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The purpose of this study was to conduct a scoping review of publications that explored blockchain technology in the context of interoperability and challenges of electronic health record (EHR) implementations. We synthesize the literature regarding standards and security, specifically regulation, regulatory operability, and conformance to standards. We review open practitioner questions that were not addressed in the studies as directions for further research.

In order to manage COVID-19 patient population and bed capacity issues, remote patient monitoring (RPM) is a strategy used to transition patients from inpatients to home. We describe our RPM implementation process for post-acute care COVID-19 pneumonia patients. We also evaluate the impact of RPM on patient outcomes, including hospital length of stay (LOS), post-discharge Emergency Department (ED) visits, and hospital readmission.

[This corrects the article DOI: 10.1093/jamiaopen/ooac012.].

Given time constraints, poorly organized information, and complex patients, primary care providers (PCPs) can benefit from clinical decision support (CDS) tools that aggregate and synthesize problem-specific patient information. First, this article describes the design and functionality of a CDS tool for chronic noncancer pain in primary care. Second, we report on the retrospective analysis of real-world usage of the tool in the context of a pragmatic trial.

We aim to reduce overfitting and model overconfidence by distilling the knowledge of an ensemble of deep learning models into a single model for the classification of cancer pathology reports.

There is a growing need for innovation to prepare a well-trained health informatics workforce with data science and digital technology skills. To meet the workforce demands and prepare students for a career in health informatics, a Health Data Science (HDS) concentration was added to the Master's in Health Informatics (MSHI) program at the University of Illinois at Chicago.

New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for [...]

The objective of this study is to understand the primary topics of consumer discussion on Twitter associated with telehealth for mental health or substance abuse for prepandemic versus during-pandemic time-periods, using a state-of-the-art machine learning (ML) natural language processing (NLP) method.

A novel approach of department-focused electronic health record (EHR) training was implemented to improve efficiency and time management of EHR use. Based off baseline log data, 5 in-person training sessions were designed, focusing on the common inefficiencies of 6 chosen participants. Log data of 4 key metrics and 2 efficiency scores were analyzed 4 months post-training. A survey was conducted to assess self-reported EHR competence. Individually, several participants had improved [...]

Many options are currently available for sepsis surveillance clinical decision support (CDS) from electronic medical record (EMR) vendors, third party, and homegrown models drawing on rule-based (RB) and machine learning (ML) algorithms. This study explores sepsis CDS implementation from the perspective of implementation leads by describing the motivations, tool choices, and implementation experiences of a diverse group of implementers.