MIMIC-III (Medical Information Mart for Intensive Care III) is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. https://mimic.mit.edu/docs/iii/
Metadata
List of tables in database
select
database_name,
table_name,
estimated_size
from
duckdb_tables;
database_name | table_name | estimated_size |
---|
List of table columns
select
schema_name,
table_name,
column_name,
column_index,
data_type
from
duckdb_columns;
schema_name | table_name | column_name | column_index | data_type |
---|
All patients
select * from patients;
subject_id | gender | dob | dod | dod_hosp | dod_ssn | expire_flag |
---|
All admissions
select * from all_admissions;
hadm_id | subject_id | admittime | dischtime | deathtime | admission_type | admission_location | discharge_location | insurance | language | religion | marital_status | ethnicity | edregtime | edouttime | diagnosis | hospital_expire_flag | has_chartevents_data |
---|
Exploring Patients
Lets start by exploring the patients table
--number of patients
select count(*) as n_patients from patients;
--number of unique patients
select count(distinct subject_id) as n_patients from patients;
-- distinct gender
select distinct gender from patients;
-- breakdown by gender
select gender, count(*) as n_patients from patients
group by gender;
gender | n_patients |
---|
Exploring Admissions
- Identify the data types of the columns
- How many patients were admitted
- How many admissions?
- How old are patients at admissions
- Group patients into various age groups
- Breakdown of admissions by race and ethnicity
- Number of admitted patients over time
- Number of admissions by day: weekday vs weekends
- Hospital length of stay or Duration
- Breakdown by admission types and admission source
- Where are the patients admitted from?
- Where are patients discharged to?
- Types & percentage of insurers
- What percentage of patients are admitted from the ED. ED Admit Rate
- What are the average duration of patients in the ED
- What are the top diagnosis by age groups?
- Number of patients that expired in the hospital.