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# AHRQ_pipeline | ||
# AHRQ_pipeline | ||
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Key Steps | ||
Load Libraries: | ||
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caret | ||
data.table | ||
dplyr | ||
sets | ||
scales | ||
tidyr | ||
stringr | ||
Load Data: | ||
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Load patient data from a CSV file. | ||
Load multiple years of AHRQ SDOH data from CSV files. | ||
Load a CSV file containing feature names for AHRQ SDOH variables. | ||
Preprocess AHRQ Data: | ||
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Merge AHRQ data from multiple years into a single data frame. | ||
Pad ZIP codes and STATEFIPS codes with leading zeros for consistency. | ||
Optionally perform imputation for missing values. | ||
Merge Data: | ||
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Merge the preprocessed AHRQ data with patient data using crosswalk variables: | ||
STATEFIPS | ||
ZIPCODE | ||
YEAR | ||
Write Output: | ||
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Write the merged data to a CSV file. | ||
Additional Information | ||
The notebook includes code for data summarization and visualization using bar charts. | ||
Potential areas for further work include: | ||
Implementing imputation strategies. | ||
Exploring different merging approaches. | ||
Conducting further analysis on the merged data. | ||
For more details and the full code, please refer to the notebook itself. | ||
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The AHRQ SDOHD data used in this notebook can be accessed from the following link: | ||
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AHRQ SDOHD: https://www.ahrq.gov/sdoh/data-analytics/sdoh-data.html#download | ||
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