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At least 1,531 records · Page 85Linked to original sources
PubMed2001

Motivational interviewing for HIV risk reduction among gay men in commercial and public sex settings.

The present paper addresses the feasibility of combining motivational interviewing and cognitive interventions to HIV risk reduction in commercial venues and public sex environments (PSEs). The logic for these two approaches is considered and an intervention combining key elements of the two is presented. The intervention uses a questionnaire format to encourage individuals to compare their desired versus actual behaviour (i.e. chosen personal risk reduction strategy versus 'slip-ups'/unwanted risk taking), and to recognize their risk-related cognitions. High-risk individuals are identified, and health-focused conversations developed from the brief schedule. The structure and key design issues in the development of a feasible, acceptable and evidence-based tool are reviewed. The limitations of more complex, focused interventions in the context of commercial and PSE settings are discussed.

Cognitive Behavioral Therapy↗
PubMed2004

Development and validation of a clinical prediction rule for hospitalization due to pneumonia or influenza or death during influenza epidemics among community-dwelling elderly persons.

BACKGROUND: Uncertainties among health care providers and patients about the risk of serious influenza-associated complications and the potential benefits of vaccination may contribute to unsatisfactorily low influenza vaccination rates. To quantify the risk of serious outcomes (hospitalization due to pneumonia or influenza or death due to any cause) during influenza seasons, we developed a clinical prediction rule for the probability of hospitalization due to pneumonia or influenza or death among elderly persons. METHODS: We developed the clinical prediction rule using data from linked administrative databases in a cohort of 16,280 noninstitutionalized and unvaccinated elderly persons. Validation of the rule was conducted in 5 unvaccinated and 6 vaccinated cohorts, each consisting of >11,000 elderly members of 3 managed care organizations. Logistic regression was used to produce a prognostic score on the basis of the following predictors: age; sex; presence of pulmonary, cardiac, and renal disease; dementia or stroke and cancer; number of outpatient visits; and hospitalization due to pneumonia or influenza during the previous year. RESULTS: Reliability of the regression model was good (P=.65, by goodness-of-fit test), and it discriminated well between those who did and those who did not experience an outcome (area under the receiver-operating curve, 0.83; 95% confidence interval, 0.81-0.85). Validation revealed moderately lower but acceptable discriminating values (0.72-0.81). In the derivation cohort, the prognostic accuracy of the rule was high when a cutoff score for the upper 50th percentile was used: > or =10 of 1000 subjects with a score in the upper 50th percentile were predicted to have an outcome, and 89% of all outcomes were observed in this high-risk group, whereas <10 of 1000 subjects with a score in the lower 50th percentile were predicted to have an outcome, and only 11% of outcomes occurred in this group. Among unvaccinated subjects in the single-derivation cohort and the 11 validation cohorts combined, the outcome event rates were 35 events/1000 subjects in the higher-risk group and 6 events/1000 subjects in the lower-risk group. With vaccination, these event rates dropped by 15 events/1000 subjects and 2 events/1000 subjects, respectively. CONCLUSIONS: This prediction rule may be a useful tool to complement other age-based strategies, to further encourage vaccination, especially among those at the highest risk of serious complications due to influenza.

Aged↗
PubMed2006

Administrative data fail to accurately identify cases of healthcare-associated infection.

OBJECTIVE: Some policy makers have embraced public reporting of healthcare-associated infections (HAIs) as a strategy for improving patient safety and reducing healthcare costs. We compared the accuracy of 2 methods of identifying cases of HAI: review of administrative data and targeted active surveillance. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional prospective study was performed during a 9-month period in 2004 at the Children's Hospital of Philadelphia, a 418-bed academic pediatric hospital. "True HAI" cases were defined as those that met the definitions of the National Nosocomial Infections Surveillance System and that were detected by a trained infection control professional on review of the medical record. We examined the sensitivity and the positive and negative predictive values of identifying HAI cases by review of administrative data and by targeted active surveillance. RESULTS: We found similar sensitivities for identification of HAI cases by review of administrative data (61%) and by targeted active surveillance (76%). However, the positive predictive value of identifying HAI cases by review of administrative data was poor (20%), whereas that of targeted active surveillance was 100%. CONCLUSIONS: The positive predictive value of identifying HAI cases by targeted active surveillance is very high. Additional investigation is needed to define the optimal detection method for institutions that provide HAI data for comparative analysis.

Cross Infection↗
PubMed2005

Pandemic influenza preparedness in Maryland: improving readiness through a tabletop exercise.

In February 1999, the Maryland Department of Health and Mental Hygiene initiated pandemic influenza planning for the state of Maryland. This process involved several major steps, including the development of the Maryland Pandemic Influenza Preparedness Plan, and culminated in a high-level tabletop exercise to test the plan in April 2004. During the tabletop exercise, participants were presented with nine different fictitious scripts encompassing a single scenario. They were asked to respond to the information presented in each script, discuss organization-specific questions posed by the exercise facilitator, and make decisions regarding action steps that their organization would take in response to the various issues raised. The exercise identified a number of important gaps that need to be addressed, including (1) additional surge capacity specific to a pandemic, (2) greater understanding of the realities and implications of pandemic influenza among elected officials and decision-makers, (3) coordination of pandemic influenza planning with the existing emergency response infrastructure coupled with additional training in incident command, (4) further steps to operationalize several aspects of the Maryland Pandemic Influenza Preparedness Plan, and (5) additional federal guidance.

Disease Outbreaks↗