The attached data exercise is an excerpt from a real Quality Improvement project that was recently completed in the CHOP Emergency Department (ED). Children who come to the ED for an extreme allergic reaction were being kept for observation longer than needed, which resulted in a longer than necessary ED stay. The ED Anaphylaxis QI project team utilized data to identify what portion of the medication administration process was taking too long to implement interventions to decrease the waiting time. Ultimately, patients now receive their treatment in a timely manner and are able to return home sooner as a result of the data analytics you will mimic through the exercise!
This exercise will evaluate your ability to build a cohort and some calculations related to that cohort. We estimate that the data exercise will take about four hours to complete. Please use whatever statistical programming language, programming language, or data manipulation tool you are most comfortable with (SAS, R, SPSS, STATA, Python, SQL, etc).
This exercise will evaluate your ability to build a cohort of patients and calculate some metrics related to that cohort. You should have the following:
• 5 Datasets, which contain all the data you need to complete the exercise
• A data dictionary listing the datasets and the fields contained in each dataset, along with a description of each field
Part 1: Assembling the project cohort
The project goal is to identify patients seen in the emergency department with anaphylaxis or allergic reactions, determine if they had an order for epinephrine, and if they had a follow up outpatient visit after their emergency department visit.
Your task is to assemble the study cohort by identifying encounters that meet the following criteria:
1. The patient's visit is a Hospital Encounter
2. The hospital encounter occurs after August 1, 2014
3. The patient's age is between 1 and 18
4. The patient received an Emergency Department diagnosis (primary or secondary)of anaphylaxis or allergic reaction, identified by the following ICD9 Codes:
ICD_CD
995.0
995.3
995.6
995.60
995.61
995.62
995.63
995.64
995.65
995.66
995.67
995.68
995.69
995.7
999.4
999.41
999.42
999.49
5. The encounter was not at an Urgent Care department. Patients seen in Urgent Care departments also receive diagnoses that are flagged as ED diagnoses, but encounters at Urgent Care departments should be excluded.
Part 2: Creating Additional Fields
With your anaphylaxis and allergic reaction cohort, create the following indicators:
1. ANAPH_DX_IND: 1 if the encounter has at least one diagnosis where the text of diagnosis name contains the word ‘anaphylaxis', 0 if it does not
2. EPI_ORDER: 1 if the patient had at least onemedication order name (med_ord_nm) where the text of the medication name contains the word ‘epinephrine', 0 if they did not
3. FOLLOW_UP: 1 if the patient was seen for an outpatient visit within 7 days of being discharged from their anaphylaxis/allergy hospital visit, 0 if they were not seen for an outpatient visit within 7 days. A patient who is seen at any point on the 7th day should be flagged (e.g., a patient who presents to the ED on 2/6/2015 at 1AM who had an outpatient follow up visit on 2/13/2015 at 3PM should be flagged as having an outpatient visit within 7 days, even though this is greater than 168 hours apart).
4. FOLLOW_UP_DATE: The date of the first (if any) outpatient follow up that occurs within 7 days. The field should be blank if there is no follow up within 7 days.
5. DAYS_TO_FOLLOW_UP: The number of days from the patient's discharge from the hospital to the first (if any) outpatient follow up visit (e.g., a patient discharged at 3PM on 1/3/2015 who had an initial outpatient follow up at 5PM on 1/6/2015 should have a DAYS_TO_FOLLOW_UP of 3). The field should be blank if there is no follow up within 7 days.
Part 3: Export the data set into a csv file
Export a dataset containing these required fields:
Please down load the data exercise fron the below link:
https://www.dropbox.com/l/q0fDXxujY8aZe2LGMxirfs