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Prior research on health information exchange (HIE) typically measured provider usage through surveys or they summarized the availability of HIE services in a healthcare organization. Few studies utilized user log files. Using HIE access log files, we measured HIE use in real-world clinical settings over a 7-year period (2011-2017). Use of HIE increased in inpatient, outpatient, and emergency department (ED) settings. Further, while extant literature has generally viewed the ED [...]

We sought reduce electronic health record (EHR) burden on inpatient clinicians with a 2-week EHR optimization sprint.

The study sought to describe the prevalence and nature of clinical expert involvement in the development, evaluation, and implementation of clinical decision support systems (CDSSs) that utilize machine learning to analyze electronic health record data to assist nurses and physicians in prognostic and treatment decision making (ie, predictive CDSSs) in the hospital.

Location visualization is essential for locating people/objects, improving efficiency, and preventing accidents. In hospitals, Wi-Fi, Bluetooth low energy (BLE) Beacon, indoor messaging system, and similar methods have generally been used for tracking, with Wi-Fi and BLE being the most common. Recently, nurses are increasingly using mobile devices, such as smartphones and tablets, while shifting. The accuracy when using Wi-Fi or BLE may be affected by interference or multipath propagation. In [...]

The COVID-19 (coronavirus disease 2019) pandemic has underscored the critical need for all countries to strengthen their health data and information systems and ensure the routes the data travel, from submission to use, are unobstructed. Timely, credible, reliable, and actionable data are key to ensuring that political decisions are data driven and facilitate understanding, monitoring, and forecasting. To ensure that critical decisions related to the wider health and socioeconomic effects [...]

Like most real-world data, electronic health record (EHR)-derived data from oncology patients typically exhibits wide interpatient variability in terms of available data elements. This interpatient variability leads to missing data and can present critical challenges in developing and implementing predictive models to underlie clinical decision support for patient-specific oncology care. Here, we sought to develop a novel ensemble approach to addressing missing data that we term the "meta-model" and apply [...]

Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-course treatment regimens and first- and second-line treatment regimens. This research aims for fast diagnosis of M. tuberculosis resistance to PZA and identification of genetic features causing resistance.

Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop [...]

To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.