Youth population's health issues in Comal County, Texas

This study assesses adolescent's health issues in Comal County, TX. Adolescents are defined as youth between the ages of 12 to 17 years of age, who resided in Comal County during the time period of 2000 to 2007. The analysis focused on high risk behaviors including use of gateway drugs—tobacco and alcohol; illegal substance use; and reproductive health related indicators, including sexual activity, sexually transmitted diseases, and pregnancy. This study is based on the primary and secondary data collected as part of the 2008 Comal County Community Assessment. It compares findings from the primary data sources to extant data from four secondary data sources including: (1) The Centers for Disease Control & Prevention (national) Healthy People 2010; (2) The Centers for Disease Control & Prevention, Youth Risk Behavior Surveillance Survey, 2007; (3) The Texas Department of State Health Services, 2000 to 2007; and The Pride Survey (Local and Statewide). The methods are drawn from the literature on "rapid epidemiologic appraisal" (Annett H. & Rifkin S. B., 1988). The study focus on corroborating the perceptions, subjective concerns, opinions and beliefs of the Comal County key stakeholders and community participants with qualitative and quantitative indicators of health and well being. The value of this approach is to inform community leaders using a public health perspective and evidence in their decisions about priority setting and resources allocation activities for prevention of high risk behaviors and promotion of adolescent health and well being. ^

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. ^