Use of Subject Field Codes from a Machine-Readable Dictionary for Automatic Classification of Documents

We are currently eveloping a system whose goal is to emulate a human classifier who peruses a large set of documents and sons them into richly defined classes based solely on the subject content of the documents. To accomplish this task, our system tags each word in a document with the appropriate Subject Field Code (SFC) from a machine-readable dictionary. The within- document SFCs are then summed and normalized and each document is represented as a vector of the SFCs occurring in that document. These vectors are clustered using Ward's agglomerative clustering algorithm (Ward, 1963) to form classes in a document database. For retrieval, queries are likewise represented as SFC vectors and then matched to the prototype SFC vector of each cluster in the database. Clusters whose prototype SFC vectors exhibit a predetermined criterion of similarity to the query SFC vector are passed on to other system components for more computationally expensive representation and matching

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Automated generation of comparator patients in the electronic medical record

Abstract Background Well‐designed randomized trials provide high‐quality clinical evidence but are not always feasible or ethical. In their absence, the electronic medical record (EMR) presents a platform to conduct comparative effectiveness research, central to the emerging academic learning health system (aLHS) model. A barrier to realizing this vision is the lack of a process to efficiently generate a reference comparison group for each patient. Objective To test a multi‐step process for the selection of comparators in the EMR. Materials and Methods We conducted a mixed‐methods study within a large aLHS in North Carolina. We (1) created a list of 35 candidate variables; (2) surveyed 270 researchers to assess the importance of candidate variables; and (3) built consensus rankings around survey‐identified variables (ie, importance scores >7) across two panels of 7–8 clinical research experts. Prioritized algorithm inputs were collected from the EMR and applied using a greedy matching technique. Feasibility was measured as the percentage of patients with 100 matched comparators and performance was measured via computational time and Euclidean distance. Results Nine variables were selected: age, sex, race, ethnicity, body mass index, insurance status, smoking status, Charlson Comorbidity Index, and neighborhood percentage in poverty. The final process successfully generated 100 matched comparators for each of 1.8 million candidate patients, executed in less than 100 min for the majority of strata, and had average Euclidean distance 0.043. Conclusion EMR‐derived matching is feasible to implement across a diverse patient population and can provide a reproducible, efficient source of comparator data for observational studies, with additional testing in clinical research applications needed

Healthcare Passport: A population-based introductory pharmacy practice model for Medicare beneficiaries

The objective of the study was to describe the design and outcomes of a model to provide population-based, introductory pharmacy practice experiences (IPPEs). Community outreach events targeting Medicare beneficiaries were conducted. Screenings and services designed for adults 65 years and older were offered. Attendees were provided a business card known as the “Health care Passport” which identified screening stations and provided space to record results. Students participated in planning the events and providing health services. Students gained experience with population-based care, providing 2633 health screenings for 1013 attendees, and earned 2650 IPPE hours. Attendees received medication therapy management, assistance with the Medicare Part D plan review, and utilized an average of three stations, most commonly cardiovascular risk, immunizations, diabetes, and bone density. The Health care Passport is a reproducible model to provide extensive, population-based health screenings and services and effectively meet IPPE requirements for students