Health Information Systems: Scope, Definition, and Conceptual Model

The Scope and Definition of HIS (Chapter 2)

• Chapter focus: The Scope, Definition, and Conceptual Model of Health Information Systems (HIS) for the health professions.

• Source context: Visuals and captions credit Jeffery Van Daele; content covers foundations, concepts, and applications of HIS across health care, informatics, policy, and public health.

The Scope of HIS: Systems and Their Management

• The scope of HIS comprises three interrelated components:

  • Health informatics

  • Data and analytics

  • Research, policy, and public health uses of HIS

• These components rely on the fundamental capabilities and data provided by HIS; without a solid foundation, higher-level uses cannot exist.

• The model positions HIS as the footing for broader health informatics activities and data-driven decision-making.

Meaningful Data and the HIS Foundation

• Meaningful health information and data are only as good as the HIS platform and the technical foundation that serves as the data source.

• Data are created and captured in HIS that provide features and functions to support:

  • Workflows: sequences of common tasks used by health professionals and organizations

  • Processes: end-to-end methods used by healthcare providers, organizations, patients, and public health professionals

The Health Care Value Chain Context

• A Pharma-to-Patient value chain illustrates the broad ecosystem involved in health care (illustrative list includes):

  • Pharma, Biotechnology, Medical Equipment, Medical & Surgical Supplies

  • Payors, Regulators, Regulatory Agencies

  • Hospitals (Acute Care), Outpatient/Long-Term Care, Physician Contracting

  • Employers, Distributors, Integrated Networks, Providers of Care, Patients, Communities

• The chain implies data flow and interoperability needs across manufacturers, providers, payers, regulators, and patients to support care delivery and health outcomes.

Core Building Blocks and Foundational Uses of Data

• HIS that create and capture data serve as the foundation upon which all other information- and data-related capabilities depend.

• Essential building blocks for advanced data uses:

  • Clinical decision support (CDS)

  • Artificial intelligence (AI)

• Critical requirement: data must emanate from real healthcare processes to be credible and useful.

Health Informatics, Health IT, and Health Information Management

• Health informatics: 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.

• Focus of health informatics:

  • Quality- or process-improvement objectives that vary by setting

  • It constitutes the practical use of HIS capabilities by end users.

• Domains often represented in a diagram include: Health Informatics, Health Information Technology (HIT), and Health Information Management (HIM), along with various IT and organizational components such as hardware, software, data, security, policy, integration, guidelines, big data, networking, administration, and public health.

Data, Information, and the BI/CI Era

• Data: the primary unit of HIS used in day-to-day transactions by professionals and organizations.

• Data must be aggregated and compiled to create meaningful information.

• Information and knowledge generation depends on the capture of individual data elements.

• Business Intelligence (BI): value realized by flexibly analyzing comprehensive data stores representing the entire scope of an organization’s activity.

• In health care, BI leads to the notion of Clinical Intelligence (CI): applying BI concepts to clinical data and patient care contexts.

Research, Policy, and Public Health Uses of HIS

• Data created and captured in HIS become available for research, fueling university research and enabling analysts to measure health and improve efficiency/effectiveness of care processes and outcomes.

• Policymakers rely on researchers’ findings to guide health policy and program decisions.

• Data captured in Electronic Health Records (EHRs) are aggregated into databases for research and policy analysis.

Data Creation Settings and Aggregation

• Data creation occurs across multiple settings:

  • Physician practices, clinics, and hospitals

• Data are then aggregated and used for:

  • Research, analysis, and policy

  • Personal data used for public health purposes

• The cycle emphasizes how micro-level data collection feeds macro-level insights.

EHRs, Polystore, and Data Stores

• EHR data can be stored in diverse data architectures (polystore):

  • Column stores, Relational databases, Wide-column stores, Graph databases, Document stores

• Query types include:

  • Population query (aggregate/population-level analysis)

  • Single patient query (case-level clinical detail)

• Two primary uses of EHR data:

  • Primary clinical use

  • Research use

• Figure reference note: A figure (e.g., labeled with 195) illustrates these data store concepts and query types.

EHR Data Lifecycle: Collection, Processing, and Analysis

• Data collection: data input by physicians and other users via user interfaces to central databases.

• Data processing: data are reviewed and validated; quality-based registries (examples: PQRS, society-based registries) support quality measurement and reporting.

• Data analysis: downstream analysis supports clinical decision making, quality improvement, and research.

• DBMS role: database management systems manage data input, central storage, and data review.

• Other users beyond clinicians: specialty registries, researchers, and policymakers who access aggregated data.

Organizational Data and IT Infrastructure

• Database management systems example domains within organizations: Registrar's offices, class programs, academic information, team data, employee data, tuition data, accounting data, financial data, student data, course data, athletics data, registration data.

• Core IT components typically mapped in diagrams include:

  • Hardware

  • Software

  • Database

  • Network

  • Procedures

  • People

The HIT/Informatic Landscape: Hardware, Software, Network, Procedures, and People

• An integrated view of HIS infrastructure includes:

  • Hardware

  • Software

  • Database

  • Network

  • Procedures

  • People

• Emphasis on balanced integration of technology with human processes and organizational procedures to achieve effective HIS performance.

Progression and Maturation of HIS

• Maturation occurs through the progression of the HIS Conceptual Model.

• Success is the result of balanced involvement of people, processes, and technology (the three core pillars).

HIS Uses in Organizational and Community Settings

• Mission, vision, and goals drive the core systems used by an organization.

• Example: Mission could be to make the community safer; how this is achieved is via HIS to reduce malpractice and improve accurate/quality services.

• The fundamental reason for using HIS: to deliver accurate, quality services.

• Stakeholders/users include various payers, patients/consumers, public health agencies, and research organizations; different needs across these groups inform HIS deployment.

Settings and Stakeholders for HIS Uses

• Inpatient, outpatient, and ambulatory care organizations.

• Patients’/consumers’ homes.

• Payers, insurance companies, and government programs/agencies.

• Public health organizations.

• Health Information Exchanges (HIEs) and Regional Health Information Organizations (RHIOs): collaborative arrangements aimed at sharing patient-related health information.

• External regulatory, reporting, research, and public health entities also rely on HIS data and systems.

Health Information Exchange (HIE)

• HIEs enable sharing of patient-related health information across organizations and settings.

• Diagrammatic representation (for example) includes hospitals, laboratories, pharmacies, caregivers, and patients as nodes in the exchange network.

• The goal of HIEs is to facilitate timely, accurate, and interoperable data sharing to improve care coordination and population health.

Review Questions (Key Takeaways)

• Fill-in-the-blank: H__ i___ 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.

  • Answer: Health Informatics

• Fill-in-the-blank: B_ I__ is a term for value realized by flexibly analyzing comprehensive stores of data representing the totality of an organization’s/provider’s scope of activity.

  • Answer: Business Intelligence

• Additional study notes:

  • Understand how workflows and processes transform raw data into actionable information within HIS.

  • Be able to distinguish between BI and CI (Clinical Intelligence) and why clinical data analysis is central to patient care.

  • Recognize the roles of CDS and AI as foundational building blocks in modern HIS applications.

  • Be familiar with EHR data architectures (polystore concepts) and the difference between primary clinical use and research use.

  • Understand the purpose and participants in Health Information Exchanges (HIEs) and how they support public health and patient care.

(End of Chapter 2 notes)