A clinical prediction rule is a type of medical research study in which researchers try to identify the best combination of medical signs, symptoms, and other findings in predicting the probability of a specific disease or outcome.

Physicians have difficulty in estimating risks of diseases; frequently erroring towards overestimation, perhaps due to cognitive biases such as base rate fallacy in which the risk of an adverse outcome is exaggerated.

In a prediction rule study, investigators identify a consecutive group of patients who are suspected of a having a specific disease or outcome. The investigators then compare the value of clinical findings available to the physician versus the results of more intensive testing or the results of delayed clinical follow up.

These have had the consequences of their usage by physicians quantified.

When studied, the impact of providing the information alone (for example, providing the calculated probability of disease) has been negative.

However, when the prediction rule is implemented as part of a critical pathway, so that a hospital or clinic has procedures and policies established for how to manage patients identified as high or low risk of disease, the prediction rule has more impact on clinical outcomes.

The more intensively the prediction rule is implemented the more benefit will occur.

It is hoped that the use of STATworkUP may help to influence inclusion of prediction rules in practice. It is designed to correlate selected findings with a set of likely diagnoses based upon the probability settings.

Where clinical prediction rules exist these are included in constructing the relationship between findings and diagnoses.

Abstract:

IatroCom is a closely-held small company composed of doctors, computer engineers, and medical informatisists, founded by Dr Stephen Mlawsky. Our software development enterprises began in 1985 for the Macintosh computer. Throughout the years our applications became more sophisticated. In the 1990s IatroCom marketed, advertised and sold a product named MacON-CALL to doctors, nurses, and hospitals in 40 different countries around the world. Along the way the application was Internet enabled. With the advent of mobile devices, it was obvious that these could leverage our work. In 2010 we released a derivative app named STATworkUP. The delivery of integrated content on mobile devices, for use in clinical settings, just made good sense. We have built a very robust interface that is replete with great content in a nice and fairly clean user interface that is fully-relational. The objective has been to build and deploy a very useful clinical decision support application, full of good medical information, on intuitive and powerful devices like iPhones and iPads, to help busy providers do fast yet comprehensive problem assessments and to help improve care in the process of using it.

A set of functionalities are important when mobile devices are used in health care:

Decision support tools for fast yet comprehensive problem assessments
Differential Diagnosis capability
Practice Guidelines
Advantages of web enablement

STATworkUP