# Luk Arbuckle

## Time series analysis of public health data

In time series on 28 November 2008 at 3:45 pm

Since I’m finishing a course in time series analysis I decided to look for applications in biostatistics (an area I’m interested in).  In my search I found a paper On Time Series Analysis of Public Health and Biomedical Data (subscription required for the PDF).  When I downloaded the paper I thought it was a literature review, but it’s really a gentle introduction to time series analysis for health professionals (although at times the authors use terminology that I think will confuse more than enlighten).

On independence and applications
An important point made in the article is that time series analysis should be used instead of standard regression analysis when the observations (or outcome measures) are not independent.  Otherwise inferences will not be valid (since independence is a key assumption in standard regression).  Time series models, on the other hand, take correlation between observations into account (resulting in valid and more efficient inferences).  An example is given wherein standard regression would imply a downward trend in birth rate (for their particular data, recording births in an area for about three years), whereas time series methods do not allow for such a conclusion.

The authors point out the increasing use of time series analysis in health research, as evidenced by a search on PubMed.  Some application areas mentioned in the paper:

• gene expressions to describe molecular and cellular processes
• physiologic studies, in general (including image analysis for PET or fMRI, as well as some areas of critical care medicine)
• basic epidemiologic studies of infectious and chronic diseases
• environmental epidemiology
• health services research (to evaluate interventions)
• demographic analyses of population health

Although these examples of application areas for time series analysis are interesting, it doesn’t go nearly far enough in the details.  I would like to know more about how, specifically, time series analysis is being used to advance health research.  This is one reason I was originally looking for a literature review.  Another reason is that I would like to figure out the areas in which improvements in the theory and methods are still needed (i.e., brain storming for a research topic).   Maybe that’s asking too much of a single paper, but I’ve read literature reviews in the past and they usually cover such ground.  I’ll have to try and find something in a biostats journal.

## Bad blood at the American Red Cross

In news on 18 July 2008 at 11:31 pm

For years the U.S. Food and Drug Administration (FDA) has been after the American Red Cross to improve the way it collects and processes blood. Fifteen years ago they arrived at a settlement under court order that outlined how the American Red Cross would have to strengthen quality control and training, and improve its ability to identify, investigate and record problems. But, as detailed in the New York Times, only modest improvements have been made since that time.

As rightfully pointed out at the STATS blog, pharmaceutical companies would never be allowed the leeway that has been given to the American Red Cross. They failed to inform the FDA of their mistakes, let alone investigate the results of them, and as a results no one really knows how many serious health problems they are responsible for. As the old mantra goes: you can only manage what you measure.

Also disconcerting is that two-thirds of their revenue at the American Red Cross comes from blood services. But how much of that revenue goes back into blood services, or go to subsidize disaster-relief efforts? They don’t know, because of a antiquated financial systems.