Chapter 1-8: Health Information Systems and Data Analysis

This chapter focuses on the conceptual model of a Health Information System (HIS).

Health Information System (HIS): Centered on health institutes (e.g., hospitals, clinics).
- Function: Utilizes systems and management to process health data.
- Data Provision: Provides processed data to health informatics.
Health Informatics: Analyzes data and produces output for:
- Research proposals
- Policy proposals
- Public health proposals
Scope Progression: The scope of HIS gradually expands from individual health institutes to cover global public health.

Data as Foundation: Health information and data form the basis for analysis.
Support for Workflow and Processes:
- Analyzed data supports and improves workflow and processes.
- Workflow: Refers to a sequence of common tasks.
- Processes: Denotes end-to-end methods, encompassing the entire healthcare value chain.
Healthcare Value Chain: From health provider of care (hospitals, clinics) connecting to a network of related entities:
- Patients
- Payers (e.g., insurance companies)
- Regulatory agencies
- Manufacturers and suppliers
- All these entities are linked through health information systems.

Clinical Decision Support (CDS):
- Synonymous with clinical intelligence and artificial intelligence.
- Purpose: To calculate, find, and generate knowledge from data.
Main Job of Health Informatics: Analysis.
- Definition: The use of information systems and technology to redesign, improve, and recreate work in medicine, nursing, medical imaging, and public health.
- Focus Areas: Quality control and process improvement (topics often covered in higher-level courses, e.g., 4,000 level).
Conceptual Intersection of Health Informatics: A common area between:
- Health Information Technology (HIT): Involves hardware, software, application security, integration, and networking.
- Health Information Management (HIM): Deals with medical records (e.g., Electronic Medical Records - EMRs), Health Maintenance Organization (HMO) records, policy guidelines, and public health data. HIM provides data to health informatics.
Outcome: Health informatics analyzes data to create knowledge for policymakers and researchers.

Importance of Low-Level Data: Raw, low-level data is crucial for day-to-day activities.
Meaningful Information: To derive meaningful information, data must be aggregated.
- Aggregation: Not just individual patient records or single institute data, but a collection of data from a whole specific area.
- Process: Aggregate data -> analyze aggregated data -> generate knowledge -> use for higher-level analysis.
Business Intelligence (BI):
- Definition: Value realized by flexibly analyzing a comprehensive store of data representing the totality of an organization's activities.
- Healthcare Equivalent: Clinical Intelligence (CI) or Business Intelligence for Healthcare (BII).

These high-level domains utilize data, knowledge, and information derived from health informatics.
University Researchers: Use data to find meaningful insights.
Policymakers: Use the output from researchers to inform policy decisions.

EHR System: Stores aggregated data, forming databases.
Conceptual Diagram (Data Creation):
- Data is created by individual Health Information Systems (HIS).
- Data from different HIS are aggregated into centralized databases (e.g., EHR databases).
- This aggregated data is then used for research analysis and policy purposes.
Access and Querying: Individuals (e.g., physicians, hospitals) can access, query, and retrieve needed data from these centralized databases.
Data Flow: Physicians or hospitals upload data via computer interfaces, which goes into a central database. They can also retrieve data to find knowledge.

Database (DB): A collection of data.
Database Management System (DBMS): Specialized software required to manage databases.
- Function: Programs access the DBMS, which then processes queries and provides results from the database.

6 IT System Components:
- Hardware
- Software
- Database
- Network (Internet)
- Procedure
- People
Hierarchical Conceptual Model of HIS:
- Foundation (Bottom Layer): Technology infrastructure and system management.
- Mid-Layer: Data, information, people, and processes (who use the IT components).
- Analysis Layer: Business intelligence, clinical intelligence, artificial intelligence.
- Top Layer: Generates knowledge used for global HIS policy and research.

Organizational Context: HIS helps organizations achieve missions (e.g., making a community safer).
- Application: Used in areas like medical practice improvement.
Fundamental Reason for HIS: To provide accurate and quality service to the community.
Stakeholders (Who receives services?):
- Patients/Consumers
- Payers (insurance companies)
- Public health agencies
- Government
- Research organizations
- Inpatient, outpatient, ambulatory service providers
- Health Information Exchange (HIE)
- Regulatory bodies
Community Scope: All listed stakeholders belong to the broader community.

Definition: A collaborative arrangement designed for sharing patient-related health information.
Core Principle: Once a patient has a health record, all related institutes (primary care, laboratory, hospital, pharmacy specialist) can share that record.
Benefits: Prevents duplication of data (e.g., repeated laboratory tests, X-rays), thereby reducing waste of money and resources.

Health Informatics is the use of information systems and technology to redesign, improve, and recreate the way work is done in medicine, nursing, medical imaging, and public health.
Business Intelligence (BI) is a term for value realized by flexibly analyzing comprehensive stores of data representing the totality of an organization's scope of activity.