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Margo Edmunds, Reed Tuckson, Joy Lewis, Brian Atchinson, Karen Rheuban, Hank Fanberg, Lois Olinger, Robert Rosati, Cheryl Austein-Casnoff, Gary Capistrant, Latoya Thomas
CONTEXT: Telehealth is a fast-growing sector in health care, using a variety of technologies to exchange information across locations and to improve access, quality, and outcomes across the continuum of care. Thousands of studies and hundreds of systematic reviews have been done, but their variability leaves many questions about telehealth's effectiveness, implementation priorities, and return on investment. OBJECTIVES: There is an urgent need for a systematic, policy-relevant framework to integrate regulatory, operational, and clinical factors and to guide future investments in telehealth research and practice...
2017: EGEMS
Sarah Knerr, Elaine Y Hu, Steven B Zeliadt
INTRODUCTION: The frequency of neutropenia associated with lung cancer chemotherapy outside of randomized trials is largely unknown because administrative coding underestimates its prevalence. This study compared International Classification of Diseases (ICD) diagnosis codes and electronic laboratory results, alone and in combination, for identifying neutropenia events. METHODS: Retrospective cohort study of 718 veterans receiving their first course of chemotherapy for non-small cell lung cancer...
2017: EGEMS
Julie K Bower, Claire E Bollinger, Randi E Foraker, Darryl B Hood, Abigail B Shoben, Albert M Lai
INTRODUCTION: With the growing use of electronic medical records, electronic health records (EHRs), and personal health records (PHRs) for health care delivery, new opportunities have arisen for population health researchers. Our objective was to characterize PHR users and examine sample representativeness and nonresponse bias in a study of pregnant women recruited via the PHR. DESIGN: Demographic characteristics were examined for PHR users and nonusers. Enrolled study participants (responders, n=187) were then compared with nonresponders and a representative sample of the target population...
2017: EGEMS
Ken Kleinman, Susan S Huang
BACKGROUND: A key requirement for a useful power calculation is that the calculation mimic the data analysis that will be performed on the actual data, once that data is observed. Close approximations may be difficult to achieve using analytic solutions, however, and thus Monte Carlo approaches, including both simulation and bootstrap resampling, are often attractive. One setting in which this is particularly true is cluster-randomized trial designs. However, Monte Carlo approaches are useful in many additional settings as well...
2016: EGEMS
Eva Chang, Diana Sm Buist, Matthew Handley, Roy Pardee, Gabrielle Gundersen, Robert J Reid
OBJECTIVES: There has been significant research on provider attribution for quality and cost. Low-value care is an area of heightened focus, with little of the focus being on measurement; a key methodological decision is how to attribute delivered services and procedures. We illustrate the difference in relative and absolute physician- and panel-attributed services and procedures using overuse in cervical cancer screening. STUDY DESIGN: A retrospective, cross-sectional study in an integrated health care system...
2016: EGEMS
Barbara Sorondo, Amy Allen, Samreen Fathima, Janet Bayleran, Iyad Sabbagh
INTRODUCTION: This study assessed whether patient portals influence patients' ability for self-management, improve their perception of health state, improve their experience with primary care practices, and reduce healthcare utilization. METHODS: Patients participating in a nurse-led care coordination program received personalized training to use the portal to communicate with the care team. Data analysis included pre-post comparison of self-efficacy (CDSES), health state (EQVAS), functional status (PROMISĀ®), experience with the provider/practice (CG-CAHPS), and healthcare utilization (admissions and ED visits)...
2016: EGEMS
John W Nord, Alalia Berry, Barry Stults, Zachary Burningham, Srinivasan Beddhu
BACKGROUND: Patients with high total cholesterol have increased risk of cardiovascular disease. National Cholesterol Education Program (NCEP) and American Heart Association (AHA) guidelines recommend cholesterol lowering with statin medications; however, statin adherence remains poor. We hypothesized that patient-centered education on the 10-year risk for each of the major constituents of cardiovascular disease would increase statin adherence and achievement of the low-density lipoprotein cholesterol (LDL-C) goal...
2016: EGEMS
Katharine H McVeigh, Remle Newton-Dame, Pui Ying Chan, Lorna E Thorpe, Lauren Schreibstein, Kathleen S Tatem, Claudia Chernov, Elizabeth Lurie-Moroni, Sharon E Perlman
INTRODUCTION: Electronic health records (EHRs) offer potential for population health surveillance but EHR-based surveillance measures require validation prior to use. We assessed the validity of obesity, smoking, depression, and influenza vaccination indicators from a new EHR surveillance system, the New York City (NYC) Macroscope. This report is the second in a 3-part series describing the development and validation of the NYC Macroscope. The first report describes in detail the infrastructure underlying the NYC Macroscope; design decisions that were made to maximize data quality; characteristics of the population sampled; completeness of data collected; and lessons learned from doing this work...
2016: EGEMS
Lorna E Thorpe, Katharine H McVeigh, Sharon Perlman, Pui Ying Chan, Katherine Bartley, Lauren Schreibstein, Jesica Rodriguez-Lopez, Remle Newton-Dame
INTRODUCTION: Electronic health records (EHRs) can potentially extend chronic disease surveillance, but few EHR-based initiatives tracking population-based metrics have been validated for accuracy. We designed a new EHR-based population health surveillance system for New York City (NYC) known as NYC Macroscope. This report is the third in a 3-part series describing the development and validation of that system. The first report describes governance and technical infrastructure underlying the NYC Macroscope...
2016: EGEMS
Remle Newton-Dame, Katharine H McVeigh, Lauren Schreibstein, Sharon Perlman, Elizabeth Lurie-Moroni, Laura Jacobson, Carolyn Greene, Elisabeth Snell, Lorna E Thorpe
INTRODUCTION: Electronic health records (EHRs) have the potential to offer real-time, inexpensive standardized health data about chronic health conditions. Despite rapid expansion, EHR data evaluations for chronic disease surveillance have been limited. We present design and methods for the New York City (NYC) Macroscope, an EHR-based chronic disease surveillance system. This methods report is the first in a three part series describing the development and validation of the NYC Macroscope...
2016: EGEMS
Christine B Turley, Jihad Obeid, Rick Larsen, Katrina M Fryar, Leslie Lenert, Arik Bjorn, Genevieve Lyons, Jay Moskowitz, Iain Sanderson
Learning Health Systems (LHS) require accessible, usable health data and a culture of collaboration-a challenge for any single system, let alone disparate organizations, with macro- and micro-systems. Recently, the National Science Foundation described this important setting as a cyber-social ecosystem. In 2004, in an effort to create a platform for transforming health in South Carolina, Health Sciences South Carolina (HSSC) was established as a research collaboration of the largest health systems, academic medical centers and research intensive universities in South Carolina...
2016: EGEMS
Vojtech Huser, Frank J DeFalco, Martijn Schuemie, Patrick B Ryan, Ning Shang, Mark Velez, Rae Woong Park, Richard D Boyce, Jon Duke, Ritu Khare, Levon Utidjian, Charles Bailey
INTRODUCTION: Data quality and fitness for analysis are crucial if outputs of analyses of electronic health record data or administrative claims data should be trusted by the public and the research community. METHODS: We describe a data quality analysis tool (called Achilles Heel) developed by the Observational Health Data Sciences and Informatics Collaborative (OHDSI) and compare outputs from this tool as it was applied to 24 large healthcare datasets across seven different organizations...
2016: EGEMS
Nicholas G Wysham, Lynn Howie, Krish Patel, C Blake Cameron, Gregory P Samsa, Laura Roe, Amy P Abernethy, Aimee Zaas
CONTEXT: In the emerging Learning Health System (LHS), the application and generation of medical knowledge are a natural outgrowth of patient care. Achieving this ideal requires a physician workforce adept in information systems, quality improvement methods, and systems-based practice to be able to use existing data to inform future care. These skills are not currently taught in medical school or graduate medical education. CASE DESCRIPTION: We initiated a first-ever Learning Health Systems Training Program (LHSTP) for resident physicians...
2016: EGEMS
Richard D Boyce, Steven M Handler, Jordan F Karp, Subashan Perera, Charles F Reynolds
INTRODUCTION: A potential barrier to nursing home research is the limited availability of research quality data in electronic form. We describe a case study of converting electronic health data from five skilled nursing facilities to a research quality longitudinal dataset by means of open-source tools produced by the Observational Health Data Sciences and Informatics (OHDSI) collaborative. METHODS: The Long-Term Care Minimum Data Set (MDS), drug dispensing, and fall incident data from five SNFs were extracted, translated, and loaded into version 4 of the OHDSI common data model...
2016: EGEMS
Farrokh Alemi, Cari R Levy, Raya E Kheirbek
BACKGROUND: The Multimorbidity (MM) Index predicts the prognosis of patients from their diagnostic history. In contrast to existing approaches with broad diagnostic categories, it treats each diagnosis as a separate independent variable using individual International Classification of Disease, Revision 9 (ICD-9) codes. OBJECTIVE: This paper describes the MM Index, reviews the published data on its accuracy, and provides procedures for implementing the Index within electronic health record (EHR) systems...
2016: EGEMS
Anders Huitfeldt, Miguel A Hernan, Mette Kalager, James M Robins
INTRODUCTION: Because a comparison of noninitiators and initiators of treatment may be hopelessly confounded, guidelines for the conduct of observational research often recommend using an "active" comparator group consisting of people who initiate a treatment other than the medication of interest. In this paper, we discuss the conditions under which this approach is valid if the goal is to emulate a trial with an inactive comparator. IDENTIFICATION OF EFFECTS: We provide conditions under which a target trial in a subpopulation can be validly emulated from observational data, using an active comparator that is known or believed to be inactive for the outcome of interest...
2016: EGEMS
Jennifer Livaudais-Toman, Natalia Egorova, Rebeca Franco, Monica Prasad-Hayes, Elizabeth A Howell, Juan Wisnivesky, Nina A Bickell
OBJECTIVE: Administrative claims data offer an alternative to chart abstraction to assess ovarian cancer recurrence, treatment and outcomes. Such analyses have been hindered by lack of valid recurrence and treatment algorithms. In this study, we sought to develop claims-based algorithms to identify ovarian cancer recurrence and secondary debulking surgery, and to validate them against the gold-standard of chart abstraction. METHODS: We conducted chart validation studies; 2 recurrence algorithms and 1 secondary surgery among 94 ovarian cancer patients treated at one hospital between 2003-2009...
2016: EGEMS
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
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