A method to advance adolescent sexual health research: Automated algorithm finds sexual history documentation

Background:We aimed to develop and validate a rule-based Natural Language Processing (NLP) algorithm to detect sexual history documentation and its five key components [partners, practices, past history of sexually transmitted infections (STIs), protection from STIs, and prevention of pregnancy] among adolescent encounters in the pediatric emergency and inpatient settings.MethodsWe iteratively designed a NLP algorithm using pediatric emergency department (ED) provider notes from adolescent ED visits with specific abdominal or genitourinary (GU) chief complaints. The algorithm is composed of regular expressions identifying commonly used phrases in sexual history documentation. We validated this algorithm with inpatient admission notes for adolescents. We calculated the sensitivity, specificity, negative predictive value, positive predictive value, and F1 score of the tool in each environment using manual chart review as the gold standard.ResultsIn the ED test cohort with abdominal or GU complaints, 97/179 (54%) provider notes had a sexual history documented, and the NLP algorithm correctly classified each note. In the inpatient validation cohort, 97/321 (30%) admission notes included a sexual history, and the NLP algorithm had 100% sensitivity and 98.2% specificity. The algorithm demonstrated >97% sensitivity and specificity in both settings for detection of elements of a high quality sexual history including protection used and contraception. Type of sexual practice and STI testing offered were also detected with >97% sensitivity and specificity in the ED test cohort with slightly lower performance in the inpatient validation cohort.ConclusionThis NLP algorithm automatically detects the presence of sexual history documentation and its key components in ED and inpatient settings

Evaluation of a clinical decision support strategy to increase seasonal influenza vaccination among hospitalized children before inpatient discharge

Importance: Hospitalized children are at increased risk of influenza-related complications, yet influenza vaccine coverage remains low among this group. Evidence-based strategies about vaccination of vulnerable children during all health care visits are especially important during the COVID-19 pandemic. Objective: To design and evaluate a clinical decision support (CDS) strategy to increase the proportion of eligible hospitalized children who receive a seasonal influenza vaccine prior to inpatient discharge. Design, Setting, and Participants: This quality improvement study was conducted among children eligible for the seasonal influenza vaccine who were hospitalized in a tertiary pediatric health system providing care to more than half a million patients annually in 3 hospitals. The study used a sequential crossover design from control to intervention and compared hospitalizations in the intervention group (2019-2020 season with the use of an intervention order set) with concurrent controls (2019-2020 season without use of an intervention order set) and historical controls (2018-2019 season with use of an order set that underwent intervention during the 2019-2020 season). Interventions: A CDS intervention was developed through a user-centered design process, including (1) placing a default influenza vaccine order into admission order sets for eligible patients, (2) a script to offer the vaccine using a presumptive strategy, and (3) just-in-time education for clinicians addressing vaccine eligibility in the influenza order group with links to further reference material. The intervention was rolled out in a stepwise fashion during the 2019-2020 influenza season. Main Outcomes and Measures: Proportion of eligible hospitalizations in which 1 or more influenza vaccines were administered prior to discharge. Results: Among 17 740 hospitalizations (9295 boys [52%]), the mean (SD) age was 8.0 (6.0) years, and the patients were predominantly Black (n = 8943 [50%]) or White (n = 7559 [43%]) and mostly had public insurance (n = 11 274 [64%]). There were 10 997 hospitalizations eligible for the influenza vaccine in the 2019-2020 season. Of these, 5449 (50%) were in the intervention group, and 5548 (50%) were concurrent controls. There were 6743 eligible hospitalizations in 2018-2019 that served as historical controls. Vaccine administration rates were 31% (n = 1676) in the intervention group, 19% (n = 1051) in concurrent controls, and 14% (n = 912) in historical controls (P \u3c .001). In adjusted analyses, the odds of receiving the influenza vaccine were 3.25 (95% CI, 2.94-3.59) times higher in the intervention group and 1.28 (95% CI, 1.15-1.42) times higher in concurrent controls than in historical controls. Conclusions and Relevance: This quality improvement study suggests that user-centered CDS may be associated with significantly improved influenza vaccination rates among hospitalized children. Stepwise implementation of CDS interventions was a practical method that was used to increase quality improvement rigor through comparison with historical and concurrent controls

Effectiveness of Interventions to Reduce Contact Rates during a Simulated Influenza Pandemic

Measures to decrease contact between persons during an influenza pandemic have been included in pandemic response plans. We used stochastic simulation models to explore the effects of school closings, voluntary confinements of ill persons and their household contacts, and reductions in contacts among long-term care facility (LTCF) residents on pandemic-related illness and deaths. Our findings suggest that school closings would not have a substantial effect on pandemic-related outcomes in the absence of measures to reduce out-of-school contacts. However, if persons with influenzalike symptoms and their household contacts were encouraged to stay home, then rates of illness and death might be reduced by ≈50%. By preventing ill LTCF residents from making contact with other residents, illness and deaths in this vulnerable population might be reduced by ≈60%. Restricting the activities of infected persons early in a pandemic could decrease negative health impact

Development and Validation of a Symptom-Based Activity Index for Adults With Eosinophilic Esophagitis

Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients’ assessments of disease severity. We also evaluated relationships between patients’ assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings

De novo and biallelic DEAF1 variants cause a phenotypic spectrum.

PURPOSE: To investigate the effect of different DEAF1 variants on the phenotype of patients with autosomal dominant and recessive inheritance patterns and on DEAF1 activity in vitro. METHODS: We assembled a cohort of 23 patients with de novo and biallelic DEAF1 variants, described the genotype-phenotype correlation, and investigated the differential effect of de novo and recessive variants on transcription assays using DEAF1 and Eif4g3 promoter luciferase constructs. RESULTS: The proportion of the most prevalent phenotypic features, including intellectual disability, speech delay, motor delay, autism, sleep disturbances, and a high pain threshold, were not significantly different in patients with biallelic and pathogenic de novo DEAF1 variants. However, microcephaly was exclusively observed in patients with recessive variants (p < 0.0001). CONCLUSION: We propose that different variants in the DEAF1 gene result in a phenotypic spectrum centered around neurodevelopmental delay. While a pathogenic de novo dominant variant would also incapacitate the product of the wild-type allele and result in a dominant-negative effect, a combination of two recessive variants would result in a partial loss of function. Because the clinical picture can be nonspecific, detailed phenotype information, segregation, and functional analysis are fundamental to determine the pathogenicity of novel variants and to improve the care of these patients

User-Centered Design and Evaluation of Clinical Decision Support to Improve Early Peanut Introduction: Formative Study

BackgroundPeanut allergy has recently become more prevalent. Peanut introduction recommendations have evolved from suggesting peanut avoidance until the age of 3 years to more recent guidelines encouraging early peanut introduction after the Learning Early about Peanut Allergy (LEAP) study in 2015. Guideline adherence is poor, leading to missed care opportunities. ObjectiveIn this study, we aimed to develop a user-centered clinical decision support (CDS) tool to improve implementation of the most recent early peanut introduction guidelines in the primary care clinic setting. MethodsWe edited the note template of the well-child check (WCC) visits at ages 4 and 6 months with CDS prompts and point-of-care education. Formative and summative usability testing were completed with pediatric residents in a simulated electronic health record (EHR). We estimated task completion rates and perceived usefulness of the CDS in summative testing, comparing a test EHR with and without the CDS. ResultsFormative usability testing with the residents provided qualitative data that led to improvements in the build for both the 4-month and 6-month WCC note templates. During summative usability testing, the CDS tool significantly improved discussion of early peanut introduction at the 4-month WCC visit compared to scenarios without the CDS tool (9/15, 60% with CDS and 0/15, 0% without CDS). All providers except one at the 4-month WCC scenario gave at least an adequate score for the ease of use of the CDS tool for the history of present illness and assessment and plan sections. During the summative usability testing with the 6-month WCC new build note template, providers more commonly provided comprehensive care once obtaining a patient history concerning for an immunoglobulin E–mediated peanut reaction by placing a referral to allergy/immunology (P=.48), prescribing an epinephrine auto-injector (P=.07), instructing on how to avoid peanut products (P<.001), and providing an emergency treatment plan (P=.003) with CDS guidance. All providers gave at least an adequate score for ease of use of the CDS tool in the after-visit summary. ConclusionsUser-centered CDS improved application of early peanut introduction recommendations and comprehensive care for patients who have symptoms concerning for peanut allergy in a simulation

Pediatric trainees systematically under-report duty hour violations compared to electronic health record defined shifts.

Duty hour monitoring is required in accredited training programs, however trainee self-reporting is onerous and vulnerable to bias. The objectives of this study were to use an automated, validated algorithm to measure duty hour violations of pediatric trainees over a full academic year and compare to self-reported violations. Duty hour violations calculated from electronic health record (EHR) logs varied significantly by trainee role and rotation. Block-by-block differences show 36.8% (222/603) of resident-blocks with more EHR-defined violations (EDV) compared to self-reported violations (SRV), demonstrating systematic under-reporting of duty hour violations. Automated duty hour tracking could provide real-time, objective assessment of the trainee work environment, allowing program directors and accrediting organizations to design and test interventions focused on improving educational quality