GPs’ and community pharmacists’ opinions on medication management at transitions of care in Ireland

Objective. The aim of this study was to survey GPs and community pharmacists (CPs) in Ireland regarding current practices of medication management, specifically medication reconciliation, communication between health care providers and medication errors as patients transition in care.
Methods. A national cross-sectional survey was distributed electronically to 2364 GPs, 311 GP Registrars and 2382 CPs. Multivariable associations comparing GPs to CPs were generated and content analysis of free text responses was undertaken.
Results. There was an overall response rate of 17.7% (897 respondents—554 GPs/Registrars and 343 CPs). More than 90% of GPs and CPs were positive about the effects of medication reconciliation on medication safety and adherence. Sixty per cent of GPs reported having no formal system of medication reconciliation. Communication between GPs and CPs was identified as good/very good by >90% of GPs and CPs. The majority (>80%) of both groups could clearly recall prescribing errors, following a transition of care, they had witnessed in the previous 6 months. Free text content analysis corroborated the positive relationship between GPs and CPs, a frustration with secondary care communication, with many examples given of prescribing errors.
Conclusions. While there is enthusiasm for the benefits of medication reconciliation there are limited formal structures in primary care to support it. Challenges in relation to systems that support inter-professional communication and reduce medication errors are features of the primary/secondary care transition. There is a need for an improved medication management system. Future research should focus on the identified barriers in implementing medication reconciliation and systems that can improve it.

A Machine Learning Analysis of Twitter Sentiment to the Sandy Hook Shootings

Gun related violence is a complex issue and accounts for a large proportion of violent incidents. In the research reported in this paper, we set out to investigate the pro-gun and anti-gun sentiments expressed on a social media platform, namely Twitter, in response to the 2012 Sandy Hook Elementary School shooting in Connecticut, USA. Machine learning techniques are applied to classify a data corpus of over 700,000 tweets. The sentiments are captured using a public sentiment score that considers the volume of tweets as well as population. A web-based interactive tool is developed to visualise the sentiments and is available at this http://www.gunsontwitter.com. The key findings from this research are: (i) There are elevated rates of both pro-gun and anti-gun sentiments on the day of the shooting. Surprisingly, the pro-gun sentiment remains high for a number of days following the event but the anti-gun sentiment quickly falls to pre-event levels. (ii) There is a different public response from each state, with the highest pro-gun sentiment not coming from those with highest gun ownership levels but rather from California, Texas and New York.