Feliciano B. Yu

Full Implementation of Computerized Physician Order Entry and Medication-Related Quality Outcomes: A Study of 3364 Hospitals

This study compares quality of care measures for hospitals with fully implemented computerized physician order entry (CPOE) systems with hospitals that have not fully implemented such a system. Using a cross-sectional design, this study linked hospital quality data from the Centers for Medicare and Medicaid Services to the Health Information Management Systems Society Analytics database, which contains hospital CPOE adoption information. Performance on quality measures was assessed using univariate and multivariate methods. In all, 8% of hospitals have fully implemented CPOE systems; CPOE hospitals were more frequently larger, not-for-profit, and teaching hospitals. After controlling for confounders, CPOE hospitals outperformed comparison hospitals on 5 of 11 measures related to ordering medications and on 1 of 9 nonmedication-related quality measures. Using a large sample of hospitals, our study found significant positive associations between specific objective quality indicators and CPOE implementation. (Am J Med Qual 2009;24:278-286)

PEDSnet: a National Pediatric Learning Health System

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network that provides the infrastructure to support a national pediatric LHS. A consortium consisting of PEDSnet, which includes eight academic medical centers, two existing disease-specific pediatric networks, and two national data partners form the initial partners in the National Pediatric Learning Health System (NPLHS). PEDSnet is implementing a flexible dual data architecture that incorporates two widely used data models and national terminology standards to support multi-institutional data integration, cohort discovery, and advanced analytics that enable rapid learning.

Multi-Institutional Sharing of Electronic Health Record Data to Assess Childhood Obesity

Objective To evaluate the validity of multi-institutional electronic health record (EHR) data sharing for surveillance and study of childhood obesity. Methods We conducted a non-concurrent cohort study of 528,340 children with outpatient visits to six pediatric academic medical centers during 2007–08, with sufficient data in the EHR for body mass index (BMI) assessment. EHR data were compared with data from the 2007–08 National Health and Nutrition Examination Survey (NHANES). Results Among children 2–17 years, BMI was evaluable for 1,398,655 visits (56%). The EHR dataset contained over 6,000 BMI measurements per month of age up to 16 years, yielding precise estimates of BMI. In the EHR dataset, 18% of children were obese versus 18% in NHANES, while 35% were obese or overweight versus 34% in NHANES. BMI for an individual was highly reliable over time (intraclass correlation coefficient 0.90 for obese children and 0.97 for all children). Only 14% of visits with measured obesity (BMI ≥95%) had a diagnosis of obesity recorded, and only 20% of children with measured obesity had the diagnosis documented during the study period. Obese children had higher primary care (4.8 versus 4.0 visits, p<0.001) and specialty care (3.7 versus 2.7 visits, p<0.001) utilization than non-obese counterparts, and higher prevalence of diverse co-morbidities. The cohort size in the EHR dataset permitted detection of associations with rare diagnoses. Data sharing did not require investment of extensive institutional resources, yet yielded high data quality. Conclusions Multi-institutional EHR data sharing is a promising, feasible, and valid approach for population health surveillance. It provides a valuable complement to more resource-intensive national surveys, particularly for iterative surveillance and quality improvement. Low rates of obesity diagnosis present a significant obstacle to surveillance and quality improvement for care of children with obesity.

The relationship between computerized physician order entry and pediatric adverse drug events: a nested matched case-control study.

This study assesses the impact of computerized physician order entry (CPOE) implementation in pediatric hospitals on reported adverse drug events. Using a nested matched case‐control design; we linked CPOE implementation information from the health information management systems society analytics database with reported adverse drug event (ADE) from the national association of childrens hospitals and related institutions case mix comparative data program. Differences were examined using univariate and multivariate conditional logistic regression analyses. Patients from CPOE hospitals were more frequently seen in larger hospitals have more co‐morbidities than those from non‐CPOE hospitals. When matched by admitting diagnosis, age, gender and race, ADE cases were associated with more reported co‐morbidities, and were reported less frequently in hospitals with CPOE. Patients from hospitals without CPOE were 42% more likely to experience reportable ADE after adjusting for the presence of co‐morbidities. In conclusion, we found significant beneficial associations between reportable ADE and CPOE adoption in a representative sample of pediatric hospitals. Copyright

Patterns of Use of Handheld Clinical Decision Support Tools in the Clinical Setting

Objectives. To assess the patterns of use of handheld clinical decision support tools by internal medicine residents in clinical settings. Methods. Eighty-two internal medicine residents were given personal digital assistants (PDAs) containing a suite of clinical decision support (CDS) programs. A tracking program was used to prospectively track program use during the study period, and a follow-up survey regarding self-reported program use was administered after the study period. Patterns of program use from the tracking data were compared to the data from the self-report survey. Results. Sixty-eight residents were followed using the tracking data. Residents used an average of 1.81 CDS programs (SD: 1.57; range, 0—5) per month. Forty-nine residents completed the self-report survey. Residents reported using an average of 3.15 (SD: 1.61) and 3.92 (SD: 1.40) CDS programs during a typical clinic session and inpatient day, respectively. In both inpatient and outpatient settings and for both methods of assessing program use, 2 programs (Epocrates and MedCalc) were used more often than the other programs. No association was observed between age, gender, race, and PGY level with the use of handheld clinical decision support tools for either tracked or self-report data. The self-report data show higher estimates of CDS program use than the tracking data in the clinical setting. Conclusions. The data show that physicians prefer to use certain handheld CDS tools in clinical settings. Drug references and medical calculators have been consistently used more than clinical prediction rules and diagnostic systems. Self-report survey instruments may overestimate recorded use of CDS programs.

Impact of the meaningful use incentive program on electronic health record adoption by US children's hospitals

OBJECTIVE We determined adoption rates of pediatric-oriented electronic health record (EHR) features by US childrens hospitals and assessed perceptions regarding the suitability of commercial EHRs for pediatric care and the influence of the meaningful use incentive program on implementation of pediatric-oriented features. MATERIALS AND METHODS We surveyed members of the Childrens Hospital Association. We measured adoption of 19 pediatric-oriented features and asked whether commercial EHRs include key pediatric-focused capabilities. We inquired about the meaningful use programs relevance to pediatrics and its influence on EHR implementation priorities. RESULTS Of 164 general acute care childrens hospitals, 100 (61%) responded to the survey. Rates of comprehensive (across all pediatric units) adoption ranged from 37% (age-, gender-, and weight-adjusted blood pressure percentiles and immunization contraindication warnings) to 87% (age in appropriate units). Implementation rates for several features varied significantly by childrens hospital type. Nearly 60% of hospitals reported having EHRs that do not contain all features essential for high-quality care. A majority of hospitals indicated that the meaningful use program has had no effect on their adoption of pediatric features, while 26% said they have delayed or forgone incorporation of such features because of the program. CONCLUSIONS Childrens hospitals are implementing pediatric-focused features, but a sizable proportion still finds their systems suboptimal for pediatric care. The meaningful use incentive program is failing to promote and in some cases delaying uptake of pediatric-oriented features.

Health information technology vendor selection strategies and total factor productivity.

Objective: The aim of this study was to compare health information technology (HIT) adoption strategies’ relative performance on hospital-level productivity measures. Data Sources: The American Hospital Association’s Annual Survey and Healthcare Information and Management Systems Society Analytics for fiscal years 2002 through 2007 were used for this study. Study Design: A two-stage approach is employed. First, a Malmquist model is specified to calculate hospital-level productivity measures. A logistic regression model is then estimated to compare the three HIT adoption strategies’ relative performance on the newly constructed productivity measures. Principal Findings: The HIT vendor selection strategy impacts the amount of technological change required of an organization but does not appear to have either a positive or adverse impact on technical efficiency or total factor productivity. Conclusions: The higher levels in technological change experienced by hospitals using the best of breed and best of suite HIT vendor selection strategies may have a more direct impact on the organization early on in the process. However, these gains did not appear to translate into either increased technical efficiency or total factor productivity during the period studied. Over a longer period, one HIT vendor selection strategy may yet prove to be more effective at improving efficiency and productivity.

Anticonvulsant medication errors in children with epilepsy during the home-to-hospital transition.

Children with epilepsy are at risk of having their anticonvulsant regimens disrupted during the home-to-hospital transition. We sought to estimate the frequency of anticonvulsant medication errors during transition into the hospital in children with epilepsy hospitalized for reasons other than seizures, and to examine factors associated with the occurrence of such errors. We examined the medical records to identify errors related to anticonvulsant administration during the transition into the hospital and we examined potential risk factors for error occurrence. Errors were classified as relating to dosing quantity or missing a dose. Among 120 children, 29 (24%) experienced an anticonvulsant medication error. In a multivariable model, the risk factors of changes in responsibility for anticonvulsant administration and frequency of anticonvulsant administration were strongly associated with increased odds of errors. Anticonvulsant medication errors during the home-to-hospital transition may be unacceptably common in children with epilepsy hospitalized for reasons other than seizures.

Emergency Information Forms for Children With Medical Complexity: A Simulation Study

BACKGROUND: Emergency information forms (EIFs) have been proposed to provide critical information for optimal care of children with medical complexity (CMC) during emergencies; however, their impact has not been studied. The objective of this study was to measure the impact and utility of EIFs in simulated scenarios of CMC during medical emergencies. METHODS: Twenty-four providers (12 junior, 12 experienced) performed 4 simulations of CMC, where access to an EIF was block randomized by group. Scenario-specific critical action checklists and consequential pathways were developed by content experts in simulation and pediatric subspecialists. Scenarios ended when all critical actions were completed or after 10 minutes, whichever came first. Two reviewers independently evaluated the video-recorded performances and calculated scenario-specific critical action scores. Performance in scenarios with and without an EIF was compared with Pearson’s χ2 and Mann–Whitney U tests. Interrater reliability was assessed with intraclass correlation. Each provider rated the utility of EIFs via exit questionnaires. RESULTS: The median critical action score in scenarios with EIFs was 84.2% (95% confidence interval [CI], 71.7%–94.1%) versus 12.5% (95% CI, 10.5%–35.3%) in scenarios without an EIF (P < .001); time to completion of scenarios was shorter (6.9 minutes [interquartile range 5.8–10 minutes] vs 10 minutes), and complication rates were lower (30% [95% CI, 17.4%–46.3%] vs 100% [95% CI, 92.2%–100%]) with EIFs, independent of provider experience. Interrater reliability was excellent (intraclass correlation = 0.979). All providers strongly agreed that EIFs can improve clinical outcomes for CMC. CONCLUSIONS: Using simulated scenarios of CMC, providers’ performance was superior with an EIF. Clinicians evaluated the utility of EIFs very highly.

Factors Associated With Meaningful Use Incentives in Children’s Hospitals

BACKGROUND AND OBJECTIVE: Among children’s hospitals, little is known about how barriers to electronic health record (EHR) adoption are related to meaningful use (MU) incentives. We investigated hospital success with MU incentive payments and determined associations with hospital-reported challenges and characteristics. METHODS: A survey administered to 224 Children’s Hospital Association hospitals assessed a variety of potential challenges to achieving meaningful EHR use (eg, lack of access to capital) and specific MU criteria that would be challenging to fulfill (eg, implement clinical decision support rules). These results were combined with data on hospitals that received MU payments up to March 2014 and information on hospital characteristics. Associations between anticipated challenges, children’s hospital type, and receipt of MU incentives were evaluated in bivariate and multivariate analyses. RESULTS: One hundred thirty-three children hospitals completed the survey (response rate 59.4%). Thirty-five percent of responding children’s hospitals received MU incentive payments. The most frequently anticipated hospital challenges included the following: exchange clinical information with other providers outside your hospital system (49%), and generate numerator and denominator data for quality reporting directly from EHR (41%). Freestanding children’s hospitals were more likely to indicate lack of relevance of MU criteria to pediatric care (odds ratio: 37.6 [95% confidence interval: 4.6–309.3]) and more likely to receive MU incentive payments (odds ratio: 26 [95% confidence interval: 5.2–130.6]). CONCLUSIONS: As of 2014, a minority of children’s hospitals have successfully received MU incentive payments. Freestanding children’s hospitals are more likely to report MU is not relevant to pediatric care and to succeed with MU incentive payments.