Health informatics is a multidisciplinary field that applies information science and technology to health and healthcare. It investigates the structure, acquisition, management, analysis, and strategic use of health data and information to improve patient care, enhance public health, and optimize healthcare systems and research.
Ontological type
Core Methods
Clinical Applications
Core Subfields
Foundational EHR Infrastructure
1968 - 1997
Interoperability and Clinical Systems
1998 - 2010
Federated AI and Scalable Analytics
2011 - 2024
Foundational EHR Infrastructure era
John E. Ware [1] was active at Harvard University [3] and Tufts University [4] during the Foundational EHR Infrastructure era. His contributions center on standardizing health outcomes measurement, notably through the MOS 36-item short-form health survey (SF-36) [7], whose conceptual framework and item selection provided a semantically interoperable backbone for longitudinal outcome tracking in early electronic health records. Clement J. McDonald [2] was affiliated with the University of Washington [5] and Wake Forest University [6] during this era. His work on computer reminders and integrated medical records helped advance clinical decision support and data sharing, exemplified by Protocol-Based Computer Reminders [8], Reminders to Physicians from an Introspective Computer Medical Record [9], and The Regenstrief Medical Record System: 20 years of experience in hospitals, clinics, and neighborhood health centers [10], demonstrating how reminders and hospital-to-community data infrastructures underpin safety and continuity of care in the formative EHR infrastructure.
Interoperability and Clinical Systems era
William A. Ghali[1] is associated with Boston University[3] and the University of Toronto[4] during this era. His key contribution was developing Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data[7], a foundational approach that enabled consistent morbidity definitions across administrative datasets and informed interoperability efforts across EMRs and CDS. Vijaya Sundararajan[2] is associated with Columbia University[5] and the University of North Carolina at Chapel Hill[6] during this era. Her key contribution was co-authoring Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data[7], which standardized comorbidity definitions and supported cross-system analytics, a cornerstone for interoperability and policy-oriented evaluation in this period.
Federated AI and Scalable Analytics era
Leo Anthony Celi [1], affiliated with Harvard–MIT Division of Health Sciences and Technology [3] and Harvard University [4], is a leading figure in health informatics during the Federated AI and Scalable Analytics era (2011-2024). His key contribution in this era is MIMIC-III, a freely accessible critical care database [6], which enabled scalable, data-driven research and reproducible analyses across institutions. Peter Szolovits [2], affiliated with Harvard University [4] and Massachusetts Institute of Technology [5], helped shape health informatics in this era via the MIMIC-III paper [6]. The MIMIC-III paper anchored open, shareable data resources and established a model for scalable analytics in clinical settings, underpinning privacy-preserving, translational research in this era [6].