An R package for working with multiple cause of death micro-data.

## Warning

This package is still in the alpha stage.

We cannot emphasize this enough. Nothing is guaranteed to work. Please submit an issue if you find a bug.

## Introduction

Certain types of deaths, including drug overdoses or opioid-related deaths, are defined by an ICD code in both the underlying cause field and one of the twenty possible contributory cause fields. Therefore, in order to tabulate these deaths, researches cannot use compressed mortality files (CMF) (which contain only underlying cause of death), but rather must use multiple cause of death (MCOD) data.

This simple package aims to make common operations — such as downloading, munging, and cleaning — on (inherently messy) MCOD data easier.

Additionally, this package includes data necessary for calculating rates. Specifically, standard populations and annual US population counts from 1979 to 2015. Note that if you are only using 1990 to current, the NVSS Bridged Race files are preferred.

This package is largely the result of our internal code getting reused for multiple papers — therefore, the scope and usefulness of the code is likely limited. We’re releasing it publicly in the hopes that other researchers will learn from our mistakes.

## Installation

This package is not available on CRAN. Use devtools to install:

# install.packages("devtools")
devtools::install_github("mkiang/narcan")

## Usage

Ten lines of code to load packages, download the csv file, load it, and calculate the number of US residents who died from opioids, by sex, in 2015.

library(tidyverse)
library(narcan)

mcod_2015 %>%
subset_residents() %>%
unite_records() %>%
flag_opioid_deaths() %>%
group_by(sex) %>%
summarize(deaths_involving_opioids = sum(opioid_death))

# # A tibble: 2 x 2
#     sex deaths_involving_opioids
#   <chr>                    <dbl>
# 1     F                    11420
# 2     M                    21671

More examples soon.

### Accessing Population Data

Standard populations are held in the std_pops dataframe while annual population estimates (by race, sex, and age) from 1979 to 2015 are held in the pop_est dataframe.

library(narcan)
population_estimates <- narcan::pop_est
standard_populations <- narcan::std_pops

There are also several wiki examples on how to use narcan

• ICD-9 / dta: Download, select, filter, and clean the ICD-9 data in dta format.
• TODO Make one for ICD 10 csv
• TODO Make one using two years with two separate race variables
• TODO Make one showing rnifla_ and rniflag

## Irregularlities in MCOD Data

It is worth noting that there are several important irregularities in the data. This package addresses some while others are simply the way the data are.

• From 1979 to 1998, data are coded using the ICD-9 classification.
• From 1999 to 2015, data are coded using the ICD-10 classification.
• For years using the ICD-9 classification, the rnifla_ column indicates a nature of injury flag for the corresponding record_ column. A 1 indicates an N code (nature of injury) while a 0 represents all other codes (e.g., E for external causes or V coeds).
• Some years call the nature of injury flag column rnifla_ while others call it rniflag_.
• Early year ascii and csv files from NBER contain encoding errors. We suggest downloading files as dta for ICD-9 years and csv files for ICD-10 years.
• Hispanic origin is not recorded until 1989.
• Race codes changed across years.
• Some years code sex as M/F and others as 1/0 or 1/2 .
• In the restricted files, the documentation suggests state variables are coded as FIPS; however, they are actually coded as state abbreviations.

## Sources

### Multiple Cause of Death

Multiple cause of death data (in multiple formats), documentation, dictionaries, and other information are stored on the National Bureau of Economic Research (NBER) website.

The data itself come from the National Center for Health Statistics and are subject to their data use agreement. A GUI interface for these data are provided by CDC Wonder

### Standard Populations

Standard populations are stored on the Surveillance, Epidemiology, and End Results (SEER) section of the National Cancer Institute website.

### Population Estimates

THe annual US population estimates come from the United States Census Bureau’s Population Estimates Program (PEP).