Search AMIA.org

A key component for precision medicine is a good prediction algorithm for patients' response to treatments. We aim to implement machine learning (ML) algorithms into the response-adaptive randomization (RAR) design and improve the treatment outcomes.

The Alzheimer's Therapeutic Research Institute (ATRI) developed a novel clinical data management system, the ATRI electronic data capture system (ATRI EDC), to address the complex regulatory, operational, and data requirements that arise in the conduct of multicenter Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRDs) clinical trials. We describe the system, its utility, and the broader implications for the field of clinical trials and clinical research informatics.

[This corrects the article DOI: 10.1093/jamiaopen/ooab069.].

To evaluate the attitudes of the parties involved in the system toward the new features and measure the potential benefits of introducing the use of blockchain and machine learning (ML) to strengthen the in-place methods for safely prescribing medication. The proposed blockchain will strengthen the security and privacy of the patient's prescription information shared in the network. Once the ePrescription is submitted, it is only available in read-only mode. This [...]

Objectives of this study were to (1) describe barriers to using clinical practice guideline (CPG) admission order sets in a pediatric hospital and (2) determine if integrating CPG order bundles into a general admission order set increases adoption of CPG-recommended orders compared to standalone CPG order sets. We identified CPG-eligible encounters and surveyed admitting physicians to understand reasons for not using the associated CPG order set. We then integrated CPG [...]

Patient-generated health data (PGHD) have not achieved widespread clinical adoption. However, the COVID-induced shift to telemedicine may have created opportunities for PGHD as surrogates for vital signs collected in person. We assessed whether this shift was associated with greater ambulatory care PGHD use. We conducted an interrupted time series analysis of physician enrollment in, and patient-initiated vital sign transmission of non-COVID-associated PGHD through, a national PGHD platform (Validic). Ten health [...]

COVID-19 mortality forecasting models provide critical information about the trajectory of the pandemic, which is used by policymakers and public health officials to guide decision-making. However, thousands of published COVID-19 mortality forecasts now exist, many with their own unique methods, assumptions, format, and visualization. As a result, it is difficult to compare models and understand under which circumstances a model performs best. Here, we describe the construction and usability of [...]

The COVID-19 pandemic resulted in an unprecedented production of scientific literature spanning several fields. To facilitate navigation of the scientific literature related to various aspects of the pandemic, we developed an exploratory search system. The system is based on automatically identified technical terms, document citations, and their visualization, accelerating identification of relevant documents. It offers a multi-view interactive search and navigation interface, bringing together unsupervised approaches of term extraction and [...]

Researchers are increasingly collecting large amounts of deidentified data about individuals to address important health-related challenges and answer fundamental questions. Current US federal regulations permit researchers to use already collected and stored deidentified health-related data from a variety of sources without seeking consent from patients. The objective of this study was to investigate public views on the policies and processes institutions have in place for accessing, using, and sharing of [...]

During the COVID-19 pandemic, many health jurisdictions deployed digital informatics systems to support "manual" case investigation and contact tracing (CICT). This case study evaluates the implementation and use of a digital information system through the experiences of CICT workers in the City and County of San Francisco (CCSF). We conducted semi-structured, 90-min interviews with a sample of the CCSF CICT workforce (n = 37). Participants also completed standardized assessments of [...]