[Show abstract][Hide abstract] ABSTRACT: Integration of disparate information from electronic health records, clinical
data warehouses, birth certificate registries and other public health
information systems offers great potential for clinical care, public health
practice, and research. Such integration, however, depends on correctly matching
patient-specific records using demographic identifiers. Without standards for
these identifiers, record linkage is complicated by issues of structural and
Objectives: Our objectives were to develop and validate an ontology to: 1)
identify components of identity and events subsequent to birth that result in
creation, change, or sharing of identity information; 2) develop an ontology to
facilitate data integration from multiple healthcare and public health sources;
and 3) validate the ontology’s ability to model identity-changing events
Methods: We interviewed domain experts in area hospitals and public health
programs and developed process models describing the creation and transmission
of identity information among various organizations for activities subsequent to
a birth event. We searched for existing relevant ontologies. We validated the
content of our ontology with simulated identity information conforming to
scenarios identified in our process models.
Results: We chose the Simple Event Model (SEM) to describe events in early
childhood and integrated the Clinical Element Model (CEM) for demographic
information. We demonstrated the ability of the combined SEM-CEM ontology to
model identity events over time.
Conclusion: The use of an ontology can overcome issues of semantic and syntactic
heterogeneity to facilitate record linkage.
[Show abstract][Hide abstract] ABSTRACT: Introduction:
Identity information is often used to link records within or among information systems in public health and clinical settings. The quality and stability of birth certificate identifiers impacts both the success of linkage efforts and the value of birth certificate registries for identity resolution.
Our objectives were to describe: (1) the frequency and cause of changes to birth certificate identifiers as children age, and (2) the frequency of events (ie, adoptions, paternities, amendments) that may trigger changes and their impact on names.
We obtained two de-identified datasets from the Utah birth certificate registry: (1) change history from 2000 to 2012, and (2) occurrences for adoptions, paternities, and amendments among births in 1987 and 2000. We conducted cohort analyses for births in 1987 and 2000, examining the number, reason, and extent of changes over time. We conducted cross-sectional analyses to assess the patterns of changes between 2000 and 2012.
In a cohort of 48 350 individuals born in 2000 in Utah, 3164 (6.5%) experienced a change in identifiers prior to their 13th birthday, with most changes occurring before 2 years of age. Cross-sectional analysis showed that identifiers are stable for individuals over 5 years of age, but patterns of changes fluctuate considerably over time, potentially due to policy and social factors.
Identities represented in birth certificates change over time. Specific events that cause changes to birth certificates also fluctuate over time. Understanding these changes can help in the development of automated strategies to improve identity resolution.
Journal of the American Medical Informatics Association 07/2014; 22(e1). DOI:10.1136/amiajnl-2014-002774 · 3.50 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Institutional Review Boards (IRBs) are a critical component of clinical research and can become a significant bottleneck due to the dramatic increase, in both volume and complexity of clinical research. Despite the interest in developing clinical research informatics (CRI) systems and supporting data standards to increase clinical research efficiency and interoperability, informatics research in the IRB domain has not attracted much attention in the scientific community. The lack of standardized and structured application forms across different IRBs causes inefficient and inconsistent proposal reviews and cumbersome workflows. These issues are even more prominent in multi-institutional clinical research that is rapidly becoming the norm. This paper proposes and evaluates a domain analysis model for electronic IRB (eIRB) systems, paving the way for streamlined clinical research workflow via integration with other CRI systems and improved IRB application throughput via computer-assisted decision support.
[Show abstract][Hide abstract] ABSTRACT: Electronic problem lists are essential to modern health record systems, with a primary goal to serve as the repository of a patient's current health issues. Additionally, coded problems can be used to drive downstream activities such as decision support, evidence-based medicine, billing, and cohort generation for research. Meaningful Use also requires use of a coded problem list. Over the course of three years, Intermountain Healthcare developed a problem management module (PMM) that provided innovative functionality to improve clinical workflow and boost problem list adoption, e.g. smart search, user customizable views, problem evolution, and problem timelines. In 23 months of clinical use, clinicians entered over 70,000 health issues, the percentage of free-text items dropped to 1.2%, completeness of problem list items increased by 14%, and more collaborative habits were initiated.
[Show abstract][Hide abstract] ABSTRACT: The sharing of personally identifiable information across organizational boundaries to facilitate patient identification in Utah presents significant policy challenges. Our objective was to create a focus area maturity model to describe and evaluate our progress in developing a policy framework to support a statewide master person index (sMPI) for healthcare and public health operations and research in Utah.
We used various artifacts, including minutes from policy guidance committee meetings over a span of 18 months, a report from Utah's Digital Health Services Commission, and a draft technical requirements document to retrospectively analyze our work and create a focus area maturity model describing the domain of policy needed to support the sMPI. We then used our model to assess our progress and future goals.
The focus area maturity model provides an orderly path that can guide the complex process of developing a functional statewide master person index among diverse, autonomous partners. While this paper focuses on our experience in Utah, we believe that the arguments for using a focus area maturity model to guide the development of state or regional MPIs is of general interest.
[Show abstract][Hide abstract] ABSTRACT: How can health sciences librarians and biomedical informaticians offer relevant support to Clinical and Translational Science Award (CTSA) personnel?
The Spencer S. Eccles Health Sciences Library and the associate vice president for information technology for the health sciences office at the University of Utah conducted a needs assessment.
Faculty and staff from these two units, with the services of a consultant and other CTSA partners, employed a survey, focus groups, interviews, and committee discussions. An information portal was created to meet identified needs.
A directive white paper was created. The process employed to plan a virtual and physical collaborative, collegial space for clinical researchers at the university and its three inter-institutional CTSA partners is described.
The university's model can assist other librarians and informaticians with how to become part of a CTSA-focused infrastructure for clinical and translational research and serve researchers in general.
Journal of the Medical Library Association JMLA 02/2013; 101(1):4-11. DOI:10.3163/1536-5050.101.1.002 · 0.99 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We designed and implemented an electronic patient tracking system with improved user authentication and patient selection. We then measured access to clinical information from previous clinical encounters before and after implementation of the system. Clinicians accessed longitudinal information for 16% of patient encounters before, and 40% of patient encounters after the intervention, indicating such a system can improve clinician access to information. We also attempted to evaluate the impact of providing this access on inpatient admissions from the emergency department, by comparing the odds of inpatient admission from an emergency department before and after the improved access was made available. Patients were 24% less likely to be admitted after the implementation of improved access. However, there were many potential confounders, based on the inherent pre-post design of the evaluation. Our experience has strong implications for current health information exchange initiatives.
[Show abstract][Hide abstract] ABSTRACT: Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for uncertain or novel gene variants in an objective manner. Here, complementary predictors for missense gene variants were incorporated into a weighted Consensus framework that includes calculated reference intervals from known disease outcomes. Data visualization for clinical reporting is also discussed.
Genome Medicine 05/2012; 4(5):48. DOI:10.1186/gm347 · 5.34 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery of genome variation in humans. A growing number of authoritative clinical repositories archive gene variants and disease phenotypes, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here the evaluation is presented of "gene-specific" predictor models based on a naïve Bayesian classifier for 20 gene-disease datasets, containing 3986 variants with clinically characterized patient conditions. The utility of gene-specific prediction is then compared with "all-gene" generalized prediction and also with existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease datasets often outperform established generalized algorithms for novel and uncertain gene variants.
Journal of the American Medical Informatics Association 03/2012; 19(2):207-11. DOI:10.1136/amiajnl-2011-000309 · 3.50 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Clinical research, being patient-oriented, is based predominantly on clinical data— symptoms reported by patients, observations of patients made by healthcare providers, radiological images, and various metrics, including laboratory measurements that reflect physiological functions. Recently, however, a new type of data—genes and their products—has entered the picture, and the expectation is that given clinical conditions can ultimately be linked to the function of specific genes.
This new approach is a fruit of the pre-genomic era. That era, which lasted from 1990 to 2003, was defined by the Human Genome Project effort to sequence the nucleotides that make up the human genome and identify its ~25,000 genes. Since all humans have a unique nucleotide sequence, the data produced by this project represents not the genome of a single individual, but the aggregate genome of a small number of anonymous donors.
Completion of the effort ushered in the post-genomic era, characterized by the availability of the human genome as well as the complete genomes of numerous reference organisms. How genomic information feeds into clinical research is the topic of this chapter. We first review the molecules that form the “blueprint of life” and discuss the surrounding research methodologies. Then we discuss how genetic data are clinically integrated. Finally, we relate how this new type of data is used in different clinical research domains.
Clinical Research Informatics, 01/2012; Springer Verlag, London., ISBN: 978-1-84882-447-8
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] ABSTRACT: Microbiology study results are necessary for conducting many comparative effectiveness research studies. Unlike core laboratory test results, microbiology results have a complex structure. Federating and integrating microbiology data from six disparate electronic medical record systems is challenging and requires a team of varied skills. The PHIS+ consortium which is partnership between members of the Pediatric Research in Inpatient Settings (PRIS) network, the Children's Hospital Association and the University of Utah, have used "FURTHeR' for federating laboratory data. We present our process and initial results for federating microbiology data from six pediatric hospitals.
[Show abstract][Hide abstract] ABSTRACT: To evaluate the medical professionals and medical students perceived usefulness of an emergency medical card (EMC) and a continuity of care (CoC) report, in enhancing CoC.
The study reviewers included medical professionals from outpatient clinics at Intermountain Healthcare and fourth-year medical students from the University of Utah. Three cases we randomly extracted from a database of patients who had added new care information at the time. EMCs and CoC reports were populated for the cases, and information then de-identified. Using patient information in the electronic medical record (EMR), reviewers evaluated if the EMR information was adequate to support medical decisions made on the patient's diagnosis, medications, laboratory tests, and disposition. The reviewer assessed if the EMC and CoC report information would influence the medical decisions made. An online survey was used to assess the reviewers' perception on the usefulness of the two documents.
On average, 94% of the reviewers perceived the EMC to be useful in enhancing medical decision making at the point of care, and 74% found the CoC report to be useful. More specifically, the two documents were found to be useful in decreasing encounter time (100% each), increasing overall knowledge of healthcare providers (100% each), influencing decision on the treatment (94% each), and new laboratory test orders (87% and 90%, respectively).
The EMC and CoC report were found to be useful methods for transporting patient healthcare information across the healthcare continuum. The documents were found more specifically to be useful for effective decision making, improving efficiency and quality of care, at the point of care.
International Journal of Medical Informatics 06/2011; 80(6):412-20. DOI:10.1016/j.ijmedinf.2011.02.007 · 2.00 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We present a software architecture that federates data from multiple heterogeneous health informatics data sources owned by multiple organizations. The architecture builds upon state-of-the-art open-source Java and XML frameworks in innovative ways. It consists of (a) federated query engine, which manages federated queries and result set aggregation via a patient identification service; and (b) data source facades, which translate the physical data models into a common model on-the-fly and handle large result set streaming. System modules are connected via reusable Apache Camel integration routes and deployed to an OSGi enterprise service bus. We present an application of our architecture that allows users to construct queries via the i2b2 web front-end, and federates patient data from the University of Utah Enterprise Data Warehouse and the Utah Population database. Our system can be easily adopted, extended and integrated with existing SOA Healthcare and HL7 frameworks such as i2b2 and caGrid.
Journal of Medical Systems 05/2011; 35(5):1211-24. DOI:10.1007/s10916-011-9720-3 · 2.21 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Previous investigation at our resident-teaching, family medicine clinics determined that >80% of adult patients have body mass index (BMI) recorded in the electronic medical record. The quality of this measure, however, is not known. The objective of this study was to determine the accuracy of documented BMI. We used an observational study design to determine the means by which clinic staff obtain height and weight values from patients. We found that staff only obtained 35.4% of these measurements according to protocol. The major reason for noncompliance with protocol was that shoes were not removed for the measurements. Our investigation indicated that providers, quality improvement teams, and researchers should not assume the accuracy of the recorded BMI. Future investigation is warranted to improve the quality of these measurements in the outpatient setting.
[Show abstract][Hide abstract] ABSTRACT: To evaluate the patients' opinion on the usefulness of the electronic medical card (EMC) and continuity-of-care report in enhancing quality of care, and to assess the effects of the patient-entered data on the quality of data in the electronic medical record (EMR).
A structured survey assessed patients' opinion on the usefulness of the EMC and continuity-of-care report. The accuracy of EMR data involved comparing the patient-entered data in the continuity-of-care report with the healthcare-provider-entered data in the EMR. The analysis assessed whether the EMR information was consistent with the patient-entered data. A data completeness evaluation compared data entries in the EMR collected before and after the use of continuity-of-care record application.
One hundred and thirty-three patients used the application, of which 76% who had actually used the EMC and continuity-of-care report to seek medical care and/or update EMR information were surveyed. Age was associated with the reported usefulness of the documents. Few users (16%) printed the continuity-of-care reports to take to their healthcare providers for data updates and fewer (9%) to correct errors in the EMR. Overall, 68% of patients found the documents to be useful.
Patients reported that the EMC and continuity-of-care report were useful in enhancing quality of care. They were able to identify missing or erroneous data in the EMR data, making them an important source of quality control for their information in the healthcare-provider-maintained EMR.
International Journal for Quality in Health Care 02/2011; 23(1):60-7. DOI:10.1093/intqhc/mzq073 · 1.76 Impact Factor
[Show abstract][Hide abstract] 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.