PubMed · 9274071
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D Huber, C Delaney. 1997. The Nursing Management Minimum Data Set.. https://doi.org/10.1016/s0897-1897(97)80281-9
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INTRODUCTION: Sustainable control of malaria in sub-Saharan Africa is jeopardized by dwindling public health resources resulting from competing health priorities that include an overwhelming acquired immunodeficiency syndrome (AIDS) epidemic. In Mpumalanga province, South Africa, rational planning has historically been hampered by a case surveillance system for malaria that only provided estimates of risk at the magisterial district level (a subdivision of a province). METHODS: To better map control programme activities to their geographical location, the malaria notification system was overhauled and a geographical information system implemented. The introduction of a simplified notification form used only for malaria and a carefully monitored notification system provided the good quality data necessary to support an effective geographical information system. RESULTS: The geographical information system displays data on malaria cases at a village or town level and has proved valuable in stratifying malaria risk within those magisterial districts at highest risk, Barberton and Nkomazi. The conspicuous west-to-east gradient, in which the risk rises sharply towards the Mozambican border (relative risk = 4.12, 95% confidence interval = 3.88-4.46 when the malaria risk within 5 km of the border was compared with the remaining areas in these two districts), allowed development of a targeted approach to control. DISCUSSION: The geographical information system for malaria was enormously valuable in enabling malaria risk at town and village level to be shown. Matching malaria control measures to specific strata of endemic malaria has provided the opportunity for more efficient malaria control in Mpumalanga province.
Employing equipment reliability databases can generate a process of continual improvement. This paper suggests a methodology that uses equipment reliability databases, and a process of benchmarking to establish a continual improvement procedure by learning "how others are doing it". A simple decision-making procedure is suggested too, to assist in prioritizing the processes/equipment that are considered to be improved as well as a methodology to measure the improvement.
Accurate dermal quantitative structure-activity/property relationship (QSAR/QSPR) models are needed to predict percutaneous absorption of environmental contaminants. The Molsuite 2000 chemistry modeling software (ChemSW, Fairfield, CA) was used to model the Flynn component of the Kirchner in vitro human skin permeability coefficient (K(p)) data. This Kirchner- derived Flynn (K/F) database was updated to include recent literature data quality recommendations. A K/F data subset consisting of nondrug compounds was used to further optimize the developed QSPR models. The statistical fit of the models was excellent with r(2) values up to.89 for a three-descriptor parameter K/F database model and up to.96 for a four- parameter model of the data subset. A one-parameter transform model using only logarithm octanol-water partition coefficient (log K(o/w)) was also developed for the data subset (r(2) =.87). Molecular volume (MV) descriptors were not shown to be superior to molecular weight in conventional two-parameter models with log K(o/w) but may be superior in multiparameter models. A previously nonreported descriptor, surface tension in water (STW), was found to provide optimal multiparameter models. The developed models passed PRESS cross-validation and could be useful for predicting environmental systemic dermal exposure.