This award recognizes a graduate student for contributions to the department’s research mission and science through developing a novel computer program/tool that can assist in improving the efficiency and quality of conducting research. Examples of programs eligible for this award include, among many others, programs that operationalize complex measurement of a variable, (e.g., SAS macro for certain types of exposures or complex overlapping enrollment criteria), code that creates unique or high-quality graphics, or a program that solves a common logic problem.
The program intends to find the optimal penetration rate threshold for different large health systems. Using data from areas where penetration rate is higher than the threshold, researchers can accurately estimate the prevalence of disease using Electronic Health Records.
This macro code can be used to identify new users of a therapeutic drug class as well as new users of individual drugs of a particular therapeutic drug class.
In drug utilization study we are often interested in looking at concomitant use of drugs or medication switching in our patient population. Such trend analysis is important to understand prescribing practices and drug utilization in the real-world setting. Tables are often used to describe such data, but it can be cumbersome and difficult to follow when data is too big. This issue can be resolved by using ChordDiagram function in the R software, which allows the readers to visualize such data intuitively. The dataset provided for the demonstration of the code looks at initial antihypertensive regimens in newly diagnosed hypertension patients. It is not uncommon for these newly diagnosed hypertension patients to initiate their drug regimen with more than one anti-hypertensive medications. Therefore, it is important to know how often different anti-hypertensives are prescribed concomitantly. The frequency table containing such a data may not help the readers to know which anti-hypertensives drugs are prescribed more frequently together. Hence, ChorDiagram has the benefit to link information between two columns using frequencies. In the dataset provided we have three columns as medname1, medname2 and frequency. In the given code the column medname1 links to medname2 and the thickness of the link determines how often are they prescribed together. The provided code also helps to differentiate between the different drug classes using different colors for each anti-hypertensive class.
The Cohort Building Program is a reusable tool to build a cohort with a new user and active comparator design. The program can be applied to various research questions with limited coding modifications.
This macro code can be used to run a prescription sequence symmetry analysis on an index drug/class and marker drug/class. The main output of this code is the adjusted sequence ratio for a given index drug/class -> marker drug/class (potential) prescribing cascade.