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Mark Sendak, Michael Gao, Marshall Nichols, Anthony Lin, Suresh Balu
Examples of fully integrated machine learning models that drive clinical care are rare. Despite major advances in the development of methodologies that outperform clinical experts and growing prominence of machine learning in mainstream medical literature, major challenges remain. At Duke Health, we are in our fourth year developing, piloting, and implementing machine learning technologies in clinical care. To advance the translation of machine learning into clinical care, health system leaders must address barriers to progress and make strategic investments necessary to bring health care into a new digital age...
January 24, 2019: EGEMS
Danielle M Varda, Ayelet Talmi
Current approaches to addressing the problems families face when navigating complex service systems on behalf of their children rely largely on state or nationally driven efforts around the development of systems of care (SOCs). However, operationalizing meaningful family involvement within SOCs remains a challenge, with little attention paid to the role of personal social support networks (PSSNs). Specifically, risk factors related to the variations in the social connectedness of family social support networks are difficult to identify, assess, and track over time...
November 23, 2018: EGEMS
Sandra Long, Karen A Monsen, David Pieczkiewicz, Julian Wolfson, Saif Khairat
Objectives: This research tackles a critical issue in modern health care systems-namely, to determine if creating a user-centered health information system that is easy to utilize would lead to consumers who are more satisfied and more likely to accept the system. Materials and Methods: The health information system is a consumer service center that receives inquiries from consumers on how to find and pay for care. To understand if a system designed to decrease effort results in satisfaction, we redesigned the system, deployed it for 3 months, and then compared consumer satisfaction results to a control group...
October 3, 2018: EGEMS
Ragnhildur I Bjarnadottir, Robert J Lucero
Introduction: Hospital falls are a continuing clinical concern, with over one million falls occurring each year in the United States. Annually, hospital-acquired falls result in an estimated $34 billion in direct medical costs. Falls are considered largely preventable and, as a result, the Centers for Medicare and Medicaid Services have announced that fall-related injuries are no longer a reimbursable hospital cost. While policies and practices have been implemented to reduce falls, little sustained reduction has been achieved...
September 20, 2018: EGEMS
Sarah E Wiehe, Marc B Rosenman, David Chartash, Elaine R Lipscomb, Tammie L Nelson, Lauren A Magee, J Dennis Fortenberry, Matthew C Aalsma
Introduction: Although researchers recognize that sharing disparate data can improve population health, barriers (technical, motivational, economic, political, legal, and ethical) limit progress. In this paper, we aim to enhance the van Panhuis et al . framework of barriers to data sharing; we present a complementary solutions-based data-sharing process in order to encourage both emerging and established researchers, whether or not in academia, to engage in data-sharing partnerships. Brief Description of Major Components: We enhance the van Panhuis et al ...
August 22, 2018: EGEMS
Tammy Toscos, Maria Carpenter, Michelle Drouin, Amelia Roebuck, Abigail Howard, Mindy Flanagan, Connie Kerrigan
Introduction: A sizeable number of youth are currently struggling with anxiety, depression, and suicidal thoughts, yet many will not receive treatment. We sought to better understand if immediate response technology (IRT) could be used to gather mental health care data and educate youth on telemental health (TMH) resources. Methods: Using an IRT imbedded within an interactive, media-rich school-based presentation, we gathered mental health history and preferences for TMH resources from 2,789 adolescents with a wide range of demographic and psychological characteristics...
July 31, 2018: EGEMS
Xidong Deng, Terese Finitzo, Subhash Aryal
Improving quality measurement while reducing costs helps public health programs identify and better support critical aspects of the care and services delivered to the patients they serve. This is true for state-based early hearing detection and intervention (EHDI) programs as they strive to develop robust clinical quality measures to help track the quality of hearing health services provided during the EHDI processes. Leveraging today's electronic health records and public health surveillance system functionalities, state reporting requirements facilitate and yield efficient collection and analysis of data for quality measurement...
July 24, 2018: EGEMS
Nicholas V Colin, Raja A Cholan, Bhavaya Sachdeva, Benjamin E Nealy, Michael L Parchman, David A Dorr
Objective: To understand the impact of varying measurement period on the calculation of electronic Clinical Quality Measures (eCQMs). Background: eCQMs have increased in importance in value-based programs, but accurate and timely measurement has been slow. This has required flexibility in key measure characteristics, including measurement period, the timeframe the measurement covers. The effects of variable measurement periods on accuracy and variability are not clear...
July 19, 2018: EGEMS
Jessica S Ancker
Physicians need nearly a decade of training to understand complex patient data such as laboratory tests and genomic data. How can these data possibly be delivered to patients in ways that they can understand and use?
June 26, 2018: EGEMS
Daniel T Nystrom, Hardeep Singh, Jessica Baldwin, Dean F Sittig, Traber D Giardina
Objectives: Patients have unique information needs to help them interpret and make decisions about laboratory test results they receive on web-based portals. However, current portals are not designed in a patient-centered way and little is known on how best to harness patients' information needs to inform user-centered interface design of portals. We designed a patient-facing laboratory test result interface prototype based on requirement elicitation research and used a mixed-methods approach to evaluate this interface...
June 26, 2018: EGEMS
Jessica M Goehringer, Michele A Bonhag, Laney K Jones, Tara Schmidlen, Marci Schwartz, Alanna Kulchak Rahm, Janet L Williams, Marc S Williams
Context: Communication of genetic laboratory results to patients and providers is impeded by the complexity of results and reports. This can lead to misinterpretation of results, causing inappropriate care. Patients often do not receive a copy of the report leading to possible miscommunication. To address these problems, we conducted patient-centered research to inform design of interpretive reports. Here we describe the development and deployment of a specific patient-centered clinical decision support (CDS) tool, a multi-use patient-centered genomic test report (PGR) that interfaces with an electronic health record (EHR)...
June 26, 2018: EGEMS
Martin G Seneviratne, Tina Seto, Douglas W Blayney, James D Brooks, Tina Hernandez-Boussard
Background: Electronic health record (EHR) based research in oncology can be limited by missing data and a lack of structured data elements. Clinical research data warehouses for specific cancer types can enable the creation of more robust research cohorts. Methods: We linked data from the Stanford University EHR with the Stanford Cancer Institute Research Database (SCIRDB) and the California Cancer Registry (CCR) to create a research data warehouse for prostate cancer...
June 1, 2018: EGEMS
Laura Haak Marcial, Joshua E Richardson, Beth Lasater, Blackford Middleton, Jerome A Osheroff, Kensaku Kawamoto, Jessica S Ancker, Danny van Leeuwen, Edwin A Lomotan, Shafa Al-Showk, Barry H Blumenfeld
This commentary introduces the Patient-Centered Clinical Decision Support (PCCDS) Learning Network, which is collaborating with AcademyHealth to publish "Better Decisions Together" as part of eGEMs . Patient-centered clinical decision support (CDS) is an important vehicle to address broad issues in the U.S. health care system regarding quality and safety while also achieving better outcomes and better patient and provider satisfaction. Defined as CDS that supports individual patients and their care givers and/or care teams in health-related decisions and actions, PCCDS is an important step forward in advancing endeavors to move patient-centered care forward...
May 30, 2018: EGEMS
Qoua L Her, Jessica M Malenfant, Sarah Malek, Yury Vilk, Jessica Young, Lingling Li, Jeffery Brown, Sengwee Toh
Introduction: Patient privacy and data security concerns often limit the feasibility of pooling patient-level data from multiple sources for analysis. Distributed data networks (DDNs) that employ privacy-protecting analytical methods, such as distributed regression analysis (DRA), can mitigate these concerns. However, DRA is not routinely implemented in large DDNs. Objective: We describe the design and implementation of a process framework and query workflow that allow automatable DRA in real-world DDNs that use PopMedNetā„¢, an open-source distributed networking software platform...
May 25, 2018: EGEMS
Beth Prusaczyk, Vanessa Fabbre, Christopher R Carpenter, Enola Proctor
Background: Health services and implementation researchers often seek to capture the implementation process of complex interventions yet explicit guidance on how to capture this process is limited. Medical record review is a commonly used methodology, especially when used as a proxy for provider behavior, with recognized benefits and limitations. The purpose of this study was to test the feasibility of chart review to measure implementation and offer recommendations for future researchers using this method to capture the implementation process...
May 25, 2018: EGEMS
Saif Khairat, George Cameron Coleman, Samantha Russomagno, David Gotz
Aim: This study was performed to better characterize accessibility to electronic health records (EHRs) among informatics professionals in various roles, settings, and organizations across the United States and internationally. Background: The EHR landscape has evolved significantly in recent years, though challenges remain in key areas such as usability. While patient access to electronic health information has gained more attention, levels of access among informatics professionals, including those conducting usability research, have not been well described in the literature...
May 25, 2018: EGEMS
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
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