Write and execute a SQL query to list all patient numbers and encounter ids which do not have any data (missing rows) in VisitSummary table. Order the result by patient number, encounter id.

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  1. Write and execute a SQL query to list all patient numbers and encounter ids which do not have any data (missing rows) in VisitSummary table. Order the result by patient number, encounter id. 

 

 

  1. Write and execute a SQL query to list all patients whose information about race or gender has changed during their future visits. A future visit is defined as T1.encounter_id < T2.encounter_id.  Your output should have patient number, old and new race values, old and new gender values, and the encounter ids.

 

  1. Write and execute a SQL query to list all the patient data for all encounters. Even if patient data is missing in other tables, you still need to list the patient_nbr and encounter_id in your output. Your output should list all the columns (without repeating them) starting with encounter_id, patient_nbr... and it should be ordered by patient_nbr and then encounter_id. 

 

  1. Write and execute a SQL query to list all the patient data for all encounters. If the patient data is missing in other tables like Visit summary, then DO NOT include this encounter in your output. Your output should list all the columns (without repeating them) starting with encounter_id, patient_nbr... and it should be ordered by patient_nbr and then encounter_id.
VisitSummary
Patient
VisitMedication
* encounter id
* encounter id
admission type jd
discharge dispenition id
admissi on soure id
* patient nbr
max glu_serum
A1Cmsult
metfommin
firme in_hospital
repaglinide
payer code
na teglinide
medical specialty
chlorpropamide
Radmitted
glimepiride
PatientVisit
acetoheamide
* encounter id
glipizide
patient nbr
glyburide
VisitVitalStat
* encounter id
tol butamide
pioglitazone
age
rexiglitazone
weight
carbose
miglitol
VisitSummaryCount
7 encounterid
gender
troglitazone
talazamide
num lab procedures
examide
num procedures
citogli pton
VisitDiagnostic
num_medications
insulin
* encounterid
number outpatient
glyburide metformin
glipizide metformin
diag 1
numberemergercy
di ag 2
numberinpatient
glimepiride pioglitazone
diag 3
metfomin_rosiglitazone
number diagroes
metfommin pioglitazone
change
diabetes Med
Transcribed Image Text:VisitSummary Patient VisitMedication * encounter id * encounter id admission type jd discharge dispenition id admissi on soure id * patient nbr max glu_serum A1Cmsult metfommin firme in_hospital repaglinide payer code na teglinide medical specialty chlorpropamide Radmitted glimepiride PatientVisit acetoheamide * encounter id glipizide patient nbr glyburide VisitVitalStat * encounter id tol butamide pioglitazone age rexiglitazone weight carbose miglitol VisitSummaryCount 7 encounterid gender troglitazone talazamide num lab procedures examide num procedures citogli pton VisitDiagnostic num_medications insulin * encounterid number outpatient glyburide metformin glipizide metformin diag 1 numberemergercy di ag 2 numberinpatient glimepiride pioglitazone diag 3 metfomin_rosiglitazone number diagroes metfommin pioglitazone change diabetes Med
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  1. Write and execute a SQL query to list all patients whose information about race or gender has changed during their future visits. A future visit is defined as T1.encounter_id < T2.encounter_id.  Your output should have patient number, old and new race values, old and new gender values, and the encounter ids.
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