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The direct primary stands as one of the most significant and distinctive political reforms of the Progressive era in American history. In this book, the authors provide the most comprehensive treatment available on the topic and utilize new data on election outcomes, candidate backgrounds, incumbent performance and behavior, newspaper endorsements, and voters' preferences. They begin by studying whether primary elections have achieved the goals set by progressive reformers when they were first introduced over a century ago. They then evaluate the key roles these elections have played in the US electoral systems, such as injecting electoral competition into the regions that are dominated by one of the two major parties, helping select relatively qualified candidates for office, and, in some cases, holding incumbents accountable for their performance. They conclude with studying the degree to which primaries are responsible for the current, highly polarized environment. Anyone interested in US primary elections, US political history, or electoral institutions more generally should read this book.
Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.