scholarly journals Medication Class Effects on Visit-to-Visit Variability of Blood Pressure Measurements: Analysis of Electronic Health Record Data in the “Real World”

2013 ◽  
Vol 15 (9) ◽  
pp. 655-662 ◽  
Author(s):  
Timothy R. Smith ◽  
Joseph P. Drozda ◽  
Jeffrey A. Vanslette ◽  
Amanda S. Hoeffken ◽  
Robert A. Nicholson
Keyword(s):  
Blood Pressure ◽  
Electronic Health Record ◽  
Real World ◽  
Health Record ◽  
Pressure Measurements ◽  
Electronic Health Record Data ◽  
The Real ◽  
Medication Class ◽  
Record Data ◽  
Electronic Health

scholarly journals Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

2020 ◽  
Vol 27 (7) ◽  
pp. 1173-1185 ◽  
Author(s):  
Seyedeh Neelufar Payrovnaziri ◽  
Zhaoyi Chen ◽  
Pablo Rengifo-Moreno ◽  
Tim Miller ◽  
Jiang Bian ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Scoping Review ◽  
Real World ◽  
Research Trend ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Explainable Artificial Intelligence ◽  
Record Data ◽  
Electronic Health

Abstract Objective To conduct a systematic scoping review of explainable artificial intelligence (XAI) models that use real-world electronic health record data, categorize these techniques according to different biomedical applications, identify gaps of current studies, and suggest future research directions. Materials and Methods We searched MEDLINE, IEEE Xplore, and the Association for Computing Machinery (ACM) Digital Library to identify relevant papers published between January 1, 2009 and May 1, 2019. We summarized these studies based on the year of publication, prediction tasks, machine learning algorithm, dataset(s) used to build the models, the scope, category, and evaluation of the XAI methods. We further assessed the reproducibility of the studies in terms of the availability of data and code and discussed open issues and challenges. Results Forty-two articles were included in this review. We reported the research trend and most-studied diseases. We grouped XAI methods into 5 categories: knowledge distillation and rule extraction (N = 13), intrinsically interpretable models (N = 9), data dimensionality reduction (N = 8), attention mechanism (N = 7), and feature interaction and importance (N = 5). Discussion XAI evaluation is an open issue that requires a deeper focus in the case of medical applications. We also discuss the importance of reproducibility of research work in this field, as well as the challenges and opportunities of XAI from 2 medical professionals’ point of view. Conclusion Based on our review, we found that XAI evaluation in medicine has not been adequately and formally practiced. Reproducibility remains a critical concern. Ample opportunities exist to advance XAI research in medicine.

scholarly journals The PCORnet Blood Pressure Control Laboratory

2020 ◽  
Vol 13 (3) ◽  
Author(s):  
Mark J. Pletcher ◽  
Valy Fontil ◽  
Thomas Carton ◽  
Kathryn M. Shaw ◽  
Myra Smith ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Electronic Health Record ◽  
Blood Pressure Control ◽  
Comparative Effectiveness ◽  
Pressure Control ◽  
Health Record ◽  
Control Laboratory ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health

Background: Uncontrolled blood pressure (BP) is a leading preventable cause of death that remains common in the US population despite the availability of effective medications. New technology and program innovation has high potential to improve BP but may be expensive and burdensome for patients, clinicians, health systems, and payers and may not produce desired results or reduce existing disparities in BP control. Methods and Results: The PCORnet Blood Pressure Control Laboratory is a platform designed to enable national surveillance and facilitate quality improvement and comparative effectiveness research. The platform uses PCORnet, the National Patient-Centered Clinical Research Network, for engagement of health systems and collection of electronic health record data, and the Eureka Research Platform for eConsent and collection of patient-reported outcomes and mHealth data from wearable devices and smartphones. Three demonstration projects are underway: BP track will conduct national surveillance of BP control and related clinical processes by measuring theory-derived pragmatic BP control metrics using electronic health record data, with a focus on tracking disparities over time; BP MAP will conduct a cluster-randomized trial comparing effectiveness of 2 versions of a BP control quality improvement program; BP Home will conduct an individual patient-level randomized trial comparing effectiveness of smartphone-linked versus standard home BP monitoring. Thus far, BP Track has collected electronic health record data from over 826 000 eligible patients with hypertension who completed ≈3.1 million ambulatory visits. Preliminary results demonstrate substantial room for improvement in BP control (<140/90 mm Hg), which was 58% overall, and in the clinical processes relevant for BP control. For example, only 12% of patients with hypertension with a high BP measurement during an ambulatory visit received an order for a new antihypertensive medication. Conclusions: The PCORnet Blood Pressure Control Laboratory is designed to be a reusable platform for efficient surveillance and comparative effectiveness research; results from demonstration projects are forthcoming.

scholarly journals Real‐world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot

2021 ◽  
Author(s):  
Laura Lasiter ◽  
Olga Tymejczyk ◽  
Elizabeth Garrett‐Mayer ◽  
Shrujal Baxi ◽  
Andrew J. Belli ◽  
...  
Keyword(s):  
Cancer Research ◽  
Overall Survival ◽  
Electronic Health Record ◽  
Real World ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health

scholarly journals What Every Reader Should Know About Studies Using Electronic Health Record Data But Is Afraid To Ask (Preprint)

2020 ◽  
Author(s):  
Isaac S Kohane ◽  
Bruce J Aronow ◽  
Paul Avillach ◽  
Brett K Beaulieu-Jones ◽  
Riccardo Bellazzi ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Real World ◽  
Warning Signs ◽  
Health Record ◽  
Real World Data ◽  
Electronic Health Record Data ◽  
Health Records ◽  
Record Data ◽  
Electronic Health

UNSTRUCTURED Coincident with the tsunami of Covid19-related manuscripts, there has been a surge of studies using Real World Data (RWD), including those obtained from electronic health records. Unfortunately, several of these studies have resulted in withdrawn publication because of concerns regarding their soundness and quality. We argue here that there are pre-analytic hints and warning signs that are useful in judging RWD studies that might otherwise pass statistical muster. We outline several of these signs and suggest that review of RWD manuscripts include those who are familiar with how such data are generated.

Automated chronic disease surveillance and visualization using electronic health record data

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Michael Klompas ◽  
Chaim Kirby ◽  
Jason McVetta ◽  
Paul Oppedisano ◽  
John Brownstein ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Electronic Health Record ◽  
Disease Surveillance ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health

Leveraging electronic health record data to inform hospital resource management

2021 ◽  
Author(s):  
José Carlos Ferrão ◽  
Mónica Duarte Oliveira ◽  
Daniel Gartner ◽  
Filipe Janela ◽  
Henrique M. G. Martins
Keyword(s):  
Resource Management ◽  
Electronic Health Record ◽  
Health Record ◽  
Hospital Resource ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health
Sign in / Sign up

Export Citation Format

Share Document