Reports Logic
Based on current tables next data must be aggregated and analyzed:
- Number of patients per doctor
- Number of patients registered for the same phone number
- Number and percentage of patients per doctor that have set offline authorization method
- Number and percentage of patients per legal entity that have set offline authorization method
Using replicated tables from fraud data mart and BI tool the reports with outliers must be shown.
Until there is no enough statistic to use statistical methods to find outliers, the top least(5%, 25 rows) can be shown instead.
For now there are 3 reports are required - for autorization, doctors and phone_numbers.
Predefine views with aggregation
1. Doctor aggregation
number of patients per doctor (total_patients_doctor)
doctors with patients_qty<= 10 are not taken into account.
Conditions: employee, declarations
- employee.id=declarations.employee_id
- employee.employee_type='DOCTOR'
- employee.is_active=true
- employee.status='APPROVED'
- declarations.is_active=true
- declarations.status='active'
Fields:
| SOURCE | FIELD | NAME | DESCRIPTION |
|---|---|---|---|
| employee | party_id | party_id | |
| employee | legal_entity_id | legal_entity_id | |
| declarations | count(person_id) | patients_qty | qty patients by doctor (total till report date) |
| declarations | avg(qty_person_id_30)/ avg(qty_person_id_60) | patient_increase_30d | For each doctor calculate lifetime - (report_date-inserted_at) If doctor lifetime <=90 days or avg(qty_person_id_60)=0 - then null if doctor lifetime >= 90 days and avg(qty_person_id_60)>0: avg(qty_person_id_30) - average number of patients (new declarations) for a doctor for the last 30 days avg(qty_person_id_60) - average number of patients (new declarations) for a doctor for 60 days before last 30 days |
number and percentage of patients per doctor that have set offline authorization method (autorization_doctor)
doctors with patients_qty<= 10 are not taken into account.
Conditions:
- employee.id=declarations.employee_id
- declarations.person_id=presons.id
- employee.division_id=divisions.id
- employee.employee_type='DOCTOR'
- employee.is_active=true
- employee.status='APPROVED'
- declarations.is_active=true
- declarations.status='active'
- divisions.addresses.{type:"RESIDINCE"}
Fields:
| SOURCE | FIELD | NAME | DESCRIPTION |
|---|---|---|---|
| employee | party_id | party_id | |
| employee | legal_entity_id | legal_entity_id | |
| divisions | residence_settlement_type | residence_settlement_type | when type<>'CITY' then 'OTHER' else type |
| persons | count(authentication_methods.type='OFFLINE'.person_id) | offline_patients_qty | authentication_methods.type='OFFLINE' |
| persons | count(authentication_methods.type='OFFLINE'.person_id)/count(person_id) | ratio_offline_patients_qty | ratio of patients with offline method of authorization within particular doctor |
| persons | count(person_id) | patients_qty | qty patients by doctor (total till report date) |
2. Patient aggregation
Using
number of patients with same phone number (patients_phonenumber)
phone numbers with patients_qty<= 1 are not taken into account.
The table recalculates on daily basis
Conditions:
- declarations.person_id=presons.id
- declarations.is_active=true
- declarations.status='active'
Fields:
| SOURCE | FIELD | NAME | DESCRIPTION |
|---|---|---|---|
| persons | phones.{number} | phone_number | |
| persons | count(id) | patients_qty | |
| $inserted_at | report_date | the date when calculated |
3. Legal entity aggregation
number and percentage of patients per legal_entity that have set offline authorization method (autorization_legal_entity)
legal entities with patients_qty<= 50 are not taken into account.
Conditions:
- employee.id=declarations.employee_id
- declarations.person_id=presons.id
- employee.division_id=divisions.id
- employee.employee_type='DOCTOR'
- employee.is_active=true
- employee.status='APPROVED'
- declarations.is_active=true
- declarations.status='active'
- divisions.addresses.{type:"RESIDINCE"}
Fields:
| SOURCE | FIELD | NAME | DESCRIPTION |
|---|---|---|---|
| employee | legal_entity_id | legal_entity_id | |
| divisions | divisions.addresses.residence_settlement_type | residence_settlement_type | when type<>'CITY' then 'OTHER' else type |
| persons | count(authentication_methods.type='OFFLINE'.person_id) | offline_patients_qty | authentication_methods.type='OFFLINE' |
| persons | count(authentication_methods.{type}='OFFLINE'.person_id)/count(person_id) | ratio_offline_patients_qty | ratio of patients with offline method of authorization within particular legal entity |
| persons | count(person_id) | patients_qty | qty patients by legal entity (total till report date) |