Health Information Technology Commons^™

Electronic Health Record Alerts To Improve Lipid Lowering After A Recent Myocardial Infarction, Dean G. Karalis, Benjamin Richter, Scott Hessen, Patrick Moeller, Laney K. Jones

Division of Cardiology Faculty Papers

BACKGROUND: This observational, quality initiative evaluated the impact of changing from a passive (dismissible) to an active (nondismissible without action) electronic health record alert on guideline-recommended lipid-lowering therapy (LLT) prescriptions in patients with recent myocardial infarction at risk for secondary events.

METHODS: We sequentially recruited a retrospective passive-alert (February 2018-July 2019; n=733) and a prospective active-alert (August 2020-January 2022; n=587) cohort of patients who triggered an alert to intensify LLT or order a low-density lipoprotein-cholesterol (LDL-C) test if they had a recent myocardial infarction (within 12 months) and elevated (≥70 mg/dL) or missing LDL-C. Prescribed LLTs and cumulative percentages of …

Nudging Implementation Of Low Tidal Volume Ventilation: A Stepped Wedge, Cluster Randomized Trial, Meeta Prasad Kerlin, Michael O. Harhay, Fan Li, Dylan S. Small, Yingying Lu, Wei Wang, Barry D. Fuchs, Mark E. Mikkelsen, Teresa Tran, Aerielle Belk, Jasmine A. Silvestri, Tamar Klaiman, Stefania Scott, Elizabeth Levy, Michael W. Sjoding, Rachel Kohn, Karsten J. Roberts, Rinad S. Beidas, Scott D. Halpern

College of Health Professions Faculty Papers

BACKGROUND: "Nudges" embedded in the electronic health record (EHR) facilitate desired decisions while preserving autonomy and may provide a scalable strategy to overcome the common implementation barrier of lack of knowledge about a best practice. We sought to test whether EHR-based nudges targeting two intensive care unit (ICU) clinician groups would safely increase evidence-based use of low tidal volume ventilation.

METHODS: We performed a stepped-wedge, cluster randomized, hybrid type 3 effectiveness-implementation trial in 12 ICUs from February 2021 to May 2023 to test three nudges targeting clinicians responsible for order entry and respiratory therapists responsible for operationalizing orders and documentation. …

Diabetes Technology Meeting 2023, Tiffany Tian, Rachel E Aaron, Ashley Y Dunova, Johan H Jendle, David Kerr, Eda Cengiz, Andjela Drincic, John C Pickup, Kong Y Chen, Naomi Schwartz, Douglas B Muchmore, Halis K Akturk, Carol J Levy, Signe Schmidt, Riccardo Bellazzi, Alan H B Wu, Elias K Spanakis, Bijan Najafi, James Geoffrey Chase, Jane Jeffrie Seley, David C Klonoff

Center on Aging Staff Publications

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

Accuracy, Thoroughness, And Quality Of Outpatient Primary Care Documentation In The U.S. Department Of Veterans Affairs., Michael Weiner, Mindy E Flanagan, Katie Ernst, Ann H Cottingham, Nicholas A Rattray, Zamal Franks, April W Savoy, Joy L Lee, Richard M Frankel

Health Services and Informatics Research

BACKGROUND: Electronic health records (EHRs) can accelerate documentation and may enhance details of notes, or complicate documentation and introduce errors. Comprehensive assessment of documentation quality requires comparing documentation to what transpires during the clinical encounter itself. We assessed outpatient primary care notes and corresponding recorded encounters to determine accuracy, thoroughness, and several additional key measures of documentation quality.

METHODS: Patients and primary care clinicians across five midwestern primary care clinics of the US Department of Veterans Affairs were recruited into a prospective observational study. Clinical encounters were video-recorded and transcribed verbatim. Using the Physician Documentation Quality Instrument (PDQI-9) added to …

An Electronic Health Record Model For Predicting Risk Of Hepatic Fibrosis In Primary Care Patients, Aaron P Thrift, Theresa H Nguyen Wenker, Kyler Godwin, Maya Balakrishnan, Hao T Duong, Rohit Loomba, Fasiha Kanwal, Hashem B El-Serag

Faculty, Staff and Students Publications

BACKGROUND: One challenge for primary care providers caring for patients with nonalcoholic fatty liver disease is to identify those at the highest risk for clinically significant liver disease.

AIM: To derive a risk stratification tool using variables from structured electronic health record (EHR) data for use in populations which are disproportionately affected with obesity and diabetes.

METHODS: We used data from 344 participants who underwent Fibroscan examination to measure liver fat and liver stiffness measurement [LSM]. Using two approaches, multivariable logistic regression and random forest classification, we assessed risk factors for any hepatic fibrosis (LSM > 7 kPa) and significant hepatic …

Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen

Theses and Dissertations

This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.

The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …

Deep Learning Model For Personalized Prediction Of Positive Mrsa Culture Using Time-Series Electronic Health Records, Masayuki Nigo, Laila Rasmy, Bingyu Mao, Bijun Sai Kannadath, Ziqian Xie, Degui Zhi

Faculty, Staff and Student Publications

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing antibiotic therapy. Our study introduced a deep learning model, PyTorch_EHR, which leverages electronic health record (EHR) time-series data, including wide-variety patient specific data, to predict MRSA culture positivity within two weeks. 8,164 MRSA and 22,393 non-MRSA patient events from Memorial Hermann Hospital System, Houston, Texas are used for model development. PyTorch_EHR outperforms logistic regression (LR) and light gradient boost machine (LGBM) models in accuracy (AUROC

A Multi-Institutional Natural Language Processing Pipeline To Extract Performance Status From Electronic Health Records, Arash Maghsoudi, Yvonne H Sada, Sara Nowakowski, Danielle Guffey, Huili Zhu, Sudha R Yarlagadda, Ang Li, Javad Razjouyan

Faculty, Staff and Students Publications

PURPOSE: Performance status (PS), an essential indicator of patients' functional abilities, is often documented in clinical notes of patients with cancer. The use of natural language processing (NLP) in extracting PS from electronic medical records (EMRs) has shown promise in enhancing clinical decision-making, patient monitoring, and research studies. We designed and validated a multi-institute NLP pipeline to automatically extract performance status from free-text patient notes.

PATIENTS AND METHODS: We collected data from 19,481 patients in Harris Health System (HHS) and 333,862 patients from veteran affair's corporate data warehouse (VA-CDW) and randomly selected 400 patients from each data source to train …

Quehry: A Question Answering System To Query Electronic Health Records, Sarvesh Soni, Surabhi Datta, Kirk Roberts

Faculty, Staff and Student Publications

OBJECTIVE: We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

MATERIALS AND METHODS: We develop/synthesize the main components of quEHRy: concept normalization (MetaMap), time frame classification (new), semantic parsing (existing), visualization with question understanding (new), and query module for FHIR mapping/processing (new). We evaluate quEHRy on 2 clinical question answering (QA) datasets. We evaluate each component separately as well as holistically to gain deeper insights. We also conduct a thorough error analysis for a crucial subcomponent, medical concept normalization.

RESULTS: Using gold concepts, the precision of quEHRy …

Leveraging The Electronic Health Record To Implement Emergency Department Delirium Screening, Anita N Chary, Elise Brickhouse, Beatrice Torres, Ilianna Santangelo, Christopher R Carpenter, Shan W Liu, Kyler M Godwin, Aanand D Naik, Hardeep Singh, Maura Kennedy

Faculty, Staff and Students Publications

OBJECTIVE: The aim of this study is to understand how emergency departments (EDs) use health information technology (HIT), and specifically the electronic health record (EHR), to support implementation of delirium screening.

METHODS: We conducted semi-structured interviews with 23 ED clinician-administrators, representing 20 EDs, about how they used HIT resources to implement delirium screening. Interviews focused on challenges participants experienced when implementing ED delirium screening and EHR-based strategies they used to overcome them. We coded interview transcripts using dimensions from the Singh and Sittig sociotechnical model, which addresses use of HIT in complex adaptive health care systems. Subsequently, we analyzed data …

Prediction Of Brain Metastases Development In Patients With Lung Cancer By Explainable Artificial Intelligence From Electronic Health Records, Zhao Li, Rongbin Li, Yujia Zhou, Laila Rasmy, Degui Zhi, Ping Zhu, Antonio Dono, Xiaoqian Jiang, Hua Xu, Yoshua Esquenazi, W Jim Zheng

Faculty, Staff and Student Publications

PURPOSE: Early detection of brain metastases (BMs) is critical for prompt treatment and optimal control of the disease. In this study, we seek to predict the risk of developing BM among patients diagnosed with lung cancer on the basis of electronic health record (EHR) data and to understand what factors are important for the model to predict BM development through explainable artificial intelligence approaches accurately.

MATERIALS AND METHODS: We trained a recurrent neural network model, REverse Time AttentIoN (RETAIN), to predict the risk of developing BM using structured EHR data. To interpret the model's decision process, we analyzed the attention …

Low Rates Of Structured Advance Care Planning Documentation In Electronic Health Records: Results Of A Single-Center Observational Study, Adela Wu, Robert J Huang, Gabriela Ruiz Colón, Chris Zembrzuski, Chirag B Patel

Faculty, Staff and Student Publications

BACKGROUND: Proper advance care planning (ACP) documentation both improves patient care and is increasingly seen as a marker of high quality by governmental payers. The transition of most medical documentation to electronic health records (EHR) allows for ACP documents to be rapidly disseminated across diverse ambulatory practice settings. At the same time, the complexity and heterogeneity of the EHR, as well as the multiple potential storage locations for documentation, may lead to confusion and inaccessibility. There has been movement to promote structured ACP (S-ACP) documentation within the EHR.

METHODS: We performed a retrospective cohort study at a single, large university …

Prevalence Of Prediabetes And Diabetes Vary By Ethnicity Among Us Asian Adults At Healthy Weight, Overweight, And Obesity Ranges: An Electronic Health Record Study, William S Vicks, Joan C Lo, Lynn Guo, Jamal S Rana, Sherry Zhang, Nirmala D Ramalingam, Nancy P Gordon

Faculty, Staff and Student Publications

BACKGROUND: Asian adults develop Type 2 diabetes at a lower body mass index (BMI) compared to other racial/ethnic groups. We examined the variation in prevalence of prediabetes and diabetes among Asian ethnic groups within weight strata by comparing middle-aged Chinese, Filipino, South Asian, and White adults receiving care in the same integrated healthcare delivery system.

METHODS: Our retrospective cross-sectional U.S. study examined data from 283,110 (non-Hispanic) White, 33,263 Chinese, 38,766 Filipino, and 17,959 South Asian adults aged 45-64 years who were members of a Northern California health plan in 2016 and had measured height and weight. Prediabetes and diabetes were …

Patient Portal Use And Patient Education Materials Access Among Mississippi Adult Residents, Anna K. Swann

Dissertations

Patient education plays a vital role in improving the health outcomes of patients with chronic diseases and helps prevent illness in otherwise healthy individuals. Patient portals allow patients to access their EHRs, communicate with their healthcare providers, and access patient education materials. Despite the potential for patient portals and education materials to improve health outcomes, many barriers prevent patients from utilizing them. Uneducated patients are more likely to participate in risky health behaviors, which leads to poor health outcomes. Poor health outcomes lead to higher medical costs. Mississippi has a high rate of chronic diseases. Suppose the barriers to patient …

Implementation Of Standardized Longitudinal Emr-Based Monitoring Of Patients With Post-Covid Conditions, Michael K. Espino, Jean Bombach, Richard Andrews, Karin Dunn

Gulf Coast Division GME Research Day 2022

No abstract provided.

Validation Of An Electronic Trigger To Measure Missed Diagnosis Of Stroke In Emergency Departments, Viralkumar Vaghani, Li Wei, Umair Mushtaq, Dean F Sittig, Andrea Bradford, Hardeep Singh

Faculty, Staff and Students Publications

OBJECTIVE: Diagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).

METHODS: Using two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained …

Administrative Coding In Electronic Health Care Record-Based Research Of Nafld: An Expert Panel Consensus Statement, Hannes Hagström, Leon A Adams, Alina M Allen, Christopher D Byrne, Yoosoo Chang, Henning Grønbaek, Mona Ismail, Peter Jepsen, Fasiha Kanwal, Jennifer Kramer, Jeffrey V Lazarus, Michelle T Long, Rohit Loomba, Philip N Newsome, Ian A Rowe, Seungho Ryu, Jörn M Schattenberg, Marina Serper, Nick Sheron, Tracey G Simon, Elliot B Tapper, Sarah Wild, Vincent Wai-Sun Wong, Yusuf Yilmaz, Shira Zelber-Sagi, Fredrik Åberg

Faculty, Staff and Students Publications

BACKGROUND AND AIMS: Electronic health record (EHR)-based research allows the capture of large amounts of data, which is necessary in NAFLD, where the risk of clinical liver outcomes is generally low. The lack of consensus on which International Classification of Diseases (ICD) codes should be used as exposures and outcomes limits comparability and generalizability of results across studies. We aimed to establish consensus among a panel of experts on ICD codes that could become the reference standard and provide guidance around common methodological issues.

APPROACH AND RESULTS: Researchers with an interest in EHR-based NAFLD research were invited to collectively define …

Analysis Of Platforms And Functions Of Mobile-Based Personal Health Record Systems, Byung Kwan Choi, Young-Taek Park, Lee-Seung Kwon, Phoebe (Yeon) S. Kim

Nursing Faculty Publications

Objectives
Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems.
Methods
The unit of analysis was general hospitals with more than 100 beds. This study was based on a PHR survey conducted from May 1 to June 30, 2020 and the National Health Insurance administrative data as of March 31, 2020. The study considered the platform, Android and iPhone operation system (iOS), and types of functionalities of PHR systems. Among the 316 target hospitals, 103 hospitals had adopted PHR systems. …

Visualization Of Cardiac Implantable Electronic Device Data For Older Adults Using Participatory Design., Ryan Ahmed, Tammy Toscos Phd, Romisa Rohani Ghahari, Richard J Holden, Elizabeth Martin, Shauna Wagner, Carly Daley, Amanda Coupe, Michael Mirro Md

Health Services and Informatics Research

Patients with heart failure (HF) are commonly implanted with cardiac resynchronization therapy (CRT) devices as part of their treatment. Presently, they cannot directly access the remote monitoring (RM) data generated from these devices, representing a missed opportunity for increased knowledge and engagement in care. However, electronic health data sharing can create information overload issues for both clinicians and patients, and some older patients may not be comfortable using the technology (i.e., computers and smartphones) necessary to access this data. To mitigate these problems, patients can be directly involved in the creation of data visualization tailored to their preferences and needs, …

Selection Biases In Technology-Based Intervention Research: Patients' Technology Use Relates To Both Demographic And Health-Related Inequities., Tammy Toscos Phd, Michelle Drouin, Jessica Pater, Mindy Flanagan, Rachel Pfafman, Michael Mirro Md, Facc, Fhrs, Faha

Health Services and Informatics Research

OBJECTIVE: Researchers conduct studies with selection biases, which may limit generalizability and outcomes of intervention research. In this methodological reflection, we examined demographic and health characteristics of implantable cardioverter defibrillator patients who were excluded from an informatics intervention due to lack of access to a computer and/or the internet.

MATERIALS AND METHODS: Using information gathered from surveys and electronic health records, we compared the intervention group to excluded patients on demographic factors, computer skills, patient activation, and medical history.

RESULTS: Excluded patients were older, less educated, less engaged and activated in their health, and had worse health (ie, more medical …

A Beginner's Guide To Research Using Electronic Health Record Data, Jenenne A. Geske

Theses & Dissertations

Since the passage of the American Recovery and Reinvestment Act in 2009, the use of Electronic Health Records (EHRs) in the healthcare system has increased substantially. Accompanying this surge in EHR usage is a surge in healthcare data and increased opportunities to improve our understanding of health care through research using these data. The use of EHR data for research has many benefits, limitations and considerations. Using data that was originally intended to facilitate billing, insurance, and maintenance of clinical records for research can be fraught with challenges, but they can also be a rich source of information. This paper …

Effect Of A Robust Electronic Medical Record Order Set On Hepatitis C Screening Rate At A Community Hospital, Hannah Olsen, Caroline Knight, Harold Van Lonkhuyzen

MaineHealth Maine Medical Center

Background:

Hepatitis C Virus (HCV) infection is a liver infection that typically begins as an acute infection and if left untreated, can become a chronic infection. One-time HCV testing is recommended by the CDC and United States Preventive Services Task Force (USPSTF) for asymptomatic individuals based on evaluated exposure or other circumstances that increase HCV exposure (HCV Guidance, 2018); (CDC, 2012). Patients with severe mental disorders, such as schizophrenia and bipolar disorders are particularly at risk for HCV infection with past studies finding approximately 6.2 - 29.8% of patients with severe mental disorders having comorbid HCV (Ayano et al., 2018) …

Clinical Decision Support Functions And Digitalization Of Clinical Documents Of Electronic Medical Record Systems, Young-Taek Park, Phoebe (Yeon) S. Kim, Byoung-Kee Yi, Sang Mi Kim

Nursing Faculty Publications

Objectives

The objective of this study was to investigate the clinical decision support (CDS) functions and digitalization of clinical documents of Electronic Medical Record (EMR) systems in Korea. This exploratory study was conducted focusing on current status of EMR systems.

Methods

This study used a nationwide survey on EMR systems conducted from July 25, 2018 to September 30, 2018 in Korea. The unit of analysis was hospitals. Respondents of the survey were mainly medical recorders or staff members in departments of health insurance claims or information technology. This study analyzed data acquired from 132 hospitals that participated in the survey. …

Clinician Satisfaction With In-House And Cloud-Based Ehr Vendors, Massara Alazazi, Jun Sun, Nan Xiao

Information Systems Faculty Publications

This paper examines the factors that affect clinician satisfaction with electronic health records (EHR) vendors that provide in-house and cloud-based solutions. The study is concerned with the organizational level of different healthcare organizations. The model combines the IS Success model and the Task Technology Fit model, to best fit the health information systems. Five research hypotheses derived from the model and are going to be empirically tested using a field survey of EHR systems characteristics and its influence on the organization’s tasks achievement and mission alignment.

Impact Of Terminology Mapping On Population Health Cohorts Impact, Barbara A. Berkovich

Dissertations and Theses (Open Access)

Background and Objectives: The population health care delivery model uses phenotype algorithms in the electronic health record (EHR) system to identify patient cohorts targeted for clinical interventions such as laboratory tests, and procedures. The standard terminology used to identify disease cohorts may contribute to significant variation in error rates for patient inclusion or exclusion. The United States requires EHR systems to support two diagnosis terminologies, the International Classification of Disease (ICD) and the Systematized Nomenclature of Medicine (SNOMED). Terminology mapping enables the retrieval of diagnosis data using either terminology. There are no standards of practice by which to evaluate and …

The Use Of Electronic Health Records Data For Public Health: A Snapshot Of Current Practices In Nebraska’S Local Health Departments, Kushal Karan

Capstone Experience: Master of Public Health

Background: Public health issues are constantly changing and require local health departments (LHDs) to continually evolve in their approaches to address these issues. Advancements in health information technology (HIT), such as electronic health records (EHRs), play an important role in the collection of data that can be used to improve population health.

Objective: The purpose of this project was to assess the current use of electronic health records data by Nebraska’s local health departments and identify the data or tools they are using to address the health needs of the populations they serve.

Methods: In this study, a Mixed-Methods approach …

Overcoming Barriers To Implementing Electronic Health Records In Rural Primary Care Clinics, Patricia Mason, Roger Mayer, Wen-Wen Chien, Judith P. Monestime

The Qualitative Report

Medicare-eligible physicians at primary care practices (PCP) that did not implement an electronic health record (EHR) system by the end of 2015 face stiff penalties. One year prior to the 2015 deadline, approximately half of all primary clinics have not implemented a basic EHR system. The purpose of this phenomenology study was to explore rural primary care physicians and physician assistants’ experiences regarding overcoming barriers to implementing EHRs. Complex adaptive systems formed the conceptual framework for this study. Data were collected through face-to-face interviews with a purposeful sample of 21 physicians and physician assistants across 2 rural PCPs in the …

Empirical Assessment Of The Role Of Technology-Related Factors And Organization-Related Factors In Electronic Medical Records Implementation Success, Rangarajan Parthasarathy

College of Computing and Digital Media Dissertations

The objective of this research was to investigate if certain technology-related and organization-related factors that have most often been associated with successful IT/MIS implementations in other information technology and information science domains are also associated with successful Electronic Medical Records (EMR) implementations. This research uncovered a unique set of technology-related factors and organization-related factors associated with successful EMR implementations from the perspective of healthcare enablers and healthcare providers. Specific technology-related factors considered in this research were the innovativeness of EMR (measured with respect to the relative advantage, compatibility and complexity of EMR), privacy and security attributes of EMR, and usefulness …

The Impact Of Electronic Health Records On Healthcare Service Delivery, Patient Safety, And Quality, Kate Elizabeth Trout

Theses & Dissertations

The HITECH Act has provided over $30 billion of support through the Meaningful Use program to implement Electronic Health Records (EHRs) with aims to improve healthcare service delivery, efficiency, quality, and patient safety. New healthcare models, such as pay-for-performance and value-based purchasing, were envisioned to aligning quality with reimbursement mediated with the use of EHRs. It is unclear of how EHRs and Meaningful Use have impacted health service delivery, patient safety, and quality of care. Thus, making it difficult to determine if the specific set of objectives for Meaningful Use have had a positive impact on outcomes, which ultimately is …

Design And Testing Of An Ehr-Integrated, Busulfan Pharmacokinetic Decision Support Tool For The Point-Of-Care Clinician., Susan M. Abdel-Rahman, Matthew L. Breitkreutz, Charlie Bi, Brett J. Matzuka, Jignesh Dalal, K Leigh Casey, Uttam Garg, Sara Winkle, J Steven Leeder, Jeanann Breedlove, Brian Rivera

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Busulfan demonstrates a narrow therapeutic index for which clinicians routinely employ therapeutic drug monitoring (TDM). However, operationalizing TDM can be fraught with inefficiency. We developed and tested software encoding a clinical decision support tool (DST) that is embedded into our electronic health record (EHR) and designed to streamline the TDM process for our oncology partners.

METHODS: Our development strategy was modeled based on the features associated with successful DSTs. An initial Requirements Analysis was performed to characterize tasks, information flow, user needs, and system requirements to enable push/pull from the EHR. Back-end development was coded based on the algorithm …