Statistical Recognition of Trends in Health Monitoring Systems

The determination of when trends are present in an active health monitoring system is considered. The type of data collected is often voluntary response data usually of unknown, or perhaps of low quality or reliability. Often, even if the data themselves are perfectly reliable, the different monitoring stations are usually not comparable in size or scope, so aggregrate measures would tend to mask rather than detect trends for the whole system.Examples of such monitoring systems are the World Health Organization’s Research Center for International Monitoring of Adverse Reactions to Drugs and the »Programa de Investigacion de Modelos Operacionales de Prestacion de Servicios de Salud« (PRIMOPS) operating in Cali, Columbia. We study a »Center-Batch matrix« by using a transformation to a matrix of ranks. It incorporates most of the relevant information. A relatively simple statistical technique is presented for generating a warning signal whenever a pattern of increasing adverse events does occur. This rank Center-Batch method avoids some of the pitfalls of the previous methods used and in fact is often quite superior.