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pediatric ehr

Derek J Williams, Yuwei Zhu, Carlos G Grijalva, Wesley H Self, Frank E Harrell, Carrie Reed, Chris Stockmann, Sandra R Arnold, Krow K Ampofo, Evan J Anderson, Anna M Bramley, Richard G Wunderink, Jonathan A McCullers, Andrew T Pavia, Seema Jain, Kathryn M Edwards
BACKGROUND: Substantial morbidity and excessive care variation are seen with pediatric pneumonia. Accurate risk-stratification tools to guide clinical decision-making are needed. METHODS: We developed risk models to predict severe pneumonia outcomes in children (<18 years) by using data from the Etiology of Pneumonia in the Community Study, a prospective study of community-acquired pneumonia hospitalizations conducted in 3 US cities from January 2010 to June 2012...
September 29, 2016: Pediatrics
Juan D Chaparro, David C Classen, Melissa Danforth, David C Stockwell, Christopher A Longhurst
OBJECTIVE: To evaluate the safety of computerized physician order entry (CPOE) and associated clinical decision support (CDS) systems in electronic health record (EHR) systems at pediatric inpatient facilities in the US using the Leapfrog Group's pediatric CPOE evaluation tool. METHODS: The Leapfrog pediatric CPOE evaluation tool, a previously validated tool to assess the ability of a CPOE system to identify orders that could potentially lead to patient harm, was used to evaluate 41 pediatric hospitals over a 2-year period...
September 16, 2016: Journal of the American Medical Informatics Association: JAMIA
Rachel Boykan, Carolyn Milana, Grace Propper, Patricia Bax, Paula Celestino
OBJECTIVES: (1) To implement a new policy-driven referral program, Opt-to-Quit, using electronic data transfer from the electronic health record (EHR) to the New York State Smokers' Quitline (NYSSQL) and (2) to improve referrals to the NYSSQL for smoking caregivers of children admitted to a children's hospital. METHODS: Smoking caregivers of pediatric patients were referred to the NYSSQL through a standardized template built into the EHR, during the child's hospitalization or emergency department encounter...
September 2016: Hospital Pediatrics
Christoph P Hornik, Daniel K Benjamin, P Brian Smith, Michael J Pencina, Adriana H Tremoulet, Edmund V Capparelli, Jessica E Ericson, Reese H Clark, Michael Cohen-Wolkowiez
OBJECTIVE: To evaluate the relationship between ampicillin dosing, exposure, and seizures. STUDY DESIGN: This was a retrospective observational cohort study of electronic health record (EHR) data combined with pharmacokinetic model derived drug exposure predictions. We used the EHR from 348 Pediatrix Medical Group neonatal intensive care units from 1997 to 2012. We included all infants 24-41 weeks gestational age, 500-5400 g birth weight, first exposed to ampicillin prior to 25 days postnatal age...
August 10, 2016: Journal of Pediatrics
Onur Asan, Richard J Holden, Kathryn E Flynn, Yushi Yang, Laila Azam, Matthew C Scanlon
OBJECTIVES: The purpose of this study was to explore providers' perspectives on the use of a novel technology, "Large Customizable Interactive Monitor" (LCIM), a novel application of the electronic health record system implemented in a Pediatric Intensive Care Unit. METHODS: We employed a qualitative approach to collect and analyze data from pediatric intensive care physicians, pediatric nurse practitioners, and acute care specialists. Using semi-structured interviews, we collected data from January to April, 2015...
2016: Applied Clinical Informatics
Todd Lingren, Vidhu Thaker, Cassandra Brady, Bahram Namjou, Stephanie Kennebeck, Jonathan Bickel, Nandan Patibandla, Yizhao Ni, Sara L Van Driest, Lixin Chen, Ashton Roach, Beth Cobb, Jacqueline Kirby, Josh Denny, Lisa Bailey-Davis, Marc S Williams, Keith Marsolo, Imre Solti, Ingrid A Holm, John Harley, Isaac S Kohane, Guergana Savova, Nancy Crimmins
OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR). INTRODUCTION: Childhood obesity increases risk factors for cardiovascular morbidity and vascular disease. Accurate definition of a high precision phenotype through a standardize tool is critical to the success of large-scale genomic studies and validating rare monogenic variants causing severe early onset obesity...
2016: Applied Clinical Informatics
Matthew W Miller, Rachael K Ross, Christina Voight, Heather Brouwer, Dean J Karavite, Jeffrey S Gerber, Robert W Grundmeier, Susan E Coffin
OBJECTIVE: To describe the use of digital images captured by parents or guardians and sent to clinicians for assessment of wounds after pediatric ambulatory surgery. METHODS: Subjects with digital images of post-operative wounds were identified as part of an on-going cohort study of infections after ambulatory surgery within a large pediatric healthcare system. We performed a structured review of the electronic health record (EHR) to determine how digital images were documented in the EHR and used in clinical care...
2016: Applied Clinical Informatics
Eric Tham, Marguerite Swietlik, Sara Deakyne, Jeffrey M Hoffman, Robert W Grundmeier, Marilyn D Paterno, Beatriz H Rocha, Molly H Schaeffer, Deepika Pabbathi, Evaline Alessandrini, Dustin Ballard, Howard S Goldberg, Nathan Kuppermann, Peter S Dayan
INTRODUCTION: For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial...
2016: Applied Clinical Informatics
Brian P Jenssen, Eric D Shelov, Christopher P Bonafide, Steven L Bernstein, Alexander G Fiks, Tyra Bryant-Stephens
OBJECTIVES: To create and evaluate the feasibility, acceptability, and usability of a clinical decision support (CDS) tool within the electronic health record (EHR) to help pediatricians provide smoking cessation counseling and treatment to parents of hospitalized children exposed to secondhand smoke (SHS). METHODS: Mixed method study of first-year pediatric residents on one inpatient unit. Residents received training in smoking cessation counseling, nicotine replacement therapy (NRT) prescribing, and use of a CDS tool to aid in this process...
2016: Applied Clinical Informatics
Judy Rashotte, Lara Varpio, Kathy Day, Craig Kuziemsky, Avi Parush, Pat Elliott-Miller, James W King, Tyson Roffey
INTRODUCTION: Members of the healthcare team must access and share patient information to coordinate interprofessional collaborative practice (ICP). Although some evidence suggests that electronic health records (EHRs) contribute to in-team communication breakdowns, EHRs are still widely hailed as tools that support ICP. If EHRs are expected to promote ICP, researchers must be able to longitudinally study the impact of EHRs on ICP across communication types, users, and physical locations...
September 2016: International Journal of Medical Informatics
Nicholas Edwardson, Bita A Kash, Ramkumar Janakiraman
We examine the impact of electronic health record (EHR) adoption on charge capture-the ability of providers to properly ensure that billable services are accurately recorded and reported for payment. Drawing on billing and practice management data from a large, integrated pediatric primary care network that was previously a paper-based organization, monthly encounter, charge, and collection data were collected from 2008 through 2013. Two-level fixed effects models were built to test the impact of EHR adoption on charge capture...
July 13, 2016: Medical Care Research and Review: MCRR
Caleb Hui, Regis Vaillancourt, Lissa Bair, Elaine Wong, James W King
BACKGROUND: Detection, monitoring and treatment of adverse drug reactions (ADRs) are paramount to patient safety. The use of a comprehensive electronic health record (EHR) system has the potential to address inadequacies in ADR documentation and to facilitate ADR reporting to health agencies. However, effective methods to maintain the quality of documented ADRs within an EHR have not been well studied. OBJECTIVE: To evaluate the accuracy and effectiveness of ADR documentation transfer throughout the implementation of a comprehensive EHR system...
June 2016: Drugs—Real World Outcomes
David A Hanauer, Greta L Branford, Grant Greenberg, Sharon Kileny, Mick P Couper, Kai Zheng, Sung W Choi
This report describes a 2-year prospective, longitudinal survey of attending physicians in 3 clinical areas (family medicine, general pediatrics, internal medicine) who experienced a transition from a homegrown electronic health record (EHR) to a vendor EHR. Participants were already highly familiar with using EHRs. Data were collected 1 month before and 3, 6, 13, and 25 months post implementation. Our primary goal was to determine if perceptions followed a J-curve pattern in which they initially dropped but eventually surpassed baseline measures...
July 3, 2016: Journal of the American Medical Informatics Association: JAMIA
Shannon F Manzi, Vincent A Fusaro, Laura Chadwick, Catherine Brownstein, Catherine Clinton, Kenneth D Mandl, Wendy A Wolf, Jared B Hawkins
OBJECTIVE: This paper outlines the implementation of a comprehensive clinical pharmacogenomics (PGx) service within a pediatric teaching hospital and the integration of clinical decision support in the electronic health record (EHR). MATERIALS AND METHODS: An approach to clinical decision support for medication ordering and dispensing driven by documented PGx variant status in an EHR is described. A web-based platform was created to automatically generate a clinical report from either raw assay results or specified diplotypes, able to parse and combine haplotypes into an interpretation for each individual and compared to the reference lab call for accuracy...
June 14, 2016: Journal of the American Medical Informatics Association: JAMIA
Kevin Bretonnel Cohen, Benjamin Glass, Hansel M Greiner, Katherine Holland-Bouley, Shannon Standridge, Ravindra Arya, Robert Faist, Diego Morita, Francesco Mangano, Brian Connolly, Tracy Glauser, John Pestian
We describe the development and evaluation of a system that uses machine learning and natural language processing techniques to identify potential candidates for surgical intervention for drug-resistant pediatric epilepsy. The data are comprised of free-text clinical notes extracted from the electronic health record (EHR). Both known clinical outcomes from the EHR and manual chart annotations provide gold standards for the patient's status. The following hypotheses are then tested: 1) machine learning methods can identify epilepsy surgery candidates as well as physicians do and 2) machine learning methods can identify candidates earlier than physicians do...
2016: Biomedical Informatics Insights
Kristy B Arbogast, Allison E Curry, Melissa R Pfeiffer, Mark R Zonfrillo, Juliet Haarbauer-Krupa, Matthew J Breiding, Victor G Coronado, Christina L Master
IMPORTANCE: Previous epidemiologic research on concussions has primarily been limited to patient populations presenting to sport concussion clinics or to emergency departments (EDs) and to those high school age or older. By examining concussion visits across an entire pediatric health care network, a better estimate of the scope of the problem can be obtained. OBJECTIVE: To comprehensively describe point of entry for children with concussion, overall and by relevant factors including age, sex, race/ethnicity, and payor, to quantify where children initially seek care for this injury...
July 5, 2016: JAMA Pediatrics
E Melinda Mahabee-Gittens, Judith W Dexheimer, Jane C Khoury, Julie A Miller, Judith S Gordon
BACKGROUND: Tobacco smoke exposure (TSE) is unequivocally harmful to children's health, yet up to 48% of children who visit the pediatric emergency department (PED) and urgent care setting are exposed to tobacco smoke. The incorporation of clinical decision support systems (CDSS) into the electronic health records (EHR) of PED patients may improve the rates of screening and brief TSE intervention of caregivers and result in decreased TSE in children. OBJECTIVE: We propose a study that will be the first to develop and evaluate the integration of a CDSS for Registered Nurses (RNs) into the EHR of pediatric patients to facilitate the identification of caregivers who smoke and the delivery of TSE interventions to caregivers in the urgent care setting...
2016: JMIR Research Protocols
Rajiv B Kumar, Nira D Goren, David E Stark, Dennis P Wall, Christopher A Longhurst
The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data communication bridge via a patient's/parent's smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits...
May 2016: Journal of the American Medical Informatics Association: JAMIA
Scott M Sutherland, David C Kaelber, N Lance Downing, Veena V Goel, Christopher A Longhurst
Initially described more than 50 years ago, electronic health records (EHRs) are now becoming ubiquitous throughout pediatric health care settings. The confluence of increased EHR implementation and the exponential growth of digital data within them, the development of clinical informatics tools and techniques, and the growing workforce of experienced EHR users presents new opportunities to use EHRs to augment clinical discovery and improve pediatric patient care. This article reviews the basic concepts surrounding EHR-enabled research and clinical discovery, including the types and fidelity of EHR data elements, EHR data validation/corroboration, and the steps involved in analytical interrogation...
April 2016: Pediatric Clinics of North America
Jason C Fisher, David H Godfried, Jennifer Lighter-Fisher, Joseph Pratko, Mary Ellen Sheldon, Thelma Diago, Keith A Kuenzler, Sandra S Tomita, Howard B Ginsburg
PURPOSE: Quality improvement (QI) bundles have been widely adopted to reduce surgical site infections (SSI). Improvement science suggests when organizations achieve high-reliability to QI processes, outcomes dramatically improve. However, measuring QI process compliance is poorly supported by electronic health record (EHR) systems. We developed a custom EHR tool to facilitate capture of process data for SSI prevention with the aim of increasing bundle compliance and reducing adverse events...
June 2016: Journal of Pediatric Surgery
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