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1.
J Am Med Inform Assoc ; 24(6): 1134-1141, 2017 Nov 01.
Article in English | MEDLINE | ID: mdl-29016972

ABSTRACT

OBJECTIVE: One promise of nationwide adoption of electronic health records (EHRs) is the availability of data for large-scale clinical research studies. However, because the same patient could be treated at multiple health care institutions, data from only a single site might not contain the complete medical history for that patient, meaning that critical events could be missing. In this study, we evaluate how simple heuristic checks for data "completeness" affect the number of patients in the resulting cohort and introduce potential biases. MATERIALS AND METHODS: We began with a set of 16 filters that check for the presence of demographics, laboratory tests, and other types of data, and then systematically applied all 216 possible combinations of these filters to the EHR data for 12 million patients at 7 health care systems and a separate payor claims database of 7 million members. RESULTS: EHR data showed considerable variability in data completeness across sites and high correlation between data types. For example, the fraction of patients with diagnoses increased from 35.0% in all patients to 90.9% in those with at least 1 medication. An unrelated claims dataset independently showed that most filters select members who are older and more likely female and can eliminate large portions of the population whose data are actually complete. DISCUSSION AND CONCLUSION: As investigators design studies, they need to balance their confidence in the completeness of the data with the effects of placing requirements on the data on the resulting patient cohort.


Subject(s)
Data Accuracy , Electronic Health Records , Bias , Humans , Information Storage and Retrieval , Insurance Claim Reporting
2.
Int J Pediatr ; 2016: 4068582, 2016.
Article in English | MEDLINE | ID: mdl-27698673

ABSTRACT

Background and Objectives. The prevalence of severe obesity in children has doubled in the past decade. The objective of this study is to identify the clinical documentation of obesity in young children with a BMI ≥ 99th percentile at two large tertiary care pediatric hospitals. Methods. We used a standardized algorithm utilizing data from electronic health records to identify children with severe early onset obesity (BMI ≥ 99th percentile at age <6 years). We extracted descriptive terms and ICD-9 codes to evaluate documentation of obesity at Boston Children's Hospital and Cincinnati Children's Hospital and Medical Center between 2007 and 2014. Results. A total of 9887 visit records of 2588 children with severe early onset obesity were identified. Based on predefined criteria for documentation of obesity, 21.5% of children (13.5% of visits) had positive documentation, which varied by institution. Documentation in children first seen under 2 years of age was lower than in older children (15% versus 26%). Documentation was significantly higher in girls (29% versus 17%, p < 0.001), African American children (27% versus 19% in whites, p < 0.001), and the obesity focused specialty clinics (70% versus 15% in primary care and 9% in other subspecialty clinics, p < 0.001). Conclusions. There is significant opportunity for improvement in documentation of obesity in young children, even years after the 2007 AAP guidelines for management of obesity.

4.
AMIA Annu Symp Proc ; 2011: 994-1003, 2011.
Article in English | MEDLINE | ID: mdl-22195159

ABSTRACT

Integrating clinical data with administrative data across disparate electronic medical record systems will help improve the internal and external validity of comparative effectiveness research. The Pediatric Health Information System (PHIS) currently collects administrative information from 43 pediatric hospital members of the Child Health Corporation of America (CHCA). Members of the Pediatric Research in Inpatient Settings (PRIS) network have partnered with CHCA and the University of Utah Biomedical Informatics Core to create an enhanced version of PHIS that includes clinical data. A specialized version of a data federation architecture from the University of Utah ("FURTHeR") is being developed to integrate the clinical data from the member hospitals into a common repository ("PHIS+") that is joined with the existing administrative data. We report here on our process for the first phase of federating lab data, and present initial results.


Subject(s)
Databases, Factual , Hospital Information Systems/organization & administration , Hospitals, Pediatric/organization & administration , Academic Medical Centers , Comparative Effectiveness Research , Health Information Systems , United States
5.
AMIA Annu Symp Proc ; 2010: 652-6, 2010 Nov 13.
Article in English | MEDLINE | ID: mdl-21347059

ABSTRACT

It is accepted that intravenous fluid (IVF) therapy can result in hospital-acquired dysnatremias in pediatric patients, with associated morbidity and mortality. There is interest in improving IVF therapy to prevent dysnatremias, but the optimal approach is controversial. In this study, we develop Natremia Deviation and Intravenous Renderer (NaDIR), a tool that preprocesses large volumes of electronic medical record data obtained from an academic pediatric hospital in order to analyze (1) IVF therapy, (2) the epidemiology of dysnatremias, and (3) the impact of IVFs on changes in serum sodium (ΔS(Na)). We then applied NaDIR to 3,256 inpatient records over a 3 month period, which revealed (1) a 19.9% incidence of dysnatremias, (2) a significant increase in lengths of stay associated with dysnatremias, and (3) a novel linear relationship between ΔS(Na) and IVF tonicity. This demonstrates that EMR data that can be readily analyzed to discover epidemiologic and predictive knowledge.


Subject(s)
Hypernatremia , Hyponatremia , Child , Electronic Health Records , Fluid Therapy , Humans , Sodium
6.
AMIA Annu Symp Proc ; : 831, 2003.
Article in English | MEDLINE | ID: mdl-14728336

ABSTRACT

Personal computing devices such as personal organizers, handheld PC's, and tablet PC's are becoming common tools in clinical care and medical education. There is an increasing need for these devices to track various tasks students and medical trainees perform. In particular, in undergraduate medical education, there is a need for tracking the depth and breadth of each student's clinical encounters over the course of his or her education. The authors have developed an application which allows for easy and rapid deployment of a tracking system for medical students' experiences during their clinical training years.


Subject(s)
Computers, Handheld , Education, Medical, Undergraduate , Internet , Data Collection , Humans , Pennsylvania
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