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SAS® Tools for Transparent and Reproducible Research: Medication History Estimator
- Brian C. Sauer, SLC Veterans Affairs Medical Center,
- Tao He, University of Utah,
- Jonathan R. Nebeker, SLC Veterans Affairs Medical Center
Presented: SAS® Global Forum 2013
The Medication History Estimator (MHE) is designed to output data at the course-level; i.e., one row of data per drug course. Course and period Medication Possession Ratio (MPR) are calculated for each medication. Reports that describe the frequency and percent of users for each medication product, average duration of medication courses, medication possession ratios and Kaplan-Meier based persistency curves are automatically generated and formatted for professional reports and journal publications.
NOTE: THIS VERSION HAS BEEN UPDATED FROM THE PUBLISHED PROCEEDINGS. WE CORRECTED THE FIGURES AND CLARIFIED THAT THE MEDICATION POSSESSION RATIO IS THE DEFAULT MEASURE OF ADHERENCE
Epidemiological and health services research has been criticized as being unreliable.(1) Scientific evidence is strengthened when the study procedures of important findings are transparent, open for review, and easily reproduced by different investigators and in various settings.(2-4) Many research studies have common scientific workflows(5, 6) and general execution engines can be developed to reuse epidemiological software for specific clinical questions. Development of modular SAS programs that can be combined to produce epidemiological pipelines to automate components of the research process will support transparent and rapid response to nationally important clinical questions.
Estimating each patient’s medication exposure is a fundamental component of any study that aims to evaluate the safety or effectiveness of medication therapy in an observational setting. When investigators design studies that evaluate medication exposure or compare medications they are confronted with a series of decisions concerning how to characterize treatment histories and classify treatment groups. Example decisions include whether to conduct an intention-to-treat analysis or to evaluate only outcomes during medication exposure. Researchers must also decide on criteria for identifying incident or new courses of drug therapy rather than utilizing established courses. The approach used to infer a patient’s treatment history from medication orders or dispensing data influences cohort identification and treatment group classification. Nevertheless, descriptions of methods are typically not adequately explicit to replicate study procedures directly from the published narrative. This is due to the fact that journals govern the distribution of scientific findings while the task of distributing methods and protocols is customarily relegated to authors.(4)
To be compliant with the basic principles of transparency, reproducibility and reusability(2, 4, 7) we developed a generalized approach to estimate medication histories that can be used to summarize medication exposure in a population and to structure data for epidemiological evaluation. The approach is considered “generalized” because the program can be used to estimate medication histories for any drug therapy and it is flexible enough to allow a vast number of unique parameterizations. This paper describes the features of the SAS program and presents example output data structures and reports.
The Medication History Estimator (MHE) is designed to output data at the course-level – i.e., one row per drug course. A course and period Medication Possession Ratio (MPR) is calculated for each medication. Reports that describe the frequency and percent of users for each medication product, average duration of medication courses, medication possession ratios, and Kaplan-Meier based persistency curves are automatically generated and formatted for professional reports and journal publications.
MEDICATION HISTORY ESTIMATOR MODULE AND INPUT FILES
The MHE is intended to be a module within a workflow that executes pharmacoepidemiologic processes. The analytic module contains a specification file that allows the user to define the parameter settings of the program, a main program in which the user defines the file pathways and runs code, execution engine and user document. The MHE also has a user-defined input file listing the medications required to compute drug courses. To execute this module the user simply needs to specify the input parameters, list the medications of interest, set the file locations in the main program, then "run" the main program.
Download the rest of the article from here: Media:SAS_PaperSauerMHE_Sugi2013_v2.0.pdf
MHE package can be found at the following links:
- File:Drug list.txt (Download Drug_list.txt)
- File:Program Setup.txt (Download Program_Setup.txt)
- File:Readme.txt (Download Readme.txt)
- File:MHE Reports.sas (Download MHE_Reports.sas)
- File:MHE MainProgram.sas (Download MHE_MainProgram.sas)
- File:MHE ExecutionEngineV3.sas (Download MHE_ExecutionEngineV3.sas)
- File:Observation period.sas7bdat (Download Observation_period.sas7bdat)
For example data or access to the deluxe version of the MHE contact me directly. Brian