Optimization of Spectral String Data Analysis Using a Binomial Discriminator for Weak-source Detection Decisions.

Operational health physics applications, such as radiological and nuclear monitoring and detection for homeland security or radiation protection purposes, generate time sequences of independent individual measurement data. Statistical algorithms have been developed that use the analysis of patterns in the data strings to enhance the test statistic for the decision on the absence or presence of a radiation source. These hypothesis test procedures have been applied to spectral data and have been optimized for the highest rate of correct identification of a weak Cs source at constant false positive detection rates. Optimization of correct detection decisions was investigated for various string data sequence lengths and for the regions of interest in the gamma spectrum. The highest correct source identification is achieved for string data analyses of the spectral contributions that maximize a [INCREMENT]µ/σ criterion, including energy regions around and containing the photopeak, but potentially also regions in the gamma spectrum other than those photopeak energies.

Low-Fidelity Spectral Analysis Utilizing a Binomial Discriminator for Weak-Source Detection Decisions.

The identification of radiological sources by analysis of a gamma spectrum usually relies on the location of the set of radionuclide-specific electron energies corresponding to the incident photons interacting by photoelectric absorption in the detection medium. The challenge in low-level detection applications is the identification of these "photopeaks" above the background counts registered in the detector from the natural radiation environment and system noise. For source detection decisions, regions of the gamma spectrum other than at the photopeak energies may provide additional information about the presence of a source and allow for a higher rate of correct identification of a weak source. A statistical algorithm utilizing low-fidelity spectral data partitioned into three distinct regions and employing a binomial discriminator was tested in a laboratory setting against the traditional approach of source identification by exceeding a decision threshold within the photopeak region of interest. For an unshielded Cs source with no significant scatter between the source and the detector, the traditional peak identification method performs as well or better than most algorithm settings for various source strengths. However, an algorithm which also includes information in the energy range of Compton scattered photons provides improved detection capabilities for shielded weak sources. Such algorithms, including higher-fidelity developments, could be deployed to improve current tools for the search for orphan radiological sources and in the characterization of low-level environmental contamination.

Hand washing frequency in an emergency department.

Objectives Previous studies, conducted mainly in ICUs, have shown low compliance with hand-washing recommendations, with failure rates approaching 60%. Hand washing in the emergency department has not been studied. We examined the frequency and duration of hand washing in one emergency department and the effects of three variables: level of training, type of patient contact (clean, dirty, or gloved), and years of staff clinical experience. Design Observational. Setting ED of a 1100-bed tertiary referral, central city, private teaching hospital. Participants Emergency nurses, faculty, and resident physicians. Participants were informed that their activities were being monitored but were unaware of the exact nature of the study. Interventions An observer recorded the number of patient contacts and activities for each participant during 3-hour observation periods. Activities were categorized as either clean or dirty according to a scale devised by Fulkerson. The use of gloves was noted and hand-washing technique and duration were recorded. A hand-washing break in technique was defined as failure to wash hands after a patient contact and before proceeding to another patient or activity. Results Eleven faculty, 11 resident physicians, and 13 emergency nurses were observed. Of 409 total contacts, 272 were clean, 46 were dirty, and 91 were gloved. Hand washing occurred after 32.3% of total contacts (SD, 2.31%). Nurses washed after 58.2% of 146 contacts (SD, 4.1%), residents after 18.6% of 129 contacts (SD, 3.4%), and faculty after 17.2% of 134 contacts (SD, 3.3%). Nurses had a significantly higher hand washing frequency than either faculty (p < 0.0001) or resident physicians (p < 0.0001).(ABSTRACT TRUNCATED AT 250 WORDS)

Hand washing frequency in an emergency department.

STUDY OBJECTIVE: Previous studies, conducted mainly in ICUs, have shown low compliance with hand-washing recommendations, with failure rates approaching 60%. Hand washing in the emergency department has not been studied. We examined the frequency and duration of hand washing in one ED and the effects of three variables: level of training, type of patient contact (clean, dirty, or gloved), and years of staff clinical experience. DESIGN: Observational. SETTING: ED of an 1,100-bed tertiary referral, central city, private teaching hospital. PARTICIPANTS: Emergency nurses, faculty, and resident physicians. Participants were informed that their activities were being monitored but were unaware of the exact nature of the study. INTERVENTIONS: An observer recorded the number of patient contacts and activities for each participant during three-hour observation periods. Activities were categorized as either clean or dirty according to a scale devised by Fulkerson. The use of gloves was noted and hand-washing technique and duration were recorded. A hand-washing break in technique was defined as failure to wash hands after a patient contact and before proceeding to another patient or activity. RESULTS: Eleven faculty, 11 resident physicians, and 13 emergency nurses were observed. Of 409 total contacts, 272 were clean, 46 were dirty, and 91 were gloved. Hand washing occurred after 32.3% of total contacts (SD, 2.31%). Nurses washed after 58.2% of 146 contacts (SD, 4.1%), residents after 18.6% of 129 contacts (SD, 3.4%), and faculty after 17.2% of 134 contacts (SD, 3.3%). Nurses had a significantly higher hand washing frequency than either faculty (P < .0001) or resident physicians (P < .0001). Hand washes occurred after 28.4% of 272 clean contacts (SD, 2.34%), which was significantly less (P < .0001) than 50.0% of 46 dirty contacts (SD, 7.4%) and 64.8% of 91 gloved contacts (SD, 5.0%). The number of years of clinical experience was not significantly related to hand-washing frequency (P = .82). Soap and water were used in 126 of the hand washes, and an alcohol preparation was used in the remaining six. The average duration of soap-and-water hand washes was 9.5 seconds. CONCLUSION: Compliance with hand washing recommendations was low in this ED. Nurses washed their hands significantly more often than either staff physicians or resident physicians, but the average hand-washing duration was less than recommended for all groups. Poor compliance in the ED may be due to the large number of patient contacts, simultaneous management of multiple patients, high illness acuity, and severe time constraints. Strategies for improving compliance with this fundamental method of infection control need to be explored because simple educational interventions have been unsuccessful in other health care settings.