A Generic Prescription Outcome Model

In medical science progress is measured in outcome. Epidemiology studies the occurrence relation between exposure and outcome. Patients can be exposed to a variety of factors, patient related, disease related and or treatment related. Also, treatment can be defined in the broadest sense in that any intervention in patient care can be regarded as an exposure that can influence outcome.

Computerized prescriber order entry systems (CPOE systems) fit can have an influence on patient outcome just as the treatment that is described using (or not using) these systems. Therefore, CPOE systems have to be studied and the occurence relation between the use of CPOE as an exposure and outcome is just as relevant as any other medical intervention research.

Defining outcome that can be measured is a challenge. Specifically, strict definitions have to be developed to facilitate comparable research results. This BLOG attempts to describe an outcome model that can be applied to research on CPOE systems.

A definition of outcome has to take into account the process of drug treatment in patients, because CPOE systems can affect every aspect of a conceptual treatment cycle:





1. Defining the treatment indication
2. Generating the drug prescription
3. Validate the drug prescription
4. Schedule the drug
5. Prepare the drug
6. Administer the drug
7. Evaluate the effects of the prescription


The effect of a CPOE can be measured at all of these 7 levels. Most of the time the of CPOE systems and the process of drug prescription is measured in terms of error. As each level in the medication cycle involves a process, things can go wrong in the process. The potential benefits of interventions in the process of drug prescription can be expressed in efficiency, both in time as in finance.