23 research outputs found
Combining Free Text and Structured Electronic Medical Record Entries to Detect Acute Respiratory Infections
The electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).A manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis.An adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.Structured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties
Reviewing the use of resilience concepts in forest sciences
Purpose of the review Resilience is a key concept to deal with an uncertain future in forestry. In recent years, it has received increasing attention from both research and practice. However, a common understanding of what resilience means in a forestry context, and how to operationalise it is lacking. Here, we conducted a systematic review of the recent forest science literature on resilience in the forestry context, synthesising how resilience is defined and assessed.
Recent findings Based on a detailed review of 255 studies, we analysed how the concepts of engineering resilience, ecological resilience, and social-ecological resilience are used in forest sciences. A clear majority of the studies applied the concept of engineering resilience, quantifying resilience as the recovery time after a disturbance. The two most used indicators for engineering resilience were basal area increment and vegetation cover, whereas ecological
resilience studies frequently focus on vegetation cover and tree density. In contrast, important social-ecological resilience indicators used in the literature are socio-economic diversity and stock of natural resources. In the context of global change, we expected an increase in studies adopting the more holistic social-ecological resilience concept, but this was not the observed trend. Summary Our analysis points to the nestedness of these three resilience concepts, suggesting that they are complementary rather than contradictory. It also means that the variety of resilience approaches does not need to be an obstacle for operationalisation of the concept. We provide guidance for choosing the most suitable resilience concept and indicators based on the management, disturbance and application context
Drug sales data analysis for outbreak detection of infectious diseases: a systematic literature review
Article number: 604 (2014)International audienceBackground: This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases.Methods: A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection).Results: We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales.Conclusions: Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed
Early extubation after high-dose fentanyl anaesthesia for aortocoronary bypass surgery: reversal of respiratory depression with low-dose nalbuphine
Laparoscopic resection rectopexy versus laparoscopic ventral rectopexy for complete rectal prolapse
Policing transgender people and Intimate Partner Violence (IPV)
Knowledge regarding policing of transgender people in situations of intimate partner violence (IPV) is scarce within policing literature. While this may be because transgender victim-survivors of IPV are one of the most hidden groups of IPV survivors, transgender people face specific and unique forms of IPV related to their identity. Police officers, therefore, need to be aware of the specific forms of IPV transgender victim-survivors experience and must be cognizant of the specific circumstances involved when responding to incidents of transgender IPV. Police recognition of transgender IPV will increase the reporting of transgender IPV; effect responses to transgender IPV; increase outcomes of justice for victims and; push recommendations concerning changing current police responses and operational practices regarding IPV. Yet, bias towards individuals who identify as transgender has been found in the literature regarding police practices and perceptions of LGBTIQ+ people. Research suggests transgender people are generally uncomfortable seeking help from the police. Therefore, policing transgender victim-survivors of IPV poses an ongoing problem since notions of exclusion and the sense of ‘difference’ transgender people have in terms of their perceived or outward identity form barriers between police and members of the transgender community during times of victimization
