IS 6156 Jean Donnelly 90079094 Brendan McSweeney 114223513 Tim Walsh 102859661

MBS ISBP IS 6156 Group Assignment
Databases for Management Information Systems
Lecturer: Dr. Ciara Heavin
20 March 2015
Student Information:
Jean Donnelly 90079094
Timothy Walsh 102859661
Brendan McSweeney 114223513

Table of Contents
Introduction............................................................................................................................................................1
Part 1: Entity Relationship Diagram........................................................................................................................1
Part 2: Database Tables ..........................................................................................................................................4
Patient Table ......................................................................................................................................................4
Admission Table .................................................................................................................................................5
Assessment Table...............................................................................................................................................7
Consultant Table ................................................................................................................................................8
Procedure Table .................................................................................................................................................9
Booking Table...................................................................................................................................................10
Service Table ....................................................................................................................................................11
Utilisation Table ...............................................................................................................................................12
Employee Table................................................................................................................................................14
Sample Table....................................................................................................................................................14
Test Result Table ..............................................................................................................................................16
Test Table .........................................................................................................................................................17
Part 3: SQL Queries...............................................................................................................................................19
Query 1 Identification of Patients at Risk through Blood Testing ............................................................19
Query 2 Identification of Patients at Risk through Air-Transmitted Infection .........................................20
Query 3 Identification of Patients at Risk from Infection through Consultant ........................................21
Query 4 Identification of Patients at Risk of Infection at time of Taking Blood Sample ..........................22
Query 5 Identification of Under-Utilised Hospital Services .....................................................................22
Query 6 Identification of Over-Utilised Hospital Services........................................................................23
Query 7 Identification of the Operating Theatre with the Highest Usage ...............................................24
Query 7 Overview of Hospital Services Usage .........................................................................................25
Query 8 Number of Bookings per Service per Date .................................................................................27
Query 9 Identification of Hospital Services without Bookings.................................................................28
Query 10 Identification of Date for 6-week Post-Operative Check-up Appointment................................28
Part 4: Securing Patient Data using Oracle...........................................................................................................30
Conclusion ............................................................................................................................................................31
References............................................................................................................................................................31
Appendix 1............................................................................................................................................................32
Appendix 2............................................................................................................................................................34

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Surgical Department Database Development
Introduction
This report describes the design, creation and utilisation of an Oracle database for a hospital's surgical
department. This database holds the Electronic Health Records (EHRs) for all surgical patients,
incorporating their personal, admission, assessment, blood test and treatment data to provide one
unified view of the surgical system. Querying of this database will provide insights into patient care
that minimise the risks posed to patients during their hospital stay. Previous personal experiences of
surgical and medical laboratory environments and documents (Appendix 1) have informed this view
of the EHR database.
The database also holds information on the treatment procedures scheduled for patients in the
department, facilitating views into utilisation of hospital services for management to use in improving
the efficient running of the hospital.
Due to the nature of the EHRs held in the database, privacy and security are critical concerns and this
issue will also be addressed in this report.
Part 1: Entity Relationship Diagram
The scope of this database is a hospitals Surgical Wards. The database maintains patient's Electronic
Health Records (EHRs) comprising information on the patient, his/her assessments, admissions, tests,
results and procedures.
The following Entity Relationship Diagram (ERD) provides a graphical representation of these
normalised database tables, their attributes and the relationships between them. The following
assumptions were made regarding this scenario:
 This database scope extends only to a hospitals surgical wards
 Patient_ID is assigned by the hospital and is a unique personal identifier that may be used for
that patient for multiple admissions.
 The capacity of Services is measured in hours/day and represents the hours per day that it is
available for use.
 Utilisation of services is examined historically in this scenario.
 Usage is measured in hours.
 The usage hours for a service is input at the end of each day if that service is used.
 Each blood sample may be divided in order to undergo multiple tests.
Due to limitations in the Microsoft Visio application available for creation of the ERD, some of the
relationships depicted are not as intended. Please note the following:
 Booking can be performed by one and only one consultant
 Booking refers to one and only one patient
 Admission refers to one and only one patient

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 Sample belongs to one and only one patient
 Sample is taken by one and only one employee
 Booking is made for one and only one procedure
 Booking is made for one and only one service

3
TestResult
PK,FK1 TestID
PK,FK2 SampleID
Test_Result
Utilisation
PK Utilisation_Date
PK,FK1 Service_ID
Usage
Service
PK Service_ID
Service_Name
Capacity
Booking
PK BookingID
Booking_Date
FK1 ServID
FK2 ProcedureID
FK3 PatientID
FK4 Consultant_ID
Procedure
PK ProcedureID
Procedure_Desc
Patient
PK PatientID
First_Name
Last_Name
Date_of_Birth
Address_Line1
Town
County
Phone
GP_ID
Admission
PK AdmissionID
Admission_Date
Discharge_Date
Ward No
Bed No
FK1 PatientID
Health_Ins_Code
Sample
PK SampleID
Test_Date
FK1 EmpID
FK2 PatientID
Employee
PK EmpID
EmpFirstName
EmpLastName
Position
Test
PK TestID
Test_Description
LowerLimit
UpperLimit
Units
Consultant
PK Consultant_ID
ConsFirstName
ConsLastName
Specialty
Hospital Surgical Ward
Database System
Assessment
PK Assessment_Date
PK,FK1 Patient_ID
PK,FK2 Consultant_ID
FK3 Emp_ID
Treatment_Plan

4
Part 2: Database Tables
A patient's Electronic Health Record (EHR) is compiled from a range of Oracle database tables in which
all patient information and records are held. Various views then can provide a complete record or
partial views that elucidate on particular aspects of the patient record of interest to a subset of staff
or hospital managers.
This section describes the tables created for the Surgical Ward database and shows a sample of the
SQL used to create and modify each table. The Create, initial Insert and Alter tables, if applicable, are
included here for each table with subsequent tables included in Appendix 2. A sample of each table is
also illustrated.
Patient Table
The Patient table holds personal and contact information for each patient.
CREATE TABLE PatientTJB661 (
Patient_ID number (10) primary key Not Null,
First_Name varchar2(50),
Last_Name varchar2(50),
Date_of_Birth date,
Address_Line1 varchar2(50),
Town varchar2(50),
County varchar2(50),
Phone number(20) Not Null,
GP_ID Number (10) Not Null);
INSERT ALL
INTO PATIENTTJB661 VALUES(659222,'John','Smith','29-May-80','5 Oak
Lawn','Mallow','Cork',0875623598,9945)
INTO PATIENTTJB661 VALUES(659536,'Mary','Murphy','31-Aug-90','Ard na
Ri','Pouladuff','Cork',0852222351,9946)
INTO PATIENTTJB661 VALUES(581229,'Brian','Walsh','10-Aug-90','6 Ard
Dara','Blarney','Cork',0866291562,9947)
INTO PATIENTTJB661 VALUES(588772,'Aoife','Ward','09-Sep-87','2 Old
Road','Cobh','Cork',0877543249,9948)
INTO PATIENTTJB661 VALUES(627391,'Peter','Cashman','17-Jul-
86','Ardfield','Douglas','Cork',0853579054,9949)

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INTO PATIENTTJB661 VALUES(650097,'Kate','Ryan','19-Jun-82','2 Low
Road','Bantry','Cork',0866642364,9950)
INTO PATIENTTJB661 VALUES(639696,'Barry','Buckley','20-Nov-89','5 New
Road','Blackpool','Cork',0855523670,9951)
INTO PATIENTTJB661 VALUES(611396,'Luara','Manley','11-May-91','6 Lee Road','Cork
City','Cork',0877512368,9952)
INTO PATIENTTJB661 VALUES(599062,'Dan','Lynch','23-Nov-92','High
Road','Macroom','Cork',0855442319,9953)
INTO PATIENTTJB661 VALUES(609655,'Lisa','Healy','15-Jul-
88','Woodview','Glanmire','Cork',0866519655,9954)
SELECT 1 FROM DUAL;
Figure 1. Patient Table
Admission Table
On a patient's first surgical admission to this hospital, he/she is allocated a Patient_ID which acts as a
unique identifier for the current and all subsequent admissions. Each admission is allocated a new
Admission_ID. The Admissions table holds the patient's health insurance details as well as admission
details such as the allocated accommodation for the patient for this hospital stay and the relevant
admission and discharge dates.
Create Table AdmissionTJB661 (
Admission_ID Number (10) primary key Not Null,
Patient_ID Number (6) Not Null,
Admission_Date date,
Discharge_Date date,
Ward_No Number (4) Not Null,

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Bed_No Number (4) Not Null,
Health_Insurance_Code Varchar2(20));
Insert All
Into AdmissionTJB661 Values(10000,659222,'5-Feb-15','7-Feb-15',10,1000,'VHI221112')
Into AdmissionTJB661 Values(10001,659536,'6-Feb-15','9-Feb-15',10,1001,'LAYA133331')
Into AdmissionTJB661 Values(10002,581229,'11-Feb-15','14-Feb-15',10,1002,'AVIVA155551')
Into AdmissionTJB661 Values(10003,588772,'12-Feb-15','14-Feb-15',11,1003,'GLO199991')
Into AdmissionTJB661 Values (10004,627391,'6-Feb-15','8-Feb-15',11,1004,'VHI442224')
Into AdmissionTJB661 Values(10006,639696,'10-Feb-15','12-Feb-15',11,1006,'GLO771117')
SELECT * FROM DUAL;
ALTER TABLE AdmissionTJB661
ADD CONSTRAINT
FK_ConAdm1_Patient
Foreign key(Patient_ID)
References PatientTJB661(Patient_ID);
Figure 2. Admission Table

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Assessment Table
The patient's EHR includes details of his/her initial consultation with the consultant prior to admission
for surgery. Details of any other medical personnel present are noted in addition to Treatment Plan
notes indicating the procedures scheduled for the patient's treatment.
CREATE TABLE AssessmentTJB661
(Assessment_Date Date Not Null,
Patient_ID Number (10) Not Null,
Consultant_ID Number (10) Not Null,
Emp_ID Number (10),
Primary key(Assessment_Date,Patient_ID,Consultant_ID));
INSERT ALL
INTO AssessmentTJB661 VALUES('30-Jan-15',659222,81265,220221)
INTO AssessmentTJB661 VALUES('01-Feb-15',588772,38264,220221)
INTO AssessmentTJB661 VALUES('02-Feb-15',639696,15599,220591)
SELECT 1 FROM DUAL;
ALTER TABLE AssessmentTJB661
ADD CONSTRAINT
FK_ConAssess1_Patient

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Figure 3. Assessment Table
Consultant Table
The details concerning consultants working in the hospital's surgical wards are recorded in the
Consultant table.
CREATE TABLE ConsultantTJB661
(Consultant_ID number (10)primary key not null,
Consultant_First_Name varchar(50),
Consultant_Last_Name varchar(50)not null,
Consultant_Specialty varchar(50)not null);
INSERT ALL
INTO ConsultantTJB661 VALUES('25252','Harry','Holmes','Dermatology')
INTO ConsultantTJB661 VALUES('84263','Mary','Smith','Dermatology')
INTO ConsultantTJB661 VALUES('75526','John','Dulea','Paediatrics')
INTO ConsultantTJB661 VALUES('15599','Ray','McCarthy','Oncology')
INTO ConsultantTJB661 VALUES('48522','Paul','McDonnell','Neurology')
INTO ConsultantTJB661 VALUES('21493','Sinead','Barry','Cardiology')
INTO ConsultantTJB661 VALUES('38264','Benedict','Sullivan','Oncology')
INTO ConsultantTJB661 VALUES('74581','Catherine','Corcoran','Dermatology')
INTO ConsultantTJB661 VALUES('30510','Kieran','Tarrant','Neurology')
INTO ConsultantTJB661 VALUES('81265','Anne ','DePuis','Cardiology')
SELECT 1 FROM DUAL;

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Figure 4. Consultant Table
Procedure Table
The treatment procedures undertaken in these surgical wards are described in the Procedures table.
CREATE TABLE Procedure661TJB
(Procedure_ID number(10) primary key not null,
Procedure_Desc varchar (50));
INSERT ALL
INTO Procedure661TJB VALUES(1311,'Colonoscopy')
INTO Procedure661TJB VALUES(2287,'Appendectomy')
INTO Procedure661TJB VALUES(3921,'Tonsillectomy')
INTO Procedure661TJB VALUES(4326, 'Chest X-ray')
INTO Procedure661TJB VALUES(5679, 'Myringotomy')
INTO Procedure661TJB VALUES(6111,'Splenectomy')
INTO Procedure661TJB VALUES(7481,'Angioplasty')
INTO Procedure661TJB VALUES(8091,'Pericariectomy')
INTO Procedure661TJB VALUES(9002,'MRI Scan')
INTO Procedure661TJB VALUES(1098,'Coronary Artery Surgery')
SELECT 1 FROM DUAL;

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Figure 5. Procedure Table
Booking Table
The Booking table describes the booking of treatment procedures for particular patients and
consultants on a particular date. The hospital service (i.e. the operating theatre, X-ray or MRI facilities)
booked for the procedure is also recorded here.
CREATE TABLE BookingTJB661
(Booking_ID number(10) primary key not null,
Patient_ID number(10) not null,
Booking_Date date,
Consultant_ID number(10),
Procedure_ID number(10),
Service_ID number(10));
INSERT ALL
INTO BookingTJB661 VALUES(56330,588772,'14-Feb-2015',21493,9002,132)

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SELECT 1 FROM DUAL;
ALTER TABLE BookingTJB661
ADD CONSTRAINT
FK_ConBook1_Procedure
Foreign key(Procedure_ID)
References Procedure661TJB(Procedure_ID);
Figure 6. Booking Table
Service Table
The hospital services, i.e. the operating theatres, X-ray or MRI scanner units, available in these surgical
wards are detailed in the Service table. The capacity of each (the hours/day that each is available for
use) is also recorded here.
CREATE TABLE ServiceTJB661
(Service_ID number(10) primary key not null,
Service_Name varchar2(50),
Capacity number (10));

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INSERT ALL
INTO ServiceTJB661 VALUES(123,'Operating Theatre 1',10)
INTO ServiceTJB661 VALUES(128,'X-ray 1',8)
INTO ServiceTJB661 VALUES(131,'MRI scanner 1',8)
INTO ServiceTJB661 VALUES(132,'MRI scanner 2',8)
SELECT 1 FROM DUAL;
Figure 7. Service Table
Utilisation Table
The usage of each service, measured in hours, is recorded at the end of each day if that service is used.
This information is recorded in the Utilisation table.
CREATE TABLE UtilisationTJB661
(Service_ID number(10) not null,
Utilisation_Date date not null,
Usage number (10,2),
Primary key(Service_ID,Utilisation_Date));

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INSERT ALL
INTO UtilisationTJB661 VALUES(123,'14-Feb-2015',12.25)
SELECT 1 FROM DUAL;
SELECT 1 FROM DUAL;
ALTER TABLE UtilisationTJB661
ADD CONSTRAINT
FK_ConUtil1_Service
Foreign key(Service_ID)
References ServiceTJB661(Service_ID);
Figure 8. Utilisation Table

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Employee Table
The Employee table contains information on nursing and auxiliary staff employed in the surgical
wards.
CREATE TABLE EmployeeTJB661
(Emp_ID number(10) primary key not null,
Emp_First_Name varchar2(50),
Emp_Last_Name varchar2(50),
Position varchar2(50));
INSERT INTO
EmployeeTJB661
VALUES(220591,'Anne','Horgan','Senior Phlebotomist');
Figure 9. Employee Table
Sample Table
The Sample table holds information on blood test samples taken from patients during their hospital
stay. Each patient sample may be divided and undergo multiple blood tests as detailed in the Test
table.
Create Table SampleTJB661
(Sample_ID Number(10) primary key Not Null,
Patient_ID Number(10) Not Null,

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Test_Date date,
Employee_ID Number(10)Not Null);
INSERT ALL
INTO SampleTJB661 VALUES (1049,659222,'05-Feb-2015',220591)
SELECT * FROM DUAL;
ALTER TABLE SampleTJB661
ADD CONSTRAINT
FK_ConSamp1_Patient
Figure 10. Sample Table

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Test Result Table
Each blood sample from a patient may be divided and undergo multiple tests, as detailed in the Test
table. Each result for each test is recorded in this Test Result table.
CREATE TABLE TEST_RESULTTJB661
(Test_ID Number (10) Not Null,
Sample_ID Number (10) Not Null,
Test_Result Decimal (5,2) Not Null,
Primary key(Test_ID,Sample_ID));
INSERT ALL
INTO TEST_RESULTTJB661 VALUES(121,1049,6.8)
INTO TEST_RESULTTJB661 VALUES(125,1051,138)

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SELECT * FROM DUAL;
ALTER TABLE Test_ResultTJB661
ADD CONSTRAINT
FK_ConTestRes1_Test
Foreign key(Test_ID)
References TestTJB661(Test_ID);
Figure 11. Test Result Table
Test Table
The individual tests that a blood sample may undergo are detailed in this Test table, along with the
upper and lower limits that are recommended for the results of each. The units of measurement for
each test are also specified here.
CREATE TABLE TESTTJB661 (
Test_ID Number (5) primary key Not Null,
Test_Description VARCHAR2(30),
Lower_Limit Decimal (5,2) Not Null,
Upper_Limit Decimal (5,2) Not Null,
Units VARCHAR2(12)
);

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INSERT ALL
INTO TESTTJB661 VALUES(121,'WBC White Blood Cells',4.4,11.3,'x10E9/l')
INTO TESTTJB661 VALUES(122,'RBC Red Blood Cells',4.5,5.1,'x10E12/l')
INTO TESTTJB661 VALUES(123,'HB Haemoglobin',12.3,15.3,'g/dl')
INTO TESTTJB661 VALUES(124,'PLT Platelets',140,440,'x10E9/l')
INTO TESTTJB661 VALUES(125,'Sodium',132,144,'pmol/l')
INTO TESTTJB661 VALUES(126,'Potassium',3.5,5.0,'pmol/l')
INTO TESTTJB661 VALUES(127,'Chloride',95,107,'pmol/l')
INTO TESTTJB661 VALUES(128,'Calcium',2.1,2.62,'pmol/l')
INTO TESTTJB661 VALUES(129,'Cholesterol',3.5,5.0,'pmol/l')
INTO TESTTJB661 VALUES(130,'Urea',2.5,7.0,'pmol/l')
SELECT * FROM DUAL;
Figure 12. Test Table

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Part 3: SQL Queries
This report will provide hospital management with information gleaned from the surgical department
database which minimises patient risk and maximises efficiency of utilisation of hospital services. The
following queries illustrate some examples of the types of SQL queries that can be used to extract
relevant and pertinent information from the system.
Query 1 Identification of Patients at Risk through Blood Testing
Patients at risk of a negative outcome may be identified by means of an SQL query on their blood tests
results. On admission of the patient for surgery, a full range of blood tests are carried out and the
results queried in order to confirm that the patient is in optimum health prior to his/her procedure.
Each test result should be within the upper and lower limits for that particular test. Further blood tests
are conducted throughout the patient's hospital stay to ensure that recovery is progressing normally
and that the patient is in good health.
This query identifies patients whose test results fall outside those limits and, if conducted prior to
surgery, whose suitability for the treatment procedure may need be reassessed by their consultant.
SELECT
P.Patient_ID,P.First_Name,P.Last_Name,S.Test_Date,T.Test_ID,T.Test_Description,R.Test_Result,T.L
ower_Limit,T.Upper_Limit,T.Units
FROM Test_ResultTJB661 R,TestTJB661 T,SampleTJB661 S,PatientTJB661 P
WHERE T.Test_ID = R.Test_ID
AND S.Sample_ID = R.Sample_ID
AND P.Patient_ID = S.Patient_ID
AND (R.Test_Result < T.Lower_Limit
OR R.Test_Result > T.Upper_Limit);
Figure 13. Query 1 Identification of Patients at Risk through Blood Testing

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The result of the above query has identified that one patient, Kate Ryan, has haemoglobin levels well
below the lower limit. This indicates that her consultant should reassess her suitability for surgery;
she may require a blood transfusion prior to surgery or surgery may need to be postponed until her
haemoglobin levels recover to within normal limits. If no action is taken, this patient is at risk of
negative outcomes during surgery.
This query also identifies that another patient, Lisa Healy, has a cholesterol level elevated above the
upper limit and is consequently at increased risk of a heart attack. Her consultant needs to take
action to educate Lisa around health and lifestyle choices she can make to lower her cholesterol and
improve her heart health for the future.
Query 2 Identification of Patients at Risk through Air-Transmitted Infection
The accommodation of multiple patients in wards exposes patients to the risk of cross-infection by
airborne pathogens in the event of another patient in the ward suffering from a contagious condition.
On discovering that a patient has received a diagnosis of such a condition, the hospital management
are obliged to notify and test any patient that shared a ward with the infected patient during the time
that that patient may have been infectious.
This example assumes that a patient who was in Ward 10 on 09 February 2015 was subsequently
diagnosed with a highly infectious condition. The SQL query below allows management to identify the
patient information of any patient who was accommodated in Ward 10 on that day.
SELECT P.Patient_ID,P.First_Name,P.Last_Name
FROM PatientTJB661 P,AdmissionTJB661 A
WHERE P.Patient_ID=A.Patient_ID
AND A.Ward_no=10
AND '09-feb-15'between A.Admission_Date and A.Discharge_Date;
Figure 14. Query 2 Identification of Patients at Risk through Air-Transmitted Infection

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The result indicates that Mary Murphy was accommodated in Ward 10 on the date in question and
should undergo tests immediately.
Query 3 Identification of Patients at Risk from Infection through Consultant
A risk is posed to any patient who has undergone a treatment procedure under a consultant who,
soon afterwards, becomes ill as the consultant may have been unwittingly incubating infection at the
time. On discovering that a consultant has become ill, the hospital management are obliged to notify
and test any patient that has been in contact with him/her in a particular timeframe. This would allow
them to monitor that patient closely for infection and provide the best possible care.
In this example, consultant Mary Smith was taken ill on the evening of 15 Feb 2015. This SQL query
selects all patients that underwent a procedure under Dr Smith on that day.
Select P.Patient_ID,P.First_Name,P.Last_Name
from BookingTJB661 B, PatientTJB661 P, Consultanttjb661 C
where C.Consultant_ID=B.Consultant_ID
and P.Patient_ID=B.Patient_ID
and B.Booking_Date='15-feb-15'
and C.Consultant_First_Name='Mary'
and C.Consultant_Last_Name='Smith';
Figure 15. Query 3 Identification of Patients at Risk from Infection through Consultant
Peter Cashman underwent a treatment procedure under Dr. Mary Smith on that date and should be
monitored carefully for signs of infection and/or considered for a prophylactic course of antibiotics.

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Query 4 Identification of Patients at Risk of Infection at time of Taking Blood Sample
Stringent hygiene and best practices for the taking of blood samples from patients are in place
throughout the hospital system for the protection of patients. Where these procedures are breached,
some risk is posed to patients.
In this example, it has come to hospital management attention that Nurse Mary Murphy has taken
blood samples from patients without wearing gloves. This query identifies all patients from whom
Mary took blood samples.
SELECT P.Patient_ID,P.First_Name,P.Last_Name,Test_Date
FROM PatientTJB661 P,SampleTJB661 S,EmployeeTJB661 E
WHERE P.Patient_ID=S.Patient_ID
AND E.Emp_ID=S.Employee_ID
AND Emp_First_Name='Mary'
AND Emp_Last_Name='Crowley';
Figure 16. Query 4 Identification of Patients at Risk of Infection at time of Taking Blood Sample
Both Kate Ryan and Lisa Healy have had blood samples drawn by Nurse Mary Crowley and their body
temperature should be carefully monitored for signs of infection for a number of days.
Query 5 Identification of Under-Utilised Hospital Services
The efficient running of the hospital's surgical department requires that any available services (i.e.
operating theatres, X-ray machines or MRI scanners) that are being underused be identified. This
information can then be acted upon to increase the number of bookings to these services that are
facilitated by the system. Should no further demand for these services exist, efficiency can be
increased by the temporary closure of some.

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In the surgical department setting, it is challenging to schedule services for some treatment
procedures as the time required to carry out the same procedure varies with each case. Therefore
some buffer has been included here and this SQL query identifies services that are being utilised to
less than 80% of their daily capacity. The results are displayed here in ascending order of most under-
utilised service.
SELECT
S.Service_ID,S.Service_Name,U.Utilisation_Date,U.Usage,S.Capacity,ROUND((U.Usage/S.Capacity)*1
00,0) AS "PERCENTAGE_UTILISATION"
FROM UtilisationTJB661 U,ServiceTJB661 S
WHERE U.Service_ID=S.Service_ID
AND U.Usage < (S.Capacity*0.80)
ORDER BY PERCENTAGE_UTILISATION ASC;
Figure 17. Query 5 Identification of Under-Utilised Hospital Services
The results are displayed here in ascending order of most under-utilised service assisting hospital
management in their identification of the poorest performing services. They can then plan to increase
bookings in the services in question or formulate cost-saving temporary closures as appropriate.
Query 6 Identification of Over-Utilised Hospital Services
The hospital management can optimise the efficient running of the hospital's surgical department by
identifying where services may be consistently over-utilised. They are then in a position to improve
their services usage by balancing the treatment procedure workload more evenly over the services
available to them. Again, due to difficulties in predicting the duration of many procedures, some
leeway has been allowed and services that are being utilised to more than 120% capacity are
identified. The results are displayed here in descending order from the most over-utilised services.

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SELECT
S.Service_ID,S.Service_Name,U.Utilisation_Date,U.Usage,S.Capacity,ROUND((U.Usage/S.Capacity)*1
00,0) AS "PERCENTAGE_UTILISATION"
AND U.Usage > (S.Capacity*1.20)
ORDER BY PERCENTAGE_UTILISATION DESC;
Figure 18. Query 6 Identification of Over-Utilised Hospital Services
The results are displayed here in descending order from the most over-utilised services to assist
hospital management in their deliberations. This information should be considered in conjunction
with the results of Query 5 so that utilisation of similar services can be balanced more effectively.
Query 7 Identification of the Operating Theatre with the Highest Usage
Should hospital management require more granular data to aid their balancing efforts, the Operating
Theatre with the highest usage can be isolated. This query could be amended to select the most
utilised of any type of hospital service.
SELECT U.Utilisation_Date,S.Service_Name,U.Usage
WHERE U.SERVICE_ID = S.SERVICE_ID
AND U.Usage=
(SELECT MAX(U.Usage)
WHERE S.Service_Name like '%Operating Theatre%'
AND S.Service_ID=U.Service_ID);

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Figure 19. Query 7 Identification of the Operating Theatre with the Highest Usage
The results show that the usage of Operating Theatre 4 on 14 February was the highest usage
recorded.
Query 7 Overview of Hospital Services Usage
Some further queries on usage pattern of hospital services provide additional depth and statistical
analysis. These reports provide an effective overview of the utilisation situation when considered by
hospital management as a collection.
SELECT S.SERVICE_NAME, ROUND(MIN(U.USAGE)) AS "MIN_USAGE", ROUND(AVG(U.USAGE)) AS
"AVG_USAGE", ROUND(MAX(U.USAGE)) AS "MAX_USAGE"
FROM UTILISATIONTJB661 U, SERVICETJB661 S
WHERE U.SERVICE_ID = S.SERVICE_ID
GROUP BY S.SERVICE_NAME
ORDER BY S.SERVICE_NAME;
Figure 20 Query 7(a) Minimum, Average and Maximum Usage of Hospital Services

26
This query relating to Minimum, Average and Maximum Usage per Service Points out where there are
large variations in usage of services that may be difficult for hospital management to handle due to
the allocation of staff and other resources. This is a very useful overview report for hospital
management to monitor the ongoing situation.
SELECT U.Utilisation_Date,S.Service_ID,S.Service_Name,U.Usage,S.Capacity
AND U.Usage > S.Capacity;
Figure 21. Query 7(b) Hospital Services where Usage exceeds Capacity
This report displays a summary of all under-utilised services where usage exceeds capacity so that
hospital management can identify all under-performing services at a glance.
SELECT Service_ID,avg(Usage)
FROM UtilisationTJB661
GROUP BY Service_ID
HAVING avg(Usage)<7;

27
Figure 22. Query 7(c) Hospital services with Average Daily Usage of less than 7 hours
This query identifies services with average usage of less than 7 hours/day throughout our Utilisation
records. This highlights the most consistently under-utilised services for hospital management to
consider.
Query 8 Number of Bookings per Service per Date
In the case of an Operating Theatre which is dedicated to routine procedures where procedure
duration can be estimated with some degree of accuracy (for example, a colonoscopy), an X-ray
machine or an MRI scanner, it is useful for management to identify the number of bookings that have
been booked for a particular day. This can provide insight into the predicted utilisation of a service for
a future date, thereby facilitating the filling of vacant slots by additional bookings from the waiting
list.
SELECT S.SERVICE_NAME, B.BOOKING_DATE, COUNT(B.BOOKING_ID) AS "NUM_BOOKINGS"
FROM SERVICETJB661 S, BOOKINGTJB661 B
WHERE S.SERVICE_ID = B.SERVICE_ID
GROUP BY S.SERVICE_NAME, B.BOOKING_DATE
ORDER BY S.SERVICE_NAME, B.BOOKING_DATE;
Figure 23. Query 8 Number of Bookings per Service per Date

28
Query 9 Identification of Hospital Services without Bookings
Efficiency of the running of the surgical department can be further enhanced using the information
available regarding the bookings of hospital services. If a particular service is completely without
bookings on a particular day, hospital management will be able to temporarily close that service for
that day and make cost-saving adjustments to their staffing levels, cleaning services, etc.
This example selects details of all Services which do not have any bookings on 14 February 2015.
SELECT *
FROM SERVICETJB661
WHERE SERVICE_ID NOT IN
(SELECT DISTINCT B.SERVICE_ID
FROM BOOKINGTJB661 B
WHERE B.Booking_Date='14-Feb-15')
ORDER BY SERVICE_ID;
Figure 24. Query 9 Identification of Hospital Services without Bookings
Query 10 Identification of Date for 6-week Post-Operative Check-up Appointment
Patients that undergo surgery require to be seen by their consultant 6-weeks after their operation for
a check-up in order to minimise post-operative risks.
In this example, consultants run clinics for check-ups on Thursdays only so the appointment date will
be scheduled for the first Thursday after a patient's procedure booking date. This SQL query returns
an instruction report for administrative staff who are tasked with sending out check-up appointments
to surgical patients.

29
SELECT 'Make an appointment for '||P.First_Name||' '||P.Last_Name||' '||'with
'||C.Consultant_First_Name||' '||C.Consultant_Last_Name||' on
'||((next_day(B.Booking_Date,'Thursday'))+42) AS "INSTRUCTION"
FROM PatientTJB661 P,ConsultantTJB661 C,BOOKINGTJB661 B
WHERE P.Patient_ID=B.Patient_ID
AND C.Consultant_ID=B.Consultant_ID;
Figure 25. Query 10 Identification of Date for 6-week Post-Operative Check-up

30
Part 4: Securing Patient Data using Oracle
The sensitive nature of the data in our EHRs necessitates the most stringent of data security settings.
A variety of security threats from internal and external sources deserve consideration, some human
and others technological. Data management training and regular upskilling is important to offset
human error and misuse while Oracle offers a range of preventive, detective and administrative
features, as described in Forrester's 2010 report (Figure 1) to counteract technological elements.
Figure 26. Three Pillars of Enterprise Database Security (Forrester, 2010)
Oracle security features such as regular patching, strong AAA standards and establishing multi-layer
protection through physical (e.g. device isolation) and technical safeguards (e.g. firewalls, secure
transmission modes and encryption).
The principle of least privilege states that users should be given the least amount of privileges to
perform their jobs. Overly ambitious granting of privileges which may be an issue in hospitals where
there is an often an imbalance between staff levels and work to be completed leaving a system open
for abuse and intrusion. User privileges should be reviewed periodically to determine relevance to
current job responsibilities.

31
Conclusion
This report has described the design and creation of a valuable surgical department database and
illustrated a small sample of the information available to hospital management through its effective
querying and understanding of EHRs. These EHRs are the key to effective and efficient hospital
operations - providing the highest possible level of patient care and making cost savings with minimal
reductions in patient services, while offering the highest level of patient data privacy and security.
It is hoped that this system provides beneficial guidance in control and planning functions in this
department and provides a template for its extension to other hospital departments and functions.
References
Forrester Research, 2010. Yuhanna, Noel, "Your Enterprise Database Security Strategy"
Oracle Security Overview 10g Release, Oracle Security Products and Features,
http://docs.oracle.com/cd/B12037_01/network.101/b10777/galsyste.htm. Accessed 19 March
2015

34
Appendix 2
Alter Assessment Table
ADD CONSTRAINT
FK_ConAssess1_Patient
ADD CONSTRAINT
FK_ConAssess2_Consultant
Foreign key(Consultant_ID)
References ConsultantTJB661(Consultant_ID);
ADD CONSTRAINT
FK_ConAssess3_Employee
Foreign key(Emp_ID)
References EmployeeTJB661(Emp_ID);
Insert into Booking Table
INSERT ALL

35
SELECT 1 FROM DUAL;
Alter Booking Table
ADD CONSTRAINT
FK_ConBook2_Service
Foreign key(Service_ID)
References ServiceTJB661(Service_ID);
ADD CONSTRAINT
FK_ConBook3_Consultant
Foreign key(Consultant_ID)
References ConsultantTJB661(Consultant_ID);
ADD CONSTRAINT
FK_ConBook4_Patient
Insert into Utilisation Table
INSERT ALL

36
Insert into Employee table
INSERT INTO
EmployeeTJB661
VALUES(497365,'Bernadette','Fahy','Senior Phlebotomist');
INSERT INTO
EmployeeTJB661
VALUES(220515,'Mary','Donovan','Staff Nurse');
INSERT INTO
EmployeeTJB661
VALUES(220393,'Evelyn','Cronin','Phlebotomist');
INSERT INTO
EmployeeTJB661
VALUES(220221,'Jo','Hill','Phlebotomist');
INSERT INTO
EmployeeTJB661
VALUES(614252,'Julianne','Twomey','Staff Nurse');
INSERT INTO
EmployeeTJB661
VALUES(220444,'Mary','Crowley','Staff Nurse');

37
INSERT INTO
EmployeeTJB661
VALUES(365088,'Catherine','Redmond','Phlebotomist');
INSERT INTO
EmployeeTJB661
VALUES(762473,'Una','Mahony','Phlebotomist');
INSERT INTO
EmployeeTJB661
VALUES(220600,'Ciara','Whelan','Phlebotomist');
Alter Sample Table
ALTER TABLE SampleTJB661
ADD CONSTRAINT
FK_ConSamp2_Employee
Foreign key(Employee_ID)
References EmployeeTJB661(Emp_ID);
Alter Test Result Table
ALTER TABLE Test_ResultTJB661
ADD CONSTRAINT
FK_ConTestRes2_Sample
Foreign key(Sample_ID)
References SampleTJB661(Sample_ID);

IS 6156 Jean Donnelly 90079094 Brendan McSweeney 114223513 Tim Walsh 102859661

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