Drop Table Results Drop Table Evaluations Drop Table Eval Ru

Drop Table Resultsdrop Table Evaluationsdrop Table Eval Rules

Drop Table Resultsdrop Table Evaluationsdrop Table Eval Rules

DROP TABLE RESULTS; DROP TABLE EVALUATIONS; DROP TABLE EVAL_RULES; DROP TABLE MEDICAL_RECORDS; DROP TABLE APPLICATIONS; DROP TABLE ACADEMIES; DROP TABLE APPLICANTS; CREATE TABLE APPLICANTS( SSN CHAR(9) PRIMARY KEY, FirstName VARCHAR2(10), LastName VARCHAR2(20), DOB DATE); CREATE TABLE ACADEMIES( AcadID VARCHAR2(10) PRIMARY KEY, AcadName VARCHAR2(100)); CREATE TABLE APPLICATIONS( AppID NUMBER PRIMARY KEY, SSN CHAR(9) REFERENCES APPLICANTS(SSN), AcadID VARCHAR2(10) REFERENCES ACADEMIES(AcadID), Year INT CHECK (Year BETWEEN 2010 AND 2020)); CREATE TABLE MEDICAL_RECORDS( SSN CHAR(9) REFERENCES APPLICANTS(SSN), DateUpdated DATE, Pulse INT, Systolic INT, Diastolic INT); CREATE TABLE EVAL_RULES( RuleID NUMBER PRIMARY KEY, RuleName VARCHAR2(50)); CREATE TABLE EVALUATIONS( EvalID NUMBER PRIMARY KEY, EvalDate DATE, AppID NUMBER REFERENCES APPLICATIONS(AppID)); CREATE TABLE RESULTS( EvalID NUMBER REFERENCES EVALUATIONS(EvalID), RuleID NUMBER REFERENCES EVAL_RULES(RuleID), Result INT CHECK (Result IN (0, 1))); INSERT INTO APPLICANTS VALUES ('', 'John', 'Layman', '22-APR-1998'); INSERT INTO APPLICANTS VALUES ('', 'Tim', 'Bowe', '22-APR-1993'); INSERT INTO APPLICANTS VALUES ('', 'Nick', 'Reynolds', '22-APR-1983'); INSERT INTO ACADEMIES VALUES ('USAFA', 'United States Air Force Academy'); INSERT INTO ACADEMIES VALUES ('USMA', 'United States Military Academy'); INSERT INTO ACADEMIES VALUES ('USUHS', 'Uniformed Services University of the Health Sciences'); INSERT INTO APPLICATIONS VALUES (1, '', 'USAFA', 2014); INSERT INTO APPLICATIONS VALUES (2, '', 'USMA', 2015); INSERT INTO APPLICATIONS VALUES (3, '', 'USMA', 2015); INSERT INTO APPLICATIONS VALUES (4, '', 'USUHS', 2015); INSERT INTO APPLICATIONS VALUES (5, '', 'USAFA', 2015); INSERT INTO APPLICATIONS VALUES (6, '', 'USMA', 2015); INSERT INTO APPLICATIONS VALUES (7, '', 'USUHS', 2015); INSERT INTO MEDICAL_RECORDS VALUES ('', '10-MAR-2015', 70, 150, 80); INSERT INTO MEDICAL_RECORDS VALUES ('', '20-MAY-2014', 60, 120, 80); INSERT INTO MEDICAL_RECORDS VALUES ('', '25-APR-2015', 100, 145, 95); INSERT INTO EVAL_RULES VALUES(1,'Age'); INSERT INTO EVAL_RULES VALUES(2,'Pulse'); INSERT INTO EVAL_RULES VALUES(3,'Blood Pressure');

Paper For Above instruction

The provided script primarily focuses on establishing a structured relational database schema and populating it with initial data, emphasizing the healthcare application context. It begins by dropping existing tables related to applicants, evaluations, medical records, and evaluation rules to reset the database environment, ensuring no conflicts arise from previous data. Subsequently, it creates key tables that represent the core entities within this healthcare system: applicants, academies, applications, medical records, evaluation rules, evaluations, and results.

The Applicants table captures individual demographic data, including their social security number, first and last names, and date of birth. The Academies table lists various medical or military academies with unique identifiers and names. The Applications table records the submission of applicants to specific academies within an academic year range, enforcing data validity through a check constraint on the year field.

The Medical Records table stores health-related metrics tied to each applicant, such as pulse rate and blood pressure readings, along with the date when these records were updated. The Evaluation Rules define various criteria used to assess applicants, like age, pulse, and blood pressure. The Evaluations table logs assessment events linked to specific applications, including evaluation dates. Finally, the Results table associates evaluations with particular rules, indicating whether the applicant passes (1) or fails (0) each criterion.

This schema enables detailed tracking of applicant data, medical history, and assessment outcomes, facilitating comprehensive analysis within the healthcare management system. The initial data inserts populate the database with sample applicants, academies, application submissions across different years, health records, and evaluation rules, providing a foundational dataset for queries or further development.

In the context of healthcare informatics, designing such relational schemas is critical for building systems that can manage diverse and sensitive data effectively. Proper normalization, data integrity constraints, and clear entity relationships ensure reliable data storage, retrieval, and analysis, supporting decision-making processes such as candidate assessment and health monitoring. The emphasis on constraints like foreign keys and check conditions demonstrates best practices in maintaining data validity, crucial in real-world health information systems where accuracy and confidentiality are paramount.

This foundational structure illustrates how healthcare information systems integrate multiple data entities—demographic, medical, evaluative—into a cohesive framework. Extending this schema with additional tables for procedures, diagnoses, billing, or longitudinal health data could further enhance its comprehensiveness. Such systems ultimately aim to improve healthcare delivery by enabling timely, data-driven insights into patient health and operational efficiencies.

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