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Michael G Kahn, Tiffany J Callahan, Juliana Barnard, Alan E Bauck, Jeff Brown, Bruce N Davidson, Hossein Estiri, Carsten Goerg, Erin Holve, Steven G Johnson, Siaw-Teng Liaw, Marianne Hamilton-Lopez, Daniella Meeker, Toan C Ong, Patrick Ryan, Ning Shang, Nicole G Weiskopf, Chunhua Weng, Meredith N Zozus, Lisa Schilling
OBJECTIVE: Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths and limitations of electronic health record (EHR) data for operational analytics, quality improvement, and research. Existing published DQ terms were harmonized to a comprehensive unified terminology with definitions and examples and organized into a conceptual framework to support a common approach to defining whether EHR data is 'fit' for specific uses...
2016: EGEMS
Jennifer C Nelson, Robert Wellman, Onchee Yu, Andrea J Cook, Judith C Maro, Rita Ouellet-Hellstrom, Denise Boudreau, James S Floyd, Susan R Heckbert, Simone Pinheiro, Marsha Reichman, Azadeh Shoaibi
INTRODUCTION: The large-scale assembly of electronic health care data combined with the use of sequential monitoring has made proactive postmarket drug- and vaccine-safety surveillance possible. Although sequential designs have been used extensively in randomized trials, less attention has been given to methods for applying them in observational electronic health care database settings. EXISTING METHODS: We review current sequential-surveillance planning methods from randomized trials, and the Vaccine Safety Datalink (VSD) and Mini-Sentinel Pilot projects-two national observational electronic health care database safety monitoring programs...
2016: EGEMS
Erin Holve, Samantha Weiss
In September 2015 the EDM Forum hosted AcademyHealth's newest national conference, Concordium. The 11 papers featured in the eGEMs "Concordium 2015" special issue successfully reflect the major themes and issues discussed at the meeting. Many of the papers address informatics or methodological approaches to natural language processing (NLP) or text analysis, which is indicative of the importance of analyzing text data to gain insights into care coordination and patient-centered outcomes. Perspectives on the tools and infrastructure requirements that are needed to build learning health systems were also recurrent themes...
2016: EGEMS
Andrew J Knighton, Lucy Savitz, Tom Belnap, Brad Stephenson, James VanDerslice
INTRODUCTION: Intermountain Healthcare is a fully integrated delivery system based in Salt Lake City, Utah. As a learning healthcare system with a mission of performance excellence, it became apparent that population health management and our efforts to move towards shared accountability would require additional patient-centric metrics in order to provide the right care to the right patients at the right time. Several European countries have adopted social deprivation indices in measuring the impact that social determinants can have on health...
2016: EGEMS
Barbara Sorondo, Amy Allen, Janet Bayleran, Stacy Doore, Samreen Fathima, Iyad Sabbagh, Lori Newcomb
INTRODUCTION: This project implemented an integrated patient self-reported screening tool in a patient portal and assessed clinical workflow and user experience in primary care practices. METHODS: An electronic health risk assessment based on the CMS Annual Wellness Visit (AWV) was developed to integrate self-reported health information into the patient's electronic health record (EHR). Patients enrolled in care coordination tested the implementation. The evaluation plan included quantitative and qualitative measures of patient adoption, provider adoption, workflow impact, financial impact, and technology impact...
2016: EGEMS
Wayne Psek, F Daniel Davis, Gloria Gerrity, Rebecca Stametz, Lisa Bailey-Davis, Debra Henninger, Dorothy Sellers, Jonathan Darer
INTRODUCTION: Healthcare leaders need operational strategies that support organizational learning for continued improvement and value generation. The learning health system (LHS) model may provide leaders with such strategies; however, little is known about leaders' perspectives on the value and application of system-wide operationalization of the LHS model. The objective of this project was to solicit and analyze senior health system leaders' perspectives on the LHS and learning activities in an integrated delivery system...
2016: EGEMS
Guy Divita, Marjorie E Carter, Le-Thuy Tran, Doug Redd, Qing T Zeng, Scott Duvall, Matthew H Samore, Adi V Gundlapalli
INTRODUCTION: Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of "best-of-breed" functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support. BACKGROUND: MetaMap, cTAKES and similar well-known natural language processing (NLP) tools do not have sufficient scalability out of the box...
2016: EGEMS
Mark E Patterson, Derick Miranda, Greg Schuman, Christopher Eaton, Andrew Smith, Brad Silver
BACKGROUND: Leveraging "big data" as a means of informing cost-effective care holds potential in triaging high-risk heart failure (HF) patients for interventions within hospitals seeking to reduce 30-day readmissions. OBJECTIVE: Explore provider's beliefs and perceptions about using an electronic health record (EHR)-based tool that uses unstructured clinical notes to risk-stratify high-risk heart failure patients. METHODS: Six providers from an inpatient HF clinic within an urban safety net hospital were recruited to participate in a semistructured focus group...
2016: EGEMS
Adrian Meyer, Laura Green, Ciearro Faulk, Stephen Galla, Anne-Marie Meyer
INTRODUCTION: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information. FRAMEWORK: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures...
2016: EGEMS
Donald A Szlosek, Jonathan Ferrett
INTRODUCTION: As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation...
2016: EGEMS
Andrew J Knighton, Tom Belnap, Kim Brunisholz, Kelly Huynh, Jay T Bishoff
INTRODUCTION: The introduction of the protein-specific antigen (PSA) test in care means that prostate cancer (PCa) is being detected earlier and more frequently. The result of increased screening using PSA, digital rectal examination and awareness of prostate was an increase in the number of men with low risk cancers. Active surveillance has become a viable alternative to immediate treatment with surgery, radiation and other forms of localized treatment. Evidence suggests that there is no significant difference in mortality rates between AS and surgery...
2016: EGEMS
Farhood Farjah, Scott Halgrim, Diana S M Buist, Michael K Gould, Steven B Zeliadt, Elizabeth T Loggers, David S Carrell
INTRODUCTION: The incidence of incidentally detected lung nodules is rapidly rising, but little is known about their management or associated patient outcomes. One barrier to studying lung nodule care is the inability to efficiently and reliably identify the cohort of interest (i.e. cases). Investigators at Kaiser Permanente Southern California (KPSC) recently developed an automated method to identify individuals with an incidentally discovered lung nodule, but the feasibility of implementing this method across other health systems is unknown...
2016: EGEMS
Sebastien Haneuse, Michael Daniels
Electronic health records (EHR) data are increasingly seen as a resource for cost-effective comparative effectiveness research (CER). Since EHR data are collected primarily for clinical and/or billing purposes, their use for CER requires consideration of numerous methodologic challenges including the potential for confounding bias, due to a lack of randomization, and for selection bias, due to missing data. In contrast to the recent literature on confounding bias in EHR-based CER, virtually no attention has been paid to selection bias possibly due to the belief that standard methods for missing data can be readily-applied...
2016: EGEMS
Rachel L Richesson, Michelle M Smerek, C Blake Cameron
INTRODUCTION: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups...
2016: EGEMS
Wayne Zachary, Russell Charles Maulitz, Drew A Zachary
INTRODUCTION: Care coordination (CC) is an important fulcrum for pursuing a range of health care goals. Current research and policy analyses have focused on aggregated data rather than on understanding what happens within individual cases. At the case level, CC emerges as a complex network of communications among providers over time, crossing and recrossing many organizational boundaries. Micro-level analysis is needed to understand where and how CC fails, as well as to identify best practices and root causes of problems...
2016: EGEMS
Elizabeth A Bayliss, J David Powers, Jennifer L Ellis, Jennifer C Barrow, MaryJo Strobel, Arne Beck
PURPOSE: Identifying care needs for newly enrolled or newly insured individuals is important under the Affordable Care Act. Systematically collected patient-reported information can potentially identify subgroups with specific care needs prior to service use. METHODS: We conducted a retrospective cohort investigation of 6,047 individuals who completed a 10-question needs assessment upon initial enrollment in Kaiser Permanente Colorado (KPCO), a not-for-profit integrated delivery system, through the Colorado State Individual Exchange...
2016: EGEMS
Christopher A Harle, Gloria Lipori, Robert W Hurley
INTRODUCTION: Advances in health policy, research, and information technology have converged to increase the electronic collection and use of patient-reported outcomes (PROs). Therefore, it is important to share lessons learned in implementing PROs in research information systems. CASE DESCRIPTION: The purpose of this case study is to describe a novel information system for electronic PROs and lessons learned in implementing that system to support research in an academic health center...
2016: EGEMS
Erin Holve
"Open science" includes a variety of approaches to facilitate greater access to data and the information produced by processes of scientific inquiry. Recently, the health sciences community has been grappling with the issue of potential pathways and models to achieve the goals of open science-namely, to create and rapidly share reproducible health research. eGEMs' continued dedication to and milestones regarding the publication of innovative, useful, and timely research to help contribute to the push towards open science is discussed, as well as the EDM Forum's new data sharing platform, CIELO...
2016: EGEMS
Oliwier Dziadkowiec, Tiffany Callahan, Mustafa Ozkaynak, Blaine Reeder, John Welton
OBJECTIVES: We examine the following: (1) the appropriateness of using a data quality (DQ) framework developed for relational databases as a data-cleaning tool for a data set extracted from two EPIC databases, and (2) the differences in statistical parameter estimates on a data set cleaned with the DQ framework and data set not cleaned with the DQ framework. BACKGROUND: The use of data contained within electronic health records (EHRs) has the potential to open doors for a new wave of innovative research...
2016: EGEMS
Jeremy Adler, Shehzad A Saeed, Ian S Eslick, Lloyd Provost, Peter A Margolis, Heather C Kaplan
INTRODUCTION: Improving symptoms for patients with chronic illness is difficult due to poor recall and imprecise assessments of therapeutic response to inform treatment decisions. Daily variation in symptoms may obscure subtle improvement or lead to erroneous associations between symptom changes and alteration in medication or dietary regimens. This may lead to mistaken impressions of treatment efficacy (or inefficacy). Mobile health technologies that collect daily patient reported outcome (PRO) data have the potential to improve care by providing more detailed information for clinical decision-making in practice and may facilitate conducting single subject (n-of-1) trials...
2016: EGEMS
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