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Outcomes mentioned on online health communities (OHCs) by patients can serve as a source of evidence for off-label drug usage evaluation, but identifying these outcomes manually is tedious work. We have built a natural language processing model to identify off-label usage of drugs mentioned in these patient posts.

A number of clinical decision support tools aim to use observational data to address immediate clinical needs, but few of them address challenges and biases inherent in such data. The goal of this article is to describe the experience of running a data consult service that generates clinical evidence in real time and characterize the challenges related to its use of observational data.

As we enter an era of health care that incorporates telehealth for routine provision of care, we can build a system that consciously and proactively includes vulnerable patients, thereby avoiding further exacerbation of health disparities. A practical way to reach out to Latino patients is to use media they already widely use. Rather than expect patients to adapt to suboptimal systems of telehealth care, we can improve telehealth for Latinos [...]

Medications frequently require prior authorization from payers before filling is authorized. Obtaining prior authorization can create delays in filling prescriptions and ultimately reduce patient adherence to medication. Electronic prior authorization (ePA), embedded in the electronic health record (EHR), could remove some barriers but has not been rigorously evaluated. We sought to evaluate the impact of implementing an ePA system on prescription filling.

To explore the use of health plan quality measures specified for electronic clinical data to monitor immunizations.

The 21st Century Cures Act, passed in 2016, and the Final Rules it called for create a roadmap for enabling patient access to their electronic health information. The set of data to be made available, as determined by the Office of the National Coordinator for Health IT through the US Core Data for Interoperability expansion process, will impact the value creation of this improved data liquidity. In this commentary, we [...]

The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic health records more accurately than existing guideline-based dosing recommendations.

The collection of patient reported outcomes (PROs) allows us to incorporate the patient's voice into their care in a quantifiable, validated manner. Large-scale collection of PROs is facilitated by the electronic health record and its portal, though, historically, patients have eschewed the portal and completed patient-reported outcome measures in the clinic via tablet. Furthermore, access and use of the portal is associated with known racial inequities. Our institution oversees the [...]