EHTH Medical Corp. DatabaseEHTH Medical Corp. Database

Damon WilsonDamon Wilson Kevin YeinKevin Yein

Andy ChangAndy Chang Sai RakchartSai Rakchart

Mike LeeMike Lee Shehzad WadalawalaShehzad Wadalawala

Larry HuanLarry Huan Paolo VincentiPaolo Vincenti

Dark Horse Dark Horse ConsultingConsultingpresents…presents…

Presentation OverviewPresentation Overview

Company Introduction Company Introduction EER DiagramEER DiagramRelational SchemaRelational SchemaNormalization AnalysisNormalization AnalysisIn-Depth Query AnalysisIn-Depth Query Analysis

EHTH Medical CorporationEHTH Medical Corporation

– Two doctor private practice.Two doctor private practice.

– 2000 active patients2000 active patients

– Based in San Jose, CA.Based in San Jose, CA.

– General medicineGeneral medicine

– Specialization in Specialization in pulmonologypulmonology and and oncologyoncology..

Database GoalsDatabase Goals

• Provide EHTH Medical with an efficient means of Provide EHTH Medical with an efficient means of storing and retrieving informationstoring and retrieving information

• Evaluate and study related risk factors for particular Evaluate and study related risk factors for particular diseasesdiseases

• Increase the flexibility of EHTH Medical’s information Increase the flexibility of EHTH Medical’s information system.system.

EER DiagramEER Diagram

EER DiagramEER Diagram

Relational SchemaRelational SchemaEntities/1:N Relationships 

1. Employee (SSN, LName, FName, MName, Home_Phone)1a. Secretary (SSN1)1b. Physician (SSN1, pager_number) 1c. MedStaff (SSN1, Work_Days)

2. Patient(SSN, LName, FName, MName, PlanID, Name_of_Provider, Home_Address, Home_City, Home_State, Home_Zip Home_Phone, Work_Phone, Birth_Month, Birth_Day, Birth_Year, Sex, Marital_Status, Employer, Ethnicity, etc.

2a. General_Patient (SSN2) 2b. Cancer_Patient (SSN2, Area, Stage, Treatment)2c. Pulmonological_Patient (SSN2)

3. Condition (CID, CName, Description)4. Drug (DID, DName, Category, Active_Ingredient, Dosage)5. Family (FID, FName)6. Appointment (AID, Patient_SSN2, Time, Month, Day, Year, Secretary_SSN1a, Doctor_SSN1b, Claim_ID7, Cancel, Description)7. Claim (CID, Phy_SSN1b, InsProvID8, AID6, Fname_phys, Lname-phys)8. Insurance_Provider (InsProvID, Name, Address, City, State, Zip, Phone, Type)9. Insurance_Plan (PlanID, Ins_Prov_ID8, Copayment, Deductable, Name_of_provider) 10. Outside_Doctor(DocID, LName, FName, MName, Address, City, etc.

N:M Relationships 11. Treats (PhysSSN1b, PatientSSN2) 12. ParticipatesIn (StaffSSN1c, AID6, Month, Day, Year, Time)13. ReferredTo (OutPhysID10, PatientSSN2, RefferingPhySSN1b, Month, etc. 14. RelatedTo (SSN2, FID5)

15. Has (PatientSSN2, CondID3, Onset_Month, Onset_Year)16. Taking (SSN2, DrugID4, Start_Month, Start_Day, Start_Year, End_Month, End_Day, End_Year)17. AllergicTo (PatientSSN2, DrugID4)18. For (DrugID4, CondID3)19. NoToBeTakenWith (DrugID14, DrugID24) 20. Had(PatientSSN2, CondID3, End_Month, End_Year) 

Multi Attributes21. Family_Siblings(FID5, FName, LName, MName, Status, Cause_of_Death)22. Family_Parents(FID5, FName, LName, MName, Status, Cause_of_Death)

23. Family_Dependents(FID5, FName, LName, MName, Status, Cause_of_Death)

24. Family_Notes(FID5, Info)25.

Patient_Emergency_Contact(PatientSSN2, FName, LName, MName, Phone, Relationship)26. Family_Maternal_Relatives(FID5, FName, LName, MName, Status, Cause_of_Death)27. Family_Paternal_Relatives(FID5, FName, LName, MName, Status, Cause_of_Death)

28. Patient_Hospital_Visit(PatientSSN2, Month, Day, Year, Reason, Treatment)29. Claim_Charges(ClaimID7, ProcedureID, Amount, Month, Day, Year)

Normalization AnalysisNormalization Analysis7. Claim7. Claim

CID Phy_SSN1b InsProvID8 AID6 Fname_phys Lname-phys

FD1

FD2

Transitive Dependency violates 3NF

NormalizationClaim1

CID Phy_SSN1b InsProvID8 AID6

Phy_SSN1b Fname_phys Lname-phys

Claim2

FD3

FD4

Normalization AnalysisNormalization Analysis9. Insurance_Plan9. Insurance_Plan

PlanID Ins_Prov_ID8 Copayment Deductable Name_of_provider

FD1

FD2

Partial Dependency violates 2NF

Normalization

Insurance_Plan1

Insurance_Plan2

FD3

FD4

PlanID Ins_Prov_ID8 Copayment Deductable

Ins_Prov_ID8 Name_of_provider

Scheduling QueryScheduling Query

EnglishEnglishFor a specific day, generate a schedule that lists the patient name, For a specific day, generate a schedule that lists the patient name, reason for appointment, and time of appointment, for all the day’s reason for appointment, and time of appointment, for all the day’s appointments.appointments.

Important aspectsImportant aspects• Determine free appointment timesDetermine free appointment times• Organize scheduling systemOrganize scheduling system• Identify trendsIdentify trends

Scheduling Query ScreenshotScheduling Query Screenshot

Total Revenue QueryTotal Revenue Query

EnglishEnglishList the total revenue earned by the practice for the last month, List the total revenue earned by the practice for the last month, grouped by insurance provider.grouped by insurance provider.

Important aspectsImportant aspects• Determine origin of clienteleDetermine origin of clientele• Focus marketing tacticsFocus marketing tactics• Insurance provider relationshipsInsurance provider relationships

Total Revenue Query ScreenshotTotal Revenue Query Screenshot

Patient Frequency QueryPatient Frequency Query

EnglishEnglishList patient name and insurance plan for all patients whoList patient name and insurance plan for all patients whohave had an appointment in every month of the selected year. have had an appointment in every month of the selected year.

Double Negative JargonDouble Negative JargonList all patients for which there does not exist a month in the selectedList all patients for which there does not exist a month in the selectedyear for which there was no appointment.year for which there was no appointment.

Important AspectsImportant Aspects• Identify important / critical patientsIdentify important / critical patients• Identify hypochondriacsIdentify hypochondriacs

Patient Frequency ScreenshotPatient Frequency Screenshot

Forecasting QueryForecasting Query

EnglishEnglishUse a moving average to forecast the number of patients that EHTH Use a moving average to forecast the number of patients that EHTH Medical will see in the next month.Medical will see in the next month.

Interesting aspectsInteresting aspects• Predict future demandPredict future demand• Helps determine staffing and supply requirementsHelps determine staffing and supply requirements

Forecasting Query ScreenshotForecasting Query Screenshot

Hypothesis QueryHypothesis Query

EnglishEnglishTests hypothesis that Asian ethnicity is correlated to the onsetTests hypothesis that Asian ethnicity is correlated to the onsetof cancer. of cancer.

Returns 95% Confidence interval for the number ofReturns 95% Confidence interval for the number ofAsians that should have cancer if the the hypothesis is true.Asians that should have cancer if the the hypothesis is true.Also returns actual number of cases of cancer among Asians.Also returns actual number of cases of cancer among Asians.

Interesting AspectsInteresting Aspects• Specialize treatment towards different patient groupsSpecialize treatment towards different patient groups• Warn high risk patientsWarn high risk patients• Can vary conditions and ethnicitiesCan vary conditions and ethnicities

Hypothesis Query ScreenshotHypothesis Query Screenshot

Form ScreenshotsForm Screenshots

Questions…Questions…