Pediatric asthma hospitalizations among urban minority children and the continuity of primary care.

OBJECTIVE: To examine the effect of ambulatory health care processes on asthma hospitalizations. METHODS: A retrospective cohort study using electronic health records was completed. Patients aged 2-18 years receiving health care from 1 of 5 urban practices between Jan 1, 2004 and Dec 31, 2008 with asthma documented on their problem list were included. Independent variables were modifiable health care processes in the primary care setting: (1) use of asthma controller medications; (2) regular assessment of asthma symptoms; (3) use of spirometry; (4) provision of individualized asthma care plans; (5) timely influenza vaccination; (6) access to primary healthcare; and (7) use of pay for performance physician incentives. Occurrence of one or more asthma hospitalizations was the primary outcome of interest. We used a log linear model (Poisson regression) to model the association between the factors of interest and number of asthma hospitalizations. RESULTS: 5,712 children with asthma were available for analysis. 96% of the children were African American. The overall hospitalization rate was 64 per 1,000 children per year. None of the commonly used asthma-specific indicators of high quality care were associated with fewer asthma hospitalizations. Children with documented asthma who experienced a lack of primary health care (no more than one outpatient visit at their primary care location in the 2 years preceding hospitalization) were at higher risk of hospitalization compared to those children with a greater number of visits (incidence rate ratio 1.39; 95% CI 1.09-1.78). CONCLUSIONS: In children with asthma, more frequent primary care visits are associated with reduced asthma hospitalizations.

Use of EHR-Based Pediatric Quality Measures: Views of Health System Leaders and Parents.

Measures of health care quality are produced from a variety of data sources, but often, physicians do not believe these measures reflect the quality of provided care. The aim was to assess the value to health system leaders (HSLs) and parents of benchmarking on health care quality measures using data mined from the electronic health record (EHR). Using in-context interviews with HSLs and parents, the authors investigated what new decisions and actions benchmarking using data mined from the EHR may enable and how benchmarking information should be presented to be most informative. Results demonstrate that although parents may have little experience using data on health care quality for decision making, they affirmed its potential value. HSLs expressed the need for high-confidence, validated metrics. They also perceived barriers to achieving meaningful metrics but recognized that mining data directly from the EHR could overcome those barriers. Parents and HSLs need high-confidence health care quality data to support decision making.

Design and Refinement of a Data Quality Assessment Workflow for a Large Pediatric Research Network.

BACKGROUND: Clinical data research networks (CDRNs) aggregate electronic health record data from multiple hospitals to enable large-scale research. A critical operation toward building a CDRN is conducting continual evaluations to optimize data quality. The key challenges include determining the assessment coverage on big datasets, handling data variability over time, and facilitating communication with data teams. This study presents the evolution of a systematic workflow for data quality assessment in CDRNs. IMPLEMENTATION: Using a specific CDRN as use case, the workflow was iteratively developed and packaged into a toolkit. The resultant toolkit comprises 685 data quality checks to identify any data quality issues, procedures to reconciliate with a history of known issues, and a contemporary GitHub-based reporting mechanism for organized tracking. RESULTS: During the first two years of network development, the toolkit assisted in discovering over 800 data characteristics and resolving over 1400 programming errors. Longitudinal analysis indicated that the variability in time to resolution (15day mean, 24day IQR) is due to the underlying cause of the issue, perceived importance of the domain, and the complexity of assessment. CONCLUSIONS: In the absence of a formalized data quality framework, CDRNs continue to face challenges in data management and query fulfillment. The proposed data quality toolkit was empirically validated on a particular network, and is publicly available for other networks. While the toolkit is user-friendly and effective, the usage statistics indicated that the data quality process is very time-intensive and sufficient resources should be dedicated for investigating problems and optimizing data for research.

Predicting Causes of Data Quality Issues in a Clinical Data Research Network.

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code. Nonetheless, with no prior knowledge of issue causes, partner institutions end up spending significant time investigating issues that represent either inherent data characteristics or false alarms. This work investigates whether the causes (ETL, Characteristic, or False alarm) can be predicted before spending time investigating issues. We trained a classifier on the metadata from 10,281 real-world data quality issues, and achieved a cause prediction F1-measure of up to 90%. While initially tested on PEDSnet, the proposed methodology is applicable to other CDRNs facing similar bottlenecks in handling data quality results.

Growth and development in a heliox incubator environment: a long-term safety study.

BACKGROUND: Neonates exposed to mechanical ventilation may develop bronchopulmonary dysplasia (BPD). BPD neonates exhibit a 25-30% increase in energy expenditure which may decrease the rate of growth and development. Heliox has been shown to improve pulmonary function and may decrease energy expenditure. We hypothesized that heliox would provide a safe environment for sustained growth and development. OBJECTIVE: To assess the safety of the heliox environment we observed developmental milestones; recorded changes in weight, total length, limb length and head circumference; measured blood chemistries; compared primary organ and muscle weights, and analyzed muscle enzymatic activity. DESIGN/METHODS: Four-day-old rabbit pups (n = 27) were randomized into control (21% O(2); 79% N(2)) or heliox (21% O(2); 79% He) groups, then raised for 14 days at 26.7 degrees C and 50% relative humidity. Pups were euthanized on day 14, blood drawn and primary organs, diaphragm and gastrocnemius weighed and snap-frozen. RESULTS: All pups thrived in both environments, achieving expected developmental milestones. There were no physiologically significant group differences in weight, growth factors, tissue weight, blood chemistry or muscle enzyme activity. CONCLUSIONS: No observed long-term differences in growth or development. RESULTS demonstrated that long-term heliox exposure is safe in this rabbit model. These data suggest that heliox administration may provide time for pulmonary improvement in the BPD population, warranting appropriate clinical trials.