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Emily Beth Devine, Erik Van Eaton, Megan E Zadworny, Rebecca Symons, Allison Devlin, David Yanez, Meliha Yetisgen, Katelyn R Keyloun, Daniel Capurro, Rafael Alfonso-Cristancho, David R Flum, Peter Tarczy-Hornoch
Background: The availability of high fidelity electronic health record (EHR) data is a hallmark of the learning health care system. Washington State's Surgical Care Outcomes and Assessment Program (SCOAP) is a network of hospitals participating in quality improvement (QI) registries wherein data are manually abstracted from EHRs. To create the Comparative Effectiveness Research and Translation Network (CERTAIN), we semi-automated SCOAP data abstraction using a centralized federated data model, created a central data repository (CDR), and assessed whether these data could be used as real world evidence for QI and research...
May 22, 2018: EGEMS
Zachary Burningham, Jianwei Leng, Celena B Peters, Tina Huynh, Ahmad Halwani, Randall Rupper, Bret Hicken, Brian C Sauer
Introduction: Patient Aligned Care Team (PACT) care managers are tasked with identifying aging Veterans with psychiatric disease in attempt to prevent psychiatric crises. However, few resources exist that use real-time information on patient risk to prioritize coordinating appropriate care amongst a complex aging population. Objective: To develop and validate a model to predict psychiatric hospital admission, during a 90-day risk window, in Veterans ages 65 or older with a history of mental health disease...
May 17, 2018: EGEMS
Priya Ramar, Daniel L Roellinger, Jon O Ebbert, Jenna K Lovely, Lindsey M Philpot
This case study describes the use of multiple administrative data sources within a large, integrated health care delivery system to understand opioid prescribing patterns across practice settings. We describe the information needed to understand prescribing patterns and target interventions, the process for identifying relevant institutional data sources that could be linked to provide information on the settings for prescriptions, and the lessons learned in developing, testing, and implementing an algorithm to link the data sources in a useful manner...
May 10, 2018: EGEMS
E A Bayliss, H A Tabano, T M Gill, K Anzuoni, M Tai-Seale, H G Allore, D A Ganz, S Dublin, A L Gruber-Baldini, A L Adams, K M Mazor
Context: Patient reported outcomes (PROs) are one means of systematically gathering meaningful subjective information for patient care, population health, and patient centered outcomes research. However, optimal data management for effective PRO applications is unclear. Case description: Delivery systems associated with the Health Care Systems Research Network (HCSRN) have implemented PRO data collection as part of the Medicare annual Health Risk Assessment (HRA)...
May 10, 2018: EGEMS
Samir Gupta, Lin Liu, Olga V Patterson, Ashley Earles, Ranier Bustamante, Andrew J Gawron, William K Thompson, William Scuba, Daniel Denhalter, M Elena Martinez, Karen Messer, Deborah A Fisher, Sameer D Saini, Scott L DuVall, Wendy W Chapman, Mary A Whooley, Tonya Kaltenbach
Objective: To describe a framework for leveraging big data for research and quality improvement purposes and demonstrate implementation of the framework for design of the Department of Veterans Affairs (VA) Colonoscopy Collaborative. Methods: We propose that research utilizing large-scale electronic health records (EHRs) can be approached in a 4 step framework: 1) Identify data sources required to answer research question; 2) Determine whether variables are available as structured or free-text data; 3) Utilize a rigorous approach to refine variables and assess data quality; 4) Create the analytic dataset and perform analyses...
April 13, 2018: EGEMS
Laura Goettinger Qualls, Thomas A Phillips, Bradley G Hammill, James Topping, Darcy M Louzao, Jeffrey S Brown, Lesley H Curtis, Keith Marsolo
Introduction: Distributed research networks (DRNs) are critical components of the strategic roadmaps for the National Institutes of Health and the Food and Drug Administration as they work to move toward large-scale systems of evidence generation. The National Patient-Centered Clinical Research Network (PCORnet®) is one of the first DRNs to incorporate electronic health record data from multiple domains on a national scale. Before conducting analyses in a DRN, it is important to assess the quality and characteristics of the data...
April 13, 2018: EGEMS
Adriana Arcia, Janet Woollen, Suzanne Bakken
Context: Tailored visualizations of patient reported outcomes (PROs) are valuable health communication tools to support shared decision making, health self-management, and engagement with research participants, such as cohorts in the NIH Precision Medicine Initiative. The automation of visualizations presents some unique design challenges. Efficient design processes depend upon gaining a thorough understanding of the data prior to prototyping. Case Description: We present a systematic method to exploring data attributes, with a specific focus on application to self-reported health data...
January 24, 2018: EGEMS
Lucas W Thornblade, David R Flum, Abraham D Flaxman
Background: Recurrent diverticulitis is the most common reason for elective colon surgery and, although professional societies now recommend against early resection, its use continues to rise. Shared decision making decreases use of low-value surgery but identifying which patients are most likely to elect surgery has proven difficult. We hypothesized that Machine Learning algorithms using health care utilization (HCU) data can predict future clinical events including early resection for diverticulitis...
January 24, 2018: EGEMS
Andrew J Knighton, Kimberly D Brunisholz, Samuel T Savitz
Introduction: Socio-economic status (SES) and low health literacy (LHL) are closely correlated. Both are directly associated with clinical and behavioral risk factors and healthcare outcomes. Learning healthcare systems are introducing small-area measures to address the challenges associated with maintaining patient-reported measures of SES and LHL. This study's purpose was to measure the association between two available census block measures associated with SES and LHL. Understanding the relationship can guide the identification of a multi-purpose area based measure for delivery system use...
December 15, 2017: EGEMS
Jordan Albritton, Thomas Belnap, Lucy Savitz
Research Objective: Determine whether hospitals are increasing the duration of observation stays following index admission for heart failure to avoid potential payment penalties from the Hospital Readmission Reduction Program. Study Design: The Hospital Readmission Reduction Program applies a 30-day cutoff after which readmissions are no longer penalized. Given this seemingly arbitrary cutoff, we use regression discontinuity design, a quasi-experimental research design that can be used to make causal inferences...
December 15, 2017: EGEMS
Genna R Cohen, David J Jones, Jessica Heeringa, Kirsten Barrett, Michael F Furukawa, Dan Miller, Anne Mutti, James D Reschovsky, Rachel Machta, Stephen M Shortell, Taressa Fraze, Eugene Rich
Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. A clearer understanding of how to leverage real-world data sources to empirically identify systems is a necessary first step to such policy-relevant research. We draw from our experience in the Agency for Healthcare Research and Quality's Comparative Health System Performance (CHSP) initiative to assess available data sources to identify and describe systems, including system members (for example, hospitals and physicians) and relationships among the members (for example, hospital ownership of physician groups)...
December 15, 2017: EGEMS
Brent C James, David P Edwards, Alan F James, Richard L Bradshaw, Keith S White, Chris Wood, Stan Huff
Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance. We combined an existing method for organizing complex computer systems-which we label activity-based design-with a proven approach for integrating clinical decision support into front-line care delivery-Care Process Models. The clinical decision support approach increased the structure of textual clinical documentation, to the point where established methods for converting text into computable data (natural language processing) worked efficiently...
December 15, 2017: EGEMS
Andreas Taenzer, Allison Kinslow, Christine Gorman, Shelley Schoepflin Sanders, Shilpa J Patel, Sally Kraft, Lucy Savitz
The dissemination of evidence-based best practice through the entire health care system remains an elusive goal, despite public pressure and regulatory guidance. Many patients do not receive the same quality of care at different hospitals across the same health care system. We describe the role of a data driven learning collaborative, the High Value Healthcare Collaborative (HVHC), in the dissemination of best practice using adherence to the 3-hour-bundle for sepsis care. Compliance with and adoption of sepsis bundle care elements comparing sites with mature vs non-mature care delivery processes were measured during the improvement effort for a cohort of 20,758 patients...
December 15, 2017: EGEMS
Gavin Welch, Friedrich von Recklinghausen, Andreas Taenzer, Lucy Savitz, Lisa Weiss
Context: The High Value Healthcare Collaborative (HVHC) sepsis project was a two-year multi-site project where Member health care delivery systems worked on improving sepsis care using a dissemination & implementation framework designed by HVHC. As part of the project evaluation, participating Members provided 5 data submissions over the project period. Members created data files using a uniform specification, but the data sources and methods used to create the data sets differed...
December 15, 2017: EGEMS
Friedrich Maximilian von Recklinghausen, Andreas Taenzer, Chrissie Gorman, Jay Knowlton, Allison Kinslow, Ron Russell
Introduction: Intensive Care Unit (ICU) length of stay is a strong indicator of severity of illness and cost in the care of sepsis patients. In this case study, we examine the difference between an electronic health record (EHR) based submissions with Centers for Medicare and Medicaid Services (CMS) payment data. Methods: Member submitted EHR data contained 26,733 unique patient's records. The CMS data contained demographics, diagnosis, and revenue codes. After linking EHR data to CMS data, we found a discrepancy in ICU days from CMS claims vs...
December 15, 2017: EGEMS
Jay Knowlton, Tom Belnap, Bonnie Patelesio, Elisa L Priest, Friedrich von Recklinghausen, Andreas H Taenzer
Introduction: Health systems can be supported by collaborative networks focused on data sharing and comparative analytics to identify and rapidly disseminate promising care practices. Standardized data collection, quality assessment, and cleansing is a necessary process to facilitate meaningful analytics for operations, quality improvement, and research. We developed a framework for aligning data from health care delivery systems using the High Value Healthcare Collaborative central registry...
December 15, 2017: EGEMS
Lucy A Savitz, Lisa T Weiss
The purpose of this special issue is to disseminate learning from the High Value Healthcare Collaborative (HVHC). The HVHC is a voluntary, member-led organization based on trusted, working relationships among delivery system leaders. HVHC's mission is to be a provider-based learning health system committed to improving healthcare value through data, evidence, and collaboration. We begin by describing the organization and structure of HVHC in order to lay the context for a series of papers that feature work from this learning health system...
December 15, 2017: EGEMS
Michael Stoto, Gareth Parry, Lucy Savitz
The last in a series of four papers on how learning health systems can use routinely collected electronic health data (EHD) to advance knowledge and support continuous learning, this review describes how delivery system science provides a systematic means to answer questions that arise in translating complex interventions to other practice settings. When the focus is on translation and spread of innovations, the questions are different than in evaluative research. Causal inference is not the main issue, but rather one must ask: How and why does the intervention work? What works for whom and in what contexts? How can a model be amended to work in new settings? In these settings, organizational factors and design, infrastructure, policies, and payment mechanisms all influence an intervention's success, so a theory-driven formative evaluation approach that considers the full path of the intervention from activities to engage participants and change how they act to the expected changes in clinical processes and outcomes is needed...
December 7, 2017: EGEMS
Seth Blumenthal
Introduction: The use of information from clinical registries for improvement and value-based payment is increasing, yet information about registry use is not widely available. We conducted a landscape survey to understand registry uses, focus areas and challenges. The survey addressed the structure and organization of registry programs, as well as their purpose and scope. Setting: The survey was conducted by the National Quality Registry Network (NQRN), a community of organizations interested in registries...
December 7, 2017: EGEMS
Michael Stoto, Michael Oakes, Elizabeth Stuart, Randall Brown, Jelena Zurovac, Elisa L Priest
The third paper in a series on how learning health systems can use routinely collected electronic health data (EHD) to advance knowledge and support continuous learning, this review describes how analytical methods for individual-level electronic health data EHD, including regression approaches, interrupted time series (ITS) analyses, instrumental variables, and propensity score methods, can also be used to address the question of whether the intervention "works." The two major potential sources of bias in non-experimental studies of health care interventions are that the treatment groups compared do not have the same probability of treatment or exposure and the potential for confounding by unmeasured covariates...
December 7, 2017: EGEMS
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