Smart Alerts: Development of Software to Optimize Data Monitoring

Dherte PM, Negrao MPG, Mori Neto S, Holzhacker R, Shimada V, Taberner P, Carmona MJC - Smart Alerts: Development of a Software to Optimize Data Monitoring. Background and objectives: Monitoring is useful for vital follow-ups and prevention, diagnosis, and treatment of several events in anesthesia. Although alarms can be useful in monitoring they can cause dangerous user`s desensitization. The objective of this study was to describe the development of specific software to integrate intraoperative monitoring parameters generating ""smart alerts"" that can help decision making, besides indicating possible diagnosis and treatment. Methods: A system that allowed flexibility in the definition of alerts, combining individual alarms of the parameters monitored to generate a more elaborated alert system was designed. After investigating a set of smart alerts, considered relevant in the surgical environment, a prototype was designed and evaluated, and additional suggestions were implemented in the final product. To verify the occurrence of smart alerts, the system underwent testing with data previously obtained during intraoperative monitoring of 64 patients. The system allows continuous analysis of monitored parameters, verifying the occurrence of smart alerts defined in the user interface. Results: With this system a potential 92% reduction in alarms was observed. We observed that in most situations that did not generate alerts individual alarms did not represent risk to the patient. Conclusions: Implementation of software can allow integration of the data monitored and generate information, such as possible diagnosis or interventions. An expressive potential reduction in the amount of alarms during surgery was observed. Information displayed by the system can be oftentimes more useful than analysis of isolated parameters.

NIAIC - Medical Device Equipment Alerts (MEDA)

NIAIC - Medical Device Equipment Alerts

NIAIC - Medical Device and Equipment Alerts 2013

Medical Device and Equipment Alerts MDEA Updates - 2013

NIAIC - Medical Device and Equipment Alerts 2012

Medical Device and Equipment Alerts MDEA Updates - 2012

Drug Alerts 2011 to 2012

PAS Alerts 2011 to 2012

NIAIC - Medical Device and Equipment Alerts 2010

Medical Device and Equipment Alerts MDEA Updates - 2010

NIAIC - Medical Device and Equipment Alerts 2011

Medical Device and Equipment Alerts MDEA Updates - 2011

Drug Alerts 2007-2008

2007-2008

Drug Alerts 2009-2010

2009-2010

NIAIC - Medical Device and Equipment Alerts 2009

Medical Device and Equipment Alerts MDEA Updates - 2009

Drug Alerts

PAS Alerts

Optimized molecular resolution of cross-contamination alerts in clinical mycobacteriology laboratories

BACKGROUND. The phenomenon of misdiagnosing tuberculosis (TB) by laboratory cross-contamination when culturing Mycobacterium tuberculosis (MTB) has been widely reported and it has an obvious clinical, therapeutic and social impact. The final confirmation of a cross-contamination event requires the molecular identification of the same MTB strain cultured from both the potential source of the contamination and from the false-positive candidate. The molecular tool usually applied in this context is IS6110-RFLP which takes a long time to provide an answer, usually longer than is acceptable for microbiologists and clinicians to make decisions. Our purpose in this study is to evaluate a novel PCR-based method, MIRU-VNTR as an alternative to assure a rapid and optimized analysis of cross-contamination alerts. RESULTS. MIRU-VNTR was prospectively compared with IS6110-RFLP for clarifying 19 alerts of false positivity from other laboratories. MIRU-VNTR highly correlated with IS6110-RFLP, reduced the response time by 27 days and clarified six alerts unresolved by RFLP. Additionally, MIRU-VNTR revealed complex situations such as contamination events involving polyclonal isolates and a false-positive case due to the simultaneous cross-contamination from two independent sources. CONCLUSION. Unlike standard RFLP-based genotyping, MIRU-VNTR i) could help reduce the impact of a false positive diagnosis of TB, ii) increased the number of events that could be solved and iii) revealed the complexity of some cross-contamination events that could not be dissected by IS6110-RFLP.

Evaluation of email alerts in practice: Part 2. Validation of the information assessment method.

RATIONALE AND OBJECTIVE:. The information assessment method (IAM) permits health professionals to systematically document the relevance, cognitive impact, use and health outcomes of information objects delivered by or retrieved from electronic knowledge resources. The companion review paper (Part 1) critically examined the literature, and proposed a 'Push-Pull-Acquisition-Cognition-Application' evaluation framework, which is operationalized by IAM. The purpose of the present paper (Part 2) is to examine the content validity of the IAM cognitive checklist when linked to email alerts. METHODS: A qualitative component of a mixed methods study was conducted with 46 doctors reading and rating research-based synopses sent on email. The unit of analysis was a doctor's explanation of a rating of one item regarding one synopsis. Interviews with participants provided 253 units that were analysed to assess concordance with item definitions. RESULTS AND CONCLUSION: The content relevance of seven items was supported. For three items, revisions were needed. Interviews suggested one new item. This study has yielded a 2008 version of IAM.

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.