Medical expenditures of terminal cancer patients during the last year of life.

To measure the patterns of medical expenditures under conventional modes of cancer care for the terminally ill, we examined Blue Cross and Blue Shield Plan claims records for care during the 12 months preceding the deaths of 1,054 nonelderly patients diagnosed as having breast, colon-rectal, or lung cancer. Expenditures averaged +21,219 for the terminal year and grew exponentially as death approached, with +6,161 (29%) being spent in the final month alone. We found very few significant differences in spending or utilization by diagnosis, age, or sex of the terminal patient, but sizable differences by state of residence and between nonmetropolitan and metropolitan area residents. Our findings represent a baseline against which experience under new hospital payment strategies and alternative delivery systems might be compared.

Statistical-uncertainty-based adaptive filtering of lidar signals.

An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometeorological humidity data were used to calibrate the ratio of the lidar gains of the H(2)O and the N(2) photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem.

Development of a scanning, solar-blind, water Raman lidar.

The need for an instrument capable of measuring water-vapor fluxes over mixed canopy and large areas has long been recognized. Such a device would greatly enhance the study of evapotranspiration processes and has great practical value for water management. To address this problem, a scanning water Raman lidar has been designed and constructed. Analytical methods have also been developed to take advantage of the type of information that this lidar can generate. The lidar is able to measure the absolute water content and calculate the evaporative flux quickly over relatively large areas. This capability provides new opportunities for the study of microscale atmospheric processes. The variogram data indicate that the spatial sampling size must be of the order of 10 m if fluxes and scalars are to be properly represented. Examples of data are presented.