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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 [...]

Substance use screening in adolescence is unstandardized and often documented in clinical notes, rather than in structured electronic health records (EHRs). The objective of this study was to integrate logic rules with state-of-the-art natural language processing (NLP) and machine learning technologies to detect substance use information from both structured and unstructured EHR data.

Little is known regarding variation among electronic health record (EHR) vendors in quality performance. This issue is compounded by selection effects in which high-quality hospitals coalesce to a subset of market leading vendors. We measured hospital performance, stratified by EHR vendor, across 4 quality metrics.

Differential privacy is a relatively new method for data privacy that has seen growing use due its strong protections that rely on added noise. This study assesses the extent of its awareness, development, and usage in health research.

The study sought to conduct a systematic review to explore the functions utilized by electronic cancer survivorship care planning interventions and assess their effects on patient and provider outcomes.

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 [...]

Advances in standardization of observational healthcare data have enabled methodological breakthroughs, rapid global collaboration, and generation of real-world evidence to improve patient outcomes. Standardizations in data structure, such as use of common data models, need to be coupled with standardized approaches for data quality assessment. To ensure confidence in real-world evidence generated from the analysis of real-world data, one must first have confidence in the data itself.

Despite a proliferation of applications (apps) to conveniently collect patient-reported outcomes (PROs) from patients, PRO data are yet to be seamlessly integrated with electronic health records (EHRs) in a way that improves interoperability and scalability. We applied the newly created PRO standards from the Office of the National Coordinator for Health Information Technology to facilitate the collection and integration of standardized PRO data. A novel multitiered architecture was created to [...]

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