accept COVID-19 vaccination predicts willingness to accept other COVID-19 therapeutics. However, disparity in acceptance rates in our population is significantly attenuating over time, suggesting a “late-adopter,” phenomenon that has implications for continued efforts to encourage therapeutics and vaccines for COVID-19. Disclosures All Authors: No reported disclosures.

2083. HIV Testing Rates in NC Emergency Departments Before and During Covid Mitigation

Abstract Background During the early stages of the COVID-19 pandemic, non-emergent services were limited or suspended in multiple ways. Restrictions in primary care may have limited STI testing, such as HIV, where timely access to testing and care is critical to mitigation efforts. Conversely, Emergency Departments (ED) operated with fewer restrictions and more in-person options. Even though patient census numbers decreased in some areas from those seen pre-covid lockdown, EDs and hospitals often became overwhelmed with patients seeking care for both severe acute illness but just importantly services that might normally have been received in outpatient settings. Methods Observational study of HIV screening year-over-year in four EDs that are part of a large healthcare system located in the Southeast. Screenings of individuals 18 and over seen in the EDs were normalized per 1000 patients. Rates were also compared to two primary care clinics, located in the same metropolitan area, serving mainly Medicaid and uninsured patients. Results From March 2019 through February 2020 there were 33.47 tests per 1000 patients at two community clinics and 7.79 tests per 1000 patient at four EDs located in the same region during that span. From March 2020 to February 2021, screening numbers in the primary care clinics dropped to an average of 22.7/1000; however, screenings in the ED remained stable and slightly increased to 10.7/1000. From March 2021 to February 2022, screenings in the primary care clinics returned to an average 36.9/1000 with screenings in the ED still above pre-covid levels at 9.48/1000. These trends in the ED screening remained consistent across gender, race, and ethnicity. Patient census at four ED sites located in the southwestern region of North Carolina dropped significantly during the first year of physical distancing covid-19 mitigation measures when compared to the two years prior. These census numbers increased during the second year of covid-19 but failed to return to previous levels. During the first year of physical distancing covid-19 mitigation measures HIV testing rates in the emergency department remained constant, and even increased in more urban areas, despite the significant decrease in overall patient census. Conclusion With the observation that HIV screening decreased in primary care settings during the beginning of the covid-19 pandemic, there exists the possibility that new HIV infections may yet remain undiagnosed. That HIV testing remained constant in the ED, however, reinforces the importance of having embedded procedures in place for screening and linking both newly positive and at-risk patients into care to help mitigate the HIV epidemic. Disclosures All Authors: No reported disclosures.

Perceptions About Cannabis Following Legalization Among Pregnant Individuals With Prenatal Cannabis Use in California

As rates of prenatal cannabis use increase and cannabis legalization spreads across the US, studies are needed to understand the potential impacts of legalization from the perspectives of pregnant individuals who use cannabis. To characterize pregnant individuals' perspectives on legalization of cannabis for adult use in California (effective in 2018) in relation to prenatal cannabis use behaviors and beliefs. This qualitative study was conducted in Kaiser Permanente Northern California, a large health care system with universal screening for self-reported cannabis use at entrance to prenatal care. Eighteen semistructured focus groups were conducted from November 17 to December 17, 2021, using a secure video conferencing platform with Black and White pregnant participants who self-reported cannabis use during early pregnancy. Data were analyzed from March to June 2022. Video-recorded interviews were transcribed and analyzed using thematic analysis to identify major themes and subthemes. Among 53 participants (mean [SD] age, 30.3 [5.2] years), 23 (43%) identified as non-Hispanic Black and 30 (57%) identified as non-Hispanic White; 16 participants (30%) reported continued cannabis use at the time of recruitment. Major themes regarding the perceived impact of legalization included easier access (via retailers and delivery), greater acceptance (including reduced stigma and more discussions about prenatal cannabis use with health care practitioners), and trust in cannabis retailers (including safety and effectiveness of diverse products sold and perceptions of cannabis retailer employees as knowledgeable, nonjudgmental, and caring). Responses were mixed about whether retailer marketing and advertising were associated with prenatal cannabis use and whether legalization resulted in reduced concerns about Child Protective Services involvement. The findings of this qualitative study suggest pregnant individuals perceive cannabis legalization as having reduced barriers to prenatal cannabis use and that legalization has created challenges and opportunities for supporting the health of pregnant individuals. The results of this qualitative study highlight key areas that can be further explored in future educational materials, public health campaigns, and policy adaptations to address increasing rates of prenatal cannabis use.

Nursing process, derived from the clinical care classification system components, as an earlier indicator of nursing care during a pandemic

BackgroundDuring COVID pandemic response, an early signal was desired beyond typical financial classifications or order sets. The foundational work of Virginia K Saba informed the essential, symbiotic relationship of nursing practice and resource utilization by means of the Clinical Care Classification System [CCC]. Scholars have confirmed the use of the CCC as the structure for data modeling, focusing on the concept of nursing cost [1]. Therefore, the purpose of this retrospective, descriptive study was to determine if analysis of CCC Care Component codes could provide a high granularity signal of early shifts in patient demographics and in nursing care interventions and to, then, determine if nursing care intervention shifts indicated changes in resource utilization. MethodsFor a large multi-facility healthcare system in the USA, patients cared for in an acute care setting/hospital-based care unit were the population of interest. Through prior and ongoing efforts of ensuring Evidenced-Based Clinical Documentation [EBCD], a data model was utilized to determine changes in the patient’s nursing diagnoses, nursing interventions, during care episodes, for patients with acute symptoms or diagnosed/confirmed COVID. ResultsThe structure of CCC revealed 22 billion individual instances of the CCC Care Component/Concept codes for the data sets for 2017 and during COVID, a considerably large data set suitable for pre- and post- event analyses. The component codes were included in a string data set for concept/diagnosis/intervention. DiscussionBy our analysis, these CCC Information Model elements determined a clear ability to detect increasing demands of nursing and resources, prior to other data models, including supply chain data, provider documented diagnostic codes, or laboratory test codes. Therefore, we conclude CCC System structure and Nursing Intervention codes allow for earlier detection of pandemic care nursing resource demands, despite the perceived challenges of “timeliness of documentation” attributed to more constrained timelines of data models of nursing care.

Prevalence and Penetrance of Rare Pathogenic Variants in Neurodevelopmental Psychiatric Genes in a Health Care System Population.

Autism, schizophrenia, and other clinically distinct neurodevelopmental psychiatric disorders (NPDs) have shared genetic etiologies, including single-gene and multigenic copy number variants (CNVs). Because rare variants are primarily investigated in clinical cohorts, population-based estimates of their prevalence and penetrance are lacking. The authors determined the prevalence, penetrance, and NPD risk of pathogenic single-gene variants in a large health care system population. The authors analyzed linked genomic and electronic health record (EHR) data in a subset of 90,595 participants from Geisinger's MyCode Community Health Initiative, known as the DiscovEHR cohort. Loss-of-function pathogenic variants in 94 high-confidence NPD genes were identified through exome sequencing, and NPD penetrance was calculated using preselected EHR diagnosis codes. NPD risk was estimated using a case-control comparison of DiscovEHR participants with and without NPD diagnoses. Results from single-gene variant analyses were also compared with those from 31 previously reported pathogenic NPD CNVs. Pathogenic variants were identified in 0.34% of the DiscovEHR cohort and demonstrated a 34.3% penetrance for NPDs. Similar to CNVs, sequence variants collectively conferred a substantial risk for several NPD diagnoses, including autism, schizophrenia, and bipolar disorder. Significant NPD risk remained after participants with intellectual disability were excluded from the analysis, confirming the association with major psychiatric disorders in individuals without severe cognitive deficits. Collectively, rare single-gene variants and CNVs were found in >1% of individuals in a large health care system population and play an important contributory role in mental health disorders. Diagnostic genetic testing for pathogenic variants among symptomatic individuals with NPDs could improve clinical outcomes through early intervention and anticipatory therapeutic support.

Evaluation of a Multifaceted Protocol in Reducing Unnecessary Telemetry Monitoring across a Large Healthcare System.

Telemetry is frequently overused in hospitals. The goal of this study was to evaluate a telemetry protocol aimed at decreasing inappropriate telemetry utilization across four different hospitals within a large healthcare system by modifying the electronic telemetry order to incorporate the 2017 American Heart Association practice guidelines on the appropriate use of telemetry and using an electronic nursing screening task form to safely discontinue telemetry. We performed a retrospective analysis of telemetry utilization before and after we implemented a protocol across four hospitals within a large healthcare system. We compared the average number of days of telemetry monitoring and hospital length of stay during the preintervention period with the 6-month postintervention period. There were a total of 23,774 encounters evaluated. There was a statistically and clinically significant 24% decrease in telemetry duration between pre- and postintervention time periods (P < 0.0001). The mean (standard error) telemetry duration was 4.11 (0.17) and 2.36 (0.13) days in pre- and postintervention periods, respectively. The results of our study demonstrate a statistically significant decrease in overall duration of telemetry monitoring by nearly 1.75 days across each of the four hospitals with the implementation of a multifaceted telemetry protocol that included hardwiring the American Heart Association practice guidelines into the electronic order and using a nursing-driven discontinuation protocol.

Advocating, implementing, and supporting the journey to full-practice authority in a large healthcare system.

Madura, Brenda MS, APRN, CNM-BC; Zaletel, Cynthia L. MSN, APRN-FPA, CNS, FNP-BC, CCRN, CCNS, TNS; Lancaster, Rachelle J. PhD, RN Author Information

Improving knowledge of substance use disorder treatment across a large healthcare system.

Improving knowledge of substance use disorder treatment across a large healthcare system.

S132 Disparity of Care Is Not Observed Across Racial and Ethnic Groups During Hospitalization for Inflammatory Bowel Disease

Background: Although Inflammatory Bowel Disease (IBD) is more common in non-Hispanic White populations, rates are increasing among non-Whites. Despite some possible differences in disease phenotypes between racial groups, disease management guidelines are identical for different groups. However, multiple studies have demonstrated that social determinants of health (SDOH) play a critical role in disease management and outcomes for patients with IBD, as patients from minority populations often have delayed diagnosis, increased surgeries, and post-surgical complications. Several factors likely contribute to these healthcare disparities, with financial compensation and access to healthcare among them. Hospital admission ideally provides a setting that removes these barriers, and therefore should not be associated with healthcare disparities, though this has not been previously studied. We sought to identify if SDOH guide inpatient management of patients with IBD. Methods: We conducted a retrospective cohort study of adult patients with IBD-related inpatient admissions to any of Northwell Health’s 21 hospitals between 2010-2018. Patients were identified by a hospital admission primary diagnosis of ulcerative colitis (UC) or Crohns disease (CD), or a secondary diagnosis of UC or CD with a primary diagnosis of diarrhea, abdominal pain, or gastrointestinal bleeding. We analyzed data on patient demographics, medical history, and inpatient management features, including the use of imaging, medications, and procedures. Biological medication was defined as the use of infliximab, adalimumab, certolizumab. Race/ethnicity was characterized as Hispanic, Asian, Black, White, other, and unknown. Insurance status was characterized as private, Medicare, or Medicaid. Self-pay patients were excluded from analysis. Variables were tested using logistic regression for binary outcomes. To control the overall Type 1 error rate for the hypothesis that there were racial disparities in inpatient management of IBD, the Holm-Bonferroni method was used to adjust the P-value thresholds for statistical significance in each of the multiple tests performed to evaluate the hypothesis. Results: In total, 1,732 patients were identified and included in the analysis. Overall, 57% (n = 985) were White, 9% Hispanic, 5% Asian, 13% Black, 6% other, 9% unknown. 55% of patients were female, 45% had Crohn’s Disease, 14% were on steroids prior to admission. 47% of patients had private insurance, with the remaining having either Medicare or Medicaid. When assessing hospital interventions and outcomes based on racial/ethnic group, there was no difference in length of stay, use of medications (corticosteroids, aminosalicylic acid formulations, opioids, biological) during hospital admission and on discharge, stool testing performed as inpatient, imaging (CT, MRI) or endoscopies performed. Conclusion(s): SDOH play a critical role in the disease course and outcomes for patients with IBD. In this large retrospective study, we found that among patients hospitalized for IBD exacerbations there was no disparity of care across racial/ethnic groups. Our findings suggest that factors such as insurance status and access to healthcare are likely the main contributors to the healthcare disparities seen in the outpatient setting. Our results reflect the experience in a large urban health care system, and further studies are needed to replicate the data in other settings.

28 Factors impacting genomic testing rates among epithelial ovarian cancer patients across a large community-based healthcare system

28 Factors impacting genomic testing rates among epithelial ovarian cancer patients across a large community-based healthcare system

Severe COVID-19 outcomes in pediatrics: an observational cohort analysis comparing Alpha, Delta, and Omicron variants

COVID-19 can rarely lead to severe illness in pediatric patients. The aim of this study was to determine if severe outcomes in pediatric COVID-19 have changed over the course of the pandemic. This was a multicenter, observational cohort analysis from a large regional healthcare system in metro Detroit using electronic health record data to evaluate emergency visits, hospitalization, and severe COVID-19 disease in pediatric patients. Consecutive pediatric patients presenting to the emergency department with a primary diagnosis of COVID-19 were included. Outcomes data was gathered from three distinct time intervals that coincided with Alpha, Delta, and Omicron variant predominance (Time interval 1 (T1) 1/1/2021-6/30/2021: Alpha, T2 7/1/2021-12/31/2021: Delta, T3 1/1/2022-6/16/2022): Omicron. The primary outcome was severe disease inclusive of composite intensive care unit admission, mechanical ventilation, multisystem inflammatory syndrome in children (MIS-C), myocarditis, or death. Secondary outcomes included severe outcomes considering viral coinfection and vaccination status. Between 1/1/2021 and 6/16/2022, there were 4517 emergency COVID-19 visits, of which 12.5% (566) of children were hospitalized. 24.4% (138), 31.6% (179), and 44.0% (249) of admissions occurred during T1, T2 and T3 respectively. Most patients were male (55.1%) and 59.9% identified as Caucasian. The median age was 5.0 (interquartile range 1.0, 13.0) with infants comprising 22.8% (129), toddlers 25.1% (142), children 23.0% (130), and teenagers 29.2% (165). Over the course of the pandemic, the proportion of infants in hospitalization increased from 16.7% in T1 to 19.6% in T2 to 28.5% in T3 (p<0.01) while the proportion of teenagers in hospitalization decreased from 39.1% in T1 to 31.3% in T2 to 22.1% in T3 (p<0.001). Oxygen therapy was required in a minority (29.9%) of cases with supplemental oxygen utilized the least in T3 (16.5%) and most in T2 (30.2%). Composite severe disease decreased throughout the pandemic occurring in 36.2% in T1, 27.4% in T2, and 18.9% in T3. A multivariable logistic regression analysis revealed the odds of composite severe disease was significantly lower in T3 compared to T1 (adjusted odds ratio [aOR] 0.35, 95% Confidence Interval 0.21-0.60, p<0.001). Fully vaccinated or fully vaccinated and boosted admission rates remained low throughout all periods with 4.4% in T1, 4.5% in T2 and 8.4% in T3. Viral coinfection was most common during T2 (16.8%) followed by T3 (12.5%) and least common in T1 (5.1%) (p=0.006). Coinfection occurred more commonly in younger children with a median age of 1.2 (0.0, 4.5) compared to those with mono-infection with a median age of 6 (1.0, 14.0) (p<0.001). Severe outcomes occurred in 45.6% of coinfection cases compared to 22.1% without coinfection (p<0.001). While Omicron cases had the highest admission frequency, severe illness was lower than Delta and Alpha variants. Coinfection with respiratory viruses increased the risk of severe outcomes and impacted infants more than older children. None.

Impact of vaccination on postacute sequelae of SARS CoV-2 infection in patients with rheumatic diseases

ObjectiveVaccination decreases the risk of severe COVID-19 but its impact on postacute sequelae of COVID-19 (PASC) is unclear among patients with systemic autoimmune rheumatic diseases (SARDs) who may have blunted...

Implementation of an Adaptable COVID-19 Utilization and Resource Visualization Engine (CURVE) to Depict In-Hospital Resource Forecasts Over Time

We developed an interactive web-based, decision support application that can adapt to the rapid pace of change in region-specific pandemic related variables and knowledge, thereby providing timely, accurate insights to inform a large healthcare system’s proactive response to COVID-19 hospital resource planning. We designed the COVID-19 Utilization and Resource Visualization Engine (CURVE) app to be adaptable to real-time changes as the pandemic evolved, enabling decisions to be supported by contemporary local data and accurate predictive models. To demonstrate this flexibility, we sequentially implemented a Susceptible-Infected-Removed (SIR) model that incorporates social-distancing and imperfect detection (SIR-D2), an extended-state-space Bayesian SIR model (eSIR), and a time-series model (ARIMA). CURVE improves upon other pandemic forecasting solutions by providing adaptable decision support that generates locally calibrated forecasts aligned to health system specific data to guide COVID-19 pandemic planning. The app additionally enables systematic monitoring of forecast model performance and realignment that keeps pace with the pandemic’s volatile spread and behavior. CURVE provides a flexible pandemic decision support framework that places the most accurate, locally relevant information in front of decision makers to enable health systems to be proactive and prepared.

Cognitive screening among older adults with diabetes across diverse clinic settings

AimsDiabetes increases risk of cognitive dysfunction and dementia, which can make it harder to manage diabetes. We aimed to examine cognitive screening for older adults with diabetes in 1) endocrine (Endo), 2) geriatric (Geri) and 3) multidisciplinary endocrine-geriatric (Geri-Endo), to study differences between these settings and to elucidate risk factors of cognitive dysfunction. MethodsWe performed cognitive screening for subsets of patients ≥ age 65 with diabetes in one large healthcare system. We compared results and differences from the three clinic types and used adjusted multivariate logistic regression models to predict risk of cognitive dysfunction. ResultsAmong 198 patients screened, those in Geri-Endo (N = 86) and Geri (N = 32) were more likely to have lower Mini-Cog scores, higher prevalence of hypertension and cardiovascular (CV) events. Endo and Geri-Endo patients had longer durations of diabetes, higher incidence of hypoglycemia, and were more likely to use insulin. Age > 75 years (p = 0.0105), previous CV events (p = 0.0006) and body mass index < 30 (p = 0.0115) were significantly associated with lower Mini-Cog scores. ConclusionsOur study shows that cognitive screening can help identify at risk older adults with diabetes. Thus, yearly screening should be part of routine diabetes care.

Development and Implementation of Integrated Radiologist-Speech Pathologist Report for Modified Barium Swallow Study: Experience at a Multi-hospital Single Health Care System

Dysphagia, or a disorder of swallowing, is very common and is reported in 1 out of 25 adults with approximately 1 million new cases per year in the United States alone. This also disproportionately impacts elderly patients, with a prevalence of 17%. Patients with dysphagia may have severe clinical complications such as starvation, dehydration, and airway obstruction- which may further increase mortality. Hence, timely and accurate diagnosis of dysphagia is hence crucial in management considerations. The gold standard for evaluating and diagnosing dysphagia is a modified barium swallow study (MBSS). The study is typically performed as a collaborative effort between a speech language pathologist (SLP) and a radiologist, who bring their individual skill sets to the table. Current MBSS reporting involves separately dictated and interpreted reports from the SLP and radiologist. In this paper, we elucidate our experience in a multi-institutional healthcare system wherein we have devised a single, integrated report for MBSS, which involves collaborative effort between SLP and the radiologist. We weight the advantages and disadvantages of unified reporting, the challenges of implementing it in a large healthcare system, and note how it can help improve efficiency and deliver unified patient care. We hope that this would be a template for other institutions as well as improve standardization of reporting techniques.

Sustained barcode medication administration rates less than 2 percent in a large healthcare system

Purpose Implementation of bar code medication administration (BCMA) technology is an effective strategy to decrease medication administration errors. Consistent use of BCMA technology within a hospital system should result in improved patient safety through the reduction of medication related administration errors. Based on this premise, a large health system established an annual goal to reduce BCMA override rates to less than 2%. Methods A large health system located in the Intermountain West developed a BCMA override reporting tool to assist with reducing BCMA override rates. An essential component of the reporting tool is the visual management strategy which allows caregivers to easily identify goal progress. The tool also includes information that managers can use to determine how often their direct reports override medications. Pharmacy caregivers can also use the data from the reporting tool to address specific issues related to medications that do not scan properly. Results Implementation of the tool and education on its use, resulted in individual follow up with nursing units and nurses, ultimately producing sustained barcode overrides less than 2%. Conclusion By implementing reporting systems that identifies specific opportunities for improvement, barcode override rates can be decreased to less than 2% in a large healthcare system.

Abstract PR001: Socioeconomic analysis and disparities in germline genetic testing for pancreatic cancer

Abstract Introduction: Germline genetic testing is now recommended for patients with pancreatic ductal adenocarcinoma (PDAC). We explored whether attributes of testing, such as uptake fraction and rate, were associated with various clinical features. Here we identified barriers to germline testing and explored a relationship between lag of germline diagnosis and patient social profiles, including median income, race, and ethnicity from New York’s largest healthcare system. Methods: Patients with PDAC were identified using billing records across our institution with an IRB-approved protocol. Germline mutation data were assessed through chart review. Median income was annotated using zip codes and www.census.gov. Date of diagnosis (DOD) was recorded as the date of biopsy or, if no biopsy was performed, the date of earliest lesion-found CT scan. Lag of testing was calculated as the difference between DOD and the date of germline sample collection. Results: Between Mar 2016 and Feb 2022, 305 patients with PDAC were identified, with 103 (36.3%) having reports found (F), and 202 (63.7%) not having reports found (NF). Availability of germline testing did not vary by median income (F: 95954 dollars vs NF: 94368 dollars, t=0.414, p=0.68). There was no significant difference in the geographic distribution (gender, race, and ethnicity) of patients between F and NF: gender (F: Male 41%, Female 59%; NF: Male 43%, Female 57%; p=0.92), race (F: Asian 8%, African American 13%, White 55%, Others 5%, Not Reported 19%; NF: Asian 9%, African American 16%, White 54%, Others 6%, Not Reported 15%; p=0.92), ethnicity (F: Non-Hispanic 81%, Hispanic 11%, Others 5%; NF: Non-Hispanic 83%, Hispanic 4%, Others 12%; p=0.16). Pearson analysis between median income (x) and lag of testing (y) showed a negative correlation (y=-0.0027x+315.6, R=-0.241, p=0.014). Level of income (cutoff: 100k) also affected the mean days in lag of testing (below 100k: 111.8d, above 100k: -44.0d, t=2.190, p=0.031). African American (AA) patients` had a significant lag of testing compared to White (W) patients (AA: 194.4d, W: -20.9d, t=2.123, p=0.037) and insignificant lag compared to Asian (A) patients (AA: 194.4d, A: -7.33d, t=1.924, p=0.068). In addition, no African American patients had germline genetic testing performed before the diagnosis of pancreatic cancer, whereas 1 Asian patient (11.1%) and 11 White patients (18.6%) had testing performed before the diagnosis. Finally, Hispanic (H) patients had a statistically insignificant lag of testing compared to non-Hispanic (NH) patients (H: 193.9d, NH: 27.76d, t=1.419, p=0.160). Conclusion: Analysis of germline and clinical data from our 305-patient cohort identified a striking and concerning negative correlation between patient median income and lag between DOD and germline testing. In addition, patient race and ethnicity also significantly contributed to delays in germline testing. These results compel further investigation into the operational processes and socioeconomic barriers that will prompt germline testing at our institution. Citation Format: Xianghui Zou, Baho Sidiqi, Sunita Patruni, Christopher Hollweg, Noah Kauff, Daniel King. Socioeconomic analysis and disparities in germline genetic testing for pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr PR001.

Abstract A022: Standardization of a neoadjuvant therapy (NAT) pathway for pancreatic cancer across a geographically large and diverse healthcare system improves patient outcomes and successful completion of NAT

Abstract Optimal management of patients with potentially resectable pancreatic ductal adenocarcinoma (PDAC) is controversial and variation exists within/across academic and healthcare systems. Herein we describe the initial results of a neoadjuvant therapy (NAT) pathway across one of New York’s largest, most diverse health care systems. The NATP was established at Northwell Health in June 2019, consisting of an initial, single-day pancreas multi-disciplinary clinic (PMDC) visit, followed by NAT, interval scans and PMDC re-reviews at two and four months, prior to consideration of radiation and of surgical resection. We conducted an IRB-approved retrospective analysis of patients enrolled to this pathway. Primary endpoints included completion of NAT pathway and overall survival (OS). Kaplan-Meier analysis was used to estimate OS. The cohort consisted of 55 patients: 44% men, mean age 69.7 years, and 48% non-White. Surgical stage at diagnosis was locally advanced (LAPC; 49%), borderline resectable (BRPC; 35%) and resectable (RPC; 16%). NAT consisted of gemcitabine/nab-paclitaxel (GnP, 41%; 147 total cycles), FOLFIRINOX (36%; 167 total cycles), and a combination of both regimens (23%). Eighteen (33%) received radiotherapy (94%, SBRT) and 72% received &amp;gt;=50 Gy. Average duration of NAT pathway (from biopsy to surgery) was 5.9 mo (IQR 4.7-7.6 mo): average time from biopsy to C1 of NAT was 25 days (IQR 18-39 days), from C1 to post NAT completion imaging was 3.9 mo (IQR 3.5-4.8 mo) and from RT to surgery was 36.0 days (IQR 30.5-43.8 days). Of 55 patients who began the pathway, 24 (44%; 6% RPC, 53% BRPC, 41% LAPC) completed the pathway and underwent surgical exploration; 22 did not complete the pathway and 9 are currently undergoing NAT. Reasons for not completing NAT included metastasis (24%), transfer of care (12%), local progression (5.5%), and death (3.6%). Out of 24 patients who were surgically explored, 71% underwent successful resection (53% R0, 18% R1&amp;lt;1mm and 30% R1) compared to prior institutional resection rate in NAT patients of 17% (p=0.015). There were 11 deaths (20%) and median OS was reached at 17.7 mo (95% CI 7.9, 27.6): 16.3 mo 95% CI 7.2, 25.4) and 26.1 mo (95% CI 3.2, 49) for GnP and FOLFIRINOX, respectively. Patients enrolled in the NAT pathway had a higher rate of germline mutation testing (52% vs 30%, p=0.002). The percentage of patients that remained within the Northwell Health system for their post-NAT was higher among patients in the pathway, compared to prior (87% versus 44%). Implementation of a standardized NAT approach at a large diverse healthcare system increased the percentage of PDAC patients who underwent surgical resection and improved patient retention rate. Citation Format: Ruwan Parakrama, Baho Sidiqi, Lyudmyla Demyan, Shamsher Pasha, Danielle Pinto, Tiffany Zavadsky, Xianghui Zhou, Sunita Patruni, Adrianna Kapusta, Oliver Standring, Matthew J. Weiss, Joseph M. Herman, Daniel A. King. Standardization of a neoadjuvant therapy (NAT) pathway for pancreatic cancer across a geographically large and diverse healthcare system improves patient outcomes and successful completion of NAT [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A022.

Systematic Evaluation of Synthetic Panel Data Quality with an Application to Chronic Lymphocytic Leukemia

OBJECTIVES The dynamic and evolving clinical trial landscape, with its nascent incorporation of real-world data, has the potential to transform healthcare. With these exciting developments come challenges in protecting patient privacy, while retaining data information and encouraging transparency and reproducibility of methods. An emerging technology to ameliorate this challenge is synthetic data generation (SDG). The promises of SDG are to provide realistic, representative, and sharable data that retains all the potential learning of the original (parent) data. We demonstrate a flexible framework for generating and evaluating synthetic data from a challenging clinical use case of chronic lymphocytic leukemia (CLL) patients. We demonstrate the potential to generate a synthetic cohort using real-world data on a cohort of patients treated with chimeric antigen receptor T-cell (CAR T) therapy. Many analytes, and their longitudinal progression, have been shown to predict clinical outcomes in CLL. Therefore, when generating synthetic data for this cohort, it is essential to preserve these longitudinal analyte 'fingerprints’ associated with other clinical information to capture latent disease progression adequately. METHODS We used Generative Adversarial Networks (GANs), a type of unsupervised deep learning algorithm, to generate synthetic CLL patients and their latent disease progression over time. 389 Patients were identified within a large tertiary healthcare system (providing care to approximately 5mil patients) by ICD9/10 codes who could provide longitudinal values for the synthetic cohort. We simulated synthetic patient data using EMR (Electronic Medical Record) data, including laboratory test values, patient-reported health state utility values (HSUVs), and other baseline characteristics. RESULTS Clinical attributes showed a strong relation between analyte trajectories and outcomes. Synthetic data was indistinguishable from original data in both statistical tests and in performance in machine learning algorithms to predict disease progression and worsening outcomes. Wasserstein Conditional GAN outperformed vanilla GAN, conditional GAN, and Wasserstein GAN. Synthetic patient data generated by GAN accurately reflect the means, standard deviations, and correlations of each variable over time to the extent that synthetic data cannot be distinguished from actual data by a logistic regression. Moreover, our unsupervised model predicts changes in total HSUVs with the same accuracy as specifically trained supervised models, additionally capturing the correlation structure of the covariates. LIMITATIONS and CONCLUSIONS Many synthetic data-generative methods emphasize retention of relationship among data elements and may preclude certain data anomalies. The real-world data may retain properties associated with the experiment or data generation process and carry them over into the synthetic cohort. The ideal synthetic cohort would support any statistical discovery possible in, and be verifiable against, the parent dataset - while reducing probability of patient identification to zero. This application of statistical tests to evaluate deep learning algorithms provides a novel perspective on synthetic data generation and poses the bases for the establishment of best practices for synthetic data quality assessment.