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Introduction: In treating lower urinary tract symptoms (LUTS), the risk of overtreatment with antibiotics must be reconciled with the risk of an untreated urinary tract infection (UTI) progressing to acute pyelonephritis (APN). Using Cerner HealthFacts, a longitudinal clinical informatics database, we aimed to determine risk factors associated with the development of APN from UTI in an effort to guide the initiation of empiric antibiotics. Methods: We queried the Cerner HealthFacts database for women over age 18 with a positive urine culture. Any patient with an International Classification of Disease (ICD) code indicating chronic pyelonephritis was excluded. Development of APN within 30 days of the positive culture, specified by ICD coding, was our primary outcome. Patient and facility factors were assessed as potential risk factors for the development of APN using multivariable regression. Results: Out of 58 344 women with a positive urine culture, 3.9% (2296) developed APN. Mean patient age was 54.4 ± 25.3 years. Overall, 12 variables were predictive for APN and 11 variables were protective against APN.Presence of obstructive and reflux uropathies (OR 4.58), presentation to an acute care facility (OR 3.19), urinary retention (OR 2.30), history of UTI (OR 2.19), and renal comorbidities (OR 2.07) conferred the highest odds of APN development. The most protective variable against APN development was cognitive impairment (OR 0.49).Conclusions: Identified risk factors associated with APN development may aid decisions regarding empiric antibiotic initiation for patients presenting with LUTS while awaiting urine culture results. The relationship between cognitive impairment and progression to APN deserves further study.

Background Systemic Sclerosis (SSc) is an autoimmune condition of unknown etiology. We aim to investigate incidence, characteristics, and risk factors for gastrointestinal (GI) dysmotility in patients diagnosed with SSc using Cerner HealthFacts, a national longitudinal database representing approximately 69 million patients. Methods All patients over 18 years of age with SSc were included in our analysis. Incidence of GI dysmotility was identified using ICD coding. Patient characteristics were evaluated as potential risk factors for development of GI dysmotility using multivariable regression built using all variables with p<0.1 on univariable analysis. Results Overall, 0.4% (58/13,930) of patients with SSc developed GI dysmotility. Mean age was 57.23±15.22 years and 16% (2,228/13,930) were male and 86.1% (11,502/13,930) were female. In terms of race, 70.15% (9,772/13,930) were white and 14.82% (2,064/13,930) were African American. 92.51% (12,886/13,930) received care at an acute care facility and 81.51% (11,354/13,930) received care at an urban facility. The variables which conferred the highest odds of developing GI dysmotility included presence of hepatic comorbidities (OR 2.35), digestive comorbidities (OR 6.8), muscular dystrophy (OR 569.2), and Raynaud (OR 1.98). In univariable analysis and multivariable regression with 95% CI; 4 variables were predictive for GI dysmotility, and none were protective against GI dysmotility. Conclusions In this longitudinal national database study of patient with diagnosed SSc - hepatic, digestive comorbidities, muscular dystrophy, and Raynaud were noted to be associated with high risk of developing GI dysmotility. Careful evaluation and follow up is advised for SSc patients. Supported by None

Background: Electronic health record (EHR) data have many quality problems that may affect the outcome of research results and decision support systems. Many methods have been used to evaluate EHR data quality. However, there has yet to be a consensus on the best practice. We used a rule-based approach to assess the variability of EHR data quality across multiple healthcare systems. Methods: To quantify data quality concerns across healthcare systems in a PCORnet Clinical Research Network, we used a previously tested rule-based framework tailored to the PCORnet Common Data Model to perform data quality assessment at 13 clinical sites across eight states. Results were compared with the current PCORnet data curation process to explore the differences between both methods. Additional analyses of testosterone therapy prescribing were used to explore clinical care variability and quality. Results: The framework detected discrepancies across sites, revealing evident data quality variability between sites. The detailed requirements encoded the rules captured additional data errors with a specificity that aids in remediation of technical errors compared to the current PCORnet data curation process. Other rules designed to detect logical and clinical inconsistencies may also support clinical care variability and quality programs. Conclusion: Rule-based EHR data quality methods quantify significant discrepancies across all sites. Medication and laboratory sources are causes of data errors.

Background: Long-acting injectable (LAI) antipsychotics (APs) each have an oral equivalent formulation, while aripiprazole, olanzapine, and ziprasidone each also have a short-acting injectable (SAI) equivalent formulation. Inpatient prescribing patterns of LAIs and their oral/SAI equivalents are less characterized in populations other than Medicaid, Medicare, and Veterans Affairs populations. Mapping out inpatient prescribing patterns remains an important first step to ensure appropriate use of antipsychotics during this critical juncture of patient care prior to discharge. This study determined inpatient prescribing patterns of first- (FGA) and second-generation antipsychotic (SGA) LAIs and their oral/SAI formulations.Methods: This was a large retrospective study using the Cerner Health Facts® database. Hospital admissions due to schizophrenia, schizoaffective disorder, or bipolar disorder from 2010 to 2016 were identified. AP utilization was defined as the proportion of inpatient stays during which at least 1 AP was administered to the total number of inpatient visits over the observed period. Descriptive analyses were used to determine prescribing patterns for APs. Chi-square tests were used to determine utilization differences across years.Results: 94,989 encounters were identified. Encounters during which oral/SAI of SGA LAIs were administered were most common (n = 38,621, 41%). Encounters during which FGA LAIs or SGA LAIs were administered were the least common (n = 1,047, 1.1%). Prescribing patterns differed across years (p < 0.05) within the SGA LAI subgroup analysis (N = 6,014). Paliperidone palmitate (63%, N = 3,799) and risperidone (31%, N = 1,859) were the most frequently administered. Paliperidone palmitate utilization increased from 30% to 72% (p < 0.001), while risperidone utilization decreased from 70% to 18% (p < 0.001).Conclusions: Compared with their oral or SAI formulations, LAIs were underutilized from 2010 to 2016. Among SGA LAIs, the prescribing patterns of paliperidone palmitate and risperidone changed significantly.