Impact of increasing the re-supply interval on the seasonality of subsidised prescription use in Australia

Objective: To evaluate the impact of increasing the minimum resupply period for prescriptions on the Pharmaceutical Benefits Scheme (PBS) in November 1994. The intervention was designed to reduce the stockpiling of medicines used for chronic medical conditions under the PBS safety net. Methods: Interrupted times series regression analyses were performed on 114 months of PBS drug utilisation data from January 1991 to June 2000. These analyses assessed whether there had been a significant interaction between the onset of the intervention in November 1994 and the extreme levels of drug utilisation in the months of December (peak utilisation) and January (lowest utilisation) respectively. Both serial and 12-month lag autocorrelations were controlled for. Results: The onset of the intervention was associated with a significant reduction in the December peak in drug utilisation; after the introduction of the policy there were 1,150,196 fewer proscriptions on average or that month (95% Cl 708,333-1,592,059). There was, however, no significant change in the low level of utilisation in January. The effect of the policy appears to be decreasing across successive postintervention years. though the odds of a prescription being dispensed in December remained significantly lower in 1999 compared to each of the pre-intervention years (11% vs. 14%) Conclusion: Analysis of the impact of increasing the re-supply period for PBS prescriptions showed that the magnitude of peak utilisation in December had been markedly reduced by the policy, though this effect appears to be decreasing over time. Continued monitoring and policy review is warranted in order to ensure that the initial effect of the intervention be maintained.

Estimating trends and seasonality in coronary heart disease

We present two methods of estimating the trend, seasonality and noise in time series of coronary heart disease events. In contrast to previous work we use a non-linear trend, allow multiple seasonal components, and carefully examine the residuals from the fitted model. We show the importance of estimating these three aspects of the observed data to aid insight of the underlying process, although our major focus is on the seasonal components. For one method we allow the seasonal effects to vary over time and show how this helps the understanding of the association between coronary heart disease and varying temperature patterns. Copyright (C) 2004 John Wiley Sons, Ltd.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.

Is there change over time in the season-of-birth effect for schizophrenia? Data from the southern hemisphere

The aim of this paper is to examine distributions of schizophrenia and general population births over time in order to determine whether (a) the pattern has changed over time, (b) any pattern was similar for both males and females, and (c) whether there is any indication that there is any relationship between the changes in pattern between schizophrenia and general population births. Birth month and year for 7807 individuals with ICD8/9 schizophrenia were gained from the Queensland Mental Health Statistical System for 1914-1975. Monthly births for the general population in Queensland for the same period were obtained from the Australian Bureau of Statistics. For each decade we obtained two comparisons, (1) between two 'seasons' (summer-autumn/winter-spring), and (2) between the third (coldest) quarter and the remaining quarters. Based on expected contrasts from general population proportions, odds ratios and their confidence intervals were used to analyse these comparisons for all subjects, and for males and females separately. The seasonality found in our previous studies was again evident (OR 1.09; 95% CI= 1.01-1.17). However there was no significant change in its pattern over time either for the total group or for males and females separately. When the general population births alone were examined using the same contrasts, seasonality was also observed, but here there were fluctuations over time. These results suggest that exposures linked to changes in general population births over time should be examined in disorders such as schizophrenia which demonstrate seasonality in births. The Stanley Foundation supported this project.

Analytical validation for a series of marker compounds used to assess renal drug elimination processes

Renal drug elimination is determined by glomerular filtration, tubular secretion, and tubular reabsorption. Changes in the integrity of these processes influence renal drug clearance, and these changes may not be detected by conventional measures of renal function such as creatinine clearance. The aim of the current study was to examine the analytic issues needed to develop a cocktail of marker drugs (fluconazole, rac-pindolol, para-aminohippuric acid, sinistrin) to measure simultaneously the mechanisms contributing to renal clearance. High-performance liquid chromatographic methods of analysis for fluconazole, pindolol, para-aminohippuric acid, and creatinine and an enzymatic assay for sinistrin were developed or modified and then validated to allow determination of each of the compounds in both plasma and urine in the presence of all other marker drugs. A pilot clinical study in one volunteer was conducted to ensure that the assays were suitable for quantitating all the marker drugs to the sensitivity and specificity needed to allow accurate determination of individual renal clearances. The performance of all assays (plasma and urine) complied with published validation criteria. All standard curves displayed linearity over the concentration ranges required, with coefficients of correlation greater than 0.99. The precision of the interday and intraday variabilities of quality controls for each marker in plasma and urine were all less than 11.9% for each marker. Recoveries of markers (and internal standards) in plasma and urine were all at least 90%. All markers investigated were shown to be stable when plasma or urine was frozen and thawed. For all the assays developed, there were no interferences from other markers or endogenous substances. In a pilot clinical study, concentrations of all markers could be accurately and reproducibly determined for a sufficient duration of time after administration to calculate accurate renal clearance for each marker. This article presents details of the analytic techniques developed for measuring concentrations of marker drugs for different renal elimination processes administered as a single dose to define the processes contributing to renal drug elimination.