Systematic data quality assessment of electronic health record data to evaluate study-specific fitness: Report from the PRESERVE research study.

Study-specific data quality testing is an essential part of minimizing analytic errors, particularly for studies making secondary use of clinical data. We applied a systematic and reproducible approach for study-specific data quality testing to the analysis plan for PRESERVE, a 15-site, EHR-based observational study of chronic kidney disease in children. This approach integrated widely adopted data quality concepts with healthcare-specific evaluation methods. We implemented two rounds of data quality assessment. The first produced high-level evaluation using aggregate results from a distributed query, focused on cohort identification and main analytic requirements. The second focused on extended testing of row-level data centralized for analysis. We systematized reporting and cataloguing of data quality issues, providing institutional teams with prioritized issues for resolution. We tracked improvements and documented anomalous data for consideration during analyses. The checks we developed identified 115 and 157 data quality issues in the two rounds, involving completeness, data model conformance, cross-variable concordance, consistency, and plausibility, extending traditional data quality approaches to address more complex stratification and temporal patterns. Resolution efforts focused on higher priority issues, given finite study resources. In many cases, institutional teams were able to correct data extraction errors or obtain additional data, avoiding exclusion of 2 institutions entirely and resolving 123 other gaps. Other results identified complexities in measures of kidney function, bearing on the study's outcome definition. Where limitations such as these are intrinsic to clinical data, the study team must account for them in conducting analyses. This study rigorously evaluated fitness of data for intended use. The framework is reusable and built on a strong theoretical underpinning. Significant data quality issues that would have otherwise delayed analyses or made data unusable were addressed. This study highlights the need for teams combining subject-matter and informatics expertise to address data quality when working with real world data.

A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program.

As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS- CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.

Skeletal Outcomes in Children and Young Adults with Glomerular Disease.

BACKGROUND: Children with glomerular disease have unique risk factors for compromised bone health. Studies addressing skeletal complications in this population are lacking. METHODS: This retrospective cohort study utilized data from PEDSnet, a national network of pediatric health systems with standardized electronic health record data for more than 6.5 million patients from 2009 to 2021. Incidence rates (per 10,000 person-years) of fracture, slipped capital femoral epiphysis (SCFE), and avascular necrosis/osteonecrosis (AVN) in 4598 children and young adults with glomerular disease were compared with those among 553,624 general pediatric patients using Poisson regression analysis. The glomerular disease cohort was identified using a published computable phenotype. Inclusion criteria for the general pediatric cohort were two or more primary care visits 1 year or more apart between 1 and 21 years of age, one visit or more every 18 months if followed >3 years, and no chronic progressive conditions defined by the Pediatric Medical Complexity Algorithm. Fracture, SCFE, and AVN were identified using SNOMED-CT diagnosis codes; fracture required an associated x-ray or splinting/casting procedure within 48 hours. RESULTS: We found a higher risk of fracture for the glomerular disease cohort compared with the general pediatric cohort in girls only (incidence rate ratio [IRR], 1.6; 95% CI, 1.3 to 1.9). Hip/femur and vertebral fracture risk were increased in the glomerular disease cohort: adjusted IRR was 2.2 (95% CI, 1.3 to 3.7) and 5 (95% CI, 3.2 to 7.6), respectively. For SCFE, the adjusted IRR was 3.4 (95% CI, 1.9 to 5.9). For AVN, the adjusted IRR was 56.2 (95% CI, 40.7 to 77.5). CONCLUSIONS: Children and young adults with glomerular disease have significantly higher burden of skeletal complications than the general pediatric population.

A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program.

Background: As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. Methods and Findings: In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS-CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. Conclusions: The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses. Funding Source: This research was funded by the National Institutes of Health (NIH) Agreement OT2HL161847-01 as part of the Researching COVID to Enhance Recovery (RECOVER) program of research. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the RECOVER Program, the NIH or other funders.

Assessment of 135 794 Pediatric Patients Tested for Severe Acute Respiratory Syndrome Coronavirus 2 Across the United States.

Importance: There is limited information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and infection among pediatric patients across the United States. Objective: To describe testing for SARS-CoV-2 and the epidemiology of infected patients. Design, Setting, and Participants: A retrospective cohort study was conducted using electronic health record data from 135 794 patients younger than 25 years who were tested for SARS-CoV-2 from January 1 through September 8, 2020. Data were from PEDSnet, a network of 7 US pediatric health systems, comprising 6.5 million patients primarily from 11 states. Data analysis was performed from September 8 to 24, 2020. Exposure: Testing for SARS-CoV-2. Main Outcomes and Measures: SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) illness. Results: A total of 135 794 pediatric patients (53% male; mean [SD] age, 8.8 [6.7] years; 3% Asian patients, 15% Black patients, 11% Hispanic patients, and 59% White patients; 290 per 10 000 population [range, 155-395 per 10 000 population across health systems]) were tested for SARS-CoV-2, and 5374 (4%) were infected with the virus (12 per 10 000 population [range, 7-16 per 10 000 population]). Compared with White patients, those of Black, Hispanic, and Asian race/ethnicity had lower rates of testing (Black: odds ratio [OR], 0.70 [95% CI, 0.68-0.72]; Hispanic: OR, 0.65 [95% CI, 0.63-0.67]; Asian: OR, 0.60 [95% CI, 0.57-0.63]); however, they were significantly more likely to have positive test results (Black: OR, 2.66 [95% CI, 2.43-2.90]; Hispanic: OR, 3.75 [95% CI, 3.39-4.15]; Asian: OR, 2.04 [95% CI, 1.69-2.48]). Older age (5-11 years: OR, 1.25 [95% CI, 1.13-1.38]; 12-17 years: OR, 1.92 [95% CI, 1.73-2.12]; 18-24 years: OR, 3.51 [95% CI, 3.11-3.97]), public payer (OR, 1.43 [95% CI, 1.31-1.57]), outpatient testing (OR, 2.13 [1.86-2.44]), and emergency department testing (OR, 3.16 [95% CI, 2.72-3.67]) were also associated with increased risk of infection. In univariate analyses, nonmalignant chronic disease was associated with lower likelihood of testing, and preexisting respiratory conditions were associated with lower risk of positive test results (standardized ratio [SR], 0.78 [95% CI, 0.73-0.84]). However, several other diagnosis groups were associated with a higher risk of positive test results: malignant disorders (SR, 1.54 [95% CI, 1.19-1.93]), cardiac disorders (SR, 1.18 [95% CI, 1.05-1.32]), endocrinologic disorders (SR, 1.52 [95% CI, 1.31-1.75]), gastrointestinal disorders (SR, 2.00 [95% CI, 1.04-1.38]), genetic disorders (SR, 1.19 [95% CI, 1.00-1.40]), hematologic disorders (SR, 1.26 [95% CI, 1.06-1.47]), musculoskeletal disorders (SR, 1.18 [95% CI, 1.07-1.30]), mental health disorders (SR, 1.20 [95% CI, 1.10-1.30]), and metabolic disorders (SR, 1.42 [95% CI, 1.24-1.61]). Among the 5374 patients with positive test results, 359 (7%) were hospitalized for respiratory, hypotensive, or COVID-19-specific illness. Of these, 99 (28%) required intensive care unit services, and 33 (9%) required mechanical ventilation. The case fatality rate was 0.2% (8 of 5374). The number of patients with a diagnosis of Kawasaki disease in early 2020 was 40% lower (259 vs 433 and 430) than in 2018 or 2019. Conclusions and Relevance: In this large cohort study of US pediatric patients, SARS-CoV-2 infection rates were low, and clinical manifestations were typically mild. Black, Hispanic, and Asian race/ethnicity; adolescence and young adulthood; and nonrespiratory chronic medical conditions were associated with identified infection. Kawasaki disease diagnosis is not an effective proxy for multisystem inflammatory syndrome of childhood.

Parental Vaccine Hesitancy and Declination of Influenza Vaccination Among Hospitalized Children.

OBJECTIVES: Parents frequently decline the influenza vaccine for their child during hospitalization. In this study, we aimed to assess the role of vaccine hesitancy in these declinations. METHODS: This cross-sectional survey study was conducted among English-speaking parents of influenza vaccine-eligible children who were hospitalized between October 2014 and April 2015. Between July 2015 and September 2015, parents were recruited via mail to complete the validated Parent Attitudes about Childhood Vaccines (PACV) survey (modified for influenza vaccination). PACV scores (0-100 scale) were dichotomized into scores of ≥50 (hesitant) and <50 (nonhesitant). The primary outcome was parental declination of the influenza vaccine for their child during hospitalization. A secondary outcome was the declination reason documented during hospitalization. The main independent variable was parental vaccine hesitancy status, determined by the PACV score. Multivariable logistic regression was used to examine the association between vaccine hesitancy and influenza vaccine declination, adjusting for sociodemographic, visit, and clinical characteristics. The relationship between vaccine hesitancy and declination reason was also explored. RESULTS: Of 199 parents (18% response rate), 24% were vaccine hesitant and 53% declined the influenza vaccine for their child during hospitalization. Vaccine hesitancy (versus nonhesitancy) was associated with declining influenza vaccination (adjusted odds ratio: 6.4; 95% confidence interval: 2.5-16.5). The declination reason differed by vaccine hesitancy status, with a higher proportion of parents who were hesitant versus nonhesitant reporting "vaccine concern" or "vaccine unnecessary." CONCLUSIONS: Vaccine hesitancy was prevalent in this limited sample of parents of hospitalized children and associated with influenza vaccine declination. Additional investigation in a large, diverse, prospectively recruited cohort is warranted given the potential sampling bias present in this study.

Effect of provider-selected order indications on appropriateness of antimicrobial orders in a pediatric hospital.

PURPOSE: The effect of mandatory provider-selected order indications (PSOIs) on appropriateness of antimicrobial ordering in a tertiary pediatric hospital was evaluated. METHODS: Mandatory PSOIs for 14 antimicrobials were implemented in September 2013. Data on initial and final orders in the first 24 hours after ordering were collected from the electronic medical record. Orders from pre-PSOI and post-PSOI implementation were randomly selected and compared with documentation at the time of order to elicit the documentation-determined clinical indication (DDCI). Appropriateness of the order for the DDCI was evaluated and compared between groups using 2-sample t tests, chi-square tests, and logistic regression. RESULTS: Among the total 1,304 orders included in the review, 275 (21.1%) were inappropriate based on DDCI. The indications associated with the greatest number of inappropriate orders in both groups were suspected sepsis/bacteremia, meningitis/central nervous system infection, and pneumonia. A total of 128 (18.3%) of 700 initial orders were inappropriate compared with the DDCI in the pre-PSOI period, and 82 (17.8%) of 461 initial orders were inappropriate in the post-PSOI period (p = 0.83). A total of 78 (11.1%) of 700 final orders were inappropriate in the pre-PSOI period, and 29 (6.3%) of 461 final orders were inappropriate in the post-intervention period (p = 0.01). Overall, 84 (12%) of 700 inappropriate orders reached the patient in the pre-PSOI period versus 43 (9.3%) of 461 inappropriate orders in the post-PSOI period (p = 0.15). CONCLUSION: PSOIs were effective in reducing inappropriate antimicrobial orders in the first 24 hours after ordering if the correct indication was selected.

Risk of Rotavirus Nosocomial Spread After Inpatient Pentavalent Rotavirus Vaccination.

BACKGROUND: Infants born prematurely or with underlying conditions are at increased risk of severe rotavirus disease and associated complications. Given the theoretical risk of nosocomial transmission of vaccine-type rotavirus, rotavirus vaccination is recommended for infants at or after discharge from neonatal care settings. Because the first dose should be administered by 104 days of age, some infants may be age-ineligible for vaccination if delayed until discharge. METHODS: This prospective cohort included infants admitted to an urban academic medical center between birth and 104 days who received care in intensive care settings. Pentavalent human-bovine reassortant rotavirus vaccine (RV5) was used, per routine clinical care. Stool specimens were collected weekly (February 2013-April 2014) and analyzed for rotavirus strains using real-time reverse transcription-polymerase chain reaction. Demographic and vaccine data were collected. RV5 safety was not assessed. RESULTS: Of 385 study infants, 127 were age-eligible for routine vaccinations during hospitalization. At discharge, 32.7% were up-to-date for rotavirus vaccination, compared with 82.7% for other vaccinations. Of rotavirus-unvaccinated infants, 42.6% were discharged at age >104 days and thus vaccination-ineligible. Of 1192 stool specimens collected, rotavirus was detected in 13 (1.1%): 1 wild-type strain from an unvaccinated infant; 12 vaccine-type strains from 9 RV5-vaccinated infants. No vaccine-type rotavirus cases were observed among unvaccinated infants (incidence rate: 0.0 [95% confidence interval: 0.0-1.5] cases per 1000 patient days at risk). CONCLUSIONS: These data suggest that delaying rotavirus vaccination until discharge from the hospital could lead to missed vaccination opportunities and may be unnecessary in institutions using RV5 with comparable infection control standards.

A longitudinal analysis of data quality in a large pediatric data research network.

OBJECTIVE: PEDSnet is a clinical data research network (CDRN) that aggregates electronic health record data from multiple children's hospitals to enable large-scale research. Assessing data quality to ensure suitability for conducting research is a key requirement in PEDSnet. This study presents a range of data quality issues identified over a period of 18 months and interprets them to evaluate the research capacity of PEDSnet. MATERIALS AND METHODS: Results were generated by a semiautomated data quality assessment workflow. Two investigators reviewed programmatic data quality issues and conducted discussions with the data partners' extract-transform-load analysts to determine the cause for each issue. RESULTS: The results include a longitudinal summary of 2182 data quality issues identified across 9 data submission cycles. The metadata from the most recent cycle includes annotations for 850 issues: most frequent types, including missing data (>300) and outliers (>100); most complex domains, including medications (>160) and lab measurements (>140); and primary causes, including source data characteristics (83%) and extract-transform-load errors (9%). DISCUSSION: The longitudinal findings demonstrate the network's evolution from identifying difficulties with aligning the data to a common data model to learning norms in clinical pediatrics and determining research capability. CONCLUSION: While data quality is recognized as a critical aspect in establishing and utilizing a CDRN, the findings from data quality assessments are largely unpublished. This paper presents a real-world account of studying and interpreting data quality findings in a pediatric CDRN, and the lessons learned could be used by other CDRNs.

Diagnostic Approach in Fetal Coarctation of the Aorta: A Cost-Utility Analysis.

BACKGROUND: Coarctation of the aorta (CoA) is difficult to diagnose by fetal echocardiogram (F-Echo), often requiring multiple F-Echos during gestation and neonatal echocardiograms (N-Echos) after birth. Furthermore, CoA is the most common ductal-dependent lesion missed on routine physical exam. OBJECTIVES: We sought to determine the most cost-effective diagnostic approach in caring for infants in whom an initial F-Echo is concerning for CoA. METHODS: Four paradigms for management after initial F-Echo could not rule out CoA were compared, with a single paradigm involving additional F-Echos: (1) multiple F-Echos for diagnostic clarity and performance of N-Echo on neonates with remaining high suspicion for CoA on F-Echos (prenatal-multiple), (2) no further F-Echo and performance of N-Echo on neonates with high suspicion for CoA on initial F-Echo (postnatal-selective), (3) no further F-Echo and performance of N-Echo on all neonates (postnatal-all), and (4) no further F-Echo or N-Echo with reliance on routine physical exam to identify afflicted infants (postnatal-none). Decision analysis models were constructed. Probabilities dictating clinical course and costs were calculated using our institution's study population. The utility-state values were derived from existing literature. The measure of effectiveness was quality-adjusted life years. To represent societal perspectives, cost was defined as hospital reimbursement payments. RESULTS: From 2007 to 2014 at our institution, 92 patients were diagnosed with CoA and met the inclusion criteria for this study. These patients presented to care either through prenatal diagnosis (n = 31), postnatal examination findings while clinically well (n = 41), or after clinical deterioration in extremis (n = 20), with one patient subsequently dying. Presenting in extremis was associated with a 20% increase in the cost of their subsequent care and with a 51% increase in length of hospital stay. Postnatal-none was the least effective paradigm but also the least costly, thus forming the baseline model. Of the three other diagnostic approaches modeled, Postnatal-all was the cost-effective paradigm, maximizing utility due to avoidance of high-cost/low-utility disease states such as presentation in extremis and death. Prenatal-multiple was the next most effective but was also the most expensive. CONCLUSIONS: Echocardiography is the screening gold standard in avoiding the devastating clinical manifestations of a missed CoA. When a diagnosis of CoA cannot be ruled out on initial F-Echo, the most cost-effective approach is performance of N-Echo on all neonates with no further prenatal evaluation.

Once-Daily Ceftriaxone Plus Metronidazole Versus Ertapenem and/or Cefoxitin for Pediatric Appendicitis.

BACKGROUND: Appendicitis is a common surgical emergency in pediatric patients, and broad-spectrum antibiotic therapy is warranted in their care. A simplified once-daily regimen of ceftriaxone and metronidazole (CTX plus MTZ) is cost effective in perforated patients. The goal of this evaluation is to compare a historic regimen of cefoxitin (CFX) in nonperforated cases and ertapenem (ERT) in perforated and abscessed cases with CTX plus MTZ for all cases in terms of efficacy and cost. METHODS: A retrospective review compared outcomes of nonperforated, perforated, and abscessed cases who received the historic regimen or CTX plus MTZ. Length of stay, time to afebrile, time to full feeds, postoperative abscess, and wound infection rates, inpatient readmissions, and antibiotic costs were evaluated. RESULTS: There were a total of 841 cases reviewed (494 nonperforated, 247 perforated, and 100 abscessed). Overall, the CTX plus MTZ group had a shorter time to afebrile (P < .001). Treatment groups did not differ in length of stay. Postoperative abscess rates were similar between groups (4.1% vs 3.3%, not significant). Other postoperative complications were similar between groups. Total antibiotic cost savings were over $110 000 during the study period (from November 2010 to June 2013). CONCLUSIONS: Both CFX and/or ERT and CTX plus MTZ result in low abscess and complication rates, suggesting both are effective strategies. Treatment with CTX plus MTZ results in a shorter time to afebrile, while also providing significant antibiotic cost savings. Ceftriaxone plus MTZ is a streamlined, cost-effective regimen in the treatment of nonperforated, perforated, and abscessed appendicitis.

A clinical model of obesity treatment is more effective in preschoolers and Spanish speaking families.

OBJECTIVE: Preschool and minority children have not been well represented in obesity treatment studies. This analysis of clinical obesity treatment was carried out within a diverse population of children 2-12 years to identify demographic characteristics associated with successful treatment. DESIGN AND METHODS: A medical record review captured BMI and demographics for children 2-12 years who began treatment during a 42-month period (n = 479). Associations of body mass index z-score (BMI-Z) change with child and family demographics were examined with logistic regression and time-to-event analysis. RESULTS: Treatment led to a mean BMI-Z decrease of 0.18. Half of children with follow-up (n = 273) exceeded the a priori cut-off for successful treatment of -0.1 BMI-Z. Preschoolers and children of Spanish-speakers were more likely to succeed, (Adjusted OR: 5.8 [95% CI: 2.7-12.2] and 2.3 [95% CI: 1.1, 4.9]). The hazard ratio for treatment failure was 3.7 [95% CI: 2.1, 6.8] for children starting treatment at 6-12 years compared to preschoolers, adjusted for other demographics. CONCLUSIONS: This mode of treatment was more likely to succeed among children treated before school age and among children whose parents spoke only Spanish. Screening and treatment for obesity in preschoolers and Hispanic immigrant families deserve further prospective study.

Emergency department crowding is associated with decreased quality of analgesia delivery for children with pain related to acute, isolated, long-bone fractures.

OBJECTIVES: The authors sought to determine which quality measures of analgesia delivery are most influenced by emergency department (ED) crowding for pediatric patients with long-bone fractures. METHODS: This cross-sectional, retrospective study included patients 0-21 years seen for acute, isolated long-bone fractures, November 2007 to October 2008, at a children's hospital ED. Nine quality measures were studied: six were based on the timeliness (1-hour receipt) and effectiveness (receipt/nonreceipt) of three fracture-related processes: pain score, any analgesic, and opioid analgesic administration. Three equity measures were also tested: language, identified primary care provider (PCP), and insurance. The primary independent variable was a crowding measure: ED occupancy. Models were adjusted for age, language, insurance, identified PCP, triage level, ambulance arrival, and time of day. The adjusted risk of each timeliness or effectiveness quality measure was measured at five percentiles of crowding and compared to the risk at the 10th and 90th percentiles. The role of equity measures as moderators of the crowding-quality models was tested. RESULTS: The study population included 1,229 patients. Timeliness and effectiveness quality measures showed an inverse association with crowding-an effect not moderated by equity measures. Patients were 4% to 47% less likely to receive timely care and were 3% to 17% less likely to receive effective care when each crowding measure was at the 90th than at the 10th percentile (p < 0.05). For three of the six quality measures, quality declined steeply between the 75th and 90th crowding percentiles. CONCLUSIONS: Crowding is associated with decreased timeliness and effectiveness, but not equity, of analgesia delivery for children with fracture-related pain.

Emergency department crowding is associated with decreased quality of care for children.

OBJECTIVE: We sought to determine which of several simple indicators of emergency department crowding are most predictive of quality of care in 2 pediatric disease models: acute asthma and pain associated with long-bone fractures. METHODS: We performed a retrospective, cross-sectional study of patients 2 to 21 years old seen for acute asthma and patients 0 to 21 years old seen for acute, isolated long-bone fractures from November 1, 2007, to October 31, 2008, at a single, academic children's hospital emergency department. The main outcome measures were quality measures based on 3 asthma care-related processes-asthma score, ß-agonist, and corticosteroid-and 2 fracture-related processes-analgesic and opioid analgesic. Good quality care was defined as receipt of an indicated process within 1 hour of arrival. Poor quality care was defined as nonreceipt or delayed receipt of an indicated process. Nine crowding measures were assigned based on conditions at each patient's arrival. We calculated the adjusted risk of receiving good quality care for each quality measure at 5 percentiles of crowding for each crowding measure. RESULTS: The asthma population included 927 patients, and the fracture population included 1229 patients. Among the 5 quality measures, we found rates of good quality care ranging from 23% to 64%. In adjusted models, we found an inverse association between crowding and quality. The 2 crowding measures with a consistently inverse association with the 5 quality measures across both populations were total patient-care hours and number arriving in prior 6 hours. Across the 10 models combining 1 of 2 key crowding variables with 1 of 5 quality measures, patients in the 2 populations were 0.40 (95% confidence interval, 0.27-0.55) to 0.78 (confidence interval, 0.71-0.85) times as likely to receive the indicated care process within 1 hour when each crowding measure was at the 75th than at the 25th percentile. CONCLUSIONS: Two measures of ED crowding are consistently associated with lower-quality asthma- and fracture-specific care in the ED for pediatric patients.

Emergency department crowding is associated with decreased quality of care for children with acute asthma.

STUDY OBJECTIVE: We seek to determine which dimensions of quality of care are most influenced by emergency department (ED) crowding for patients with acute asthma exacerbations. METHODS: This cross-sectional study with retrospective data collection included patients aged 2 to 21 years treated for acute asthma during November 2007 to October 2008 at a children's hospital ED. We studied 3 processes of care-asthma score, ß-agonist, and corticosteroid administration-and 9 quality measures representing 3 quality dimensions: timeliness (1-hour receipt of each process), effectiveness (receipt/nonreceipt of each process), and equity (language, identified primary care provider, and insurance). Primary independent variables were 2 crowding measures: ED occupancy and number waiting to see an attending-level physician. Models were adjusted for age, language, insurance, primary care access, triage level, ambulance arrival, oximetry, smoke exposure, and time of day. For timeliness and effectiveness quality measures, we calculated the adjusted risk of each quality measure at 5 percentiles of crowding for each crowding measure and assessed the significance of the adjusted relative interquartile risk ratios. For equity measures, we tested their role as moderators of the crowding-quality models. RESULTS: The asthma population included 927 patients. Timeliness and effectiveness quality measures showed an inverse, dose-related association with crowding, an effect not moderated by equity measures. Patients were 52% to 74% less likely to receive timely care and were 9% to 14% less likely to receive effective care when each crowding measure was at the 75th rather than at the 25th percentile (P<.05). CONCLUSION: ED crowding is associated with decreased timeliness and effectiveness-but not equity-of care for children with acute asthma.

The impact of electronic medical records data sources on an adverse drug event quality measure.

OBJECTIVE: To examine the impact of billing and clinical data extracted from an electronic medical record system on the calculation of an adverse drug event (ADE) quality measure approved for use in The Joint Commission's ORYX program, a mandatory national hospital quality reporting system. DESIGN: The Child Health Corporation of America's "Use of Rescue Agents-ADE Trigger" quality measure uses medication billing data contained in the Pediatric Health Information Systems (PHIS) data warehouse to create The Joint Commission-approved quality measure. Using a similar query, we calculated the quality measure using PHIS plus four data sources extracted from our electronic medical record (EMR) system: medications charged, medication orders placed, medication orders with associated charges (orders charged), and medications administered. MEASUREMENTS: Inclusion and exclusion criteria were identical for all queries. Denominators and numerators were calculated using the five data sets. The reported quality measure is the ADE rate (numerator/denominator). RESULTS: Significant differences in denominators, numerators, and rates were calculated from different data sources within a single institution's EMR. Differences were due to both common clinical practices that may be similar across institutions and unique workflow practices not likely to be present at any other institution. The magnitude of the differences would significantly alter the national comparative ranking of our institution compared to other PHIS institutions. CONCLUSIONS: More detailed clinical information may result in quality measures that are not comparable across institutions due institution-specific workflow, differences that are exposed using EMR-derived data.

Scope and impact of early and late preterm infants admitted to the PICU with respiratory illness.

OBJECTIVE: To determine the clinical course and outcomes of children born early preterm (EPT, <32 weeks), late preterm (LPT, 32 to 35 weeks), and full term (FT, >or=36 weeks) who were subsequently admitted to the pediatric intensive care unit (PICU) with respiratory illness. STUDY DESIGN: Retrospective chart review of patients <2 years old admitted to a tertiary PICU with respiratory illness. RESULTS: Two hundred seventy-one patients met inclusion criteria: 17.3% were EPT, 12.2% were LPT, and 70.5% were FT. Lower respiratory tract infection was the most common diagnosis (55%) for all groups. Median PICU length of stay was longer for EPT (6.3 days) and LPT infants (7.1 days) compared with FT infants (3.7 days; P < .03 for both comparisons). EPT and LPT infants had longer hospital stays (median, 11.7 and 13.8 days, respectively) compared with FT infants (median, 7.1 days; P < .03 and P = .004, respectively). Median hospital charges were also greater for EPT ($85 151) and LPT ($83 576) groups compared with FT group ($55 122; P < .01 and P < .02, respectively). CONCLUSIONS: EPT and LPT infants comprise a considerable proportion of PICU admissions for respiratory illness and have greater resource utilization than FT infants.