Comprehensive Notes on Biomedical and Health Informatics (Hersh 2022)

What is biomedical and health informatics?

  • Core idea: BMHI is the field focused on the optimal use of information (often with technology) to improve health, healthcare, public health, and biomedical research

  • Foundational sites and writings by Hersh:

    • Web site: http://informatics.health/

    • Blog: https://informaticsprofessor.blogspot.com

    • Key articles/chapters:

    • Medical informatics: improving healthcare through information (Hersh, 2002)

    • Barriers to the field (Hersh, 2004)

    • Characterization and changes in the profession (Hersh, 2006)

    • Career opportunities in informatics (Hersh, 2008)

    • Reconciling definitions of terms (Hersh, 2009)

    • The informatics professional workforce (Hersh, 2010)

  • Emphasis: multiple viewpoints exist; the field spans definitions, applications, and career paths; ongoing reconciliation of terms is common

Other views and definitions of informatics

  • Early definition (Greenes, 1990): informatics as storage, acquisition, and use of information

  • US perspectives:

    • Bernstam (2010): "The science of information applied to biomedicine … data plus meaning."

    • Stead (2010): paradigm shift from “individual brains to systems of brains” in biomedicine

    • AMIA definition (Kulikowski, 2012): interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, decision making, aimed at improving human health

  • European/global perspectives referenced (Haux 2010; Hasman 2011; Geissbuhler 2011)

Defining informatics and its core focus

  • Informatics (Hersh, 2009):

    • Discipline focused on acquisition, storage, and use of information in a specific setting/domain

    • Emphasizes information over technology

    • Sometimes defined as the activity at the intersection of people, information, and technology

    • Described as the science of sociotechnical systems (Coiera, 2007)

    • Fundamental Theorem (Friedman, 2009): based on the relentless pursuit of assisting people

What informatics is and isn’t (Friedman, 2013)

  • Is:

    • Cross-training where basic informational sciences meet a biomedical application domain

    • Relentless pursuit of assisting people

    • “Tower of achievement” comprising: model formulation, system development, system implementation, study of effects

  • Isn’t:

    • Scientists or clinicians tinkering with computers

    • Merely analysis of large data sets per se

    • Limited roles related to deployment of EHRs (point of disagreement)

    • The profession of health information management (HIM) as a core identity

    • Anything done using a computer

Preferred terminology and scope today

  • Term: Biomedical and health informatics (BMHI) – field concerned with optimal use of information (often with technology) to improve health, healthcare, public health, and biomedical research

  • Informatics applied in a more focused domain is {X} informatics (e.g., nursing informatics, dental informatics, pathology informatics, etc.)

  • Can be classified by the level of domain, with overarching areas such as imaging and research

  • Practitioners are usually called informaticians (informaticists)

Adjective problem in informatics

  • Illustration (conceptual) of how informatics sits among related terms:

    • Informatics = People + Information + Technology

    • Biomedical and Health Informatics → a domain-specific application of informatics

    • Related domains include Legal Informatics, Chemoinformatics, Bioinformatics (cellular/molecular), Medical/Clinical Informatics (person/clinical field), Public Health Informatics (population), Consumer Health Informatics, Imaging Informatics, Research Informatics

  • The adjective problem highlights: the same informatics core concepts apply across domains, but the domain name shifts the focus and audience

Informatics as a core competency for health professionals

  • IOM (Greiner, 2003): modern healthcare professionals must have informatics competency as part of patient-centered care

  • Informatics competency ≠ just computer literacy; the “Google generation” may lack strong information skills (Rowlands, 2008)

  • Informatics is a core component of the learning health system (Friedman, 2010; Smith, 2012)

Historical perspectives and terminology

  • Origin of the term informatics attributed to Dreyfus (1962)

  • Became widespread in France (informatique), Russia, and then Europe in the 1960s for computing issues related to information use

  • “Medical informatics” first used in 1974

  • History documented by Collen (2015); early pioneers documented via oral histories (NLM project)

  • Today, informatics is used across domains (law, chemistry, social sciences, etc.) beyond biomedicine

Distinctions from related fields

  • Information Technology (IT): computer hardware/software and related tech

  • Computer Science: underlying academic discipline for IT and technologies

  • Management Information Systems (MIS): domain in business schools underpinning IT

  • Health Information Technology (HIT): health-related application of IT

Other related terms in the field

  • Health Information Management (HIM): historically focused on management of (paper) medical records; has three main levels:

    • RHIA (Registered Health Information Administrator) – bachelor’s level

    • RHIT (Registered Health Information Technologist) – associate level

    • CCS (Certified Coding Specialist) – usually less than associate level

  • ICT (Information and Communications Technology): IT with emphasis on telecommunications

  • eHealth: ICT use for health

  • Telemedicine/Telehealth: healthcare delivery separated by time/distance

  • mHealth: mobile devices in health

  • Digital health: broad IT-related aspects of health and healthcare

  • Evidence-based medicine (EBM): applying best scientific evidence to medical decision-making

  • Evidence-based practice (EBP): applying EBM in clinical practice

  • Comparative effectiveness research (CER): compares diagnostic/treatment options for effectiveness/safety/outcomes (patient-centered outcomes research)

  • Information retrieval: searching knowledge-based information; part of knowledge management

Other related terms (continued)

  • Health systems science (HSS): distinguishing sciences from basic/clinical sciences; clinical informatics appears in textbooks (Hersh 2020)

Records and information systems in healthcare

  • Electronic health record (EHR): digital health record; largely supersedes electronic medical record (EMR)

  • Personal health record (PHR): patient-controlled health record

  • Health information exchange (HIE): exchange of health information across organizational boundaries; formerly RHIO (Regional Health Information Organization); now a noun (HIE)

EHR adoption: virtues and challenges

  • Prominent focus on improving quality, safety, and efficiency

  • Challenges:

    • Difficult integration of IT with clinical workflow

    • Some HIT may be deleterious

    • Financial benefits of IT do not always accrue to those who pay

    • Larger organizational/financing problems complicate change

Informatics in modern biomedical research

  • NIH Roadmap emphasizes informatics in accelerating biomedical research discovery

  • Researchers generate huge data; need tools to evaluate, combine, visualize data

  • Tools range from supercomputers to personal computers; NIH priorities include high-throughput tech, translational research, supporting healthcare reform, global health, empowering researchers

Translational and precision medicine concepts

  • Translational research (bench to bedside): also from controlled to community/population settings; faster translation into clinical care

  • NIH Clinical & Translational Science Award (CTSA) program supports translational research and bioinformatics

  • Translational bioinformatics: bioinformatics applied to health-related problems

  • Precision medicine: tailoring clinical care to individual characteristics, including genome

  • Previously called personalized medicine (Schleidgen et al., 2013)

  • Clinical research informatics (CRI): informatics applied to clinical research; IT vs informatics distinction is clear in this domain

Data, information, knowledge, wisdom (DIKW) and wisdom additions

  • DIKW progression:

    • Data: raw material collected and stored

    • Information: data given meaning and organization

    • Knowledge: understanding and applicability to new situations

    • Wisdom: knowing how to apply knowledge effectively

  • Some scholars add wisdom to the DIKW pyramid

  • Blum (1984) introduced the Data → Information → Knowledge model in informatics

Data science and its relation to informatics

  • Data science: "the science of learning from data"; methods for analysis/processing; evidence-based improvement of methods (Donoho, 2017)

  • Data scientist nickname: “sexiest job of the 21st century” (Davenport, 2012)

  • Some debate whether data science is distinct from informatics (Hersh, 2015; Payne, 2018)

  • Data analytics: extensive use of data, statistics, models to drive decisions/actions (Davenport, 2007)

  • Big data era characterized by four Vs: Volume, Velocity, Variety, Variability

  • Key healthcare-focused data science notions include performance improvement, innovation, product development, and broader organizational needs; AI/automation are increasingly integral

  • Four Vs expressed as:
    ext{4 Vs} = igl\
    Volume,
    Velocity,
    Variety,
    Variability
    igr}

How informatics differs from data science

  • Informatics involves a cycle: biological/social/technical processes → create knowledge → apply knowledge in real-world health contexts

  • Data science and informatics share the aim of generating knowledge, but informatics emphasizes use of that knowledge in health care, research, and clinical practice

  • Key distinction: informatics is not just generating knowledge but applying it to health-related use cases

Is medicine/health an information science?

  • Time-use studies show physicians spend substantial time with information and documentation

  • Outpatient example (Mamlin, 1973):

    • 37.8% charting, 5.3% consulting, 1.7% other activities, 55.2% with patients

    • 14-39% of work outside the exam room

    • 15-23% of workday with patient-related tasks when not present

  • Time studies in hospitals/EDs (Ammenwerth 2009; Chisholm 2011; etc.):

    • Direct patient care 15-38%

    • Indirect patient care 50-67% (review results, documentation, communication)

  • Widespread EHR adoption era studies (2010s):

    • Interns: ~40% of time interacting with computers

    • Internists: ~48 minutes lost per day due to EHR (perceived)

    • Residents in teaching hospitals: ~50% of time with computers vs 10% with patients

    • Physicians: ~2 hours of EHR/desk time per 1 hour with patients; additional 1-2 hours per night

    • Primary care studies: 50%–60% of workday with EHR/desktop tasks

  • Overall takeaway: informatics and information management have become deeply interwoven with clinical workflows and time allocation; debates persist about the ideal balance

Who does biomedical and health informatics? Workforce landscape

  • Historically focused on the HIT workforce; leaders in informatics

  • Key groups and competencies include:

    • Education and certification

    • Salaries

    • Informatics competencies for informaticians and non-informaticians

Healthcare IT workforce perspectives and domains

  • Traditional groupings in healthcare IT: IT, HIM, CI, plus others (librarians, managers, etc.)

  • Informatics professionals also work outside traditional healthcare settings

  • Popular workplace mapping shows broader domains beyond HIT such as health, research, bio-imaging, consumer health, public health, etc.

HIT workforce size, measurement, and data sources

  • Most studies focus on hospital settings; main groups include IT and HIM

  • Data sources include HIMSS Analytics Database (HIM) and Bureau of Labor Statistics (CI)

  • No consistent, universally accepted estimates; evolution ongoing

HIMSS Analytics Database studies and results

  • 2008 study:

    • IT per non-IT staff ≈ 1:60

    • IT FTE per bed grows as stages move from 0 to 4 in EMR adoption models

    • Extrapolated U.S. IT staff ≈ 108,390; would rise to ≈ 149,174 if all hospitals reached Stage 4

    • Informed workforce development funding of the HITECH Act

  • 2018 study:

    • Similar IT FTE/bed at comparable stages; major shift to Stage 6 increased estimated size to ≈ 161,160 FTE

    • If all hospitals reached Stages 6-7, estimated growth ≈ 19,852–153,114 FTE

HIM, CI, and the broader workforce

  • HIM (Calhoun, 2012): leadership emphasizing advanced degrees and career maps; adapt or disappear (Butler, 2014)

  • Historical roles/training in HIM: RHIA, RHIT, CCS

  • HIM workforce size (BLS 2020): 341,600 RHIT/CCS-type roles in 2019; expected growth ~8% by 2029; RHIA and other roles not counted here

  • Clinical informatics (CI): professionals at the intersection of healthcare and IT; hard to distinguish from IT in some settings (HealthITJobs.com, 2015)

  • Early CI need estimates: one physician and one nurse per US hospital (~10,000) (Safran, 2005)

Competencies and workforce taxonomy

  • Key competency studies (past decade):

    • Core content of clinical informatics (Gardner, 2009)

    • Core competencies for graduate education in biomedical informatics (Kulikowski, 2012)

    • Foundational domains of applied health informatics (Valenta, 2018)

    • Domains, tasks, and knowledge for clinical informatics subspecialty practice (Silverman, 2019)

    • Importance of characterizing the informatics profession (Fridsma, 2019)

    • Domains, tasks, and knowledge for health informatics practice (Gadd, 2020)

  • Data on workforce are often incomplete; lack of standardized SOC/ISCO coding for informatics

Data, governance, and leadership domains in practice

  • AMIA practice workforce analysis (Integrated with CIS data from Silverman, Gadd, 2019/2020):

    • Domain 1–5 data on Foundational Knowledge, Enhancing Decision-Making, Health Information Systems, Data Governance & Analytics, Leadership & Transformation

    • CIS domains mirror similar structure with slightly different emphasis and totals

  • Fundamental knowledge and skills (Valenta, 2018):

    • Provide a common vocabulary across informatics domains

    • Understand the environment: individual health, healthcare, public health, and research

  • Domain 2: Enhance decision-making, care delivery, and outcomes:

    • Analyze health processes; evaluate HIS impact; pursue discovery; develop and evaluate CDS; drive innovation

  • Domain 3: Health and enterprise information systems:

    • Plan/develop/acquire/implement/evaluate HIS; ensure integration across care continuum; security/privacy/safety considerations; curate institutional knowledge repositories

  • Domain 4: Data governance, management, and analytics:

    • Establish governance structures and policies; acquire/manage data; ensure quality/meaning; incorporate emerging data sources; derive insights; minimize biases; implement/assess ML/AI

  • Domain 5: Leadership, professionalism, strategy, and transformation:

    • Lead change, build alignment, steward informatics initiatives; collaborate across organizations

Informatics leadership and roles

  • Common leaders in health IT:

    • Chief Information Officer (CIO)

    • Chief Clinical Informatics Officer (CCIO), Chief Medical Information Officer (CMIO), Chief Nursing Informatics Officer (CNIO)

    • Others (e.g., CMIOs in dental/pharmacy) exist but less common

  • Organizations often create dedicated clinical informatics departments, sometimes separate from IT, with clinical leadership (CMIO) and increasingly incorporate HIM

CIO and CMIO: roles, salaries, and trends

  • CIO: strategic IT leader; typical profile includes data analytics and clinical experience as important future skills; salary around six figures (example: mean ≈ $288k; gender differences noted in surveys)

  • CMIO/CHIO: liaison between clinicians and IT; executive informatician; leadership is about consensus-building, communication, and clinical insight; increasingly report to CMIO/CMO rather than CIO

  • Gartner-AMDIS CMIO surveys show focus on enterprise data warehouse, data analytics, population health; common that many CMIOs still practice medicine; reporting structures vary; average salaries around high $300k range in some datasets

Certification in HIT/informatics

  • Nursing informatics: ANCC offers certification (e.g., Informatics Nurse)

  • HIM: RHIA, RHIT, CCS, CHDA, CHPS, CDIP, etc. (AHIMA certifications)

  • Physicians: Clinical Informatics subspecialty

    • Accredited by ABMS since 2011; administered by ABPM and ABP; over 2,000 board-certified as of 2019-2020

    • Grandfathering for training extended into 2022; new certification requirements evolving

  • Clinician informatics subspecialty milestones:

    • 2014: ACGME fellowship accreditation rules; initial programs accredited

    • 2019: >2000 board-certified; >45 accredited fellowship programs

    • 2020: Fellowships contributing to COVID-19 response; combined fellowships explored

  • Advanced Health Informatics Certification (AHIC) proposed to certify broader informatics workforce (Gadd, 2016, 2020)

  • Other HIT certifications (HIMSS): CPHIMS (Certified Professional in Healthcare Information & Management Systems) and CAHIMS (Certified Associate)

Other stakeholders in informatics

  • Clinicians (physicians, medical students) and patients are key beneficiaries and participants in informatics

  • Patients: high online health information-seeking and self-diagnosis trends (e.g., 58% of US adults look online for health information; 35% attempt self-diagnosis) [Fox, 2013]

  • Clinical and translational scientists; next-generation researchers; nurses (Forman, 2020)

Informatics education and training

  • Informatics is interdisciplinary; programs span clinical, biomedical, health, bio-, nursing, etc.

  • Education historically academic but expanding into applied master’s degree programs; roughly 75–80 such programs in the US (Cox, 2021)

  • NLM funds programs to train researchers at PhD/postdoc levels across many universities; other funding sources support clinical informatics subspecialty fellowships

  • OHSU as an example program; consult program websites for details

Academic programs and career pathways

  • AMIA maintains a list of informatics programs and courses

  • NLM funds training institutes; many pathways into BMHI exist

  • Career pathways: multiple inputs/outputs; no single ladder; opportunities exist in healthcare systems, clinical leadership, IT leadership, biomedical research, industry, academia, etc.

  • Cardinal rule of informatics education:

    • What you do when you get out = f(What you did before you started, What you learned in the program)

    • This highlights the importance of prior experiences and the education you receive in shaping career outcomes

Conclusions and outlook

  • The field is rapidly expanding with many opportunities across settings

  • Professional practice and education of informaticians require ongoing attention

  • Core focus remains on the optimal use of information and technology to advance human health

Resources for further information (selected categories)

  • Organizations:

    • AMIA: https://www.amia.org/

    • HIMSS: https://www.himss.org/

    • AHIMA: http://www.ahima.org/

    • AMDIS: https://amdis.org/

    • Alliance for Nursing Informatics (ANI): https://www.allianceni.org/

    • PHII: https://phii.org/

    • ISCB: http://www.iscb.org/

    • SIIM: https://siim.org/

    • ACM: https://www.acm.org/

    • MLA: https://www.mlanet.org/

  • Journals (examples): JAMIA, MIM, IJMI, JMIR, JBI, ACI, etc.

  • Textbooks and key references (selected):

    • Hersh (ed.), Health Informatics: Practical Guide (8th ed., Lulu, 2022)

    • Shortliffe & Cimino (eds.), Biomedical Informatics (5th ed., Springer, 2021)

    • Skochelak et al., Health Systems Science (2nd ed., Elsevier, 2020)

    • Richesson & Andrews (eds.), Clinical Research Informatics (2nd ed., Springer, 2019)

  • Key online resources mentioned: NIH Roadmap on bioinformatics; ONC Health IT resources; US HHS ONC strategic plans; NLM strategic plan

  • Notable concepts to remember:

    • DIKW pyramid and the role of wisdom in healthcare informatics

    • The 4 Vs of Big Data: extVolume,extVelocity,extVariety,extVariabilityext{Volume}, ext{Velocity}, ext{Variety}, ext{Variability}

    • Translational research and translational bioinformatics concepts

    • The evolving landscape of CI/HIM/ IT leadership roles and the importance of clinician-informaticist collaboration

Quick references to key figures and sources

  • Hersh (2022) – core source for definitions, scope, and workforce analyses in BMHI

  • Bernstam (2010), Stead (2010) – US perspectives on informatics as a science of information and systemic paradigm shifts

  • Kollikowski (2012); Gardner (2009); Kulikowski (2012); Valenta (2018); Silverman (2019); Gadd (2020) – competency and domain frameworks

  • Safran (2005); Mamlin (1973); Gottschalk (2005); Chen (2011); Mamlyn (2016); Sinsky (2016); Tai-Seale (2017); Arndt (2017) – time-use studies and EHR impact on workflow

  • AMIA, HIMSS, AHIMA – major professional associations shaping education, certification, and practice

  • NIH CTSA program; Collins (2010) – translational research and precision medicine emphasis

Note: The notes above summarize the material from the provided transcript, preserving key points, definitions, historical context, terminology, workforce considerations, certifications, and resource references. For exam preparation, focus on understanding the relationships between informatics definitions, the core competencies, the five practice domains, and the leadership/certification landscape, as well as real-world implications for clinical care, research, and education.