Classification of support staff in a consortium medical library: a case study.

A representative committee of Houston Academy of Medicine-Texas Medical Center Library staff and faculty, under the direction of the library administration, successfully redesigned a job classification system for the library's nonprofessional staff. In the new system all nonprofessionals are assigned to one of five grade levels, each with a corresponding salary range. To determine its appropriate grade level each job is analyzed and assigned a numerical value using a point system based on a set of five factors, each of which is assigned a relative number of points. The factors used to measure jobs are: education and experience, complexity of work, administrative accountability, manual skill, and contact with users. Each factor is described according to degrees, so that a job can be given partial credit for a factor. An advisory staff classification committee now participates in the ongoing administration of the classification system.

Patient classification system: An integrated method for measuring nursing intensity and optimizing resource allocation

A patient classification system was developed integrating a patient acuity instrument with a computerized nursing distribution method based on a linear programming model. The system was designed for real-time measurement of patient acuity (workload) and allocation of nursing personnel to optimize the utilization of resources.^ The acuity instrument was a prototype tool with eight categories of patients defined by patient severity and nursing intensity parameters. From this tool, the demand for nursing care was defined in patient points with one point equal to one hour of RN time. Validity and reliability of the instrument was determined as follows: (1) Content validity by a panel of expert nurses; (2) predictive validity through a paired t-test analysis of preshift and postshift categorization of patients; (3) initial reliability by a one month pilot of the instrument in a practice setting; and (4) interrater reliability by the Kappa statistic.^ The nursing distribution system was a linear programming model using a branch and bound technique for obtaining integer solutions. The objective function was to minimize the total number of nursing personnel used by optimally assigning the staff to meet the acuity needs of the units. A penalty weight was used as a coefficient of the objective function variables to define priorities for allocation of staff.^ The demand constraints were requirements to meet the total acuity points needed for each unit and to have a minimum number of RNs on each unit. Supply constraints were: (1) total availability of each type of staff and the value of that staff member (value was determined relative to that type of staff's ability to perform the job function of an RN (i.e., value for eight hours RN = 8 points, LVN = 6 points); (2) number of personnel available for floating between units.^ The capability of the model to assign staff quantitatively and qualitatively equal to the manual method was established by a thirty day comparison. Sensitivity testing demonstrated appropriate adjustment of the optimal solution to changes in penalty coefficients in the objective function and to acuity totals in the demand constraints.^ Further investigation of the model documented: correct adjustment of assignments in response to staff value changes; and cost minimization by an addition of a dollar coefficient to the objective function. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Point-of-sale machines in school cafeterias and parental influence on child food choices

The prevalence of obesity has reached epidemic proportions in the United States. Twenty-five percent of school aged students are overweight. Schools have the opportunity to help slow this epidemic. School cafeterias in the United States feed millions of students every day through the National School Lunch Program.^ Point-of-sale machines are used in most school cafeterias to help streamline the process of purchasing school lunches. The point-of-sale software allows school personnel to place special notes on student's accounts to provide alerts about parental requests. This study investigated what the alerts are used for, who uses the alerts, and if there are any patterns by demographic characteristics. ^ Counts and percentages were used to determine what the alerts were used for and who used them. This study found that students who were white non-Hispanic, paid status, or in elementary school were most likely to have alerts placed on their accounts. Also, the majority of point-of-sale alerts were used as allowances (i.e., allowed to purchase snacks from the balance on the school lunch account), rather than restrictions (i.e., restricted from purchasing high calorie foods or specific food items). Using chi-square analysis, a total of 688 alerts were analyzed. There were significant differences in alert frequencies for intent category by grade level (p=0.000), snack access (p=0.000), and gender (p=0.002). Therefore, the results are significant, and one can conclude there is a significant relationship between gender, grade level, and snack access, and the presence of an alert on the school lunch account.^ Also, school administrators may want to take into consideration possible changes to their program, such as requiring more time to run the software. The results of this study can assist school administrators to better understand that a point-of-sale alert program may help their school lunch programs run more efficiently, while also providing parental influence on students’ food choices at the point-of-sale.^ School food service authorities should consider implementing a structured point-of-sale alert policy to encourage parental input on their children's food choices. When implementing the point-of-sale policy, schools should publicize this policy online, through school lunch menus, and parent communications increase participation throughout the school district.^

Performance recovery from exercise: A review from a statistical point of view

Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^

Point of decision signs and stair use in a university worksite setting: General versus specific messages

Point-of-decision signs to promote stair use have been found to be effective in various environments. However, these signs have been more consistently successful in public access settings that use escalators, such as shopping centers and transportation stations, compared to worksite settings, which are more likely to contain elevators that are not directly adjacent to the stairs. Therefore, this study tested the effectiveness of two point-of-decision sign prompts to increase stair use in a university worksite setting. Also, this study investigated the importance of the message content of the signs. One sign displayed a general health promotion message, while the other sign presented more specific information. Overall, this project examined whether the presence of the point-of-decision signs increases stair use. In addition, this research determined whether the general or specific sign promotes greater stair use. ^ Inconspicuous observers measured stair use both before the signs were present and while they were posted. The study setting was the University of Texas School of Nursing, and the target population was anyone who entered the building, including employees, students, and visitors. The study was conducted over six weeks and included two weeks of baseline measurement, two weeks with the general sign posted, and two weeks with the specific sign posted. Each sign was displayed on a stand in the decision point area near the stairs and the elevator. Logistic regression was used to analyze the data. ^ After adjustment for covariates, the odds of stair use were significantly greater during the intervention period than the baseline period. Furthermore, the specific sign period showed significantly greater odds of stair use than the general sign period. These results indicate that a point-of-decision sign intervention can be effective at promoting stair use in a university worksite setting and that a sign with a specific health information message may be more effective at promoting stair use than a sign with a general health promotion message. These findings can be considered when planning future worksite and university based stair promotion interventions.^