HL7reporting 0.0.10

A package designed to improve HL7 Data Quality reporting in the field of public health informatics.

HL7reporting

Github Project

Background

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How it Started

My name is PJ Gibson and I am a data analyst with the Indiana State Department of Health. My Informatics department arranged a grant with a group who could improve the quality of hospital reporting. We needed to track the progress of this hospital reporting, which required diving into HL7 Admission/Discharge/Transfer (ADT) messages and assessing for data completion and validity. Enter me.

The Goal

The main purpose of this package is to give data quality analysis functions to workers in public health informatics.

Functions

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NSSP_Element_Grabber

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Documentation

NSSP_Element_Grabber(data,Timed = True, Priority_only=False, outfile='None')

Creates dataframe of important elements from PHESS data.

NOTE:  Your input should contain column titles:
	MESSAGE, PATIENT_VISIT_NUMBER, PATIENT_MRN,
	FACILITY_NAME

	if you don't have visitnum, mrn, or facname, create empty cols
appended to your message column

Parameters
----------
data: pandas DataFrame, required, from PHESS sql pull

Timed:  Default is True.  Prints total runtime at end.
Priority_only:  Default is False.  
    If True, only gives priority 1 or 2 elements
outfile:  Default is 'None':
    Replace with file name for dataframe to be wrote to as csv
    Will be located in working directory.
    DO NOT INCLUDE .csv IF YOU CHOOSE TO MAKE ONE

Returns
-------
dataframe with columns of NSSP priority elements for each message (row)

Code Examples

# read in data
data1 = pd.read_csv('somefile.csv',engine='python')

# process through NSSP_Element_Grabber() function
parsed_df = NSSP_Element_Grabber(data1,Timed=False,
                                    Priority_only=True,outfile='None')

*if you don't have mrn, visit_num, or facility_name

data1 = pd.read_csv('somefile.csv',engine='python')

# create new dataframe with correct column names
cols = ['MESSAGE','PATIENT_MRN', 'PATIENT_VISIT_NUMBER', 'FACILITY_NAME']
new_input_dataframe = pd.DataFrame(columns=cols)

# define new dataframe column using our data
new_input_dataframe['MESSAGE'] = data1['message'] # replace message according to correct column title of data1

# process through NSSP_Element_Grabber() function
parsed_df = NSSP_Element_Grabber(new_input_dataframe, Timed=False,
                                    Priority_only=True,outfile='None')

Visualization of Output

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FAQs

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Where can I access function documentation outside of this location?

Within a Jupyter Notebook document, you can type:

FunctionNameHere?

into a jupyter notebook cell and then run it with SHIFT + ENTER. The output will show you all the function documentation including a brief description and argument descriptions.

Why Python?

I work entirely in Python. In the field of public health informatics, R is the most popular programming language. I have created this package to run as intuitively as possible with a minimal amount of python knowledge. I could be wrong, but I believe that one day, public health informatics may become Python-dominant, so this package could help as an introduction to the environment to those unfamiliar.

For plottting, what if I want to make small changes such as color changes, formatting, or simple customizing?

Right now I don't have things set up for that sort of work. My best solution would be for you to dive into my Github reposiory python file linked here. You can copy the defined functions into your document and make minor adjustments as you see fit.

Why isn't the NSSP_Element_Grabber() function working?

The most common problem in this situation is a incorrectly formatted input. The input needs to be a pandas dataframe containing the following columns:

['MESSAGE','PATIENT_MRN','PATIENT_VISIT_NUMBER','FACILITY_NAME']

caps DOES matter. If your raw data file does not contain MRN, visit number, or facility name, you may create a dataframe with all NaN values for these columns and the function should still work properly.

My question isn't listed above...what should I do?

feel free to contact me at:

[e-mail]

with any additional questions.

The Author

PJ Gibson - Data Analyst for Indiana State Department of Health

Special Thanks

• Harold Gil - Director of Public Health Informatics for Indiana State Department of Health. Harold assigned me this project, gave me relevant supporting documentation, and helped me along the way with miscellaneous troubleshooting.
• Matthew Simmons - Data Analyst for Indiana State Department of Health. Matthew helped walk me through some troubleshooting and was a supportive figure throughout the project.
• Shuennhau Chang, Logan Downing, Ryan Hastings, Nicholas Hinkley, Rachel Winchell. Members of my informatics team that also supported me indirectly!