A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times

The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

Emergency Management in Developed Countries: An Investigation of Hazard Risk, Vulnerability and Government Response in the UK and USA

During the summer of 2007 the United Kingdom experienced some of the worst flooding in its history, with the city of Hull amongst the worst affected. Meanwhile, the city of New Orleans, USA was subject to severe flooding in August 2005 as a result of Hurricane Katrina. The study has found that both the UK and US government disaster management programmes were ill prepared for these flood events. Many parallel issues have been discovered and discussed. The conditions of vulnerability that are evident in developing countries are not widely present in the UK or US but this must not be allowed to lead to complacency and lack of preparation and awareness. The cost in terms of mortality is relatively low compared to similar events in developing countries; however, the economic implications are considerable and must be addressed.

Effect of a pharmacist-led multicomponent intervention focussing on the medication monitoring phase to prevent potential adverse drug events in nursing homes

OBJECTIVES: To determine the extent to which the use of a clinical informatics tool that implements prospective monitoring plans reduces the incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

DESIGN: Randomized cluster trial.

SETTING: Twenty-five nursing homes serviced by two long-term care pharmacies.

PARTICIPANTS: Residents living in nursing homes during 2003 (1,711 in 12 intervention; 1,491 in 13 usual care) and 2004 (1,769 in 12 intervention; 1,552 in 13 usual care).

INTERVENTION: The pharmacy automatically generated Geriatric Risk Assessment MedGuide (GRAM) reports and automated monitoring plans for falls and delirium within 24 hours of admission or as part of the normal time frame of federally mandated drug regimen review.

MEASUREMENTS: Incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

RESULTS: GRAM triggered monitoring plans for 491 residents. Newly admitted residents in the intervention homes experienced a lower rate of potential delirium onset than those in usual care homes (adjusted hazard ratio (HR)=0.42, 95% confidence interval (CI)=0.35–0.52), overall hospitalization (adjusted HR=0.89, 95% CI=0.72–1.09), and mortality (adjusted HR=0.88, 95% CI=0.66–1.16). In longer stay residents, the effects of the intervention were attenuated, and all estimates included unity.

CONCLUSION: Using health information technology in long-term care pharmacies to identify residents who might benefit from the implementation of prospective medication monitoring care plans when complex medication regimens carry potential risks for falls and delirium may reduce adverse effects associated with appropriate medication use.

Effects of an integrated medicines management program on medication appropriateness in hospitalized patients

Purpose. The effects of an integrated medicines management (IMM) program on medication appropriateness are discussed.

Exploring the impact of depressive symptoms and medication beliefs on medication adherence in hypertension-A primary care study

Objective: This Study aimed to assess the levels of adherence in a sample of hypertensive patients being cared for in primary care in Northern Ireland and to explore the impact of depressive symptoms and medication beliefs on medication adherence.