hospital patients analysis
Lukman Omotosho
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create table patients ( patient varchar(100) primary key not null, birthdate date, deathdate date, ssn varchar(100), drivers varchar(100), passport varchar(100), prefix char(10), first_name char(30), last_name char(30), suffix char(10), maiden char(20), marital char(10), race char(20), ethnicity char(30), gender char(10), birthplace char(30), address varchar(100)); create table patient_condition ( start_date date, stop_date date, patient varchar(100), encounter_id varchar(100), code_id int, condition_description varchar(100)); create table medications ( start_date date, stop_date date, patient varchar(100), encounter_id varchar(100), code_id int, medication_description varchar(100), reason_code int, reason_description char(100)); select * from patients limit 10; select * from medications limit 10; select * from patient_condition limit 10; #The most reoccurent disease in patient select condition_description, count(*) as no_of_occurence from patient_condition group by condition_description order by no_of_occurence desc limit 10; #Number of viral sinusitis conditions in males and females select p.gender, pc.condition_description, count(*) as no_of_occurencies from patients p inner join patient_condition pc on p.patient = pc.patient group by p.gender, pc.condition_description having pc.condition_description = 'Viral sinusitis (disorder)' order by no_of_occurencies; #Number of males and females with Acute Bronchitis select p.gender, pc.condition_description, count(*) as no_of_occurencies from patients p inner join patient_condition pc on p.patient = pc.patient group by p.gender, pc.condition_description having pc.condition_description = 'Acute bronchitis (disorder)' order by no_of_occurencies; #Number of pregnancy according to ethnic group select p.ethnicity, pc.condition_description, count(*) as no_of_occurencies from patients p inner join patient_condition pc on p.patient = pc.patient group by p.ethnicity, pc.condition_description having pc.condition_description = 'Normal pregnancy' order by no_of_occurencies desc limit 10; #Medications and the reason for their use select medication_description, reason_description, count(*) as frequency from medications group by medication_description, reason_description order by frequency desc; #The medications most used by each ethnic group select p.ethnicity, m.medication_description, count(*) as frequency from patients p inner join medications m on p.patient = m.patient group by p.ethnicity, m.medication_description order by frequency desc; #Number of dead patient who took injections select count(p.deathdate) as no_of_death from (select * from medications where medication_description like '%Injection') i inner join patients p on i.patient = p.patient; #Medications most used by married patients select p.marital, m.medication_description, count(*) as frequency from patients p inner join medications m on p.patient = m.patient group by p.marital, m.medication_description having p.marital = 'M' order by frequency desc limit 10; #The race using the most drugs related to disorder select p.race, m.reason_description, count(*) as frequency from patients p inner join medications m on p.patient = m.patient group by p.race, m.reason_description having m.reason_description like '%(disorder)' order by frequency desc; #Conditions encountered by most dead patient select pc.condition_description, count(deathdate) as frequency from patients p inner join patient_condition pc on p.patient = pc.patient group by pc.condition_description order by frequency desc limit 10; #Conditions with the highest average number of days to recover select condition_description, avg(datediff(stop_date, start_date)) as recover_days from patient_condition group by condition_description order by recover_days desc limit 10; #Conditions with the lowest average number of days to recover select condition_description, avg(datediff(stop_date, start_date)) as recover_days from patient_condition group by condition_description order by recover_days limit 10; #Average number of days it takes for each gender to recover from disorders select p.gender, pc.condition_description, avg(datediff(pc.stop_date, pc.start_date)) as recover_days from patients p inner join patient_condition pc on p.patient = pc.patient group by gender, condition_description having pc.condition_description like '%(disorder)' order by 2; #Birthplace of patients with highest number of conditions select p.birthplace, count(pc.condition_description) as no_of_conditions from patients p inner join patient_condition pc on p.patient = pc.patient group by birthplace order by no_of_conditions desc limit 1; #Number of pregnancy by race select p.race, pc.condition_description, count(*) as no_of_pregnancies from patients p inner join patient_condition pc on p.patient = pc.patient group by race, condition_description having pc.condition_description = 'Normal pregnancy' order by no_of_pregnancies desc; #The name of patients with the most number of conditions select p.first, p.last, count(*) as no_of_conditions from patients p inner join patient_condition pc on p.patient = pc.patient group by first, last order by no_of_conditions desc limit 10; #The patients with the least number of conditions select p.first, p.last, count(*) as no_of_conditions from patients p inner join patient_condition pc on p.patient = pc.patient group by first, last order by no_of_conditions limit 10;
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Posted Sep 10, 2024
I utilized SQL to extract, transform, and analyze patient records. Key areas of focus included patient demographics, conditions and medications.
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