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Natural language processing (NLP) and machine learning approaches were used to build classifiers to identify genomic-related treatment changes in the free-text visit progress notes of cancer patients.

Alzheimer's disease (AD) is a severe neurodegenerative disorder and has become a global public health problem. Intensive research has been conducted for AD. But the pathophysiology of AD is still not elucidated. Disease comorbidity often associates diseases with overlapping patterns of genetic markers. This may inform a common etiology and suggest essential protein targets. US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) collects large-scale postmarketing surveillance data [...]

The population-based assessment of patient-centered outcomes (PCOs) has been limited by the efficient and accurate collection of these data. Natural language processing (NLP) pipelines can determine whether a clinical note within an electronic medical record contains evidence on these data. We present and demonstrate the accuracy of an NLP pipeline that targets to assess the presence, absence, or risk discussion of two important PCOs following prostate cancer treatment: urinary incontinence [...]

We sought to assess the current state of risk prediction and segmentation models (RPSM) that focus on whole populations.

The objective of this article is to examine consumer perceptions of health information technology (health IT) utilization and benefits through an integrated conceptual framework.

Usable tools to support individual primary care clinicians in their diagnostic processes could help to reduce preventable harm from diagnostic errors. We conducted a formative study with primary care providers to identify key requisites to optimize the acceptability of 1 online collective intelligence platform (Human Diagnosis Project; Human Dx).

The widespread adoption and use of electronic health records and their use to enable learning health systems (LHS) holds great promise to accelerate both evidence-generating medicine (EGM) and evidence-based medicine (EBM), thereby enabling a LHS. In 2016, AMIA convened its 10th annual Policy Invitational to discuss issues key to facilitating the EGM-EBM paradigm at points-of-care (nodes), across organizations (networks), and to ensure viability of this model at scale (sustainability). In [...]

Electronic medical record (EMR) implementation at centers caring for homeless people is constrained by limited resources and the increased disease burden of the patient population. Few informatics articles address this issue. This report describes Boston Health Care for the Homeless Program's migration to new EMR software without loss of unique care elements and processes.

Health information technology (HIT) is intended to provide safer and better care to patients. However, poorly designed or implemented HIT poses a key risk to patient safety. It is essential for healthcare providers and researchers to investigate the HIT-related events. Unfortunately, the lack of HIT-related event databases in the community hinders the analysis and management of HIT-related events.

Although electronic health record systems have been implemented in many health settings globally, how organizations can best implement these systems to improve medication safety in mental health contexts is not well documented in the literature. The purpose of this case report is to describe how a mental health hospital in Toronto, Canada, leveraged the process of obtaining Healthcare Information Management Systems Society (HIMSS) Stage 7 on the Electronic Medical Record [...]